Research

My research interests are in market microstructure, financial econometrics, and asset pricing. I have presented at several international conferences, and my research has won multiple best paper awards.

• The Cross-Section of Price Efficiency

  Abstract: Inventory management by market makers can result in quoted prices deviating from unobserved fundamental prices. In a setting where prices have a factor structure, optimal inventory management implies that pricing errors of different securities are positively correlated if they load on the same risk factors. Using a state space model, I obtain estimates of 1-minute pricing errors for a panel of 1500 US stocks for the period 2016 – 2022. Daily cross-sectional regressions of pricing error correlations reveal that pricing error correlations increase in the similarity of factor betas. Investigating the role of liquidity demand in addition to liquidity supply, my results show that ETF flows are associated with higher pricing error correlations.

• Who Knows? Information Differences Between Trader Types, with Albert J. Menkveld

  We study the informativeness of client and intermediary trades. Order informativeness depends on the horizon and frequency we analyze. Aligned with the literature on high-frequency trading, intermediaries are more informed than clients at the highest frequency, as measured by the contribution of the respective order flow series to the variance of efficient price innovations. Once we move to lower frequencies, the client share increases and the intermediary share stays constant. This is reflected in the gross trading revenues of clients and intermediaries at different frequencies.

  This paper has been awarded the best paper award in Investments and Asset Pricing at the FMA European Conference 2023 and the best paper award at the Derivative Markets Conference 2023 of the Auckland Centre for Financial Research and the Auckland University of Technology. It was a semi-finalist for the best paper award at the 2023 FMA Annual Meeting.

• Price Dislocations: Insights from Trade Repository Data, with Albert J. Menkveld and Shihao Yu

  We identify periods of large price movements, price dislocation events, in EuroSTOXX 50 index futures and link them to information in trade repository data. Price dislocation events are accompanied by an increase in trading volume and in the number of executed trades. The market becomes more competitive in the sense that market concentration decreases, both on the liquidity-demand and the liquidity-supply side. Our results further show that, contemporaneously, public order book variables explain most of the price dislocation events; adding trade repository data adds relatively little. We further find that predicting price dislocations is extremely hard, even after adding private trade repository data to standard order book data.

  This project was carried out within the Alberto Giovannini Programme for Data Science of the ESRB.