RESEARCH

Working papers


Non-Standard Errors (#fincap)
with Albert Menkveld, Anna Dreber, Felix Holzmeister, Juergen Huber, Magnus Johannesson, Michael Kirchler, Sebastian Neusüss, Michael Razen, Utz Weitzel, and others (300+ co-authors)

Presented at: 2021 Microstructure Exchange series

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.


Presented at: 2021 FMA Annual Meeting, 2020 Australasian Finance and Banking Conference (AFBC), 2020 Financial Research Network (FIRN) PhD Symposium, Annual 2020 International Risk Management Conference (IRMC) , 2020 Econometric Research in Finance (ERFIN) Workshop, 2020 UNSW-UniMelb Market Microstructure Workshop, 2020 International Conference on Derivatives and Capital Markets (ICDCM), Monash University, Tianjin University, UNSW Brown Bag Seminar

I show that short interest is arguably the strongest market return predictor internationally. Short interest significantly and negatively predicts returns in 24 out of 32 countries examined; this predictability survives out-of-sample tests, persists outside recessions, and is not subsumed by other well-known return predictors. The results indicate that short interest contains valuable information for forecasting international market returns that is distinct and more powerful than that of other globally available predictors. However, the predictive power of short interest varies across regions and increases when short selling is constrained by local short sale regulations or equity lending market frictions.


Rationally Neglected Stocks
with Oleg Chuprinin and Chang-Mo Kang

Presented at: 2021 Annual Conference on Asia-Pacific Financial Markets (CAFM), 2019 Paris December Finance Meeting, 2019 Financial Research Network (FIRN) Annual Meeting, 2019 Behavioural Finance and Capital Markets (BFCM) Conference (Amery Partners Best Paper Award), 2019 International Finance and Banking Society (IFABS) Angers Conference, 2019 Security Industry Research Centre of Asia Pacific (SIRCA) Young Researchers Workshop, UNSW Brown Bag Seminar

There are large cross-sectional differences in the probability and magnitude of mispricing among stocks. Mispricing is traditionally attributed to stock-specific frictions. We show that mispricing can be explained in a rational equilibrium where investors allocate investigative resources to stocks to maximize their expected profits from arbitrage. Stocks with smaller dollar profit potential are allocated less attention and their percentage mispricing is higher on average. For such stocks, information discovery by investors is slow and the mispricing is corrected mostly through mandatory disclosures by firms. Using measures of institutional attention and trading discreteness, we confirm this mechanism empirically. The attention allocation channel explains the cross-sectional pattern of mispricing better than any classic arbitrage frictions.


Can Slow and Steady Win the Race? Examining Slow and Fast Liquidity Providers in Modern Equity Markets
with Sean Foley and Thomas Ruf

Presented at: 2019 Australasian Banking and Finance Conference (AFBC), 2019 Sydney Banking and Financial Stability Conference (SBFC), 2019 UNSW Business School Research Fair (Best Poster Award)

We find that increased speed competition from high-frequency market makers (HFT MMs) reduces but does not entirely eliminate the participation of slower liquidity-providing MMs. The presence of HFT MMs reduces slower MMs’ profits without impacting the profitability of executed trades. These results indicate that HFT MMs do not expose slower MMs to increased adverse selection. However, these findings only hold when the bid-ask spread is constrained by the minimum tick size. Tick-constrained spreads help slower MMs to retain profitability in their market-making business and remain as liquidity providers.