Value at Risk Models in Indian Markets: A Predictive Ability Evaluation Study - Theoretical Economics Letters

TEL > Vol.9 No.8, December 2019

Value at Risk Models in Indian Markets: A Predictive Ability Evaluation Study ()

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Download as PDF (Size: 1284KB) PP. 2824-2838

DOI: 10.4236/tel.2019.98177 593 Downloads 2,263 Views Citations

Author(s)

Kushagra Goel¹, Sunny Oswal^2*

Affiliation(s)

¹Faculty of Management, NMIMS University, Mumbai, India.
²NMIMS University, Mumbai, India.

ABSTRACT

Value at risk (VaR) is a method of measuring the potential loss in portfolio value for a given distribution of historical returns over a given time period. Measurement of risk therefore becomes essential for a corporate decision. This study attempts to rank the overall predictive ability of select value at risk models in estimating market risks of Indian financial markets. This study estimates the respective predictive ability by employing numerical and graphical measures. The findings plug the gaps in the literature and estimate the best method to be used in the industry. The results evidentially prove that parametric model using normal distribution with GARCH (1,1) fits best for estimating value at risk.

KEYWORDS

Value-at-Risk, Monte Carlo Simulation, Implied Volatility, Historical Based Approach

Share and Cite:

Goel, K. and Oswal, S. (2019) Value at Risk Models in Indian Markets: A Predictive Ability Evaluation Study. Theoretical Economics Letters, 9, 2824-2838. doi: 10.4236/tel.2019.98177.

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