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Forecasting stock market volatility using Realized GARCH model : international evidence

Sharma, Prateek; Vipul - In: The quarterly review of economics and finance : journal … 59 (2016), pp. 222-230

Persistent link: https://www.econbiz.de/10011627288

Improved VaR forecasts using extreme value theory with the Realized GARCH model

Paul, Samit; Sharma, Prateek - In: Studies in economics and finance 34 (2017) 2, pp. 238-259

Persistent link: https://www.econbiz.de/10011822635

Forecasting gains of robust realized variance estimators: evidence from European stock markets

Sharma, Prateek; Sharma, Swati - In: Economics Bulletin 35 (2015) 1, pp. 61-69

The classical realized variance (RV) estimator is biased due to microstructure effects and asset price jumps. Robust realized variance (RRV) estimators adjust for these biases, and make more efficient of use of the intraday data. This article examines the benefits of using RRV estimators instead...

Persistent link: https://www.econbiz.de/10011199668

Forecasting gains of robust realized variance estimators: evidence from European stock markets

Sharma, Prateek; Sharma, Swati - In: Economics Bulletin 34 (2014) 4, pp. 2377-2386

Persistent link: https://www.econbiz.de/10011039042

Improved VaR forecasts using extreme value theory with the Realized GARCH model

Paul, Samit; Sharma, Prateek - In: Studies in Economics and Finance 34 (2017) 2, pp. 238-259

Purpose This study aims to forecast daily value-at-risk (VaR) for international stock indices by using the conditional extreme value theory (EVT) with the Realized GARCH (RGARCH) model. The predictive ability of this Realized GARCH-EVT (RG-EVT) model is compared with those of the standalone...

Persistent link: https://www.econbiz.de/10015014008