Dobrislav Dobrev

Dobrislav Dobrev’s research is focused on volatility, jumps, and co-movements of high frequency financial time series with emphasis on robust inference in finite samples, data reduction techniques, and applications to risk measurement and forecasting.  He has contributed to the development of a variety of methods such as range-based and duration-based estimation approaches, robustification via neighborhood truncation and functional filtering procedures, as well as, most recently, robust techniques for latent factor extraction.  He is currently working on problems related to proper identification and attribution of major market moving events, low-frequency data modeling incorporating high-frequency statistics, and out-of-sample forecasting of macro-financial variables.

He holds a PhD in Finance from Northwestern University’s Kellogg School of Management, an MSc in Applied Mathematics from Sofia University, Bulgaria, and is the winner of the 2007 Chookaszian Prize in Risk Management.

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