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Retail trading and analyst coverage
Do speed bumps curb low-latency investment? Evidence from a laboratory market
Too-international-to-fail? Supranational bank resolution and market discipline
Supranational resolution of insolvent banks does not necessarily improve welfare. Supranational regulators are more inclined to bail-out banks indebted towards international creditors because they take into account cross-border contagion. When banks’ creditors are more likely to be bailed out, market discipline decreases and risk-taking by indebted banks increases. Depending on the trade-off between giving the right incentives ex ante and limiting contagion ex post, both a national and a supranational resolution framework can be optimal. In particular, if market discipline is low under both national and supranational resolution mechanisms, supranational resolution improves welfare as it stimulates interbank trade.
Speed and learning in high-frequency auctions
Queuing and inventories in limit order markets
Limit order markets use a queuing system in which limit orders must wait in line to execute. We show that the queue position of a limit order influences its adverse selection risk and inhibits inventory risk management. Trade may worsen market maker risk sharing, unlike many protocols without queuing. We uncover a crowding-out effect: An inventory shock reduces liquidity provision by market makers later in the queue. Using futures data, we confirm both low risk sharing and the crowding-out effect. These two results imply a trade-off, as the queuing sequence that optimizes risk sharing decreases quoted depth up to 8.4%. • Queue position affects adverse-selection risk and inventory management. • Market-maker risk sharing may worsen due to queuing. • Inventory shocks reduce liquidity provision later in the queue. • Canadian futures data confirm low risk sharing and crowding-out effects. • Optimizing risk sharing lowers quoted depth by up to 8.4%.
The Value of ETF Liquidity
We analyze how ETFs compete. Drawing on a new model and empirical analysis, we show that ETF secondary market liquidity plays a key role in determining fees. More liquid ETFs for a given index charge higher fees and attract short-horizon investors who are more sensitive to liquidity than to fees. Higher turnover from these investors sustains the ETF’s high liquidity, allowing the ETF to extract a rent through its fee, and creating a first-mover advantage. Liquidity segmentation through clientele effects generates welfare losses. Our findings resolve the apparent paradox that higher-fee ETFs not only survive but also flourish in equilibrium.
Need for Speed? Exchange Latency and Liquidity
A faster exchange does not necessarily improve liquidity. On the one hand, speed enables a high-frequency market maker (HFM) to update quotes faster on incoming news. This reduces payoff risk and thus lowers the competitive bid-ask spread. On the other hand, HFM price quotes are more likely to meet speculative high-frequency bandits, and thus are less likely to meet liquidity traders. This raises the spread. The net effect of exchange speed depends on a security's news-to-liquidity-trader ratio.
Nonstandard Errors
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—nonstandard 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 more reproducible or higher rated research. Adding peer‐review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.