The Analysis of Portfolio Risk Management using VAR Approach Based on Investor Risk Preference (original) (raw)
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Application of VaR (Value at Risk) method on Belgrade Stock Exchange (BSE) optimal portfolio
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The main objective of this study is to determine the adequacy of the measurement of market risks of financial institutions in Serbia by the method of Value at Risk (VaR). For investors, in the current global financial crisis, it is particularly important to accurately measure and allocate risk and efficiently manage their portfolio. Possibility of application of VaR methodology, which is basically designed and developed for liquid and developed markets, should be tested on the emerging markets, which are characterized by volatility, illiquidity and shallowness of the market. Value of VaR in this study was calculated using historical and parametric methods and backtesting analysis was used to verify the adequacy of the application of VaR models. Backtesting VaR model performance analysis was conducted to compare the ex-ante VaR estimate to the ex-post returns. The empirical results show that parameter exponentially weighted moving average model gives lower values at risk in both cases (95% and 99%) due to the fact that this method assigns weights to more recent returns while our portfolio is exposed to a lower volatility in recent time. Based on the results of Kupiec's and Christoffersen's test, it was observed that VaR estimates obtained by both, parametric and historical simulation, give a good prediction of market risk, at 95% and 99% confidence level.
Portfolio Risk Management with Value at Risk: A Monte-Carlo Simulation on ISE-100
2013
Value at Risk (VaR) is a common statistical method that has been used recently to measure market risk. In other word, it is a risk measure which can predict the maximum loss over the portfolio at a certain level of confidence. Value at risk, in general, is used by the banks during the calculation process to determine the minimum capital amount against market risks. Furthermore, it can also be exploited to calculate the maximum loss at investment portfolios designated for stock markets. The purpose of this study is to compare the VaR and Markowitz efficient frontier approach in terms of portfolio risks. Along with this angle, we have calculated the optimal portfolio by Portfolio Optimization method based on average variance calculated from the daily closing prices of the ninety-one stocks traded under the Ulusal-100 index of the Istanbul Stock Exchange in 2011. Then, for each of designated portfolios, Monte-Carlo Simulation Method was run for thousand times to calculate the VaR. Finally, we concluded that there is a parallel relationship between the calculated optimum portfolio risks and VaR values of the portfolios.
Value at Risk: A Standard Tool in Measuring Risk : A Quantitative Study on Stock Portfolio
2011
The role of risk management has gained momentum in recent years most notably after the recent financial crisis. This thesis uses a quantitative approach to evaluate the theory of value at risk which is considered a benchmark to measure financial risk. The thesis makes use of both parametric and non parametric approaches to evaluate the effectiveness of VAR as a standard tool in measuring risk of stock portfolio. This study uses the normal distribution, student t-distribution, historical simulation and the exponential weighted moving average at 95% and 99% confidence levels on the stock returns of Sonny Ericsson, Three Months Swedish Treasury bill (STB3M) and Nordea Bank. The evaluations of the VAR models are based on the Kupiec (1995) Test. From a general perspective, the results of the study indicate that VAR as a proxy of risk measurement has some imprecision in its estimates. However, this imprecision is not all the same for all the approaches. The results indicate that models which assume normality of return distribution display poor performance at both confidence levels than models which assume fatter tails or have leptokurtic characteristics. Another finding from the study which may be interesting is the fact that during the period of high volatility such as the financial crisis of 2008, the imprecision of VAR estimates increases. For the parametric approaches, the t-distribution VAR estimates were accurate at 95% confidence level, while normal distribution approach produced inaccurate estimates at 95% confidence level. However both approaches were unable to provide accurate estimates at 99% confidence level. For the non parametric approaches the exponentially weighted moving average outperformed the historical simulation approach at 95% confidence level, while at the 99% confidence level both approaches tend to perform equally. The results of this study thus question the reliability on VAR as a standard tool in measuring risk on stock portfolio. It also suggest that more research should be done to improve on the accuracy of VAR approaches, given that the role of risk management in today's business environment is increasing ever than before. The study suggest VAR should be complemented with other risk measures such as Extreme value theory and stress testing, and that more than one back testing techniques should be used to test the accuracy of VAR.
2008
The knowledge of equity style of mutual funds has benefited investors by mitigating the issue of asymmetric information between fund managers and investors. Having information of portfolio risk enables investors to do risk budgeting. In this study, style analysis by Sharpe (1992) is used to decompose the fund returns into various asset classes. Subsequently, Value−at−Risk (VaR) measure is applied to calculate the portfolio risk based on Jorion (2007). Notably, this study finds that: First, VaR of value style funds is higher than VaR of growth style funds for both diversified and undiversified VaR. Second, adding international stocks as an asset class increases the undiversified VaR for both value and growth style funds. Third, growth style funds exhibit more portfolio diversification effect than value style funds as measured by reduction in diversified VaR. Fourth, adding international stocks to the portfolio intensifies the diversification effect. This study highlights the importance of estimating portfolio risk in addition to using style−based classification in the context of Malaysian fund management industry.
Market risk estimates the uncertainty of future earnings, due to the changes in market conditions. Value at Risk has become the standard measure that financial analysts use to quantify market risk. For estimating risk, the issue is that different ways to estimate volatility can lead to very different VaR calculations. The performance of SMA with rolling windows of 100 and EWMA using 0.94 (proposed by RiskMetrics) as smoothing constant λ and rolling window of 100 days, perhaps the most widely used methodology for measuring market risk is analyzed from investment activities on 7 stock exchange indices from developed and emerging markets. Binary Loss Function (BLF) is employed to measure the accuracy of VaR calculations because VaR models are useful only if they predict future risks accurately. The subject of this research is to determine the possibility of application of the SMA and EWMA models VaR with 95% and 99% confidence level in investment processes on the stock exchange markets of the selected countries. The methodology applied in the research includes analyses, synthesis and statistical/mathematical methods. The aim of the research is to show whether the models work the same and whether financial analysts from emerging countries can use the same model as their counterparts from the developed countries. The results show that risk managers in developing just as those in developed countries can use risk metric EWMA model as a tool for estimating market risk at 95% confidence level.
Possibilities of Var Application in Financial Investments
SHS Web of Conferences, 2020
Value at Risk is one of the quantitative methods used in banking and insurance. It is basically a statistical estimate of the worst loss that may occur with a certain probability in a certain future period. The main aim of this paper is application of Value at Risk model to the problem of optimal portfolio creation. It focuses on banking sector in Slovak republic and uses Value at Risk to assess the risk of commercial bank sector in Slovakia. To achieve this goal, it uses several methods of formal logic like analysis, synthesis, deduction, comparison as well as statistical methods. The first part is dedicated to a description and characterization of Value at Risk. Second part is oriented on characteristics of Slovak banking sector. Results consist of application of Value at risk on five biggest commercial banks in Slovakia. The conclusion of this paper is focused on the sets of recommendations for Value a Risk application and possible source of problems, which could occur while appl...
Managing market risk with VaR (Value At Risk)
Management Journal of Contemporary Management Issues, 2013
Market risk estimates the uncertainty of future earnings, due to the changes in market conditions. Value at Risk has become the standard measure that financial analysts use to quantify market risk. For estimating risk, the issue is that different ways to estimate volatility can lead to very different VaR calculations. The performance of SMA with rolling windows of 100 and EWMA using 0.94 (proposed by RiskMetrics) as smoothing constant λ and rolling window of 100 days, perhaps the most widely used methodology for measuring market risk is analyzed from investment activities on 7 stock exchange indices from developed and emerging markets. Binary Loss Function (BLF) is employed to measure the accuracy of VaR calculations because VaR models are useful only if they predict future risks accurately. The subject of this research is to determine the possibility of application of the SMA and EWMA models VaR with 95% and 99% confidence level in investment processes on the stock exchange markets of the selected countries. The methodology applied in the research includes analyses, synthesis and statistical/mathematical methods. The aim of the research is to show whether the models work the same and whether financial analysts from emerging countries can use the same model as their counterparts from the developed countries. The results show that risk managers in developing just as those in developed countries can use risk metric EWMA model as a tool for estimating market risk at 95% confidence level.
Estimating the Accuracy of Value-at-Risk (VAR) in Measuring Risk in Equity Investment in India
SSRN Electronic Journal, 2000
Over the past few years, the Value-at-Risk (VaR) has become a standard measure of market risk embraced by banks, trading firms, mutual funds and others, including even the non financial firms. But any risk measure is useful and reliable only insofar as it can be verified for its accuracy. This paper attempts to evaluate the accuracy of VaR in estimating the risk in equity investment in India. For this purpose we have used daily data for 30 securities comprising BSE-Sensex and two major stock indices-BSE Sensex and NSE Nifty for the period January 2006 to February 2007 and portfolionormal method (parametric approach to VaR calculation) for calculation of VaR. The hypothesis regarding accuracy of VaR estimates has been tested using Chi-square test. The results show that VaR estimate does not accurately measure the risk in equity investment in India as VaR overestimates the loss in 24 securities out of 30 securities. It is only in case of 4 securities that the observed number of violations is exactly equal to the expected number. These results may be attributed to non-normal distribution of equity returns in Indian securities market as against the normally distributed returns assumed under portfolio-normal method. All the securities are showing excess kurtosis estimate, exhibiting the leptokurtic returns' distribution and also, out of 30 securities, 20 are showing negatively skewed returns and 10 are showing positively skewed returns. Moreover the assumption of past representing the future is also not validated in the present case in the context of stock volatility observed during the period. We
The Volatility of Individual Securities in Measuring Value at Risk of a Portfolio
International Journal of Academic Research in Business and Social Sciences, 2020
Nowadays, investing in a portfolio of stocks or securities has been one of the most efficient ways for investors to increase wealth. Risk and return of each security are two main criteria to be considered in constructing an optimal portfolio. Previously, market risk is being measured using the standard deviation of changes in prices of the stock is referred to as price volatility. However, the majority of investors fail to relate it with the return of investment. Thus, the Value at Risk (VaR) concept has been successfully introduced to summarise the market risk of a portfolio as one number, for example in Ringgit Malaysia (RM). In this study, there are three main approaches consist of Delta Normal, Historical Simulation and Monte Carlo Simulation to measure monthly VaR for a portfolio of stocks from Sime Darby Sdn Bhd. at 95 and 99% confidence level. Empirical results show that VaR at 99% confidence level is higher than 95%. The findings also indicated that property stocks have the highest volatility and can be considered as the riskiest among the securities observed. Finally, risk managers and investors would be in a position to select a better stock portfolio with a known risk measure by employing the concept of VaR.