TY - UNPB
T1 - Learning about adverse selection in markets
AU - Aliyev, Nihad
AU - He, Xue-Zhong
AU - Putniņš, Tālis J.
PY - 2023
Y1 - 2023
N2 - How does a market learn about the number of informed traders and thus adverse selection risk? Using a model, we show that trade sequences convey information about adverse selection risk. Consequently, buy/sell order imbalances can destabilize markets, triggering extreme price movements, flash crashes, and liquidity evaporation. The increasing prevalence of these effects in markets can be explained by more active learning about adverse selection by competitive, high-frequency market makers. We use our model to estimate the uncertainty in adverse selection risk for US stocks and show that it decreases market liquidity and increases extreme price movements.
AB - How does a market learn about the number of informed traders and thus adverse selection risk? Using a model, we show that trade sequences convey information about adverse selection risk. Consequently, buy/sell order imbalances can destabilize markets, triggering extreme price movements, flash crashes, and liquidity evaporation. The increasing prevalence of these effects in markets can be explained by more active learning about adverse selection by competitive, high-frequency market makers. We use our model to estimate the uncertainty in adverse selection risk for US stocks and show that it decreases market liquidity and increases extreme price movements.
KW - adverse selection
KW - multidimensional learning
KW - market stability
KW - extreme price movements
U2 - 10.2139/ssrn.3286933
DO - 10.2139/ssrn.3286933
M3 - Preprint
T3 - SSRN
BT - Learning about adverse selection in markets
PB - SSRN
ER -