this, put forward the view that stock and bond return volatility is key. Evidence from the 2000s suggest that the relative … that the relative equity and bond yield values are, to a large extent, driven by inflation volatility. High inflation … volatility persisted during the first half of the twentieth century when the equity yield was higher. This was followed by more …

model specifications, volatility effects and other robustness considerations continue to support our results. These results …

This paper examines the ability of different GARCH models to forecast stock return volatility under a range of forecast …-based threshold limit. Our key results demonstrate that de-noising returns improves the accuracy of volatility forecasts regardless of … whether we use statistical metrics, tests of equal predictive accuracy or a VaR procedure. In terms of a particular volatility …

This paper considers whether adding two established anomalies, momentum and low volatility, will improve our … derived from each asset pricing model. Our results suggest that the momentum and volatility factors provide no additional … model. Of note, the momentum and low volatility factors exhibit limited statistical significance, have similar coefficients …

This paper examines mean and volatility spillovers between the Turkish stock market with international stock, exchange …

of the stocks with high idiosyncratic volatility (high IVOL). An out-of-sample prediction of future profitability is …

This paper analyses the dynamic transmission mechanism of volatility spillovers between key global financial indicators … and G20 stock markets. To examine the volatility spillover relations a bivariate GARCH-BEKK model, which captures … volatility spillovers, is combined with complex network theory. Here, we construct a volatility network of international …

Forecasts of stock market volatility is an important input for market participants in measuring and managing investment … Machine Learning methods, and specifically Artificial Neural Network (ANN) models to forecast volatility. The ANN models are …

incorporation of supply and demand shocks generally improves the forecast of portfolio volatility under various portfolio weighting …

The HAR model dominates current volatility forecasting. This model implies a restricted lag approach, with three …, as Lasso models providing an improved fit. Out-of-sample forecasts for daily, weekly and monthly volatility, evaluated …