Terrence Hendershott

Algorithmic Trading and the Market for Liquidity

We examine the role of algorithmic traders (ATs) in liquidity supply and demand in the 30 Deutscher Aktien Index stocks on the Deutsche Boerse in Jan. 2008. ATs represent 52% of market order volume and 64% of nonmarketable limit order volume. ATs more actively monitor market liquidity than human traders. ATs consume liquidity when it is cheap (i.e., when the bid-ask quotes are narrow) and supply liquidity when it is expensive. When spreads are narrow ATs are less likely to submit new orders, less likely to cancel their orders, and more likely to initiate trades. ATs react more quickly to events and even more so when spreads are wide.

Bundling and Optimal Auctions of Multiple Products

We study the optimal (i.e. revenue maximizing) auction of multiple products. We make three major points. First, we extend the relationship between price discrimination and optimal auctions from the single-product case to the multiple-product case. A monopolist setting prices for multiple products may offer discounts on purchases of bundles of products; similarly, the optimal auction of multiple products facilitates price discrimination by allocating products inefficiently to customers who are willing to purchase both products. Second, we demonstrate that optimal auctions are qualitatively distinct from monopoly sales of multiple products. Because of uncertainty about the values of other consumers, two products are bundled probabilistically in an optimal auction for a customer who is willing to buy both of them. A customer may then receive a discount on a lower-valued product without receiving a higher-valued product. Third, we show that in an optimal auction of two products the allocation of one product may vary with the amount of competition for the other product.

High-Frequency Trading and the Execution Costs of Institutional Investors

This paper studies whether high-frequency trading (HFT) increases the execution costs of institutional investors. We use technology upgrades that lower the latency of the London Stock Exchange to obtain variation in the level of HFT over time. Following upgrades, the level of HFT increases. Around these shocks to HFT institutional traders’ costs remain unchanged. We find no clear evidence that HFT impacts institutional execution costs.

Electronic trading in financial markets

Technological innovations such as electronic communication networks bypass human intermediaries, increasing competition and reducing transaction costs for electronic trading in financial markets.

How Slow is the NBBO? A Comparison with Direct Exchange Feeds

This paper provides evidence on the benefits of faster proprietary data feeds from stock exchanges over the regulated “public” consolidated data feeds. We measure and compare the National Best Bid and Offer (NBBO) prices in each data feed at the same data center. Price dislocations between the NBBOs occur several times a second in very active stocks and typically last one to two milliseconds. The short duration of dislocations makes their costs small for investors who trade infrequently, while the frequency of the dislocations makes them costly for frequent traders. Higher security price and days with high trading volume and volatility are associated with dislocations.

High Frequency Trading and the 2008 Short Sale Ban

We examine the effects of high-frequency traders (HFTs) on liquidity using the September 2008 short sale-ban. To disentangle the separate impacts of short selling by HFTs and non-HFTs, we use an instrumental variables approach exploiting differences in the bans cross-sectional impact on HFTs and non-HFTs. Non-HFTs’ short selling improves liquidity, as measured by bid-ask spreads. HFTs’ short selling has the opposite effect by adversely selecting limit orders, which can decrease liquidity supplier competition and reduce trading by non-HFTs. The results highlight that some HFTs’ activities are harmful to liquidity during the extremely volatile short-sale ban period.

Market Predictability and Non-Informational Trading

This paper studies the ability of non-informational order imbalances (buy minus sell volume) to predict daily stock returns at the market level. Using a model with three types of participants (an informed trader, liquidity traders, and a finite number of arbitrageurs), we derive predictions relating returns to lagged returns and lagged order imbalances. Empirical tests using New York Stock Exchange non-informational basket/portfolio trading data provide results consistent with adverse selection at the market-level, but no evidence of limited risk-bearing capacity. Finally, we establish that these market-wide non-informational order imbalances also affect individual stock return comovement by examining additions to the S&P500 Index.

Electronic Communications Networks and Market Quality

We compare the execution quality of trades with market makers to trades executed on Electronic Communications Networks (ECNs). Average quoted, realized, and effective spreads are smaller for ECN trades than for market-maker trades even though ECN trades are more informative than trades with market makers. Increased trading on ECNs also improves most measures of overall market quality. In the cross section, more ECN trading is associated with lower quoted, effective, and realized spreads, both overall and on trades with market makers. More ECN trading is also associated with less quoted depth.

Price Discovery Without Trading: Evidence from Limit Orders

We analyze the contribution to price discovery of market and limit orders by high‐frequency traders (HFTs) and non‐HFTs. While market orders have a larger individual price impact, limit orders are far more numerous. This results in price discovery occurring predominantly through limit orders. HFTs submit the bulk of limit orders and these limit orders provide most of the price discovery. Submissions of limit orders and their contribution to price discovery fall with volatility due to changes in HFTs’ behavior. Consistent with adverse selection arising from faster reactions to public information, HFTs’ informational advantage is partially explained by public information.

Information and Trading on Electronic Communications Networks

The differences between ECNs and Nasdaq market makers are used to formulate and test several hypotheses about the choice of trading venue and the importance of ECN trades in the price discovery process. Trades are more likely to occur on ECNs when spreads are narrow and when trading volume and stock-return volatility are high. Medium and large trades on ECNs have lower effective spreads than comparable market-maker trades, although this is not the case for small trades unless they occur on noninteger ticks. ECN trades have greater permanent price impacts than market-maker trades implying that informed trades are more likely to occur on ECNs. Overall, more private information is revealed through ECN trades than through market-maker trades even though more trades occur with market makers.