In this paper, an attempt has been made to model the volatility of NIFTY index of National Stock Exchange (NSE) and … comprises 3736 data points for the analysis by using Box-Jenkins or ARIMA model. The volatility in the Indian stock market … suggested by Hannan-Rissanen. As per the analysis, ARIMA (1,0,1) model was found to be the best fit to forecast the volatility …

for exogenous shock to market data. After the data fitting and VaR estimation, we conclude that the range-based volatility … regime switching into volatility process can boost the efficiency for VaR estimation. We also present an empirical … with non-regime switching volatility model, our model outperforms other alternatives on the estimation of volatility …

Volatility is an important component of asset pricing; an increase in volatility on markets can trigger changes in the … risk distribution of financial assets. In conventional financial theory, investors are considered to be rational and any … hypothesized that there are movements in risk that are driven by volatility linked to sentiment-driven noise trader activity whose …

influential for Value at Risk (VaR) performance than the conditional volatility specification. We also show that some recently … proposed asymmetric probability distributions and the APARCH and FGARCH volatility specifications beat more standard … parameter in conditional volatility in the APARCH and FGARCH models explains their better performance. Indeed, our estimates …

theory assumes that return shocks can be caused by changes in conditional volatility through a time-varying risk premium. On … leverage effect and the volatility feedback effect. We stress the importance of distinguishing between realized volatility and … implied volatility, and find that implied volatilities are essential for assessing the volatility feedback effect. The …

We examine the performance of volatility models that incorporate features such as long (short) memory, regime …-t). Second, we perform a comprehensive panel forecasting analysis of the MSM models as well as other competing volatility models … (GMM) estimation are both suitable for MSM-t models, (ii) empirical panel forecasts of MSM-t models show an improvement …

characterized by volatility clustering and asymmetry. Also revealed as a stylized fact is Long memory or long range dependence in … market volatility, with significant impact on pricing and forecasting of market volatility. The implication is that models … that accomodate long memory hold the promise of improved long-run volatility forecast as well as accurate pricing of long …