Abstract
Measuring and modeling unobservable volatility is one of the key issues in finance and risk management. Value at Risk (VaR) is a natural application of volatility estimates and therefore allows to differentiate between volatility estimation approaches. In this paper we consider daily VaR measures for WIG20 index using one-step-ahead forecasts of volatility in a crisis period. We compare forecasts from GARCH family models based on daily data with forecasts from HAR-RV and ARFIMA models for realized volatility based on intraday returns. Both VaR forecasts obtained from models that use intraday information in defining volatility and simple models based on daily returns deliver similar results. However, when loss functions are considered, HAR-RV models allow to minimize opportunity cost of capital.
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