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Measuring Idiosyncratic Risk Absorbing Capacity of Companies‟ A Welfare Optimization Approach


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1 School of Management, Auro University, Surat (Gujarat), India
     

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Financial Institutions require measurement of concentration risk to ensure their funds are not concentrated with one sector, or investments surrounding one sector. To develop this idea, tools like Gini coefficient are adequately utilized, besides, the Gini Coefficient also support in Income inequality measure. However, Gini coefficient do not serve good with negative values and “adjusted gini coefficient” can only be applied with large bootstrapped samples.so unlike, the other papers, in this research, and alternative strategy for portfolio weight selection was considered, here, variance of the bootstrapped OLS regression coefficient series was considered as proxy to “adjusted gini measure”. Traditionally, the aggregate “employee costs” can adequately serve as measure of income inequality or idiosyncratic diversification; provided the explanatory variables were also idiosyncratic in nature. The study clearly explained that how the cement companies in India can be compared based on their self-absorbing capacities to handle such idiosyncratic wage risk burden.

Keywords

OLS, Bootstrapping, Risk Optimization.
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  • Alessi, L., Barigozzi, M., &Capasso, M. (2007).Generalized Dynamic Factor Model+ GARCH Exploiting multivariate information for univariate prediction (No. 2006/13).LEM Working Paper Series.

  • Bai, J., & Ng, S. (2005). Tests for skewness, kurtosis, and normality for time series data. Journal of Business & Economic Statistics, 23(1), 49-60.

  • Bakk-Simon, K., Borgioli, S., Girón, C., Hempell, H. S., Maddaloni, A., Recine, F., &Rosati, S. (2011). Shadow banking in the euro area: an overview. ECB occasional paper, (133).

  • Ball, L., &Mankiw, N. G. (1921).Inter-generational risk sharing in the spirit of Arrow. Debreu, and Rawls, with applications to social security design, Harvard Institute of Economic Research DP.

  • Blenman, L. P., & Xu, M. (2009).Joint Ventures, Risk Sharing and Optimal Contract Design.

  • Boyle, P. P., & Ma, C. (2005).Mean-preserving-spread risk aversion and the CAPM.Department of Accounting, Finance and Management.

  • Carney, M. (1998). The competitiveness of networked production: the role of trust and asset specificity. Journal of Management Studies, 35(4), 457-479.

  • Chang (2004). Bootstrap unit ischolar_main tests in panels with cross-sectional dependency. Journal of Econometrics, 120(2), 263-293.

  • Chen, B., Gel, Y. R., Balakrishna, N., & Abraham, B. (2011).Computationally efficient bootstrap prediction intervals for returns and volatilities in ARCH and GARCH processes. Journal of Forecasting, 30(1), 51-71.

  • Das, S. (2006). On agent-based modeling of complex systems: Learning and bounded rationality. Department of Computer Science and Engineering. La Jolla, CA, 92093-0404.

  • Freitakas, E. The impact„s of loan„s portfolio concentration and diversification to the banking sector. Seven years of Bulgaria's membership in the European Union, 5.

  • Gabrielsen, A., Kirchner, A., Liu, Z., &Zagaglia, P. (2015).Forecasting Value-at-Risk with time-varying variance, skewness and kurtosis in an exponential weighted moving average framework.Annals of Financial Economics, 10(01), 1550005.

  • Guo, H. (2004). Limited stock market participation and asset prices in a dynamic economy. Journal of Financial and Quantitative Analysis, 39(03), 495-516.

  • Hara, C. (2001). Equilibrium Prices of the Market Portfolio in the CAPM with Incomplete Financial Markets. working paper, University of Cambridge.

  • Krakowski, M. (2005). Determinants of the informal economy: the importance of regional factors. Discussion paper, Hamburg institute of International business, Hamburg : Germany.

  • Mackowiak, B., &Wiederholt, M. (2009).Optimal sticky prices under rational inattention. The American Economic Review, 99(3), 769-803

  • Milne, A. (2002). Bank capital regulation as an incentive mechanism: Implications for portfolio choice. Journal of banking & finance, 26(1), 1-23.

  • Miyamoto, J. M. (1992). Generic analysis of utility models. In Utility theories: Measurements and applications (pp. 73-106). Springer Netherlands

  • MR, N., MIDI, H., & IMON, A.(July, 2009) Estimating Regression Coefficients using Weighted Bootstrap with Probability. WSEAS TRANSACTIONS on MATHEMATICS, Vol 9(7).

  • Rudloff, B. (2009). Coherent hedging in incomplete markets. Quantitative Finance, 9(2), 197-206.

  • Scherer, B. (2012). Asset allocation with shadow assets.The Journal of Wealth Management, 15(3), 30.

  • Stoikov, S. F., &Zariphopoulou, T. (2005).DYNAMIC ASSET ALLOCATION AND CONSUMPTION CHOICE IN INCOMPLETE MARKETS*. Australian Economic Papers, 44(4), 414-454.

  • Stoikov, S., &Zariphopoulou, T. (2004).Optimal investments in the presence of unhedgeable risks and under CARA preferences.Preprint. Department of Mathematics, University of Texas, Austin..


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  • Measuring Idiosyncratic Risk Absorbing Capacity of Companies‟ A Welfare Optimization Approach

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Authors

Rohit Malhotra
School of Management, Auro University, Surat (Gujarat), India

Abstract


Financial Institutions require measurement of concentration risk to ensure their funds are not concentrated with one sector, or investments surrounding one sector. To develop this idea, tools like Gini coefficient are adequately utilized, besides, the Gini Coefficient also support in Income inequality measure. However, Gini coefficient do not serve good with negative values and “adjusted gini coefficient” can only be applied with large bootstrapped samples.so unlike, the other papers, in this research, and alternative strategy for portfolio weight selection was considered, here, variance of the bootstrapped OLS regression coefficient series was considered as proxy to “adjusted gini measure”. Traditionally, the aggregate “employee costs” can adequately serve as measure of income inequality or idiosyncratic diversification; provided the explanatory variables were also idiosyncratic in nature. The study clearly explained that how the cement companies in India can be compared based on their self-absorbing capacities to handle such idiosyncratic wage risk burden.

Keywords


OLS, Bootstrapping, Risk Optimization.

References