Risk Everywhere: Modeling and Managing Volatility

January 26, 2016
  • Contributors:

    Tim Bollerslev, Benjamin Hood, John Huss, Lasse H. Pedersen
  • Topic:

    Risk Management

Working paper

Based on a high-frequency dataset for more than 50 commodities, currencies, equity indices and fixed income instruments spanning more than two decades, the authors document strong similarities in realized volatilities patterns across assets and asset classes.

The authors assert that exploiting these similarities within and across asset classes in panel-based estimation of new realized volatility models results in improved out-of-sample R2s compared with forecasts from existing models and more conventional procedures that do not incorporate the information in the high-frequency intraday data and/or the commonalities in the volatilities.

This paper presents a framework to evaluate the utility gains from the use of risk models, highlighting the interplay between transaction costs, the speed of different risk models and their practical implementation.




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