volatility forecasting of stock returns and exchange rates. … dynamics adapts to the non-normal nature of financial data, which helps to robustify the volatility estimates. The new model …

volatility of individual stock returns and exchange rate returns. …

. Applying our model to high-frequency transaction data, we detect two distinct regimes in the intraday volatility process: a … dominant volatility regime that is observable throughout the trading day representing the risk-transferring trading activity of … investors, and a minor volatility regime that concentrates around market liquidity shocks which mainly capture impacts of firm …

This paper studies the information content of the S&P 500 and VIX markets on the volatility of the S&P 500 returns. We … risk-neutral distributions as well as the term structure of volatility smiles and of variance risk premia. We find that the …

Following recent advances in the non-parametric realized volatility approach, we separately measure the discontinuous … volatility models. We analyze the distributional properties of the jump measures vis-à-vis the corresponding realized volatility … accuracy of high-frequency volatility models …

credit and equity markets advocate the use of market price and volatility channels as explanatory factors. In particular, the … evolution of CDS spreads is analyzed along with the level of the equity market and a well-chosen implied volatility index. We … leptokurtosis are captured. Incidentally, the sensitivity of aggregate CDS spreads to equity market price and volatility channels …

-day and intra-day volatility models by estimating the AR(1)-GARCH(1,1)-skT and the AR(1)-HAR-RV-skT frameworks, respectively … intra-day volatility model is not as appropriate as it was expected to be for each of the different asset classes; stock … performance of the inter-day and intra-day volatility models across various markets. The inter-day specification predicts and …

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

accurately. Taking into consideration the main characteristics of the conditional volatility of asset returns, I estimate an …Predicting the one-step-ahead volatility is of great importance in measuring and managing investment risk more … excess kurtosis that the asset returns exhibit and ii) the fractional integration of the conditional variance. The model …