Imperial College London


Business School

Casual - Lib. Ass, Clerks & Gen. Admin Assistants







349ACE ExtensionSouth Kensington Campus





Oleg has a PhD in Financial Economics at Imperial College Business School.

His research activities are mainly focused on empirical asset pricing in high-frequency markets and big-data solutions for financial econometrics.

Current projects

  • Low-Frequency Investment with High-Frequency Measures: Is it Profitable?
    I compare the profitability of the same investment strategy against two implementations of its trading signals: one that conventionally uses daily returns (LF) and the other that takes advantage of high-frequency (HF) returns. Although economic differences favour the HF implementation, the evidence is not statistically significant. Nonetheless, the HF implementation is more robust to the choice of parameters and provides, for the most illiquid stocks, strong economic benefits that are inversely increasing in the length of the formation period.
  • Intraday momentum
    I find that statistical time-series predictability does not imply intraday economic profitability, whereas cross-sectional sorts on past performance see stocks, which lost or won the most in the morning, earn in the last half-hour of trading about 15.6 and 19.4% in annualized terms, and well above the rest of the cross-section. The effect is fundamentally different from Heston et al. (2010) and is robust to stock characteristics, the day-of-week effect, variations in the formation and holding periods (afternoon), but exhibits some dependence on the sample period, suggesting that specific market mechanisms or frictions play a relevant role on intraday price formation.
  • Acceleration in prices
    Is price acceleration an informative trading signal? We find that buying stocks whose returns are decelerating and shorting stocks whose returns are accelerating, produces a wide spread in returns. While, these profits are not explained by the state-of-the-art equity factor models, they are subsumed by our la5 factor, a simple reversal strategy with a lookback of one week. Our results cast doubt on acceleration being a separate phenomenon and suggest that the lookback period in trending strategies has been shrinking over time.


Github account okomarov with code for the projects mentioned above and other contributions, like the Matlab to WRDS interface.