The Companies Act 2013 has made it mandatory for firm’s Board of Directors Report to include a statement indicating elements of risk faced by companies. In the IMF report of March 2015, it is mentioned that India’s non-financial company’s external commercial borrowings rose by 107% between March 2010 to March 2014. The stress test based on exchange rate and profits demonstrated continuing high vulnerabilities of the firms. Looking at both the important factors, the current study estimates the Value-at-Risk (VaR) of 106 non-financial Indian firms. It is well a documented fact that return series is nonnormal, therefore taking bivariate distribution of return and foreign exchange rate. VaR is calculated using the extreme value theory method and Bayesian method. The results suggest that Bayesian method provides the best VaR estimates

Purpose – This paper aims to investigate the effect of non-normality in returns and market capitalization of stock portfolios and stock indices on value at risk and conditional VaR estimation. It is a well-documented fact that returns of stocks and stock indices are not normally distributed, as Indian financial markets are more prone to shocks caused by regulatory changes, exchange rate fluctuations, financial instability, political uncertainty and inadequate economic reforms. Further, the relationship of liquidity represented by volume traded of stocks and the market risk calculated by VaR of the firms is studied. Design/methodology/approach – In this paper, VaR is estimated by fitting empirical distribution of returns, parametric method and by using GARCH(1,1) with Student’s t innovation method. Findings – It is observed that both the stocks, stock indices and their residuals exhibit non-normality; therefore, conventional methods of VaR calculation are not accurate in real word situation. It is observed that parametric method of VaR calculation is underestimating VaR and CVaR but, VaR estimated by fitting empirical distribution of return and finding out 1-a percentile is giving better results as non-normality in returns is considered. The distributions fitted by the return series are following Logistic, Weibull and Laplace. It is also observed that VaR violations are increasing with decreasing market capitalization. Therefore, we can say that market capitalization also affects accurate VaR calculation. Further, the relationship of liquidity represented by volume traded of stocks and the market risk calculated by VaR of the firms is studied. It is observed that the decrease in liquidity increases the value at risk of the firms. Research limitations/implications – This methodology can further be extended to other assets’ VaR calculation like foreign exchange rates, commodities and bank loan portfolios, etc. Practical implications – This finding can help risk managers and mutual fund managers (as they have portfolios of different assets size) in estimating VaR of portfolios with non-normal returns and different market capitalization with precision. VaR is used as tool in setting trading limits at trading desks. Therefore, if VaR is calculated which takes into account non-normality of underlying distribution of return then trading limits can be set with precision. Hence, both risk management and risk measurement through VaR can be enhanced if VaR is calculated with accuracy. Originality/value – This paper is considering the joint issue of non-normality in returns and effect of market capitalization in VaR estimation.

Joint dynamics of market index returns, volume traded and volatility of stock market returns can unveil different dimensions of market microstructure. In this study, the joint dynamics is investigated with the help of bivarite Glosten–Jagannathan–Runkle generalized autoregressive conditional heteroskedasticity (GJR-GARCH) methodology given by Bollerslev (1990), as this method helps in jointly estimating volatility equation of return and volume in a one-step estimation procedure and it also eliminates the regressor problem (Pagan, 1984). The study finds negative conditional correlation between volume traded and return of large-cap index. The relation between volume traded and volatility is found to be positive in case of large-cap index but it is negative in the case of mid-cap and small-cap indices. Volatility is affected by pronounced persistence in volatility, mean-reversion of returns and asymmetry in market. The rate of information arrival measured by intra-day volatility (IDV) is found to be a significant source of the conditional heteroskedasticity in Indian markets since the presence of volume (proxy for information flow) in volatility equation, as an independent variable, marginally reduces the volatility persistence, whereas presence of IDV, as a proxy for information flow, completely makes GARCH effect insignificant.

Education is about the moulding of young and unprepared minds. It is a process that incorporates enormous inputs and commitment on the part of all stakeholders involved: teachers, peers, parents, and society. The outcome of education is measured in terms of the status person has gained, wealth, physical comfort, standard of living, and social esteem. Higher education plays important role in shaping the future of a student. Management education is one the most popular courses at post-graduate level. Hence, this chapter is an attempt to understand the factors that a student looks for while selecting a B-school. Primary survey is done to understand the factors affecting students' decision in selecting a B-school. It is observed that teaching pedagogy, placements, faculty, specialization, and fees play important roles in a student's decision process.

No abstract