. Still, little is known about how far ahead one can forecast volatility. First, in this paper we introduce the notions of the … and forward forecast accuracy curves. Then, by employing a few popular time-series volatility models, we perform a …Volatility forecasting is crucial for portfolio management, risk management, and pricing of derivative securities …

, 60, and 300 seconds), forecast horizons (1, 5, 22, and 66 days) and the use of standard and robust-to-noise volatility … forecasting the volatility of equity prices, using high-frequency data from 2000 to 2016. We consider the SPY and 20 stocks that … real-time forecasts than the HAR-RV model, although no single extended model dominates. In general, standard volatility …

The internal models amendment to the Basel Accord allows banks to use internal models to forecast Value-at-Risk (VaR … penalised through higher capital charges. This paper investigates the performance of five popular volatility models that can be … used to forecast VaR thresholds under a variety of distributional assumptions. The results suggest that, within the current …

frequency volatilities and correlations ; Dynamic conditional correlation ; Spline-GARCH ; Idiosyncratic volatility ; Long …

This paper tests whether it is possible to improve point, quantile and density forecasts of realized volatility by … more information for the evolution of the volatility distribution beyond that contained in its own past. The best …

risk management purposes. We estimate GARCH models to capture the behavior of the conditional volatility. The expected … daily volatility converges to the unconditional variance of the long-term volatility. We find that the tGARCH model provides …