Darya Yuferova
Associate Professor of Finance
Norwegian School of Economics (NHH)
Darya Yuferova
Associate Professor of Finance
Norwegian School of Economics (NHH)
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Associate Professor of Finance
Norwegian School of Economics (NHH)
Bellia, M., Pelizzon, L., Subrahmanyam, M., and Yuferova, D. (2025)
Market Liquidity and Competition among Designated Market Makers
Management Science 71 (1), 184-201
Do competition and incentives offered to designated market makers (DMMs) improve market liquidity? We employ data from NYSE Euronext Paris to show that exogenous changes in contract design lead to significant decreases in quoted and effective spreads. In particular, market liquidity increases the most for stocks with the largest increase in competition among DMMs. Our analysis shows that competition among DMMs is an important aspect of contract design, along with elements such as rebates and requirements.
Do competition and incentives offered to designated market makers (DMMs) improve market liquidity? We employ data from NYSE Euronext Paris to show that exogenous changes in contract design lead to significant decreases in quoted and effective spreads. In particular, market liquidity increases the most for stocks with the largest increase in competition among DMMs. Our analysis shows that competition among DMMs is an important aspect of contract design, along with elements such as rebates and requirements.
Journal of Finance 79 (3), 2339-2390
In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in 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 (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.
In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in 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 (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.
Algorithmic Trading and Market Efficiency around the Introduction of the NYSE Hybrid Market
Journal of Financial Markets 69, 100909
I study the effect of algorithmic trading on market efficiency, taking into account past market and limit order flows alike. I find that an exogenous increase in algorithmic trading around the introduction of the NYSE Hybrid Market leads to a significant decrease in the predictive power of surprises in market order imbalance and limit order book imbalances, especially at the outer levels of the limit order book. However, the predictive power of past returns remains largely unchanged. This suggests that algorithmic trading improves market efficiency by facilitating the incorporation of information embedded in both market and limit order flows.
I study the effect of algorithmic trading on market efficiency, taking into account past market and limit order flows alike. I find that an exogenous increase in algorithmic trading around the introduction of the NYSE Hybrid Market leads to a significant decrease in the predictive power of surprises in market order imbalance and limit order book imbalances, especially at the outer levels of the limit order book. However, the predictive power of past returns remains largely unchanged. This suggests that algorithmic trading improves market efficiency by facilitating the incorporation of information embedded in both market and limit order flows.
Bongaerts, D., Roll, R., Rösch, D., van Dijk, M., and Yuferova, D. (2022)
How Do Shocks Arise and Spread Across Stock Markets? A Microstructure Perspective
Management Science 68 (4), 3071-3089
We study intraday, market-wide shocks to stock prices, market liquidity, and trading activity on international stock markets and assess the relevance of recent theories on "liquidity dry-ups" in explaining such shocks. Market-wide price shocks are prevalent and large, with rapid spillovers across markets. However, price shocks are predominantly driven by information; they do not revert and are often associated with macroeconomic news. Furthermore, liquidity shocks are typically isolated and transitory. Overall, we find little evidence for liquidity effects fomenting price shocks or non-fundamental contagion, nor for alternative explanations. Market-wide liquidity dry-ups are thus of little concern to international investors.
We study intraday, market-wide shocks to stock prices, market liquidity, and trading activity on international stock markets and assess the relevance of recent theories on "liquidity dry-ups" in explaining such shocks. Market-wide price shocks are prevalent and large, with rapid spillovers across markets. However, price shocks are predominantly driven by information; they do not revert and are often associated with macroeconomic news. Furthermore, liquidity shocks are typically isolated and transitory. Overall, we find little evidence for liquidity effects fomenting price shocks or non-fundamental contagion, nor for alternative explanations. Market-wide liquidity dry-ups are thus of little concern to international investors.
Jagannathan, R., Pelizzon, L., Schaumburg, E., Sherman, M., and Yuferova, D. (2022)
Recovery from Fast Crashes: Role of Mutual Funds
Journal of Financial Markets 59, 100646
We study the role mutual funds play in the recovery from fast intraday crashes based on data from the National Stock Exchange of India for a single large stock. During normal times, trading activity and liquidity provision by mutual funds is negligible compared to other traders at around 4% of overall activity. Nevertheless, for the two intraday market-wide crashes in our sample, price recovery took place only after mutual funds moved in. Market stability may require the presence of well-capitalized standby liquidity providers for recovery from fast crashes.
We study the role mutual funds play in the recovery from fast intraday crashes based on data from the National Stock Exchange of India for a single large stock. During normal times, trading activity and liquidity provision by mutual funds is negligible compared to other traders at around 4% of overall activity. Nevertheless, for the two intraday market-wide crashes in our sample, price recovery took place only after mutual funds moved in. Market stability may require the presence of well-capitalized standby liquidity providers for recovery from fast crashes.
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