* Corresponding author. Abstract: Recent theoretical work has revealed a direct connection between asset return volatility forecastability and asset return sign forecastability. This suggests that the pervasive volatility forecastability in equity returns could, via induced sign forecastability, be used to produce direction-of-change forecasts useful for market timing. We attempt to do so in an international sample of developed equity markets, with some success, as assessed by formal probability forecast scoring rules such as the Brier score. An important ingredient is our conditioning not only on conditional mean and variance information, but also conditional skewness and kurtosis information, when forming direction-of-change forecasts
We study the directional predictability of monthly excess stock market returns in the U.S. and ten o...
We study the directional predictability of monthly excess stock market returns in the U.S. and ten o...
This paper models time-varying skewness for financial return dynamics. We decompose nancial returns ...
Recent theoretical work has revealed a direct connection between asset return volatility forecastabi...
Recent theoretical work has revealed a direct connection between asset return volatility forecastabi...
Abstract: We consider three sets of phenomena that feature prominently – and separately – in the fi...
This dissertation examines the impact of high frequency data in volatility measurement on the distri...
We consider three sets of phenomena that feature prominently - and separately - in the financial eco...
We use an international dataset on 5-min interval intraday data covering nine leading markets and re...
Volatilities and correlations for equity markets rise more after negative returns shocks than after ...
Score driven (SD) conditional volatility models allow for rich volatility dynamics and realistic dis...
One of the most fundamental and widely accepted ideas in finance is that investors are compensated t...
Most of existing studies sample markets' prices as time series when developing models to predict mar...
The skewness of the conditional return distribution plays a significant role in financial theory and...
We use intraday data to compute weekly realized variance, skewness, and kurtosis for equity returns ...
We study the directional predictability of monthly excess stock market returns in the U.S. and ten o...
We study the directional predictability of monthly excess stock market returns in the U.S. and ten o...
This paper models time-varying skewness for financial return dynamics. We decompose nancial returns ...
Recent theoretical work has revealed a direct connection between asset return volatility forecastabi...
Recent theoretical work has revealed a direct connection between asset return volatility forecastabi...
Abstract: We consider three sets of phenomena that feature prominently – and separately – in the fi...
This dissertation examines the impact of high frequency data in volatility measurement on the distri...
We consider three sets of phenomena that feature prominently - and separately - in the financial eco...
We use an international dataset on 5-min interval intraday data covering nine leading markets and re...
Volatilities and correlations for equity markets rise more after negative returns shocks than after ...
Score driven (SD) conditional volatility models allow for rich volatility dynamics and realistic dis...
One of the most fundamental and widely accepted ideas in finance is that investors are compensated t...
Most of existing studies sample markets' prices as time series when developing models to predict mar...
The skewness of the conditional return distribution plays a significant role in financial theory and...
We use intraday data to compute weekly realized variance, skewness, and kurtosis for equity returns ...
We study the directional predictability of monthly excess stock market returns in the U.S. and ten o...
We study the directional predictability of monthly excess stock market returns in the U.S. and ten o...
This paper models time-varying skewness for financial return dynamics. We decompose nancial returns ...