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Topic: Risk Management and Governance in a Global EnvironmentAssignment must be worded and look exactly like the Annotated Bibliography template provided. The five aricles are provided also. Topic: Risk Management and Governance in a Global EnvironmentAssignment must be worded and look exactly like the Annotated Bibliography template provided. The five aricles are provided also. 1 Sample Annotated Bibliography Student Name Here University Sample Annotated Bibliography Autism research continues to grapple with activities that best serve the purpose of fostering positive interpersonal relationships for children who struggle with autism. Children have benefited from therapy sessions that provide ongoing activities to aid autistic children’s ability to engage in healthy social interactions. However, less is known about how K–12 schools might implement programs for this group of individuals to provide additional opportunities for growth, or even if and how school programs would be of assistance in the end. There is a gap, then, in understanding the possibilities of implementing such programs in schools to foster the social and thus mental health of children with autism. Annotated Bibliography Kenny , M. C., Dinehart, L. H., & Winick, C. B. (2016). Child-centered play therapy for children with autism spectrum disorder. In A. A. Drewes & C. E. Schaefer (Eds.), Play therapy in middle childhood (pp. 103–147). Washington, DC: American Psychological Association. In this chapter, Kenny, Dinehart, and Winick provided a case study of the treatment of a 10-year-old boy diagnosed with autism spectrum disorder (ADS). Kenny et al. described the rationale and theory behind the use of child-centered play therapy (CCPT) in the treatment of a child with ASD. Specifically, children with ADS often have sociobehavioral problems that can be improved when they have a safe therapy space for expressing themselves emotionally through play that assists in their interpersonal development. The authors outlined the progress made by the patient in addressing the social and communicative impairments associated with ASD. Additionally, the authors explained the role that parents have in implementing CCPT in the patient’s treatment. Their research on the success of CCPT used qualitative data collected by observing the patient in multiple therapy sessions . CCPT follows research carried out by other theorists who have identified the role of play in supporting cognition and interpersonal relationships. This case study is relevant to the current conversation surrounding the emerging trend toward CCPT treatment in adolescents with ASD as it illustrates how CCPT can be successfully implemented in a therapeutic setting to improve the patient’s communication and socialization skills. However, Kenny et al. acknowledged that CCPT has limitations—children with ADS, who are not highly functioning and or are more severely emotionally underdeveloped, are likely not suited for this type of therapy . Kenny et al.’s explanation of this treatments’s implementation is useful for professionals in the psychology field who work with adolescents with ASD. This piece is also useful to parents of adolescents with ASD, as it discusses the role that parents can play in successfully implementing the treatment. However, more information is needed to determine if this program would be suitable as part of a K–12 school program focused on the needs of children with ASD . Stagmitti, K. (2016). Play therapy for school-age children with high-functioning autism. In A.A. Drewes and C. E. Schaefer (Eds.), Play therapy in middle cildhood (pp. 237–255). Washington, DC: American Psychological Association. Stagmitti discussed how the Learn to Play program fosters the social and personal development of children who have high functioning autism. The program is designed as a series of play sessions carried out over time, each session aiming to help children with high functioning autism learn to engage in complex play activities with their therapist and on their own. The program is beneficial for children who are 1- to 8-years old if they are already communicating with others both nonverbally and verbally. Through this program, the therapist works with autistic children by initiating play activities, helping children direct their attention to the activity, eventually helping them begin to initiate play on their own by moving past the play narrative created by the therapist and adding new, logical steps in the play scenario themselves. The underlying rationale for the program is that there is a link between the ability of children with autism to create imaginary play scenarios that are increasingly more complex and the development of emotional well-being and social skills in these children. Study results from the program have shown that the program is successful: Children have developed personal and social skills of several increment levels in a short time. While Stagmitti provided evidence that the Learn to Play program was successful, she also acknowledged that more research was needed to fully understand the long-term benefits of the program. Stagmitti offered an insightful overview of the program; however, her discussion was focused on children identified as having high-functioning autism, and, therefore, it is not clear if and how this program works for those not identified as high-functioning. Additionally, Stagmitti noted that the program is already initiated in some schools but did not provide discussion on whether there were differences or similarities in the success of this program in that setting. Although Stagmitti’s overview of the Learn to Play program was helpful for understanding the possibility for this program to be a supplementary addition in the K–12 school system, more research is needed to understand exactly how the program might be implemented, the benefits of implementation, and the drawbacks. Without this additional information, it would be difficult for a researcher to use Stigmitti’s research as a basis for changes in other programs. However, it does provide useful context and ideas that researchers can use to develop additional research programs. Wimpory, D. C., & Nash, S. (1999). Musical interaction therapy–Therapeutic play for children with autism. Child Language and Teaching Therapy, 15(1), 17–28. doi:10.1037/14776-014 Wimpory and Nash provided a case study for implementing music interaction therapy as part of play therapy aimed at cultivating communication skills in infants with ASD. The researchers based their argument on films taken of play-based therapy sessions that introduced music interaction therapy. To assess the success of music play, Wimpory and Nash filmed the follow-up play-based interaction between the parent and the child. The follow-up interactions revealed that 20 months after the introduction of music play, the patient developed prolonged playful interaction with both the psychologist and the parent. The follow-up films also revealed that children initiated spontaneously pretend play during these later sessions. After the introduction of music, the patient began to develop appropriate language skills. Since the publication date for this case study is 1999, the results are dated. Although this technique is useful, emerging research in the field has undoubtedly changed in the time since the article was published. Wimpory and Nash wrote this article for a specific audience, including psychologists and researchers working with infants diagnosed with ASD. This focus also means that other researchers beyond these fields may not find the researcher’s findings applicable. This research is useful to those looking for background information on the implementation of music into play-based therapy in infants with ASD. Wimpory and Nash presented a basis for this technique and outlined its initial development. Thus, this case study can be useful in further trials when paired with more recent research. Topic: Risk Management and Governance in a Global EnvironmentAssignment must be worded and look exactly like the Annotated Bibliography template provided. The five aricles are provided also. The IUP Journal of Applied Economics, Vol. XVII, No. 1, 2018 40 Equity Risk Exposure: A Case of Indian Banking Industry * Research Associate under Dr. Ruchi Sharma, Department of Humanities and Social Sciences, IIT Indore, Khandwa Road Simrol, Indore 453552, Madhya Pradesh, India. E-mail: [email protected] * * Research Scholar, School of Economics, University of Hyderabad, Hyderabad 500046, Telangana, India; and is the corresponding author. E-mail: [email protected] © 2018 IUP. All Rights Reserved. Md. Danish * and Aaqib Ahmad Bhat ** Global market integration and increase in trading activities have magnified the financial system complexities and increased the degree of riskiness. Value-at-Risk (VaR) has been universally accepted as a measure of market risk in financial institutions. In this study, using the data of NSE-Nifty Bank Index and indices of SBI and ICICI Bank over a sample period from January 3, 2005 to November 19, 2014, an attempt has been made to analyze the market exposure in Indian banking industry by employing various methods of VaR. The study reveals that there is greater market turbulence during the financial crisis period than the pre- and post-crisis periods through all the three techniques of VaR. Moreover, bifurcating the full sample into three sub-samples (pre-crisis, crisis and post-crisis periods) seems to assure robustness, thereby validating the applicability of VaR methods for the Indian banking sector. Further, backtesting through Kupiec test revealed that historical simulation approach accounts for less statistical noise than other methods of estimating VaR. Introduction Financial institutions have always been imperative for stimulating investment and other financial developments of an economy. Over the past two decades, the financial system has become more complex due to increase in trading activities, which in turn led to increase in the degree of riskiness. Indulging in more financial activity other than lending and depositing of money, although may be more beneficial, at the same time makes them more prone to market turbulences, resulting in high degree of risk in their daily trading activity. Therefore, with increasing complexities and turbulence in the financial system, the risk management becomes the most crucial strategic activity in any financial firm. In the recent past, major financial and non-financial corporations experienced insolvency as evidenced by the insolvency of many financial and non-financial corporations like Lehman Brothers, Washington Mutual, Royal Bank of Scotland, WorldCom, General Motor, and CIT due to the global financial crisis of 2008. All these bankruptcies and market turbulences in the world economy also bear significant impact on Indian economy and particularly on the financial and banking sector. 41 Equity Risk Exposure: A Case of Indian Banking Industry Before proceeding to risk management, it is imperative to first have a glimpse of what risk is? Risk can be understood as the uncertainty about the future, the possibility or chance that something wrong or unpleasant may happen in future. In finance, risk is the probability that actual return on an investment will be lower than expected. Therefore, we may define risk as the future uncertainty about expected return on any financial investment due to market fluctuations. Financial risk management has always been the crucial strategic activity of any firm from their inception. But in the last two-and-a-half decades, it has become the key issue in financial management of any organization due to many recent developments in financial system all across the globe like deregulation, globalization and financial innovation. Indian economy, after the New Economic Policy in 1991, has experienced several policy and structural changes such as deregulation, removal of trade barriers, financial reforms, etc. The liberalization policy has opened various other sources of earning to the banks which include innovated new financial products, Internet banking, credit cards, mobile banking and many more. The other side of these developments of the banking sector is the introduction of new risk or increase in risk factor. This compelled banks to focus more on the risk management strategy. Initially, the Indian banks used risk control systems that kept pace with the legal environment and Indian accounting standards. In India, the statutory regulation of commercial banks by Reserve Bank of India (RBI) until the early 1990s was mainly focused on licensing, administration of minimum capital requirements, pricing of services including administration of interest rates on deposits as well as credit, reserves and liquid asset requirements (Kannan and Aulbur, 2004). But with the growing pace of deregulation and associated changes in the customer’s behavior, banks are exposed to mark-to-market accounting. In order to maintain the regulatory framework in the country in response to market dynamics, banks have to follow certain risk management norms as suggested by both RBI and Bank for International Settlements. The increased financial developments also heightened the risk and to realize the benefit of financial development, it is important to manage the associated risk professionally. In this context, the present study employs the most preferred risk management method: Value-at- Risk (VaR) method to empirically assess the risk associated with Indian banking industry. The VaR method in the context of portfolio theory developed by Markowitz (1952) is widely applied to estimate market risk and exposure. Moreover, Basel I also suggested banks to use the VaR methodology as an internal tool to quantify and manage the market risk of any financial firm or bank. The study focuses on the Indian banking industry due to the emerging importance and role in financial development in the Indian economy. Moreover, to the best of our knowledge, none of the studies earlier have analyzed the market exposure associated with Indian banking industry along with comparative analysis of different VaR techniques that fit and accurately measure the market exposure in Indian banking industry. Particularly, this study focuses on the NSE Nifty Bank Index, State Bank of India (SBI), and Industrial Credit and Investment Corporation of India (ICICI) indices. The study is organized as follows: following the The IUP Journal of Applied Economics, Vol. XVII, No. 1, 2018 42 introduction, a brief literature review is presented. Subsequently, data and methodology used in the study are discussed, followed by a discussion of the results obtained. Finally, the conclusion is offered. Literature Review In the arena of volatility and risk, both market participants and the market managers need to adopt techniques to measure and manage market risk. The success story of risk management models mainly depends on the estimates of the volatility of underlying prices. VaR methods have been extensively used in forecasting future returns, therefore it becomes imperative to analyze which of the methods estimates market exposure with higher authenticity and accuracy. To have a perspective on the comparative performance of the VaR methods, both the empirical and methodological studies have been reviewed thereon. Dutta and Bhattacharya (2008) evaluated the predictive performance of VaR methods for the stock market of India. The VaR model, assuming linearity (variance-covariance approach), is consid ered an efficient candid ate for the financial retu rns ove r th e period under consideration. The authors found the technique quite satisfactory and more comprehensive as it takes into account the scarcity of inadequate data. Further, the technique was found to work even in nonlinearity as it can take care of the volatilities and the correlations in the data. Rejeb et al. (2012) estimated the market exposure for three currencies (US dollar, euro, and Japanese yen) and four currency portfolios in the Tunisian currency market during the time period 1999-2007. Besides, the study analyzed and compared the empirical estimates of four VaR simulations, namely, the variance-covariance, historical simulation, bootstrapping and Monte Carlo. The study highlighted that market risk primarily depends on the degree of portfolio diversifications. Among the three currencies, Japanese yen was found to be the most risky currency, followed by the US dollar, while euro was found to be a less risky one. By employing the backtesting technique, the study revealed that three methods underestimate the VaR. However, the least error is found by using the variance-covariance method, then the Monte Carlo and finally, the historical simulation method. Therefore, the authors concluded that traditional variance-covariance method predicts the foreign exchange risk better in the Tunisian exchange market than the other two methods. In contrast to the above studies, Yang (2010) while examining the market exposure of Chinese stock market through various approaches of VaR, found that variance-covariance method is easily influenced by market turbulence, especially the effect of global financial crisis in 2008. The study also compared the market exposure of Chinese market to the US market and Japanese market. The study found that the behavior of Chinese market is similar to the Japanese market, however, VaR models are able to predict the market risk of Chinese market better than the other two markets. Pritsker (1997) sketched down the methodologies of the VaR for the twin attributes of accuracy versus computational time. The author held that the recent development in the literature of the risk models reveals that the outcomes of the studies vary widely, thus forcing the researcher to choose among the appropriate models. The study found that the 43 Equity Risk Exposure: A Case of Indian Banking Industry method of delta-gamma Monte-Carlo simulations was the most satisfactory among the class of the techniques used for examining market exposure. Mentel (2013) also found Monte- Carlo simulation to perform well and being a representative of a group of nonparametric methods. However, Hull and White (1998) found that for investment in securities, simple historical simulation method is more feasible. Bohdalova (2007) compared the different VaR methods of risk measurement by taking into account a hypothetical data on government bonds that mature on monthly basis. The authors found that the authenticity of all the VaR models holds and recommended that one should compare them if drawn on the comparable assumptions. In contrast to the above studies, Lambadiaris et al. (2003) assessed the performance of historical and Monte-Carlo simulation as alternative approaches to calculating VaR by using data from Greek stock and bond market. Based on various backtesting criteria, mixed results were obtained on the accuracy and adequ acy of differen t VaR approaches. Sarma et al. (2003) tried to devise the techniques and the ways to choose the best models among the most competing models. For the purpose, the author used two-stage model selection procedure (statistical accuracy test in terms of pre-specified failure rate, followed by comparing the loss functions) for the S&P 500 index and India’s NSE 50 index. The study found similar inconclusive results regarding the selection of the unique model for risk valuation. In accordance with the above studies, Linsmeier and Pearson (1996) made a comparative discussion of various methodologies aimed to measure the VaR. The study found inconclusive results in prioritizing the VaR methods. Van and Vlaar (1999), in their comparative evaluation of various VaR techniques on Dutch stock market index AEX and to the Dow Jones Industrial Average, came out with multiplicity of conclusions regarding the VaR modeling. The study found volatility clustering as the most important feature of stock market returns for VaR modeling and therefore advocated the use of GARCH models for precise modeling setup as this could effectively reduce the average failure rates and the fluctuations of failure rates over time. Similar analysis was done by Hull and White (1998) who in their treatment of VaR estimation proposed the use of volatility updating scheme like GARCH as a supplementary approach to the historical simulation method in order to arrive at a better measure of VaR. Varma (1999) tried to identify the best predictive model in the case of Indian financial system. The author found that the Generalized Autoregressive Heteroscedasticity with Generalized Error Distribution residuals (GARCH-GED) perform exceedingly better than any other model. The author recommended that in order to better judge the performance of the VaR models, we should also take into account the movements of foreign portfolio prices. Patr a an d Pad h i (2 0 1 5 ) an alyzed th e p res en ce o f Au to regres sive C o n d iti o n al Heteroscedastic (ARCH) and long-memory effects in the daily closing prices of the Bombay Stock Exchange (BSE)-BANKEX return series of India. The study employed different methods of VaR calculation such as Asymmetric Power ARCH (APARCH), Fractionally Integrated Exponential Generalized ARCH (FIEGARCH), Hyperbolic Generalized GARCH (HYGARCH) and risk metrics to check the accuracy of these methods in predicting the bank return series The IUP Journal of Applied Economics, Vol. XVII, No. 1, 2018 44 in India. Furthermore, the study also examined the forecasting capabilities of these VaR methods through backtesting techniques such as Kupiec Likelihood Ratio (LR) test and dynamic quantile test. The study found that banking shares in India have both long memory and asymmetry effects. The results based on Kupiec LR test and dynamic quantile test show that both asymmetries and long memory play an important role in market risk evaluation and its forecasting. A comparative analysis indicated that the results varied across different methods of estimating risk exposure, however HYGARCH model was found to perform well. Giot and Laurents (2003) also used VaR models to analyze long and short trading positions in commodity markets. An out-of-sample analysis is carried on various metals, energy oils and agricultural commodities to assess the performance of the Risk Metrics, skewed Student APARCH and skewed Student ARCH models. The study found skewed Student APARCH model performed best in all cases as its calculation does not require nonlinear optimization procedures. Roynstrand et al. (2012) examined the statistical power of different methods of VaR through backtesting technique. The results of the study indicated that geometric conditional coverage test given by Berkowitz et al. (2011) performs best over all other methods of VaR. Moreover, to have a satisfactory power of various tests, sample sizes of 1,000, 750 and 500 data points are found to be the minimum requirement when testing 1\%, 5\% and 10\% VaR, respectively. Therefore, the belief of sample size of 250 data points, which is the minimum requirement set by the Basel Committee on Banking Supervision (2011), seems to be misspecified. It may be summed up that over the years, accuracy, prediction and computational procedures of the VaR models have been put on the screen of methodological debate to assess the authenticity and validity of various approaches. However, the literature shows no consensus. Some studies have advocated the supremacy of variance-covariance approach, while others held the predominance of Monte-Carlo and historical simulations as a method for examining market exposure. Moreover, the validity of different approaches of VaR also varies across sectors and for different types of assets that are being examined. Therefore, the present study has adopted a holistic approach to analyzing market risk through widely accepted and recommended measures of VaR. Data and Methodology Data To carry out the study, data has been collected for daily closing prices of NSE-Nifty Bank Index, State Bank of India (SBI) and ICICI Bank from the NSE-Nifty database for the period from January 3, 2005 to November 19, 2014. Nifty Bank Index exhibits the behavior and performance of the highly liquid 12 commercial banks listed on NSE which represent 93.43\% of total market capitalization of overall banking sector in Nifty Bank Index. Nifty banking index represents the financial health of Indian banking sector, whereas SBI and ICICI Bank are the 45 Equity Risk Exposure: A Case of Indian Banking Industry largest public and private sector banks respectively in terms of market share and capital in Indian banking industry. Indian banking sector is growing rapidly in the last two decades with a vital role in growth, development as well as the financial stability in Indian economy. The end point of the sample period is selected as stock split has been adopted by various banks thereafter, which led to structural shift in the stock prices of the respective banks. As can be seen in Figures 1 and 2, due to stock split in SBI and ICICI Bank, there has been a sharp and sudden decline in their stock prices on November 20 and December 4, 2014. Other banks like Canara, PNB, and Axis Bank also did stock split in order to be compatible and increase market share during the same year. The share split should be differentiated from a structural break as stock split is a deliberate action on the part of bankers. It was done to increase capital and market share. Global financial crisis 2008 badly affected the financial condition of economy across the globe, the main sufferers being the stock markets and the financial firms. Global financial crisis that hit Indian stock market on October 13, 2008 caused benchmark indices of the economy to fall by 50\% from the highest record that they scaled in January 2008. ICICI Bank, which is the second largest lender of Indian economy, faced sudden fall in its share price following rumors that it is exposed to toxic USA and UK assets. In order to analyze and segregate the impact of global financial crisis on the financial stability and performance in Figure 1: SBI Closing Price 4000 3500 3000 2500 2000 1500 1000 500 0 Clo sin g P ric e ( ) Date 1 0-M ay -0 5 1 3-S ep t- 0 5 1 9 -J a n -0 6 3 1-M ay -0 6 0 3-O ct- 0 6 0 9-F eb -0 7 2 0-J u n-0 7 2 4-O ct- 0 7 2 7-F eb -0 8 0 9-J u l- 0 8 1 8 -N ov-0 8 0 2 -A pr-0 9 1 2 -A ug-0 9 2 1-D ec-0 9 0 4-M ay -1 0 0 3-S ep -1 0 1 0 -J a n -1 1 1 9-M ay -1 1 2 3-S ep t- 1 1 0 1-F eb -1 2 0 7-J u n-1 2 1 2-O ct- 1 2 1 9-F eb -1 3 2 7-J u n-1 3 0 5 -N ov-1 3 1 2-M ar-1 4 2 1-J u l- 1 4 0 4-D ec-1 4 1 5 -A pr-1 5 1 8 -A ug-1 5 2 9-D ec-1 5 The IUP Journal of Applied Economics, Vol. XVII, No. 1, 2018 46 Figure 2: ICICI Bank Closing Price 600 400 200 0 Clo sin g P ric e ( ) Date 0 5-M ay -0 5 0 2-S ep t- 0 5 0 5 -J a n -0 6 1 5-M ay -0 6 1 1-S ep t- 0 6 1 2 -J a n -0 7 1 9-S ep t- 0 7 2 1 -J a n -0 8 2 8-M ay -0 8 2 6-S ep t- 0 8 0 6-F eb -0 9 1 8-J u n-0 9 2 1-O ct- 0 9 2 4-F eb -1 0 2 9-J u n-1 0 2 7-O ct- 1 0 2 8-F eb -1 1 0 1-J u l- 1 1 0 4 -N ov-1 1 0 7-M ar-1 2 0 9-J u l- 1 2 0 9 -N ov-1 2 1 3-M ar-1 3 1 6-J u l- 1 3 2 0 -N ov-1 3 2 2-M ar-1 4 2 5-J u l- 1 4 0 5-D ec-1 4 1 0 -A pr-1 5 1 1 -A ug-1 5 1 6-D ec-1 5 800 1,000 1,200 1,400 1,600 1,800 2,000 2 2-M ay -0 7 India, by observing the trend of closing prices of the NSE-Nifty Bank Index, the analysis has been performed on the sub-sample periods along with full sample period. Accordingly, the full sample has been bifurcated into three sub-periods as: i. Pre-crisis period (January 3, 2008 to January 14, 2008); ii. Crisis period (January 15, 2008 to March 19, 2009); and iii. Post-crisis period (March 20, 2009 to November 19, 2014). The first phase includes the time period of the rising phase of Indian economy; the second phase comprises periods of monetary contraction and great depression in Indian economy and, finally, the third and last phase is recovery phase in Indian economy after the global financial crisis. Since VaR for different time periods will be different, to ensure comparability, data regarding other two indices is also restricted to this time period and similar bifurcation has been done. Methods A number of methods have been used in the literature to quantify the financial risk of the stock prices, but the most advanced and commonly used method to calculate the financial risk of any financial or non-financial institution is the VaR methodology. VaR tells us about 47 Equity Risk Exposure: A Case of Indian Banking Industry the maximum expected loss of a firm’s portfolio at a given confidence level for a given period of time so as to ensure that the firm has sufficient capital reserve to cover the losses. The Bank for International Settlements (BIS) Amendment 1996 prescribed VaR for Internal Model Approach (IMA) to be computed as: •Daily basis with 99\% confidence level. • A horizon of 10-day trading days. • Observation period must have a historical data of at least one year or nearly 250 days. Following the literature and based on the objectives of the study, both parametric and nonparametric methods of estimation are employed. More precisely, the study uses variance- covariance approach (parametric), historical simulation (nonparametric) and Monte-Carlo simulation for the estimation of market exposure of NSE-Nifty Bank, SBI and ICICI Bank indices. Backtesting quantifies the effectiveness and accuracy of VaR models by comparing the actual Profit and Loss (P&L) with the corresponding VaR estimates. If the estimated VaR figures are similar to the real return P&L, then it is said that the model is accurate and the validity of the risk model should be accepted. Backtesting VAR Methodologies There are a wide range of methods available to backtest the VaR methodologies, but the most frequently used and suggested methods by the Basel Committee are mainly two: •Kupiec (1995) LR Test • Basel Rule ‘Traffic Light’ Approach (1996) This study employs Kupiec LR test, which is unconditional coverage test. Kupiec test, also known as Probability of Failure (PoF) test, is the frequently used method to test the failure rates. It measures whether the number of exceeding or exception is consistent with the confidence level or not. To check the accuracy of the model in Kupiec LR test, the null hypothesis that the mo del is correct and alternate hypothesis that model is inaccurate are tested. : ˆ : 0 N X P P H  Model is correct. where P^ is the observed failure rate, X is the number of exceptions or failure, N is the total number of observations, and X/N is the failure rate. The idea behind setting the null hypothesis is to check whether the observed failure rate ( P^) (VaR value) is significantly different from predicted probability ( P). Kupiec PoF test is best conducted in the form of LR test which is the likelihood ratio. The IUP Journal of Applied Economics, Vol. XVII, No. 1, 2018 48 The formula of Kupiec LR test is as follows:                              x x n x x n pof N X N X P P LR 1 ln 2 } ) 1 ln{( 2 LR test follows chi-square ( 2) distribution with one degree of freedom. If the calculated value of LR test exceeds the critical value of chi-square distribution, then we reject the null hypothesis H0that the model is accurate. Results and Discussion First of all, descriptive statistics of the three banking indices (Nifty Bank Index, SBI, and ICICI Bank) over the three phases are given in Table 1. It is observed from the table that quite often for all the three banking indices, the value of mean is positive but close to zero, thus following the standard assumption of zero mean of VaR methodology. Besides, it signifies that there is an increasing trend in the price of all indices during pre- and post-crisis period. However, in Phase 2 (crisis phase), the value of mean is negative and quite different from zero and the standard deviation is also high, thus revealing the severity of crisis period where the chances of losses in investing in the stocks are greater with high variability. The value of skewness and kurtosis are different from zero, thus exhibiting that the underlying series does not follow standard normal distribution. Similar kind of conclusion regarding the normality has been confirmed from the JB test and its associated p-value. One important point to be noted is that in the third phase SBI shows a very high negative skewness in return. This might be as a result of the greater role for SBI in neutralizing the impact of financial crisis of 2008 and to achieve sustained increase in growth in the post-crisis era. 1 231 2 312 3 Count 7592871408 759286 14087592861408 Mean 0.001–0.004 0.0010.002–0.003 –0.001 0.002 –0.005 0.001 SD 0.0190.034 0.0170.021 0.036 0.065 0.023 0.0490.023 Kurtosis 4.4213.459 10.774.518 3.6491104.63 3.969 4.4938.720 Skewness –0.2290.0660.684–0.206 0.112–31.250 0.028 –0.019 0.613 J-B 70.512.722 365578.25 5.62371424498 29.83 28.25 2009.59 Prob. 0.0000.256 0.0000.000 0.060 0.000 0.000 0.0000.000 Table 1: Summary Statistics of Nifty, SBI and ICICI Bank Indices Phase Statistic Banking Index Nifty Bank Index SBI Index ICICI Bank Index 49 Equity Risk Exposure: A Case of Indian Banking Industry Table 2 represents the VaR figures for NSE-Nifty Bank Index, SBI and ICICI Bank during three different time periods at 1\% and 5\% level of significance by applying the variance-covariance approach. In accordance with the financial theory, the results indicate an inverse relation between the value of VaR and the level of significance. Higher level of significance (lower confidence interval) was found to be associated with lower value of VaR. Most of the results on the market exposure in the Indian banking industry came as expected. In the second phase of global financial crisis, the VaR figures are quite high at both levels than the other two time periods. High VaR figure reveals that in the second phase, the magnitude of getting a loss on holding a stock was relatively more. Global financial crisis affected almost all economies of the world in all sectors, especially the financial sector. Similar findings regarding the severity of financial crisis have been found in India and it can be seen from Table 2 where the value of VaR of Nifty Bank Index, SBI and ICICI surged and almost doubled during the time of crisis. Greater VaR values during all the three phases, especially during the crisis period, were found to be associated more with ICICI Bank as compared to SBI and Nifty Bank Index, hence signifying that the stock price of ICICI is more risky and the investors investing in ICICI stocks have greater chances of bearing a loss than investors who invest in SBI and Nifty Bank Index. Further, Table 2 reveals that VaR figures in the first and third phases are close to each other for all three stocks at both confidence levels, showing that the stock price was stable and less risky before and after the financial crisis. Banking Index Nifty Bank Index SBI Index ICICI Bank Index 1515 15 Phase Phase 1 –4.207–2.932–4.823–3.359 –5.125–3.572 Phase 2 –8.378–6.032–8.653–6.214 –11.96–8.603 Phase 3 –4.005–2.799 –4.992 –3.507 –5.353–3.751 Table 2: VaR Through Variance-Covariance Approach (in \%) Level Next, market risk and exposure for the three indices were calculated by the other two approaches of VaR methodology to compare the results with that of variance-covariance approach. In accordance with variance-covariance approach, VaR figures obtained from historical simulation methods show that the magnitude of market exposure in the second phase (financial crisis period) was more than that in other two phases (Table 3). Similarly, the results of Monte-Carlo simulation as presented in Table 4 provide evidence for greater market turbulence in crisis period for all three stocks in comparison to the other two time periods, thus, again The IUP Journal of Applied Economics, Vol. XVII, No. 1, 2018 50 Banking Index Nifty Bank Index SBI Index ICICI Bank Index Phase 1515 15 Phase 1 –4.812–3.007 –5.85–3.362 –5.898–3.402 Phase 2 –8.153–5.598–9.499–6.438 –14.7–8.244 Phase 3 –4.229–2.642–4.845–3.463 –5.367 –3.537 Table 3: VaR Through Historical Simulation (in \%) indicating that in the financial crisis period, stock prices are more volatile and risky than in the pre-crisis and post-crisis periods. Further, as observed from Tables 2 and 3, VaR figures for ICICI Bank Index in both the approaches where found to exhibit greater chances of facing market turbulence than SBI and Nifty Bank Index. Therefore, ICICI Bank seems to be relatively more risky and prone to market failure than SBI and Nifty Bank Index. It is worth noting that the magnitude of market risk for SBI in the third phase is larger than the financial crisis period under Monte-Carlo simulation which is probably as a result of using higher initial seed value for SBI data in the post-financial crisis period. Moreover, high negative skewness and kurtosis in SBI returns during the third phase are the other possible reasons. Therefore, the left side of the tail of probability density function for SBI is flatter than right side of the distribution and thus, there is an indication for chances of higher market turbulence in this phase. From the above results, it can be concluded that all the three approaches confirm that financial crisis is found to be associated with greater market exposure, and therefore the chances of turbulence of Indian banking sector were more during the financial crisis period. Also, all the three techniques of estimating market risk reveal that ICICI Bank was more risky than SBI and Nifty Bank Index. Least chances of having maximum expected shortfall were found to be associated with the aggregate Nifty Bank Index. Level Banking Index Nifty Bank Index SBI Index ICICI Bank Index Phase 1515 15 Phase 1 –4.501–3.057–4.789–3.053 –5.279 –3.58 Phase 2 –9.022–6.519–9.906–7.692–12.694 –8.897 Phase 3 –4.229–2.815–16.02–10.863 –5.079–3.821 Table 4: VaR Through Monte-Carlo Simulation (in \%) Level 51 Equity Risk Exposure: A Case of Indian Banking Industry Backtesting VaR is the modern risk management model which measures the worst expected loss that a firm can face in a given period at a specific confidence level. However, there are various techniques of VaR to quantify the financial risk of any stock price, but we do not know which of the technique is applicable to which dataset and which sector of the economy. As mentioned earlier, Kupiec LR test is most commonly applied and used frequently to test the PoF. Therefore accordingly, Kupiec test was employed to check the validity of different VaR methods in the context of the Indian banking industry. Table 5 presents the results of backtesting. It is observed from the results of the full sample period that the variance-covariance approach and Monte-Carlo simulations do not fit the Nifty Bank Index data well. The LR value for both the methods is greater than the tabulated value at 1\% level of significance. 1 Similar conclusions of inadequacy and inaccuracy of VaR techniques for fitting the other two (SBI and ICICI) banking indices were found in both variance-covariance and Monte-Carlo simulation techniques. However, in the case of historical simulation technique, the results are insignificant for all the three indices, thereby exhibiting that historical simulation technique of VaR fits and accurately measures the market risk associated with Indian banking industry. The results provide clear evidence that least statistical noise in terms of applicability for Indian banking industry is found with historical simulations rather than the other two techniques. This is due to the fact that unlike variance- covariance approach and Monte-Carlo simulations, historical simulation technique is free from any restrictive assumptions like normality in returns which is not found for the Indian banking sector. Next, the Kupiec’s backtesting technique is applied on the three phases of all the three indices. This analysis on backtesting for the full sample period was carried out to observe 1 One point to note in backtesting estimation is that estimations in this study were made only at 1\% level of significance, the main reason for this being that at both 1\% and 5\% levels, same results were obtained. X 40 241 252424 13 245 LR- 8.277*35.24*9.29* 0.0090.0120.0126.606* 35.24* 13.842* Statistic Table 5: Backtesting Aggregate Indices – Kupiec Test Results Note: N = No. of trading days, X is the no. of exceptions, 2 0 .01 = 6.635, * indicates significance at 1\% level of significance. Variance-Covariance Historical Simulation Monte-Carlo Simulation Nifty Bank Index ICICI Bank Index N = 2453 SBI Index Nifty Bank Index SBI Index ICICI Bank Index Nifty Bank Index SBI Index ICICI Bank Index The IUP Journal of Applied Economics, Vol. XVII, No. 1, 2018 52 whether the bifurcation of sample period into three phases (viz., pre-crisis, crisis and post-crisis) has improved the validity of the VaR techniques to fit the Indian banking industry or not. Table 6 presents the results for checking the validity of variance-covariance approach to fit the Nifty Bank, SBI and ICICI indices. The results found that after bifurcating the sample period into crisis, pre-crisis and post-crisis time periods, variance-covariance method of VaR is found to become viable for all the three indices. From Table 6, it is observed that in all the three indices, the null hypothesis of no difference between the probability value and the observed ratio of number of exceptions to total observation is not statistically significant. Therefore, by dividing the full sample period into three phases (pre-crisis, crisis and post- crisis), the variance-covariance approach for estimating VaR seems to correctly estimate the market risk. The main reason for this is that the full sample period seems to reduce the VaR value by smoothening the aggregate fluctuations. Therefore, the number of worst exceptions due to financial crisis was more than the predicted probability value; as a result, the model was not found to fit the indices perfectly. By dividing the full sample period into three time periods according to the market conditions and market turbulences, in each phase, we have separate VaR figures and therefore the null hypothesis of accuracy and applicability of the variance-covariance model for the Indian banking sector is accepted. In Tables 7 and 8, the adequacy and validity of historical and Monte-Carlo methods of VaR are checked after dividing the indices according to three phases. Table 6: Backtesting Variance-Covariance Method – Kupiec Test Results Note: N = No. of trading days, X is the no. of exceptions, 2 0 .01 = 6.635. Phase Phase 1 Phase 2Phase 3 Banking Index Statistic N 7592861408 Nifty Bank Index X 15 319 LR 5.69 0.0071.565 SBI Index X 14 313 LR 4.377 0.00680.0858 ICICI Bank Index X 15 414 LR 5.689 0.4080.0005 53 Equity Risk Exposure: A Case of Indian Banking Industry In Table 7, like the counterpart results of backtesting of variance-covariance method, the value of LR statistic is less than the chi-square value at 1\% level of significance for all the three banking indices. Therefore, the null hypothesis is accepted and it is inferred that Table 7: Backtesting Historical Simulation Technique – Kupiec Test Results Note: N = No. of trading days, X is the no. of exceptions, 2 0 .01 = 6.635. Phase Phase 1 Phase 2Phase 3 Banking Index Statistic N 7592861408 Nifty Bank Index X 7 214 LR 0.0476 0.2920.0005 SBI Index X 7 315 LR 0.0476 0.00670.0595 ICICI Bank Index X 7 314 LR 0.0476 0.00680.0005 Table 8: Backtesting Monte-Carlo Simulation Technique – Kupiec Test Results Note: N = No. of trading days, X is the no. of exceptions, 2 0 .01 = 6.635, * indicates significant at 1\% level of significance. Phase Phase 1 Phase 2Phase 3 Banking Index Statistic N 7592861408 Nifty Bank Index X 11 114 LR 1.358 1.630.0004 SBI Index X 15 21 LR 5.689 0.29220.99* ICICI Bank Index X 13 421 LR 3.21 0.4084 2.985 The IUP Journal of Applied Economics, Vol. XVII, No. 1, 2018 54 historical simulation too after bifurcating the full sample period into three separate phases is applicable for the Indian banking indices. Similar results were found for the Monte-Carlo simulation which is based on Geometrical Brownian Motion for generating the return series. In Table 8, the results of LR test for Nifty Bank and ICICI indices are found to be statistically insignificant, thereby signifying that Monte-Carlo simulations work well for Nifty Bank and ICICI indices. Similar results are obtained for SBI index in the pre-crisis and crisis period. However, in the post-crisis period, different result is obtained. This is mainly due to the fact that in the third phase, SBI index showed greater negative skewness and the kurtosis was also quite high. Therefore, the resulting distribution will be highly negatively skewed. It is worth noting that although all the methods of VaR were found to accurately measure market exposure after dividing the sample into three phases, the number of exceptions was found to be least for the historical simulation technique than the other two methods. Therefore, the least statistical noise in applicability for the Indian banking sector seems to be associated with the historical simulations of VaR methodology both for full sample and sub-sample indices. Therefore, dividing the full sample to analyze the severity of financial crisis was found to improve the validity of the different VaR approaches for examining the market risk associated with Indian banking industry. It may be inferred that all the three approaches of VaR were found to predict the market exposure associated with Indian banking industry accurately. However, least chances of errors were found to be associated with the historical simulation method as compared to the other two methods. Therefore, the results of the study support the recommendation of the Basel Committee to use VaR models as an internal risk management tool. Conclusion Market risk and the associated exposure is a universal phenomenon in the world, however managing risk is purely an art. The present study tried to examine the market risk and exposure of NSE-Nifty Bank Index. The main reason for analyzing the Nifty Bank Index is its emerging importance in the Indian banking sector, especially after the 1990s. Although there are a few studies on BSE banking index, to the best of authors’ knowledge, no study is available till date that has analyzed the market risk and exposure of Nifty banking index. Additionally to have a robust analysis, the present study also compared the market risk of Nifty Bank Index with two largest banks, SBI and ICICI Bank (one from public sector and other from private sector) of India. In order to analyze the impact of financial crisis of 2008 on the Indian banking sector, the study divided the data for Nifty, SBI and ICICI Bank indices into three time periods (pre-crisis, crisis and post-crisis periods). Given the applicability 55 Equity Risk Exposure: A Case of Indian Banking Industry and authenticity of VaR methods, the present study used VaR methodology to quantify the market exposure associated with the Indian banking industry. Further, by using the backtesting technique via Kupiec test, the study tried to investigate which of the VaR methods fits the Indian banking index well. In accordance with the financial theory, the study found inverse relation between the VaR figures and level of significance. As expected, the results of all the three techniques of VaR methodology (variance-covariance, historical simulation and Monte-Carlo simulation) provide evidence of greater market risk and exposure of Indian banking industry in the financial crisis period of 2008, thus signifying the severity of the financial crisis of 2008. The crisis period was found to be associated with double chances of having a loss than the pre-crisis and post-crisis periods. The study found similar results for all the three banking indices through all the three approaches of VaR. Therefore, the presence of uncertainties during the financial crisis of 2008 was found to hamper the economic performance of Indian banking sector. Among the three indices, ICICI was found to be more prone to market risk than the SBI and Nifty Bank Index. Aggregate Nifty banking index was found to be relatively safer index than the ICICI and SBI indices. The Kupiec’s backtesting test results revealed that variance-covariance and Monte-Carlo simulation could not perform well for the whole aggregate data for all the three indices. However, the value of LR for historical simulation test was found to be insignificant, thus indicating that it fits the data well. This is mainly due to the fact that the variance-covariance method and Monte-Carlo simulations are based on restrictive assumptions like normality which are not satisfied in the present case. 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Varma J R (1999), “Value at Risk Models in the Indian Stock Market”, Indian Institute of Management, Ahmedabad. 20. Woller J (1996), “The Basics of Monte Carlo Simulations”, Physical Chemistry Lab , Spring, University of Nebraska-Lincoln. 21. Yang N (2010), “Empirical Study of Value at Risk of Chinese Stock Market”, M.Sc. Business Economics, Finance Track, Universiteit Van Amsterdam. Reference # 05J-2018-01-03-01 Copyright ofIUP Journal ofApplied Economics isthe property ofIUP Publications andits content maynotbecopied oremailed tomultiple sitesorposted toalistserv without the copyright holdersexpresswrittenpermission. However,usersmayprint, download, oremail articles forindividual use. Topic: Risk Management and Governance in a Global EnvironmentAssignment must be worded and look exactly like the Annotated Bibliography template provided. The five aricles are provided also. e Macroprudential stability indicators of financial systems: Analysis of Bosnia and Herzegovina and Croatia Merim KASUMOVIĆ University of Tuzla, Bosnia and Herzegovina [email protected] Mirna MEŠIĆ Zott SE & Co. KG, Bosnia and Herzegovina [email protected] Abstract. The introduction of macroprudential stability indicators for risk estimation in financial systems is a hot topic in transition countries. Our examination is focused on the repeating rate of instability in financial systems in Bosnia, Herzegovina and Croatia based on the selection of appropriate macroprudential indicators. Empirical investigation analyzed the statistical data of the National Bank of Croatia and the Central Bank of Bosnia and Herzegovina for the period of ten years between 2003 and 2013. With multivariate logistic regression we create a model based for determination of probability of the occurrence of instability in financial systems based on real values of macroprudential indicators. Keywords: macroprudential analysis, system risk, financial system. JEL Classification: E02, B26, E63, G32. Theoretical and Applied Economics Volume XXV (2018), No. 1(614), Spring, pp. 41-54 Merim Kasumović, Mirna Mešić 42 Introduction The global financial crisis, which escalated in 2008, upset both the financial markets as well as the theorists who analyzed it. Although it was certain that the crisis was not an isolated occurrence, the speed by which the crisis expanded through the global financial system, covering a wide range of financial institutions, prompted an interesting discussion in academic circles. The causes for the financial crisis are many, however, one of the most significant causes is the risk perception by the many participants in the market. Innovations in the field of risk management gave confidence to careless financial analysts with a false certainty that changes of the financial risk assessment model would eliminate business risks in financial markets. Exposure assessment of risks based on time series which do not contain a complete business cycle, and discounting the specifics of the risk distribution in financial markets created an unrealistic base for analyzing the exposure to system risks. Many years of stable growth and low inflation encouraged investors to switch to investments with more risk. At the same time, financial engineering created new financial instruments where risk degree was hard to estimate (1) even by experienced agencies such as Moody’s and Standard & Poor’s. Aforementioned trends slowly led the system to even larger and greater system risks, while giving a false impression of safety and prosperity. Our attention is focused on how the financial system reacted on the occurrence (in this case the crash on the mortgage markets) and led to an extensive growth of instability that many authors describe as “financial contagion”. There are different points of view in terms of the potential consequences from the connection of financial institutions through claims. On the one hand, authors claim that it leads to strengthening of the stability position of the financial market. In addition, disturbances which would occur in a single region or financial institution would be spread onto a larger number of institutions which would be ready to absorb loses. (Allen and Gale, 2000: 1-6) On the other hand, many authors condemn the new trends in development of the theory of stability of the financial system, pointing out that the interconnection between financial institutions is a catalyst for fast growth of financial disorder (Dasgupta, 2010: 2-6). Many authors point out that financial regulations improved the management of risks at the level of single institutions, but at the same time led to uniform reactions of financial institutions. Since the current regulations primarily focus on the problem of adequate capitalisation and achievement of an adequate level of liquidity, it can prompt a mass sale of certain financial instruments. Due to such an occurrence, the financial institutions lean towards an adequate structure of risk weighted assets. Only instruments with the highest risk degree would be sold. This would result in a price drop of specific segments of the financial market. In this case the regulatory framework which is designed to control risks, can lead to a crash of endangered segments of the financial system. In this way the financial system stops working as a safety network, which absorbs risks, and becomes the cause for further deepening of the crisis. Macroprudential stability indicators of financial systems: Analysis of Bosnia and Herzegovina and Croatia 43 For the purpose of this paper we will follow the middle path and agree on the fact that the interconnection between financial institutions contributes to the formation of financial systems which is at the same time immune to low instabilities, but fragile in cases where serious disturbances occurred. In the chapter “System risks and stability in financial networks” authors Acemoglu, Ozdaglas and Tahbaz-Salehi introduce a model that shows a dual effect of the current regulatory framework to the preservation of stability of the financial system. According to their model, more complex financial systems can amortize impacts while their number and intensity is small. But if the toleration level is exceeded, the financial system becomes a mechanism for spreading instability, to the level where the question is if the externalities exceed the benefits of the current type of regulation. (Acemoglu et al., 2013: 2-4). We can conclude that financial regulation has generally contributed to reduction of the management risk of financial institutions, but at the same time, with their actions, increased the importance of proper understanding of system risks. Due to the fact that individual institutions are not able to manage system risks, it is necessary to implement instruments for evaluation and management of system risks on a macroeconomic level, which is actually the mission of the macroprudential analysis. The researched element in this paper is the role of macroprudential analysis as an instrument for limiting system risks, as well as risks which endanger the functionality of the financial system as a unity. The term macroprudential analysis derives from the words prudencija (lat. Prudens-prudence, foresight, experience) and macroeconomics (gr. Macro, oikonomia), which draws attention to the attempt to widen the financial regulation framework and the risk estimation in financial markets with the analysis of macroeconomic variables. The use of macroprudential indicators contributes to the neutralization of instabilities through:  Prevention of financial disturbance escalation and building a fast and efficient defense against spreading consequences for instability of the real sector  Identification and evaluation of risk exposures, as well as the connection between risks that could lead to risk overflow between different segments of the financial market that could lead to malfunction of the financial system as a unity. The basic guidelines of macroprudential policy are:  The goal of macroprudential analysis represents a respond to a system risk and to risks which endanger the functionality of the whole financial system.  The research field of macroprudential analysis is the whole financial system as well as its interactions with the real sector.  The key instruments for the implementation of the analysis are macroprudential indicators. So far there are identified a large number of macroprudential indicators divided in six categories:  Indicators of economic growth.  Indicators of payment balance.  Inflation degree. Merim Kasumović, Mirna Mešić 44  Expansion of loans and real estate prices.  The effect of financial contagion.  Interest and exchange rate. Our goal in this research is to determine whether monitoring the value of macroprudential indicators can help predict instability in the financial system. The main research hypothesis is: Based on the analysis of macroprudential indicators the probability of recurrence of instability of the financial system can be determined. Macroprudential indicators are independent variables within the framework of the basic research hypotheses. For the independent variable the following macroprudential indicators were selected: real annual rate of growth, balance per unit of GDP, the ratio of reserves to debt, the average annual inflation rate, interest rate volatility, the volatility of national exchange rates, the rate of expansion of public loans, and real estate price index. The probability of instability in the financial system is a dependent variable. The dependent variable, the probability of occurrence of instability in the financial system, takes its values in the interval between 0 and 1. The financial system is considered stable, according to the theory of business cycles, if it is in a phase of expansion or the top, and as unstable if the business cycle is at the bottom or in contraction. For the purpose of the research section of this paper we will use the statistics of the Central Bank of Bosnia and Herzegovina and the Croatian National Bank, for the period 2003-2013 year. As the main statistical methods will use multivarious logistic regression. With logistic regression, we will try to establish a model for determining the probability of occurrence of economic uncertainty, depending on the selected variables. Empirical research In the empirical part of the paper we examine the probability of occurrence of instability in the financial systems of Bosnia and Herzegovina and the Croatian Republic on the basis of the selection of appropriate macroprudential indicators. With multivariate logistic regression we will create a model to determine the probability of occurrence of instability in the financial system based on the current value of macroprudential indicators. Multivariate logistic regression is used to determine the probability that the dependent variable is found in the requested state, depending on the n independent variables. The mathematical model of logistic regression can be represented in the following form: B : V ; L 5 > where z is: V L∑ : @ 5. In the model, the variable x is the exposure to the risk factor set, and f (z) is the probability of a certain result with regard to the risk factor set. Therefore, the variable z is a measure of the overall contribution of the risk factors that were used in the model (Kvesić, 2012: 321). Macroprudential stability indicators of financial systems: Analysis of Bosnia and Herzegovina and Croatia 45 The model is due to mathematical transformation (2) reduced to the following form: 2 : U ; L1 1 E A ? : >∑ 8 - ; where: P (Y) is the probability of occurrence of favourable events; e is the base of the natural logarithm; α is the independent member of the equation; βi is the coefficient of the independent variable; Xi is the independent variable. By determining the coefficients of the independent variable and independent member of the equation the forecasting model is obtained. The condition of application of the logit model is that the independent variable is dichotomous, i.e. that it can take only two values, which is for this model needs to be quantified as a value of 0 and 1. The dependent variable of this research is the probability of occurrence of instability of the financial system. In accordance with the requirements of the model we differentiate two states in which the financial system can be. If the financial system is stable the independent variable takes the value 1, otherwise it takes the value 0. A stable financial system will be defined as a system in the expansion phase including the phase of reaching the peak of the business cycle. An unstable system is a system in the contraction phase, including the phase of reaching the bottom of the business cycle. For the independent variable were selected following macroprudential indicators: real annual rate of growth, balance deficit per unit of GDP, the ratio of reserves to debt, the average annual inflation rate, interest rate volatility, the volatility of the national exchange rate, the rate of expansion of public loans, real estate price index. By determining the coefficients of the independent variable determine the importance of each indicator by determining the probability of financial system stability. Unlike linear regression, logistic regression assumes a linear relationship between the dependent and independent variables. Since the largest number of macroprudential indicators that will be used to create the model has a cyclic characteristic it is appropriate to use just logistic regression. The advantage of this method lies in the fact that it does not use the Gaussian distribution as its base, which can lead, as we have previously stated, to an inadequate nature assumption of risk in financial markets. Specifics of financial environment of Bosnia and Herzegovina and Croatia Before we approach the development of models for determining the probability of occurrence of instability in the financial markets, we will analyze financial systems in the before mentioned countries. The degree of financial market development can be measured in different ways. Most often as indicators of development are taken: the complexity of the financial structure; Merim Kasumović, Mirna Mešić 46 development of the banking system; sophistication of the capital market; the ratio between the banking system and the capital market, the presence of non-bank financial intermediaries (Šonje, 2005: 48-58). The financial system of Bosnia and Herzegovina is built on the principles of the continental model of organization of the financial markets. This model is characterized by the dominant role of banks as a key player in the financial market. In addition to the banks in the financial market of Bosnia and Herzegovina there are also investment funds, insurance companies and reinsurance companies, microcredit organizations and leasing companies. The participation of banks in the assets of the sector ranged from 85.61\% to 86.56\% in the past three years. After the banks, the most important participants in the financial market are insurance companies, whose relative share in the assets of the sector grew in this period from 4.61\% to 5.11\%. Assets of leasing companies have been decreasing, and are reduced to only 3.24\% at the end of 2013. Microcredit organizations and investment funds participate in the total supply of financial services with a share of less than 3\%. In the observed period, the share of banks in the total supply of financial services in the market of Bosnia and Herzegovina amounted to 85.95\%, which shows that the sector of non-banking institutions is weak developed. As for the organization and regulation of the capital market, it is compounded, organized and multilayered. By the vertical principle there exist two levels, and by the horizontal principle tree. At the state level there are: the Central Bank, the Deposit Insurance Agency and the Agency for assurance. The second level is divided into two separate markets. There are two stock exchanges (Banja Luka and Sarajevo) that are independent and act independently from one another. Regulatory authorities are doubled, so that there are two Securities Commissions, two Registries of Securities and two Banking Agencies (ABRS and FBA). Market participants are active in both markets, but are subject to control and reporting on a geographic basis, depending on the residence. Organizational parts of unregulated institutions by territorial jurisdiction. Organizational parts subject to the regulatory institutions by territorial jurisdiction (Kumalić, 2013: 69). Shares represent the dominant securities, primarily thanks to the privatization process, which as a result has produced exactly this type of securities. The main characteristic of the shares traded on the stock exchanges in Bosnia and Herzegovina are expressed in their poor quality, which is in the discrepancy between their nominal value and market value (Omerhodžić, 2008: 307). The first bond turnover on the stock exchanges in Bosnia and Herzegovina was registered year 2009. Two years later, the entity governments broadcasted treasury bills, which was the first trade of short-term financial instruments on the market. Bosnia and Herzegovina as a small country with a small market capacity, double institutions and poor coordination, cannot be classified as high-quality financial market. Regardless of the development of some qualitative indicators, the financial market in Bosnia and Herzegovina is basically shallow, underdeveloped, compounded, dysfunctional, centered in banks with high concentration of the banking sector (Kumalić, 2013: 69). Macroprudential stability indicators of financial systems: Analysis of Bosnia and Herzegovina and Croatia 47 Specifics of financial environment of Croatia If we compare the financial system of Bosnia and Herzegovina and the Croatia, we can notice that both countries have a similar base structure. As before, the importance of certain groups of intermediaries in the financial market will be measured by the share of their assets in their total financial sector assets. In Croatia, the banks play a dominant role, so that the Croatian financial system is classified into financial systems with continental structure. The share of assets of commercial banks in the total amount of assets of the financial sector ranged from 76.90\% to 73.95\%. It is interesting to note that the share of commercial banks fell in favour of the non-banking sector. So that the non-banking sector at the end of 2013, covered more than a quarter of the financial market. The trend of strengthening the non-financial sector is present in more advanced financial systems. From the table above it is possible to see that this strengthening was useful for pension insurance companies whose relative share climbed from 7.75\% to 10.68\% in the reporting period. Insurance companies are also making progress from 6.04\% to 6.49\%. The regulatory framework of the financial system is complex. The Croatian National Bank conducts supervision of credit institutions and supervise payment operations, and regulates the amount of money in circulation. The local currency is the Croatian Kuna, whose exchange rate is formed depending on the supply and demand for funds in the given currency. Banks (and the state) casual trade with foreign currency with the National Bank of Croatia, either directly or on so-called. Foreign exchange auctions, and the National Bank regulates through these transactions the price of the domestic currency in the foreign exchange market (3). Supervision of the non-banking sector was organized by the Croatian Agency for Supervision of Financial Services (HANFA). Croatia has a fairly developed money market and capital market. All transactions are conducted through the Zagreb Stock Exchange. Similar to Bosnia and Herzegovina, the highest number of transactions on the Stock Exchange relating to the purchase and sale of shares, while the rest consists of selling bonds, commercial paper, certificates and rights. Trading is handled completely electronically. Responsible for proper settlement of trade transactions in the domestic capital market is the Central Clearing Depository Association. Analysis of selected macroprudential indicators Using instruments of descriptive statistics, we will analyse the collected data. For each indicator we calculated the minimum value, maximum value, the arithmetic mean and standard deviation. Since we intend to use the data for forming multivariate logistic model it is necessary to check the degree of correlation between the selected indicators. The degree of correlation measures the relationship between two variables. Logarithmic models give the best results when there is no correlation between the individual indicators. A high level of correlation data shows that it is possible to simplify the model, eliminating one of two variables that are mutual dependent. Merim Kasumović, Mirna Mešić 48 In the analysis of macro prudential indicators of Bosnia and Herzegovina, we observe a strong negative correlation between rations of reserves to foreign debt and the amount of public debt per GDP unit (-0.948). Among the analyzed data for Croatia, the amount of average annual interest rate is correlated with the annual rate of growth, the value of reserves by the rations of foreign debt and public debt per unit of gross domestic product, so we can conclude that the model would not have lost much of its relevance if you leave out this variable. Comparative analysis of macroprudential indicators of Bosnia and Herzegovina and Croatia If we compare values of macroprudential indicators we can notice that in Croatia much larger variations in value of annual growth rate were recorded than in our country. Bosnia and Herzegovina in past 11 years achieved biggest growth rate of 6.30\% in 2004. Croatia achieved top of her business cycle in 2003, when general growth of goods and services of 5.4\% was recorded. By following just this macroprudential indicator we can perceive that the reactions of market are very slow. Effects of global economical crisis led to a decline of growth rate in 2009, when the negative growth rate of -7.4\% was recorded in Croatia and -2.7\% in Bosnia and Herzegovina. As we mentioned before, a balance deficit by unit of gross domestic product is derived measure of stability of financial system. It gives us an insight in which amount the deficit of balance of payment is significant through comparison with total production of goods and services of certain country. From the attached data we can perceive that in both countries outflows of balance of payment surpassed inflows, videlicet that both countries recorded payment-balance deficit in last 11 years. Bosnia and Herzegovina really stands out by very high deficit values which in 2003 reached 19.40\% GDP. It is important to highlight that the deficit by unit of gross national product has significantly declined after 2009. It is interesting to compare values of raid reserves by debt. Bosnia and Herzegovina, in the observed period, was covering every KM of public debt with 1,114 KM of national reserves. If we observe the movement trend of this indicator, we can notice that in the period from 2006 to 2008 conservative debt policy was conducting and that the raid took very high values (from 1.34 to 1.69). In Croatia the national reserves are significantly lower and they are on average 26.6\% of public debt. This indicator showed small variations in observed period as it was indicated by standard deviation of 0.033. Price levels in Croatia and Bosnia and Herzegovina have a tendency of gradual growth. Croatia recorded significant rise in level of inflation of 6.1\% in 2008. In Bosnia and Herzegovina two sudden rises of price levels were recorded. In 2006, a level of inflation of 6.1\% was recorded, while in 2008 the level of prices raised by 7.4\%. In next year a partial correction of price levels was recorded which influenced on deflation of 0.4\%. If we look the growth trend of interest rate in Croatia we can notice three phases. In period from 2003 to 2008 interest rates were moving between 4.5 and 4.88\%. In 2008 the interest rate raised up to 9\%. This interest rates level kept for next three years, whereupon the gradually decreasing of interest rate to 7\% came. Rise of interest rates in period of ingoing of crisis is in accordance to increased risk of management in period of financial stress. Macroprudential stability indicators of financial systems: Analysis of Bosnia and Herzegovina and Croatia 49 Interest rate level which was recorded in Bosnia and Herzegovina doesnt follow this form. Highest values of interest rates were recorded in 2003, when interest rate was 10.50\%. Another unit of indebtedness of country is public debt by unit of gross national product. Again, we can notice that Croatia has a significantly higher affinity towards debt. On every kuna of national product this country took over 81.25 lipas of public debt. In Bosnia and Herzegovina the situation is remarkably different. For every KM gross national product Bosnia and Herzegovina took over on average 23.5 pfening of debt. This indicator showed sudden rise of values in both countries in 2009 which is in accordance with expectations that the state will took over additional financial funds in order to take actions against the crisis. In Croatia the public debt is increased from 84.30 to 100.40, while in Bosnia and Herzegovina rise from 17 to 21.5 was recorded. Determination of possibilities of instability appearances in financial system of Bosnia and Herzegovina and Croatia Based on previously presented data for Bosnia and Herzegovina multivariate model of logistic regression was crated: 2 : U ; L1 1 E A ? : 7 : =, = > =, 9∗ - > 7, ;∗ . ? 5 8 4, 8∗ / > 6, <∗ 0 ? 4, =∗ 1 ? ;, :∗ 2 ; Biggest informative significance for financial instability in financial system of Bosnia and Herzegovina probability evaluation has reserve ratio towards external debt. Negative value of coefficient of independence variable (β3=-140.39) shows that with reducing of reserves or debt increase the probability of instability in financial system increases. By increasing of public debt by unit of gross national product stability of financial system is disturbed. On the other side real annual growth rate and decrease of payment-balance deficit are having positive values of coefficients which shows that their growth increases probability that the financial system remains stabile. Average inflation rate in observed period has increased by 2008, after which the decrease of inflation rate was recorded. Because of this in logistic model inflation rate growth is in positive relation with system stability increase (β4 = 2.84). By using identical methodology the model for determination of probability of instability appearances in Croatia was formed: 2 : U ; L1 1 E A ? : 7 6 =, 7 > 5, :∗ - ? 4, ;∗ . ? : =, 7∗ / > 6, <∗ 0 ? 7 :, ;∗ 1 ? 5, 6∗ 2 ? 4, 8∗ 3 ? 4, 5∗ 4 ; Biggest informative significance has the reserve ratio towards foreign debt. Negative value of coefficient of independent variable (β3 = -69.3) shows that by reducing of reserves or by increasing public debt the probability of instability in financial system increases. In model the value of coefficient of exchange rate stands out (β5 = -36.7). Decline of course of Croatian kuna in accordance to euro indicates the decline of Croatian financial system. Average inflation rate has a positive coefficient (β4 = 2.8). Every decrease of inflation rate by 1\% increases the probability of crisis ingoing in financial system by 2.8 times. Merim Kasumović, Mirna Mešić 50 Concluding remarks In this paper we have primarily dealt with the issue of financial system stability conservation. We have focused on analysis of system risks as well as on risks which endanger the functioning of financial system as unity. As an answer on question how to follow position of system risk in financial system of certain country, we have set the process of macroprudential analysis. This process means the tracking of system risk by selected macroeconomical indicators. By calibration of standard values of macroprudential indicators it is possible to identify disorder on certain segments of financial markets on time, but, also, we can analyze movement of whole business cycle. Development of quality prudential model and its constant perfecting is basic assumption for sup and control on financial market. In research part of the paper we tried to give humble contribution to development of macroprudential analysis on the territory of Bosnia and Herzegovina and Croatia. Our hypothesis was to determine is it possible to determine, by tracking of values of macroprudential indicators, probability of instability appearances in financial system. We have confirmed the hypothesis by conducting two independent mathematical models, one for the financial system of Bosnia and Herzegovina, and other for system of Croatia. Models which we conceived are having an assignment to determine probability of instability appearances in financial system on the base of given values of macroprudential indicators. Featured models are based on equation of logical regression. Taking into account the fact that logistic distribution is by its nature nonlinear, and that it is not based on Gaussian distribution, we can use it for risk position simulation on financial market. Most of the analyzed indicators proved to be significant for determination of stability position on financial market of Bosnia and Herzegovina and Croatia. Biggest informative significance in models which we created had the reserve ratio to debt, annual growth rate and average annual inflation rate. It is determined by research that by reserve reduction or public debt increase the level of stability in financial system decreases. We have also confirmed that positive growth rate of gross national product and stable inflation level are indications of stabile financial system. Despite these indicators, the height of currency exchange of local currency in accordance to euro proved to be significant for position of stability determination in financial system of Croatia. The weakening of kuna course in accordance to euro indicates on weakening of financial system of Croatia. Furthermore, it has been found that the model could be simplified by eliminating one out of two indicators which showed a high level of mutual correlation. In accordance to our research it has been determined that it is not necessary to follow height of public debt by gross national product unit in neither of listed models, since the position of debt is already covered by ratio of reserve to foreign debt. On territory of Croatia we can exclude the interest rate level analysis from the model because it has been proved that analysis is in the direct relation with gross national product growth. We are hoping that this paper will stimulate researchers to turn to similar analyzes which would try to improve the quality and informative significance of macroprudential models. Macroprudential stability indicators of financial systems: Analysis of Bosnia and Herzegovina and Croatia 51 By expanding time series and covering more business cycles could be given a more reliable model. Also, by including more macroprudential indicators in faze of preliminary research and by subsequent elimination of indicators which are showing high level of correlation it is possible to increase the informative significance of model. Macroprudential analysis of individual segments of financial markets could give an insight in financial market structure. Tracking of macroprudential narrow range indicators, based on time series which would contain several business cycles, would enable better comprehension of financial stress expansion from one segment to other. On this way using the macroprudential analysis financial system infection and the way in which the disorder leads to a financial system crisis could be explained. An interesting research could be conducted by testing the prognostic values of this model type. It would be necessary to determine if model created on macroprudential indicators base can provide timely information about onset of crisis probability. Creation of prognostic models would enable the regulation which would be aimed to balance the business cycle, unlike the intervention which is aimed to repair the collapse of financial market consequences. Although we could not avoid business cycle recession, a timely information about aggravation of conditions on financial market and system risk increase could enable better entry into recession of business cycle phase. Notes (1) It is recognized that the original market disruption was caused by the expansion of mortgage loans that are following the process of securitization put into circulation in the financial market. Securitized bonds represented financial assets of underrated risks, highly sensitive to movements in the real estate market. (2) Logarithming, i.e. equating the natural logarithms of the left and right sides of the equation it is possible to transform the equation into a form that is easier to interpret and process the data. For a detailed look at this process (Kvesić, 2012: 321-232). (2) Croatian National Bank; The financial system of the Republic of Croatian http://www.hnb.hr/ financijska_stabilnost/hfinancijka_sustav-1.htm References Acemoglu, D., Ozdaglar, A. and Tahbaz-Salehi, A., 2013. Systemic Risk and Stability in Financial Networks, National Bureau of Economic Research, Cambridge. Achary, V., Engle, R. and Pierreta, D., 2013. Testing Macroprudential Stress Tests: The Risk of Regulatory Risk Weights, National Bureau of Economic Research, Cambridge. Aiyar, S., Calomiris, C. and Wieladek, T., 2012. Does Macro-Pru Leak? Evidence from a UK Policy Experiment, National Bureau of Economic Research, Cambridge. Allen, F. and Gale, D., 2000. Financial Contagion, Journal of Political Economy, Chicago. Merim Kasumović, Mirna Mešić 52 Alpanda, S., Cateau, G. and Meh, C., 2014. A Policy Model to Analyze Macroprudential Regulations and Monetary Policy, Bank of Canada, Ottawa. Backus, D., Chernov, M. and Zin, S., 2013. 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Merim Kasumović, Mirna Mešić 54 Annexes Macroprudential indicators of financial stability of Bosnia and Herzegovina Review of macropru- dential indicators 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 GDP, real annual growth rate (\%) 3,80 6,30 3,90 6,10 6,00 5,60 -2,70 0,80 1,00 -1,20 1,60 Current balance of balance of payment (\% GDP) -19,40 -16,30 -17,10 -7,80 -9,00 -14,10 -6,50 -6,10 -9,70 -9,30 -5,50 Reserve ratio towards foreign debt 0,70 0,86 0,97 1,34 1,69 1,48 1,19 1,03 0,96 0,91 0,95 Average annual inflation rate 0,60 0,40 3,80 6,10 1,50 7,40 -0,40 2,10 3,70 2,10 -0,10 Height of average annual interest rates 10,50 9,90 9,00 7,70 7,00 7,40 8,10 7,80 7,10 6,70 - Public debt by GDP unit 27,70 25,50 25,30 21,10 18,00 17,00 21,50 25,30 25,80 27,80 28,30 Source: Statistics of Central bank of Bosnia and Herzegovina. Macroeconomic stability indicators of financial system of Croatia Review of macropru- dential indicators 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 GDP, real annual growth rate (\%) 5,40 4,10 4,20 4,80 5,20 2,10 -7,40 -1,70 -0,30 -2,20 -0,90 Current balance of bilance of payment (\% GDP) -6,20 -4,20 -5,20 -6,50 -7,20 -8,80 -5,10 -1,10 -0,90 -0,10 0,90 Reserve ratio towards foreign debt 0,33 0,28 0,29 0,29 0,28 0,22 0,23 0,23 0,24 0,25 0,28 Average annual inflation rate 1,80 2,10 3,30 3,20 2,90 6,10 2,40 1,10 2,30 3,40 2,20 Exchange rate on 31.12. (HRK: 1 EUR) 7,65 7,67 7,38 7,35 7,33 7,32 7,31 7,39 7,53 7,55 7,64 Height of average annual interest rate 4,50 4,50 4,50 4,50 4,88 9,00 9,00 9,00 7,83 7,00 7,00 Public debt by GDP unit 36,30 38,20 71,20 73,90 76,80 84,30 100,40 103,30 102,60 102,10 104,70 Index of real estate prices 67 74,4 82,8 97,5 109,2 113 108,8 100 96,3 97,3 81,2 Source: Statistics of National Bank of Republic of Croatia. 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The five aricles are provided also. 71 RISK MANAGEMENT LESSONS FROM THE FINANCIAL CRISIS: A TEXTUAL ANALYSIS OF THE FINANCIAL CRISIS INQUIRY COMMISSION’S REPORT Corey J. Fox Texas State University • San Marcos, TX ABSTRACT There have been several retrospective analyses o f the financial crisis. An area that continues to receive attention is the failure o f risk management in financial firms at the heart o f the crisis. After the crisis, the United States Government convened the Financial Crisis Inquiry Commission to explore causes o f the crisis. Their conclusions have gone largely unexplored, especially in academic research. In this study, I first examine the comm ission’s report on the crisis identifying several re­ appearing themes. An exploratory follow-up analysis looking at financial and non- financial firms suggests non-financial firms have areas to improve upon compared to their financial counterparts. Keywords: Financial crisis; Risk management; Risk management failure; Financial Crisis Inquiry Commission; FCIC “ Those who cannot remember the p a st are condemned to repeat it. ” - George Santayana (Philosopher) INTRODUCTION The financial crisis o f 2008 and 2009 was the worst financial disaster to hit the United States in over seven decades. Organizations o f all types were impacted as the events in the financial industry rippled throughout the economy. The crisis left the economy in shambles, dissolved trillions o f dollars in wealth, and left millions o f people without jobs and homes (Financial Crisis Inquiry Commission [FCIC], 2011). There have been many opinions about what the root causes o f the crisis were (Jickling, 2009). While some recent research has suggested that excessive investment in financial products (both ordinary and exotic) were a considerable culprit (e.g., Tuckman, 2016; Vo, 2015) there has been much less work focused on the impact that risk management failures at the managerial level had on failing financial firms (e.g., Hubbard, 2009). In 2009, the U.S. Government commissioned a committee to look into the Journal o f Business Strategies causes o f the financial crisis. This committee, known as the Financial Crisis Inquiry Commission (FCIC), gathered and analyzed a myriad o f data before putting out a complete report based upon their extensive analysis, outlining what it believed to be the main causes o f the crisis. While this report was made public, there has been little exploration or discussion o f the findings in academic circles (per mention in academic research papers) especially as it relates to risk management within organizations. This is unfortunate since the report is built upon a vast amount o f information and has implications for management practices related to the management o f risk. As suggested by the quote above from George Santayana, it is thought that finding a cause(s) can help businesses learn, and hopefully avoid, making the same (or similar) mistakes in the future. The purpose o f this paper is to look, qualitatively, at the comm ission’s in-depth report, analyze the passages around risk management and discuss the implications o f the findings. Additionally, this paper explores whether financial and non-financial firms have learned from the failures identified in the commission’s report. The purpose behind expanding the study beyond just the large financial firms associated with the crisis, was to assess the degree o f learning (if any) at other large, visible firms. The organizational learning literature (Huber, 1991; Madsen and Desai, 2010) has suggested that firms can make adaptations to its business operations and strategy as a result o f reflections on their own experiences (experiential learning) or the experiences o f others (vicarious learning). Financial institutions that were at the center o f the crisis (such as the large financial firms and large regional banks) should be most likely to have made adaptations post crisis. However, we might also expect that other large, visible firms would make adaptations due in part to what they learned from the failings o f these financial firms. However, the changes may be less pronounced since those firms were further away from the actual learning event. In doing so, this paper makes three important contributions to the extant literature in risk management and organization studies. First, this paper adds to what is currently known about risk management failure, and more specifically risk management failure during the financial crisis. While much has been made about the failure o f complex quantitative risk management systems, less is known about managerial-level failures. Second, this paper synthesizes and condenses a broad array o f disparate statements in the FCIC report on risk management during the crisis into a small set o f important risk management issues. These issues are described and discussed in detail so that managers and organizations (in all industries) can learn from the mistakes o f these failed institutions. Last, there are prescriptive remedies given to help companies avoid risk management failures in the future. 73 RESEARCH BACKGROUND The Commission Following the financial crisis, the US government convened a commission known as the Financial Crisis Inquiry Commission (FCIC), to examine the causes o f the crisis. The FCIC was commissioned by the Fraud Enforcement and Recovery Act of 2009 and tasked with conducting a thorough investigation into the causes of the financial and crisis.2 The commission worked together for over 18 months gathering data from a multitude of sources and conducting interviews with people involved at various stages and levels o f the crisis. Over that time frame, the commission scoured over millions of pages o f documents, including the work of journalists, academics and other published sources. The commission interviewed more than 700 material ‘witnesses’ and conducted numerous public hearings across the country in an attempt to learn about what happened. Despite the widely held belief amongst industry regulators that financial firms were prudent risk managers with sophisticated financial models who had strong ‘market’ incentives to undertake sound risk management practices, the risk management systems at these large firms failed. Risk management, like strategic management, is a process directed by the top managers of a firm during strategy formulation (Chapman, 2011). Risk management is generally described as an iterative, holistic process whereby firms identify, analyze, strategize, treat and communicate risks (Chapman, 2011; Frame, 2003; Shenkir, Barton and Walker, 2010; Shortreed, 2010). During the financial crisis, for many financial firms, there was a breakdown in the process. As a result, the following research questions were explored in this paper: 1) What were the contributing factors that led to fin a n c ia l firm s ’ risk management failures during the crisis? 2) Post crisis, have firm s (both fin a n c ia l a nd non-financial) learned fro m these failures? METHODOLOGY To explore the research objectives identified, I conducted two studies. In Study 1, I pursued a textual approach research methodology. The textual approach Journal o f Business Strategies examines texts to gain insights about events. This research approach has been used before to make sense o f events surrounding situations o f crisis (e.g. Gephart, 1993). The purpose o f Study 1 was to examine where the breakdown in risk management occurred at the large financial institutions who were at the heart o f the crisis. In Study 2, I pursued an exploratory analysis where four separate types o f firms were identified - large financial institutions, large regional banks, large non-financial companies with a dedicated financial services business segment, and large non- financial companies without a dedicated financial services business. For each group identified, three representative firms were chosen and a textual analysis o f these firms’ proxy statements from before and after the crisis was undertaken. The purpose o f Study 2 was to examine whether financial and non-financial firms had learned from the failures identified in Study 1. Study 1 First, I downloaded the entire FCIC report from the FCIC website (cited in the reference section). To find passages that were about risk management, I searched the text document for the phrase ‘risk m anage’ which would catch any reference to risk m anagement or risk manager. I also searched for two other variants o f risk management by searching for ‘managing risk’ and ‘manage risk.’ In total, there were roughly 103 instances in the body o f the main report o f 410 pages. A graduate assistant and I parsed these instances and pulled out the surrounding sentences to create a list o f passages. O f the 103 passages initially identified, 34 o f the passages (33\%) were identified as containing no substantive or relevant information to address the research question. Appendix A has several examples o f these passages, all o f which were excluded from consideration. An additional 30 passages (29\%) discussed other influences o f risk management failures beyond the scope o f this study. For instance, information about regulators or the institutional environment were outside the boundary o f the firm and thus subsequently excluded. The remaining 39 passages (38\%) were related to risk management inside the financial firms so were used for the analysis. The assistant and I looked for themes in each o f the passages. After initial analysis and conversations, five sources o f failure emerged. The first category was classified as Risk Management Process Failures. This category included any mention o f problems related to risk assessment, risk evaluation and analysis, risk treatment, or risk communication. This category also included any m ention o f problems with the firms existing risk management protocols. The second category 75 was classified as Support System Failures (Compensation). This category consisted o f passages showing failures in the firm ’s compensation system which may have had an impact on risk behavior. The third category was classified as Resource Allocation Failures. This category included any passage that described the human or financial resources allocated to support the risk management function. The fourth category was called Top Management Failures. This category focused on failures created by top management overconfidence and hubris. The fifth and final category was called Objective Tradeoff Failures. This category consisted o f passages focusing on the tradeoffs made between risk and financial objectives. To validate the categories and the correct assignment o f passages to categories, six undergraduate students, majoring in Finance with a concentration in Insurance and Risk Management at a large Midwestern university, volunteered to participate in exchange for extra credit. The students were randomly given between 12 and 14 passages where each passage was evaluated by two students. In addition to the passage, students were given the category titles and a description o f each category. In addition to the five categories mentioned above, an Other category was also included i f the student thought the passage did not belong in any o f the categories. Each student was instructed to place the passage into the category which they felt best described the passage. While it is certainly possible that some o f the categories could indeed be related with one another (for instance, compensation systems might impact whether a firm focuses on performance metrics or risk management outcomes), the purpose was to validate the themes surrounding risk management according to the FCIC report (i.e., what appeared most often). Across the six volunteers, agreement was obtained ju st over 73\% o f the time. There were four passages in which both students failed to classify the passage according to one o f the pre-specified categories. These passages were omitted from consideration, leaving 35 total passages. Any remaining passages where at least one student classified the passage according to the pre-specified categories and another did not, were resolved through discussion. R e s u l t s After the analysis was complete the passages were explored in relation to the five general themes which had emerged. Below is a discussion o f each general theme, each o f which is supported with reference to several representative passages which provided information to identify the theme. Several o f the themes are similar in nature and could be interpreted as being from relatively similar sources, however Journal o f Business Strategies an effort was made to try and segment the themes to be as fine-grained as possible. All of the supporting passages discussed can be found in Appendix A under the appropriate heading.3 Risk management process failures. The most often mentioned failure found in the report points to a general failure of the risk management process in financial firms. The risk management process, according to literature in finance and strategic management, is generally conceived o f as a holistic approach spanning the entire organization (e.g., Clarke and Vanna, 1999; Fraser and Simkins, 2010; Miller, 1998; Miller and Waller, 2003) and has been referred to by various names like Enterprise (ERM), Integrated (IRM) or Strategic (SRM) risk management. This process generally includes risk identification, assessment, evaluation, treatment, review and communication (Chapman, 2011). Passages within the report suggest that there were breakdowns in each of these areas in addition to using a holistic approach. During the financial crisis, firms were still subscribing to the antiquated ‘silo’ approach to risk management. The first general problem was that risks were being managed independent of one another without much information sharing across business lines. There is evidence of this shown in Passage 1 where Citigroup’s risk management function was operating independently along each of its separate business lines. Employees just steps away from each other, working with similar risk assets, or risk products which were related, did not know what each other were doing. Information that was gained from each business line with respect to the risk assets was being kept away from other sources that could potentially benefit from such information. A second area of concern was with the risk identification, assessment, evaluation and treatment process. For instance, as suggested in Passage 2 & 3, risk managers were not able to properly identify soft risks. Soft risks are those which require judgment and are not purely financial in nature. In too many instances, instead of using judgment, managers were using mathematical models as predictors for risks. Furthermore, the models being used to determine which risks should be managed were based on assumptions that were markedly wrong. There was little evidence of scenario planning in assessing the probabilities and worst case scenarios for home price declines. Lastly, as evidenced by additional passages, managers were comfortable using financial hedges as effective treatment strategies since it had the added benefit of reducing the amount of financial slack the firm had to hold. A third problem related to risk management processes was risk communication. Risk communication involves communication and consultation 77 between management and the individuals/departments responsible for implementing and carrying out the risk management strategy to make it more effective over time (Chapman, 2011). Prior research has found that having communication links between the governing parties o f the organization and those in charge o f risk management can increase efficiency and firm performance (Grace, Leverty, Phillips and Shimpi, 2015). During the crisis it was evident that in some firms, communication between the management team and the risk management department/team was less than ideal. In Passage 4 for instance, the executive committee at Lehman Brothers failed to include the com pany’s C hief Risk Officer in decisions that directly impacted the risk o f the firm. Finally, in some cases, the entire risk management process was inadequate and lacking. In one passage, a consultant hired to examine Bear Steam ’s risk management process was highly critical suggesting that key elements in the process, such as risk identification and assessment, were infrequent. He continued that the risk management function did not have the resources it needed (as discussed in more detail below) and was o f a low priority to the firm. Support system failu res (Compensation). One o f the most common systems for supporting goals and strategic decisions in organizations is the compensation system. In the management literature, executive compensation is a tool often used to align management interests with the interests o f the firm’s owners. Scholars in the risk management arena have similarly concluded that one way to focus m anagement’s attention on risk management is to align their compensation with risk management objectives and outcomes (Lam, 2014). Firms must reward risk management behavior through incentive structures which align good risk management practices with pay. Indeed, Grace and colleagues (2015) found evidence that firm performance was enhanced when compensation was aligned with risk management. There are numerous instances in the report which suggest that several o f the failed financial firms were not incentivizing good risk management, and instead were incentivizing more risky, short-term oriented behavior. Passages 5 through 7 highlight this notion. For instance, the head o f the Federal Deposit Insurance Corporation (FDIC) remarked that incentives favored short-term risk-taking and profits over long-term risk considerations, sustainability and solvency. Lam (2014) has suggested that incentivized performance can be problematic for risk management when incentives are one dimensional — they focus on a single, bottom-line figure. At the time o f the crisis, financial firms, in particular, tied aggressive pay packages filled with stock options to the price o f the firm’s stock. In many situations, the options granted to executives came with accelerated payouts. In 2006, one year Journal o f Business Strategies before the onset o f the com pany’s demise, Merrill Lynch CEO Stanley O ’Neal made $91 million. When he walked away from the company as it began its decline he left with a total consolation package o f $161 million (Farrell and Hansen, 2009). Richard Fuld, CEO o f Lehman Brothers, was awarded $34 million before he departed. These kinds o f pay structures, littered with stock options, created incentives to increase the amount o f risk executives took to improve returns. This included greater leverage levels and, in some cases (e.g. Frannie and Freddie), fraudulent financial filings. Indeed, academic research has argued that executives at Bear Steams and Lehman Brothers in particular, had incentives to take on large amounts o f risk as they had already pulled out hundreds o f millions o f dollars in options and bonuses prior to the collapse (Bebchuk, Cohen and Spamann, 2010). Resource allocation failures. One o f the pre-requisites for successful risk management is the allocation o f necessary resources to adequately perfonn the job. Depending upon the size o f the organization and the scope o f the risk management system (and goals for the system), the two most critical resources are human and financial capital. Firms need to have staff ready to engage with the risk management process, and depending upon the risk management strategies developed, the risk management staff needs the appropriate amount o f capital to execute the strategy. During the financial crisis, the FCIC report alludes to both elements lacking. In terms o f inadequate personnel, the auditors o f several o f the failed firms were critical o f the firms ’ appointed risk managers. This included managers hired to lead the risk management departments. For instance in Passage 8, the auditors o f AIG raised concerns about the skill sets o f the top management team (CEO, CFO and CRO) and managers appointed to the ERM department concerning their capacity to do the jo b o f managing risk. Also, in Passage 9, the SEC criticized Bear Steams because their risk management functions lacked expertise in the risky products they were supposed to manage the risk, and the risk management function was understaffed. In addition to personnel, financial resources were also inadequate. Firms withheld, and sometimes cut, the resources for the risk management departments to do their jobs. For example, Passage 10 exhibits a willingness by management to tell the board o f directors at Fannie Mae that risk management had all necessary resources to act on risk management initiatives. However, the CRO disagreed as his department saw double digit budget cuts which led to a reduction in head count in the year leading up to the crisis. Top management failures. Many o f the failures in risk management during the crisis can be traced back to failures at the top o f the firm and with each 79 firms’ corporate governance. In the management literature, the upper echelon’s perspective (Hambrick and Mason, 1984) suggests that firms are a reflection o f its top management team as well as those in charge o f setting the strategic direction o f the firm. In the case o f the financial crisis, top management teams were seen as a major reason why some firms had failed. Indeed, in testimony to the FCIC, J.P. Morgan CEO Jamie Dimon, one o f the firms that survived the crisis, suggested that top management teams were to blame for the problems at the failed financial institutions and nobody else. Another cause o f risk management failure during the financial crisis was managerial hubris concerning risk management competencies. Hubris refers to an extreme level o f pride or overconfidence in o n e ’s se lf and abilities. Hubris has been associated with a number o f corporate maladies including overpaying for acquisitions (Hayward and Hambrick, 1997) and corporate social irresponsibility (Tang, Qian, Chen and Shen, 2014). Related to hubris, the overconfidence bias is the tendency for a person to have greater subjective confidence in their judgm ent or abilities than is objectively warranted. In many o f the failed financial firms, the top management teams were very confident about the effectiveness and adequacies o f their risk management systems. Numerous CEOs had made mention o f their risk management competencies even though none had necessarily been tested in remotely turbulent market environments. For instance, in Passages 4,11 & 12 the CEOs o f Lehman Brothers, AIG and Merrill Lynch touted their risk management programs, going so far as to suggest that their risk management programs were strong and a fundamental component o f their business model. Two potential reasons are apparent from the report which may have resulted in executive hubris. First, the resilience o f the big financial institutions to avoid big losses in prior debacles, like the dot com bubble, led managers and firms to believe they had robust and successful risk management systems in place. Second, hubris may have resulted from misplaced overconfidence in the complex mathematical models used for assessing risk. Financial institutions were lulled into a false sense o f security as these models would show that financial firms had little to be concerned about, and which up to that point, had kept the firms safe. In some instances, the complex models had even given the firm s’ auditors reason to believe that risk had been reduced or eliminated. As an example, in Passage 13, A IG ’s auditors were convinced that the firm ’s economic risks were essentially zero. Thus, the models appeared to have been a contributing factor to executive hubris. Auditors and CEOs were not alone in their false sense o f security. Regulators and industry experts like Fed Chairman Greenspan at the time, also believed the sophisticated modeling Journal o f Business Strategies techniques would protect financial firms from disaster. One might also consider that while cognitive bias appeared present, the other themes addressed herein are also the domain o f top managers. Thus, while top management failures are highlighted as a function o f managerial cognition, the other elements o f failure are also reflections o f decisions made by members o f the top management team at the financial firms. Objective tradeoff failures. The final contributing factor from the analysis suggests that some Anns were faced with a difficult tradeoff between, what were framed as, mutually exclusive choices. The firms could either do the right thing from a risk management perspective or pursue strategies that advanced the goals and aspirations o f the firm — but not both. For instance, in Passage 14, there is clear indication that management at some firms, including Fannie Mae, were pursuing strategies that increased their firm ’s level o f risk while in pursuit o f corporate objectives but which ran counter to good risk management practices. Additionally, some objectives and aspirations encompassed by corporate initiatives like growth, played a role in some decisions by risk management departments to loosen the reign on risk appetite. As mentioned in Passage 15, Citigroup allowed risk management departments to approve higher risk limits i f a business line was growing. Study 1 conclusions. To sum up, the analysis o f the FCIC report seems to support five areas o f risk management failure during the financial crisis. First, there were failures in the risk management process and the use o f holistic risk management models. Second, systems (more specifically, compensation systems) that should support the risk management process and promote risk management thinking, were not constructed properly. Third, the necessary human and financial resources to properly support effective risk management functions were not provided. Fourth, top management hubris created a false sense o f confidence in the existing risk management systems. Finally, firms were faced with a false choice between managing risk properly and achieving the bottom line objectives o f the company. All o f these issues, combined, led to an environment where risk management was likely to be less than adequate to deal with the challenges presented by the financial crisis. Study 2 In study two, I wanted to explore some o f the conclusions o f study one in more detail and probe whether firms, both in and outside o f the financial industry, had addressed the shortcomings which led to the failure o f risk management. As such, study two was an exploratory study - a first step, in assessing pre and post crisis firm 81 behavior. Firms were segmented into four categories, each more removed from the center o f the crisis. I started by identifying a representative set o f three firms for each o f the following four categories. The categories and representative firms were: large financial firms (J.P. Morgan Chase (JPM), Bank o f America (BAC), Wells Fargo (WFC)), large regional banks (SunTrust Banks (STI), BB&T Corp (BBT), Fifth Third Bancorp (FITB)), large non-financial firms which had a dedicated financial services business segment (General Electric (GE), Ford Motor Company (F), Deere & Co (DE)), and large non-financial firms which did not have a dedicated financial services business segment (Nike (NKE), Proctor & Gamble (PG), The Coca-Cola Company (KO)). For each firm, proxy statements filed before the crisis (2005-2007) and after the crisis (2010-2012) were pulled from the SEC website. Each o f the proxy statements was examined using a basic text analysis. I calculated averages for both sets o f data so that I could get a more accurate picture o f each firm ’s situation before and after the crisis. In study two, I looked at four things related to study one. First, related to the use o f a holistic risk management program, I looked at how often the terms ‘risk m anage,’ or some variant o f ‘manage risk’, were used in the proxy statement. Second, I looked for evidence that the appropriate human resources were allocated to risk management by searching for someone with a title who was designated as someone in charge o f managing risk (e.g., C hief Risk Officer (CRO), risk executive, or risk manager). Third, related to the focus o f compensation design, I looked for how prevalent risk and risk management were in a com pany’s discussion o f executive compensation. Last, I explored the prevalence o f ‘grow th’ and ‘return’ in the proxy statements compared to the use o f the word ‘risk ’ as this may relate to the trade-off between risk and the firm ’s bottom line. In this last part o f the analysis, I made sure to only count the word ‘risk’ when it was not in reference to anything risk management-related. The use o f word counts, as proxies for the level o f importance o f a theme or idea, has been described in prior qualitative methods research (e.g., Carley, 1993; Duriau, Reger, & Pfarrer, 2007) and used in strategic management research (e.g., Angriawan & Abebe, 2011). R e s u l t s In regards to the use o f a holistic risk management process, I searched for the phrase “risk management” and other variants (e.g., manage risk) to proxy for the importance o f a formal risk management process. The number o f instances were counted for each company and the results are displayed in Figure 1. The following Journal o f Business Strategies observations can be made when looking at the data. First, risk management was rarely discussed in the proxy documents before the crisis across all types o f firms, whereas after the crisis, risk management appeared much more frequently. Second, financial institutions and regional banks - those closest to the crisis, used the phrase more than non-financial companies (as much as two to four times more). After the crisis, financial institutions used the term more than any other type o f firm while non-financial firms without dedicated financial services business segments used the term the least (on average). This result is consistent with the findings o f the FCIC that described pre-crisis behavior related to risk management. While after- crisis behavior regarding risk management seems to have improved, the relatively infrequent mention o f risk management in non-financial firms is troubling. With regards to human resource allocation, I searched the proxy statement for evidence that the firms had a dedicated executive or manager who was responsible for risk oversight. It was important that risk oversight was governed by someone within the firm as opposed to a committee on the Board o f Directors. Search terms such as ‘chief risk,’ ‘risk executive,’ and ‘risk m anager’ were used to capture titles which designate a position dedicated to risk oversight. Prior work in the risk management literature have used similar search tenns as proxies for evidence o f risk management programs and risk management implementation. For instance, Liebenberg & Floyt (2003) uses the presence/absence o f a C hief Risk Officer (CRO) as a proxy to identify a Ann’s adoption o f enterprise risk management. Similarly, Hoyt & Liebenberg (2011) use the CRO as a proxy for risk management implementation. Along these lines, Beasley and colleagues (2005) identifies the CRO and other high level risk managers as champions o f risk management, thus suggesting that these human resources are necessary resources for successful risk management. The following observation was made from this qualitative search.4 Before the crisis, two o f the financial institutions and two o f the regional banks had a ch ief risk officer (although one o f the regional banks only mentions the CRO in 2005 but not 2006 or 2007), while none o f the non-financial companies had one before the crisis. After the crisis, all o f the financial institutions and regional banks had appointed an individual as the head o f risk oversight, while only one non-financial company had done so. However, the non-financial company that appointed a CRO had a finance- oriented business segment. This result is in-line with the FCIC report in that before the crisis, most financial firms had not allocated the appropriate human resources to risk management. Here too it seems troubling that non-financial companies have not followed in the footsteps o f their financial counterparts and appointed an individual with a risk designation. 83 The third aspect o f study one examined was the integration o f risk management outcomes and processes in compensation design. To explore this, each company’s compensation discussion section in the proxy statement was examined. O f particular interest was how each company talked about the integration o f risk processes in setting compensation policies - not simply how much o f a compensation package was ‘at risk’ but how the compensation package took into account risk assessment, management and outcomes. The following observation was made from this qualitative search.5 Before the crisis, most all o f the financial institutions and regional banks specifically identified how risk was taken into account when designing compensation while none o f the non-financial companies described in much detail how risk management was considered in setting compensation. After the crisis, all o f the financial institutions and regional banks discuss in detail how risk was considered in setting compensation. For non-financial firms, h a lf o f them discuss some aspect o f how risk was considered in setting compensation, however only one does so thoroughly. This result too is in-line with the FCIC report in that firms did a poor jo b pre-crisis in linking risk management outcomes with compensation design. The final issue examined from study one was the focus on strategies aimed to improve the bottom line and which overshadowed sound risk management. To explore this relationship, I searched for the words ‘grow th’ and ‘return’ in the firm ’s proxy statements. After getting a count o f these words, a ratio o f how often the word ‘risk’ appeared in relation to these two words was calculated. The ratios are graphed in Figure 2. As can be seen in the graphs, risk is talked about more than return after the crisis compared to before. A ratio o f less than one means that the firm talked about return more than risk. An interesting take-away appears when looking at the magnitude o f the ratios. For financial institutions and regional banks, four o f the six firms mention risk over two times more than return after the crisis, with one o f those firms mentioning risk over four times as much, and one firm mentioning it almost three times as much. While for non-financial firms, the use o f risk compared to return increases post crisis; four o f the six firms use risk and return about the same number o f times while two talk about risk less than return. These results, particularly for financial firms, appear to be in line with the FCIC report. Almost all o f the firms focus more on return and growth prior to the crisis than risk. (2) G ENERAL D IS C U S S IO N The purpose o f this study has been twofold. First, I wanted to identity the contributing factors or risk management failure leading up to, and during, the Journal o f Business Strategies financial crisis. Drawing upon the FCIC report, five ‘them es’ emerged from the passages which mention risk management. Second, I wanted to explore, in a very general sense, the extent to which failures identified at the large financial companies at the center o f the crisis, had been remedied immediately after the crisis by all types o f firms, not ju st financial firms. The analyses uncover several areas for firms to consider as they look to improve their risk management. These suggestions are aimed largely at non- financial institutions. The reason being that following the crisis, regulatory bodies in the U.S. issued a number o f regulations and specific guidance for risk-reporting aimed at financial institutions and regional banks. For instance, in response to risk management failures the government passed legislation like the Dodd-Frank Wall Street Reform and Consumer Protection Act (2010) aimed at reducing future risks to the financial industry. This legislation was largely aimed at the risk management at financial institutions, giving oversight authority to the Federal Reserve. In addition to Dodd-Frank regulations, the SEC approved the Proxy Disclosure Enhancement (2009) guidelines designed to enhance disclosures about risk in the firm ’s proxy filings. In the new guidelines, firms are required to make some reference to compensation design and risk, as well as the role the Board o f Directors plays in risk oversight. While helpful, the SEC rules do not require behavioral changes, only the disclosure o f additional infonnation. However, given the present analysis, it is apparent that financial firms and regional banks have done a much better job post-crisis in addressing how risk management and risk, in general, figure into the management o f the firm. These firms appear to be adhering to the new standards. While it is clear that financial institutions and regional banks have addressed the shortcomings o f risk management found during the financial crisis (likely in response to increased reporting and regulatory requirements), non- financial companies appear to have several areas which need improvement. While financial firms seemed to have at least made some aesthetic changes based upon their experiences (I would hesitate to call it learning without more detailed internal information about the processes o f the firm), it does not appear that non-financial companies have learned vicariously from the experiences o f the financial companies. There are multiple opportunities for non-financial firms to improve upon their risk management processes, which are addressed below. 85 C o m p e n s a t i o n S y s t e m s Compensation systems are one area that non-financial firms could improve in their pursuit o f improved risk management. As suggested by Lam (2014), incentivized performance becomes problematic when the incentives are focused on one dimension of firm performance - in many instances, stock price. Furthermore, incentives became especially problematic for financial firms when those contracts came with accelerated payout options. These two characteristics, a singular focus on stock price performance and accelerated payout options, made it difficult for managers to focus on the long-tenn outcomes o f risk when making decisions. Recent research has suggested (e.g. Rochette, 2009) and empirically found (e.g. Grace et ah, 2015) that one way to improve risk management is to tie incentives to risk management objectives in addition to other outcomes. For firms seeking to improve the alignment o f their compensation with risk management, first managers need to identify key performance indicators (KPI) that will either A) be impacted by the risk management process, or B) be reflective of success for key risk management activities. Each KPI is developed by first establishing the performance objective, then identifying the appropriate performance measure for the objective, and finally, developing the KPI. Once KPIs have been established, compensation needs to be explicitly linked to each KPI. As an example, one o f the key risk factors identified by John Deere in its 2010 financial report, which may materially impact the firm’s financial performance, is stated as “John D eere’s business results depend largely on its ability to develop, manufacture and market products that meet customer demand. ” As a result, one of Deere’s performance objectives might be: to have all customers rate their satisfaction with the quality of Deere products as the best in the industry - this would seem to substantially reduce the risk that customers are dissatisfied with Deere products. The performance measure could be: the percentage o f customers that rate Deere products as highest quality in the industry. The KPI could then be: 90\% of customers ranking Deere as having the highest quality products in the industry each quarter/half-year/ etc. If Deere is hitting this KPI, they in theory, would reduce one of the key risks that could materially impact their business. The CEO’s compensation would then be tied to this KPI. (To be clear, this is just an illustrative example using a company that is highly visible. I am not suggesting that Deere is not using KPIs tied to risk factors when it comes to designing executive compensation.) As Lam (2014) has suggested, compensation must not be aligned with simple measures of return, but with long-term risk-adjusted return hurdles with appropriate Journal o f Business Strategies vesting periods. Additionally, plans should continue to reward management for stability, continuity, and comparative performance to incentivize a long-term view when making decisions involving risk. Also, organizations may consider claw­ back policies for compensation when management knowingly engages in harmful behavior or exceeds the risk appetite o f the firm. Eliminating golden parachutes and sizeable compensation packages upon termination for poor perfonnance, as a result o f exceeding pre-specified risk thresholds, may also encourage executives to act in a responsible way as they consider risk. Lastly, management also needs to be mindful that their compensation plans, while incorporating the above, still encourage innovation and capital investment to increase long-term value. This can be done using risk-adjusted hurdle rates to detennine which projects or strategies are in-line with the firm’s stated level o f risk tolerance. Human Resource Allocation In terms o f resource inadequacies, there are several areas for improvement. First, managers need to staff the risk management function with human capital which has the appropriate certifications and qualifications given the business o f the firm, and second, provide adequate funding for the risk management function to execute on its risk management strategy. Risk managers should be chosen based upon their track record, their experience, their knowledge o f the industry and their knowledge o f the business. As risk management has become more important as a result o f recent crises, universities are offering more risk management degrees and professional organizations are offering special certificates for risk management certifications. For example (at the time o f the writing o f this paper), New York University offered a Masters Degree in Risk Management in their Global Degree Department in the business school; John Hopkins University offered a Masters Degree in ERM; and many other universities (e.g., University o f Connecticut) have financial risk management programs. Other universities, such as Stanford University, offer an online program for a Risk Management Certificate through their Center for Professional Development. Non-university entities like the National Alliance for Insurance Education and Research also offered a class-based/seminar-based Certified Risk Management (CRM) program. In addition to education-based training, many professional organizations offer certification tests for risk managers in specific functional fields. For example, the Project Management Institute offers a Risk Management Professional (RMP) certification test; the American Hospital Association offers a Certified Professional 87 Healthcare Risk Manager (HRM) designation; and the Risk and Insurance Management Society offers a Certified Risk Management Professional (CRMP) credential test. Thus, in theory, these programs should make finding risk management professionals easier and more cost efficient. Just as you would not have a C hief Financial Officer without financial or accounting expertise, firms should not have a C hief Risk Officer without substantive risk management expertise. Ideally, firms would select risk managers that are educated in the risk management field, has experience managing risk in the specific functional area, has the appropriate designation (for instance, a risk manager which is certified as a Healthcare Risk Manager is probably not the appropriate manager to work as a risk management professional in a bank), and is credentialed. F i n a n c i a l R e s o u r c e A l l o c a t i o n In addition to human capital, firms need to be more diligent about allocating financial resources to their risk management functions. By having better risk management systems as mentioned above, identifying the scope o f the risk management program should be easier for management. With a better understanding o f the scope o f the risks which need to be treated, managers can make more accurate budgets. Instead o f taking shots in the dark, managers can develop reasonable and accurate figures for risk management expenses. In addition to allocating resources to the risk management function, firms should also build up financial slack buffers that insulate the firm from risk events. There is considerable evidence that having cash on hand is not inefficient, but can drive firm value. Kim and Bettis (2014) show that large cash holdings, beyond what is needed for transactional purposes, have a positive impact on firm value. Similarly, Deb, David and O ’Brien (2017) found that cash creates shareholder value when it is used for adapting to uncertainty, such as by firms operating in competitive, research-intensive or growth-oriented industries. Thus, the adequate level o f financial resources for risk management is dependent on the firm, its existing resource position, and industry conditions. While the state o f financial resource allocation was not examined specifically in this study, future work should explore this domain. R is k vs. R e t u r n Additionally, managers need to align their risk management performance with their corporate objectives and goals. Managers may want to consider using Journal o f Business Strategies objectives that are not purely based on financial performance, such as growth and returns. For instance, S&P has begun to rank firms on their risk management activities. Depending upon the industry, firms may want to consider pursuing a particular level o f risk management ranking as a stated year-end objective. If firms want to continue incorporating financial metrics they could incorporate risk by utilizing risk-adjusted performance outcomes. Firms may also want to consider developing performance indicators which address the key risks they disclose in their annual reports (please see the example above in the Compensation Systems section for an example). A focus on reducing the key risk indicators could be considered in addition to purely performance-based measures. It is important to keep in mind that the suggestions mentioned here are not exhaustive and are but a few o f the many things management can do to improve risk management. It is important to remember that risk management should be an integral part o f a firm’s strategy. Risk management should be incorporated into the strategy-making process so that it is not subjugate to business objectives, but instead helps the firm accomplish its long-term goals and objectives. L im itatio ns a n d F u tu re R esearch As with all research there are limitations associated with this study. First, the most obvious is that this study relies on a comm ission’s report which is based on first-hand accounts o f the events leading to the crisis. Thus, there is no ability to control for any biases or omissions o f the commission. However, the creation o f the commission was done in a way which sought to limit this concern from the outset. The commission was constructed as a bi-partisan effort and was given unprecedented access to information sources that any researcher studying the crisis will not be able to collect on their own. Furthermore, while the research presented here is based on the report o f a single commission, it bears noting that the commission’s work is the amalgamation o f over 700 first-hand accounts, millions o f pages o f text and research, and countless hours o f public scrutiny. Nevertheless, this limitation should be taken into account when interpreting the findings o f this study. Second, the methodology incorporated in Study 2 o f the current research may also be considered a limitation. The author purposefully selected a limited sample o f highly visible and recognizable firms to perform the exploratory analysis. Given the exploratory nature o f the study, it was not the intent to collect a large number o f firms and employ econometric analysis. Highly visible firms are typically more heavily scrutinized by the public than are low visibility firms. The firms that I have 89 chosen, I have reasoned, would be the most susceptible to pressure to improve their risk management activities following a crisis such as the financial crisis. Investors, and the public alike, want to know what these large firms are doing to ensure the safety of investments and the economy in response to what was seen in the financial industry. Thus, if these firms had not changed their approach to risk management, it is highly likely that other firms facing less scrutiny would have done so. Finally, findings o f Study 1 are based solely upon the experiences of financial companies during the crisis. The conclusions of Study 2 are based upon an analysis of non-financial companies. As a result, this may represent a threat to the external validity of the results. The purpose o f applying lessons from financial companies to non-financial companies was to highlight the clear shortcomings in risk management at firms’ where risk management is a critical factor in achieving success, and using this as a platform for all firms to build and learn from in the future. This is similar to the ‘strategic benchmarking’ concept (Drew, 1997), where firms find examples of other firms who have capabilities or competencies in a particular area (such as risk management), and benchmark their own activities in this area versus the activities of the selected firms that have built those capabilities. In this instance, the financial firms should have capabilities and competencies in risk management. Non-financial firms, then, should be able to learn from the strategies and activities (or lack thereof) of these financial firms. Ultimately however, in choosing the method and a limited sample, the generalizability of the conclusions reached in this study should be considered when interpreting the results. Attempts were made to ensure rigor and validity in both studies, however, stricter protocols for qualitative research could be argued for. With respect to future research, there are several avenues to pursue. From a theoretical perspective, there is still much we do not know about what contributes to risk management success or failure. Just by looking at the shortcomings of risk management during the financial crisis there seems to be several management-related research themes. First, it might be instructive to understand what characteristics of executives are associated with better or worse risk management. An upper echelons perspective would be informative in this area, exploring biases, personalities and other demographic characteristics that may be associated with risk management. Additionally, research on corporate governance is a natural fit with the risk management literature. Exploring the impact of board composition, executive compensation and other governance characteristics on risk management systems might be infonnative. From a methodological perspective, future research might focus on more Journal o f Business Strategies qualitative studies. One o f the avenues mentioned briefly in the present paper is the role o f risk communication in the risk management process. Perhaps exploring how executives and risk managers are interacting and communicating can give us more insight in to why the risk management process can be so difficult for firms. Finally, future quantitative research could focus on themes touched upon in this study related to resource allocation, executive compensation and risk management performance. However, before research on these areas can commence, better measures o f risk management outcomes are necessary — this too could be an area for theoretical development. Finally, I would be remiss to not mention that the items identified in this paper were occurring against a backdrop that included a very weak institutional environment. The institutional environment (e.g., Scott and Davis, 2007) as described in the management literature, provides a backdrop for firm behavior. The institutional environment embodies both infonnal and formal pressures exerted on firms by outside influences. The FCIC report consistently mentioned the general weakness o f the institutional environment before the crisis. This was apparent in two areas -- weak regulating bodies not promoting best practices in risk management, and an overreliance on institutionalized practices such as letting firms police themselves. Whilst a more detailed discussion is beyond the scope o f the current paper, they need to be mentioned. CONCLUSION To conclude, the goal o f this paper was to highlight the shortcomings o f financial firms’ risk management activities during the financial crisis in the hopes o f uncovering areas for improvement for all firms regardless o f industry.The assumption is that risk management failures occur because organizations do not have (sophisticated) risk management systems in place. This research suggests that is not entirely true. In the case o f many o f the financial firms that failed, most had “ sophisticated” risk management systems. To make matters worse, many thought their systems were strong. The failures o f these institutions help us understand that while a system might be in place, the system needs to be constructed such that the fundamental elements like resources, incentives, corporate objectives and managers, m ust be aligned. While this may seem like a relatively basic idea, it has escaped many companies. The FCIC’s report on the financial crisis provides a wealth o f insight and information. Yet the implications for risk management as a result o f the comm ission’s 91 work has not yet been fully understood. It is easy to look back in hindsight and point out all of the missteps which occurred. The foresight required to steer clear of all possible sources o f risk during the crisis was probably outside the grasp of any human being. Be that as it may, I have identified a number o f failures that were within the grasp of managers and boards o f directors. Successful risk management was not impossible. Perhaps after exploring the reasons for failure in more detail, managers can be more cognizant of these issues in the future. ENDNOTES 1. The commission was an independent group of individuals, consisting of 10 private citizens that had experience across a number of different fields related to different aspects o f the crisis (e.g. banking, housing, finance, etc.). The members of the commission were elected by both parties in Congress to ensure bi-partisan conclusions (a majority opinion was reached although there were some members who provided a minority opinion). 2. This article is based upon, to a large extent, information which is contained in the FCIC’s report. Thus, statistics, quotes, and paraphrased comments not cited directly in the document are sourced from the FCIC’s report which is cited in the references section above. 3. The list o f passages presented in Appendix A is not exhaustive, i.e. is not the complete list o f passages used for the analysis. A complete list of passages can be obtained from the author. 4. 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BIOGRAPHICAL SKETCH OF AUTHOR Corey J. Fox is an Assistant Professor o f Management in the McCoy College o f Business at Texas State University. He received his PhD in Business Administration from Oklahoma State University. His current research focuses on issues related to risk and risk management in organizations, corporate resource allocation decisions, and corporate citizenship. His work has been published in such outlets as the Journal o f Managerial Issues and Strategic Organization. 95 Appendix A Example Passages N o S u b sta n tiv e In fo rm a tio n Doing so required research into broad and som etim es arcane subjects, such as m ortgage lending and securitization, derivatives, corporate governance, and risk m anagement. To bring these subjects out o f the realm o f the abstract, we conducted case study investigations o f specific financial firms— and in m any cases specific facets o f these institutions— that played pivotal roles. (FCIC: XII) JP M organ reported that large pension funds and some sm aller A sian central banks were reducing their exposures to Lehman, as well as to Merrill Lynch. A nd Citigroup requested a $3 to $5 billion “com fort deposit” to cover its exposure to Lehman, settling later for $2 billion. In an internal mem o, Thomas Fontana, the head o f risk m anagem ent in C itigroup’s global financial institutions group, wrote that “loss o f confidence [in Lehman] is huge at the m om ent.” (FCIC: 3281 G eithner would ask E. G erald Corrigan, the Goldman Sachs executive and form er N ew York Fed president who had co-chaired the Counterparty Risk M anagem ent Policy Group report, to form an industry group to advise on inform ation needed from a troubled investm ent bank. fFCIC: 3291 R isk M a n a g e m e n t P rocess F ailu res Passage 1: (Murray) Barnes (the Citigroup ris k officer assigned to the CDO business) told the FCIC that C itigroup’s risk m anagem ent tended to be managed along business lines, noting that he w as only two offices aw ay from his colleague w ho covered the securitization business and yet didn’t understand the nuances o f w hat was happening to the underlying loans. (FCIC: 262) P assage 2: Financial institutions and credit rating agencies em braced m athem atical m odels as reliable predictors o f risks, replacing judgm ent in too many instances. Too often, risk m anagem ent becam e risk justification. (FCIC- XIX) Passage 3: C itigroup’s risk m anagem ent function was simply not very concerned about housing m arket risks. According to 0Charles) Prince, {David) Bushnell (the C h ie f R isk Officer) and others told him, in effect, ‘Gosh, housing prices would have to go down 30\% nationwide for us to hav e....problem s,’ and that has never happened since the D epression.’ Housing prices would be down much less than 30\% when Citigroup began having problems because o f write-downs and the liquidity puts it had written. (FCIC: 262) Passage 4: Although the firm had proclaim ed that “R isk M anagem ent is at the very core o f L ehm an’s business m odel,” the E xecutive Com m ittee simply left its risk officer, M adelyn Antoncic, out o f the loop when it made this investm ent (FCIC: 177) S u p p o r t S ystem (C o m p en sa tio n ) F ailu res Passage 5: She (F D IC Chairperson Sheila B lair) concluded, “ The crisis has shown that m ost financial institution com pensation system s were not properly linked to risk m anagement. Form ula- driven com pensation allows high short-term profits to be translated into generous bonus paym ents, w ithout regard to any longer-term risks ” (FCIC: 64) P assage 6: T he Com m ission concludes that some large investm ent banks, bank holding com panies, and insurance com panies, including M errill Lynch, Citigroup, and AIG, experienced m assive losses related to the subprime m ortgage m arket because o f significant failures o f corporate governance, including risk m anagement. Executive and em ployee com pensation systems at these institutions disproportionally rew arded short-term risk taking (FCIC: 279) Passage 7: L eh m an ’s failure resulted in part from significant problem s in its corporate governance, including risk m anagement, exacerbated b y com pensation to its executives and traders that was based predom inantly on short­ term profits. (FCIC: 343) ♦Portions in parentheses and italics have been added for context while bold font has been added to highlight the term ‘risk m anagem ent’ Journal o f Business Strategies R eso u rce A llo c a tio n F ailu res P a s s a g e 8: I n th e m e e tin g w ith ( R o b e rt) W illu m s ta d (th e c h a ir m a n o f A I G s b o a r d o f d irec to rs) , th e a u d ito rs w e r e b ro a d ly c r itic a l o f (M a rtin ) S u lliv a n (C E O o f A I G ) ; (S te v e n ) B e n s in g e r (C F O o f A I G ) , w h o m th e y d e e m e d u n a b le to c o m p e n sa te f o r S u ll iv a n ’s w e a k n e s se s; a n d (R o b e rt) L e w is ( C h i e f R i s k O ffic e r a t A I G ) , w h o m ig h t n o t h a v e “th e sk ill se ts ” to ru n a n e n te rp ris e -w id e r is k m a n a g e m e n t d e p a r tm e n t. (F C IC : 2 7 3 ) P a s s a g e 9: T h e S E C ’s in s p e c to r g e n e r a l la te r c r itic iz e d t h e r e g u la to rs , w r iti n g t h a t t h e y d id n o t p u s h B e a r to r e d u c e le v e ra g e o r “m a k e a n y e ffo r ts to lim it B e a r S te a m s ’ m o r t g a g e sec u ritie s c o n c e n tr a tio n ,” d e sp ite “ a w a r e [ n e s s] th a t r isk m a n a g e m e n t o f m o r t g a g e s a t B e a r S te a m s h a d n u m e ro u s s h o rtc o m in g s , in c lu d in g la c k o f e x p e r tis e b y r is k m a n a g e r s in m o rtg a g e b a c k e d s e c u ritie s ” a n d “ p e r s is te n t u n d e rs ta f fin g ; a p ro x im ity o f r i s k m a n a g e r s to tra d e rs s u g g e s tin g a l a c k o f in d e p e n d e n c e ; tu r n o v e r o f k e y p e r s o n n e l d u r in g tim e s o f cris is; a n d t h e in a b ility o r u n w illin g n e s s to u p d a te m o d e ls t o r e fle c t c h a n g i n g c ir c u m s ta n c e s .” (F C IC : 2 8 3 ) P a s s a g e 10: M a n a g e m e n t t o l d t h e b o a r d t h a t F a n n i e ’s r is k m a n a g e m e n t f u n c tio n h a d a ll th e n e c e s s a r y m e a n s a n d b u d g e t to a c t o n th e p la n . C h i e f R is k O f f i c e r D a lla v e c c h ia d id n o t a g re e, e sp e c ia lly in lig h t o f a p la n n e d 16\% c u t in h is b u d g e t. I n a J u l y 16, 2 0 0 7 , e m a il t o C E O M u d d , D a lla v e c c h ia w ro te th a t h e w a s v e r y u p s e t t h a t h e h a d to h e a r at th e b o a r d m e e tin g t h a t F a n n ie h a d th e “ w ill a n d t h e m o n e y t o c h a n g e o u r c u ltu re a n d s u p p o rt ta k in g m o r e c re d it r is k ,” g iv e n t h e p r o p o s e d b u d g e t c u t f o r h is d e p a r tm e n t in 2 0 0 8 a fte r a 2 5 \% re d u c tio n in h e a d c o u n t i n 2 0 0 7 . (F C IC : 182) T op M a n a g e m e n t F ailu res P a s s a g e 11: O n D e c e m b e r 5 th ...S u lliv a n b o a ste d o n a n o th e r c o n fe re n c e c all a b o u t A I G ’s r is k m a n a g e m e n t s y ste m s a n d t h e c o m p a n y ’s o v e rs ig h t o f th e s u b p rim e e x p o su r e: “ T h e r i s k w e h a v e t a k e n in t h e U .S . r e s id e n tia l h o u s in g s e c to r is s u p p o rte d b y s o u n d a n a l y s is a n d a r is k m a n a g e m e n t s t r u c t u r e . . . .w e b e lie v e th e p ro b a b ility th a t it w ill su sta in a n e c o n o m ic lo ss is c lo se to z e r o ...W e a re c o n f id e n t in o u r m a rk s a n d re a s o n a b le n e s s o f o u r v a lu a tio n m e th o d s. (F C I C : 2 7 2 ) P a s sa g e 12: M e r r i l l ’s th e n - C F O J e f fre y E d w a rd s in d ic a te d th a t th e c o m p a n y ’s r e s u lts w o u ld n o t b e h u r t b y th e d is lo c a tio n in th e s u b p rim e m a rk e t, b e c a u s e “re v e n u e s f r o m s u b p rim e m o r t g a g e - r e la te d a c t iv itie s c o m p ris e [d ] le s s th a n 1\% o f o u r n e t re v e n u e s ” o v e r th e p a s t fiv e q u a rte rs , a n d b e c a u s e M e r r i l l ’s “r is k m a n a g e m e n t c a p a b ilit ie s are b e tte r t h a n e v er, a n d c r u c ia l to o u r su cc e ss in n a v ig a tin g t u r b u l e n t m a r k e ts .” (F C IC : 2 5 8 ) P a s s a g e 13: T h e c o m p a n y ’s a u d ito rs , P r ic e w a te r h o u s e C o o p e r s (P w C ), w h o w e r e a p p a r e n t ly a lso n o t a w a r e o f t h e c o lla te r a l re q u ir e m e n ts , c o n c l u d e d th a t “ th e r is k o f d e f a u lt o n [ A I G ’s] p o r tf o lio h a s b e e n e ffe c tiv e ly re m o v e d a n d a s a r e s u lt fr o m a r isk m a n a g e m e n t p e r s p e c tiv e , th e re a re n o s u b sta n tiv e e c o n o m ic ris k s in th e p o r tf o lio a n d a s a r e s u l t t h e f a ir v a lu e o f th e lia b ility s tre a m o n th e s e p o s itio n s f r o m a r isk m a n a g e m e n t p e r s p e c tiv e c o u ld r e a s o n a b ly b e c o n s id e r e d to b e z e r o .” (F C IC : 2 6 7 ) O b je c tiv e T r a d e o ff F ailures P a s s a g e 14: “ P la n s to m e e t m a r k e t sh a r e ta r g e ts re s u lte d i n s tr a te g ie s to in c re a s e p u r c h a s e s o f h ig h e r r is k p ro d u c ts , c r e a tin g a c o n flic t b e tw e e n p r u d e n t c r e d it r i s k m a n a g e m e n t a n d c o rp o ra te b u s in e s s o b je c tiv e s ,” th e F e d e r a l Ffousing F in a n c e A g e n c y (th e s u c c e s s o r to th e O ffice o f F e d e ra l H o u s i n g E n t e r p r is e O v e rsig h t) w o u ld w r ite in S e p te m b e r 2 0 0 8 o n t h e e v e o f th e g o v e rn m e n t ta k e o v e r o f F a n n ie M ae . (F C IC : 179) P a s s a g e 15: ( M u rra y ) B a r n e s ’s (C itig r o u p r is k o ffic e r a s s ig n e d to th e C D O b u s in es s ) d e c i s io n to in c re a s e th e C D O r is k lim its w a s a n n ro v e d b v h is s u p er io r, E lle n D u k e . B a m e s a n d D u k e re p o r te d to D a v id B u sh n e ll, th e c h i e f ris k o ffice r. B u s h n e ll— w h o m (C h u c k ) P r in c e (o n e -tim e C E O a t C itig ro u p ) c a l le d “th e b e s t r i s k m a n a g e r o n W a l l S tr e e t”— t o l d th e F C IC t h a t h e d id n o t r e m e m b e r s p e c ific a lly a p p r o v in g th e in c re a se b u t th a t, i n g e n er al, th e r is k m a n a g e m e n t fu n c tio n d id a p p ro v e h ig h e r r i s k lim its w h e n a b u s in e s s lin e w a s g ro w in g . H e d e s c r ib e d a “ firm - w id e in itia tiv e ” to in c re a se C i tig r o u p ’s s tr u c tu r e d p r o d u c ts b u s in e s s . (F C IC : 2 6 1 ) Volume 35, N u m ber 1 97 Figure 1 Risk Management Counts Risk Management Counts Before vs. After Crisis ■ Before Crisis After Crisis Figure 2 Risk/Return Ratios JPMBACWFC STI BBTFITB GE F DE NKE PG KO Companies (by ticker symbol)■ Before Crisis After Crisis Copyright ofJournal ofBusiness Strategies isthe property ofGibson D.Lewis Center for Business &Economic Development anditscontent maynotbecopied oremailed tomultiple sites orposted toalistserv without thecopyright holdersexpresswrittenpermission. However, usersmayprint, download, oremail articles forindividual use.