Value-at-Risk Analysis in the Presence of Asymmetry and Long Memory: The Case of Turkish Stock Market

Abstract

Value-at-Risk (VaR) is a standard tool for measuring potential risk of economic losses in financial markets. In this study, we examine the convenience of the FIGARCH (1, d, 1) and FIAPARCH (1, d, 1) models in evaluating asymmetry features and long memory in the volatility of the Turkish Stock Market. Furthermore, we investigate the performances in-sample and out-of-sample Value-at-Risk (VaR) analyses based on Kupiec-LR test by using FIGARCH(1, d, 1) and FIAPARCH (1, d, 1) models with the normal, student-t and skewed student-t distributions. For these analyses, we take into account both short and long trading positions. The empirical results display that the FIAPARCH (1, d, 1) model with skewed student-t distribution is more accurate for in-sample and out-of-sample Value-at-Risk (VaR) analysis for short and long trading positions. In addition, the FIAPARCH(1, d, 1) model with skewed student-t has better accuracy results in capturing stylized facts in the volatility of Turkish Stock Market. Consequently, evaluating of asymmetry and long memory property in volatility of the returns can ensure suitable Value-at-Risk (VaR) model selection for performance of risk management in the Turkish financial markets. The findings can be evaluated by portfolio managers, investors, regulators and financial risk managers. Keyword: Value-at-Risk; FIAPARCH Model; Long Memory; Volatility. JEL Classifications: C13; C58; G10; G15; G17

Keywords

• Value-at-Risk, FIAPARCH Model, Long Memory, Volatility