Value-at-Risk in the Presence of Structural Breaks Using Unbiased Extreme Value Volatility Estimator
- PDF / 1,109,308 Bytes
- 24 Pages / 439.37 x 666.142 pts Page_size
- 27 Downloads / 180 Views
Value‑at‑Risk in the Presence of Structural Breaks Using Unbiased Extreme Value Volatility Estimator Dilip Kumar1
© The Indian Econometric Society 2020
Abstract We provide a framework based on the unbiased extreme value volatility estimator to predict long and short position value-at-risk (VaR). The given framework incorporates the impact of asymmetry, structural breaks and fat tails in volatility. We generate forecasts of long and short position VaR for the cases when future structural breaks are known as well as unknown. We evaluate its VaR forecasting performance using various backtesting approaches for both long and short positions and compare the results with that from return based models. Our findings indicate that incorporating the impact of structural breaks in volatility indeed improves the accuracy of VaR forecasts of the proposed framework. Keywords Extreme value volatility estimator · Structural breaks · Value-at-risk · Asymmetry · Risk management JEL Classification C22 · C53
Introduction The series of crisis and crashes in a financial market (for example: the Asian financial crisis in 1997, the collapse of Long Term Capital Management in 1998, the Russian financial crisis in 1998, global financial crisis in 2007–2009 and the European debt crisis in 2009–2012) has raised the concern of the importance of accurate measurement of risk for sound risk management practices. In the recent global financial crisis of 2007–2009 and European debt crisis of 2009–2012, several big players in the financial market either went bankrupt [for example: Lehman Brothers, Bear Stearns (sold to JPMorgan Chase), Thornburg Mortgage, MF Global, Washington Mutual Bank (sold to JPMorgan Chase)] or bailed out by the government (AIG, Royal Bank of Scotland, General Motors, CIT Group). These have * Dilip Kumar [email protected]; [email protected] 1
Indian Institute of Management Kashipur, Kashipur, India
13
Vol.:(0123456789)
Journal of Quantitative Economics
raised concerns about the failure of the current risk management practices in the finance arena. The value-at-risk (VaR) is considered to be an industrial benchmark for reporting financial risk and is widely used by financial institutions, regulators, business practitioners and portfolio managers. It is used by banks and financial institutions to determine the minimum capital requirement that they may require to deal with any uncertain catastrophic event in the market. This paper contributes in this area by proposing and evaluating a framework based on the unbiased extreme value volatility estimator for estimating value-at-risk (VaR). The proposed framework also accounts for structural breaks in the market. There exist various approaches for estimating VaR which include non-parametric, semi-parametric and parametric approaches. The literature emphasizes the importance of the assumption of fat tails in estimating and predicting VaR (Bollerslev et al. 1992; Pagan 1996; Palm 1996). Various studies also highlight the importance of considering a possible
Data Loading...
