broadly, our study dispels the notion that volatility is not forecastable at long horizons and offers an approach that …

size and power properties of CUSUM based, LM and Wald volatility break tests. In a simulation study we derive the … properties of the tests under shifts in the unconditional and conditional variance as well as for smooth shifts in the volatility … process. Our results indicate that Wald tests have more power of detecting a change in the volatility than CUSUM and LM tests …

volatility and the spread used for trading. The results of the trading strategies suggest that cointegrated portfolios based on … part of the econometric analysis explores Granger causality between volatility and the spread. For this analysis, we … implement two types of forecasting models for Bitcoin volatility: the GARCH (generalized autoregressive conditional …

This paper introduces a parsimonious and yet flexible semiparametric model to forecast financial volatility. The new …

forecasts of daily integrated volatility. Our approach is based on a two-step shrinkage procedure designed to extract latent … common volatility factors from a large dimensional and high-frequency asset returns dataset. In the first step, we apply …, in order to estimate a latent return factor. This new factor is in turn utilized to construct a latent volatility factor …

In this paper, we study the methods of combining different volatility forecasts using various GARCH models. Given that … the major risk exposure for many investors in energy is the volatility of the electricity price, our motivation stems from … the fact that there is no single best model for forecasting such volatility. Ample evidence suggests that most of the …

In this paper, we use factor-augmented HAR-type models to predict the daily integrated volatility of asset returns. Our … approach is based on a proposed two-step dimension reduction procedure designed to extract latent common volatility factors …, we apply either LASSO or elastic net shrinkage on estimates of integrated volatility of all constituents in the dataset …

typically observed in measures of financial market volatility in a tractable fashion. The extensions decompose conditional … dependency structure of volatility. This leads to substantial improvements in empirical fit and predictive ability at both short … and long horizons relative to the original REGARCH. A volatility-timing trading strategy shows that capturing volatility …

volatility (RV) of ten global stock market indices in the period from January 2000 to December 2021. We train models using a …

The volatility of equity and foreign exchange market is an important input to portfolio selection and to asset pricing … models. Many investment decisions and valuation of derivatives frequently rely on predictions of volatility. In this paper we … review the existing empirical literature in forecasting volatility of financial time series. Particularly, we decompose the …