An attempt is made in this paper to examine whether stock returns in two premier two exchanges in India namely, Bombay Stock Exchange (BSE), and National Stock Exchange (NSE) follow a random walk. Towards this end, data on major indices during the period 1997 to 2009 are analyzed by using...

This paper investigates the relationship between stock market returns and volatility in the Indian stock markets using AR(1)-EGARCH(p, q)-in-Mean model. The study considers daily closing prices of two major indexes of Indian stock exchanges, viz., S&P CNX NIFTY and the BSE-SENSEX of National...

The purpose of this paper is to study the direction of causality between the stock market and macroeconomic variables. India is taken as a case study. Although, there have been many studies which attempted to find out the relationship between Indian stock market and economic variables, this...

The paper presents and tests Dynamic Value at Risk (VaR) estimation procedures for equity index returns. Volatility clustering and leptokurtosis are well-documented characteristics of such time series. An ARMA (1, 1)-GARCH (1, 1) ap- proach models the inherent autocorrelation and dynamic...

Since the global financial crisis, Central Banks have used various policy tools to sustain financial stability besides price stability. Additional Monetary Tightening is one of these tools that the Central Bank of the Republic of Turkey used in 2011-2012. The effects of this tool on the exchange...

This paper considers estimating the conditional mean and variance from a single-equation dynamic model with the mean following an ARMA (1,7) process, and the conditional variance with time-dependent conditional heteroskedasticity as represented by ARCH models. The volatility is measured by a...

This study explores the volatility models and evaluates the quality of one-step ahead forecasts of volatility constructed by (1) GARCH, (2) TGARCH, (3) Risk metrics and (4) Historical volatility. Volatility forecasts suggest that TGARCH performs relatively best in term of MSPE, followed by...

This paper investigates sensitivity of the VaR models when return series of stocks and stock indices are not normally distributed. It also studies the effect of market capitalization of stocks and stock indices on their Value at risk and Conditional VaR estimation. Three different market...

A two-step approach for conditional Value at Risk (VaR) estimation is considered. In the first step, a generalized-quasi-maximum likelihood estimator (gQMLE) is employed to estimate the volatility parameter, and in the second step the empirical quantile of the residuals serves to estimate the...