Equity Risk: Measuring Return Volatility Using Historical High-Frequency Data

Forecasting the Return Distribution Using High-Frequency Volatility Measures

The aim of this paper is to forecast (out-of-sample) the distribution of financial returns based on realized volatility measures constructed from high-frequency returns. We adopt a semi-parametric model for the distribution by assuming that the return quantiles depend on the realized measures and evaluate the distribution, quantile and interval forecasts of the quantile model in comparison to a...

The Information Content of High-Frequency Data for Estimating Equity Return Models and Forecasting Risk

NOTE: International Finance Discussion Papers are preliminary materials circulated to stimulate discussion and critical comment. References to International Finance Discussion Papers (other than an acknowledgment that the writer has had access to unpublished ma-Abstract We demonstrate that the parameters controlling skewness and kurtosis in popular equity return models estimated at daily freque...

Forecasting Volatility using High Frequency Data

Measuring causality between volatility and returns with high-frequency data

We use high-frequency data to study the dynamic relationship between volatility and equity returns. We provide evidence on two alternative mechanisms of interaction between returns and volatilities: the leverage effect and the volatility feedback effect. The leverage hypothesis asserts that return shocks lead to changes in conditional volatility, while the volatility feedback effect theory assu...

Using High-Frequency Data to Model Volatility Dynamics

he covariance matrix of asset returns is important for a wide range of individuals.1 Academics use estimates of the covariance matrix to test asset-pricing theories. Portfolio managers use the covariance matrix in designing tracking strategies where the return on their portfolio is designed to closely follow the return on a benchmark portfolio. Risk managers use the matrix to construct measures...