Anna Obizhaeva's paper "Trading in Crowded Markets" (co-authored with Yajun Wang and Stepan Gorban, MAE'2017 graduate) got the Best Paper in Investments award at the 2019 FMA Asia/Pacific Conference in July 2019.
Shortly about the paper:
"With a dramatic growth in the asset management industry, financial markets have become platforms where sophisticated institutional players trade intensively with each other, while retail traders are of much smaller importance. Traders usually seek for overlooked opportunities and try to add more diversity into their portfolios, but many trading strategies often become crowded. Crowded markets are of a deep concern, because these markets tend to be more fragile and prone to crashes.
Market participants come up with investment ideas for generating alphas, evaluate transaction costs of implementing these strategies in real markets, and try to assess, usually informally, to what extent strategies might have been crowded, i.e., how many other traders might be simultaneously entering the same strategy space and to what extent their private signals might be correlated. While there has been lots of academic research in finance on both returns anomalies and liquidity, the question about market crowdedness until recently has received little formal attention. In the 2009-presidential address, Jeremy Stein emphasizes this point and notes that "for a broad class of quantitative trading strategies, an important consideration for each individual arbitrageur is that he cannot know in real-time exactly how many others are using the same model and taking the same position as him."
Recognizing the importance of this issue, some firms started to provide tools for identifying and measuring crowdedness of trades and strategies, for example, such as the "crowding scorecard" offered by the MSCI. In our paper, we fill the gap and study theoretically the crowded-market problem, analyzing how thinking about crowdedness interacts with other aspects of trading, such as private information and liquidity".
