Denys Maslov


Strategy Performance Persistence and Mutual Fund Price Pressure (2013), Job Market Paper

  1. Abstract: I investigate whether flow-induced trading by mutual funds gives rise to the time series persistence in returns of strategies based on fourteen well-known asset pricing anomalies. I find significant persistence for eight characteristics including size, book-to-market, corporate investment anomalies, accounting anomalies, and bankruptcy likelihood. The persistence is not explained by individual stock momentum and is not limited to certain calendar months. The return predictability can be used to construct new trading strategies, which on average earn 4.5% annually. A price pressure measure of mutual fund flow-driven trading explains a substantial part of the strategy performance persistence.

Aggregation of Information about the Cross Section of Stock Returns: A Latent Variable Approach (2013), (with Nathaniel Light and Oleg Rytchkov)

  1. Abstract: We propose a new approach to estimation of expected returns on individual stocks from a large number of firm characteristics. We treat expected returns and betas as latent variables and develop a procedure that filters them out using the characteristics as signals and imposing restrictions implied by an underlying asset pricing model. The procedure is more efficient than alternatives and robust to data mining. The estimates of expected returns obtained by applying our method to thirteen asset pricing anomalies generate a wide cross-sectional dispersion of realized returns. Our results provide evidence of strong commonality in asset pricing anomalies. The use of portfolios based on the estimated expected returns as test assets increases the power of asset pricing tests.

Robustness and Monotonicity of Asset Pricing Anomalies (2012), (with Oleg Rytchkov)

  1. Abstract: We examine the sensitivity of fourteen asset pricing anomalies to extreme observations using robust regression methods. We find that although all anomalies except size are strong and robust for stocks with presumably low returns, most of them are sensitive to individual influential observations for stocks with presumably high returns. For some anomalies, extreme observations distort regression results for all stocks and even portfolio returns. When the impact of such observations is mitigated, eight anomalies become positively related to expected returns for stocks with low characteristics meaning that these anomalies have an inverted J-shaped form.

Finance Ph.D. Candidate

McCombs School of Business, U.T. Austin

Research Interests

Empirical Asset Pricing, Institutional Investors


Contact Information

McCombs School of Business

University of Texas at Austin

1 University Station; B6600

Austin, TX 78712