We study how information technology (IT) affects lender competition, entrepreneurs’ investment, and welfare in a spatial model. The effects of an IT improvement depend on whether it weakens the influence of lender–borrower distance on monitoring costs. If it does, it has a hump-shaped effect on entrepreneurs’ investment and social welfare. If not, competition intensity does not vary, improving lender profits, entrepreneurs’ investment, and social welfare. When entrepreneurs’ moral hazard problem is severe, IT-induced competition is more likely to reduce investment and welfare. We also find that lenders’ price discrimination is not welfare-optimal. Our results are consistent with received empirical work on lending to SMEs.

We examine M&A transactions between firms with current board connections and find that acquirers obtain higher announcement returns in transactions with a first-degree connection where the acquirer and the target share a common director. Acquirer returns are also higher in transactions with a second-degree connection where one acquirer director and one target director serve on the same third board. Our results suggest that first-degree connections benefit acquirers with lower takeover premiums while second-degree connections benefit acquirers with greater value creation. Overall, we provide new evidence that board connectedness plays important roles in corporate investments and leads to greater value creation.

We examine how fragmentation is affecting market quality in US equity markets. We use newly available trade reporting facilities (TRFs) data to measure fragmentation, and we use a variety of empirical approaches to compare execution quality and efficiency of stocks with more and less fragmented trading. We find that fragmentation affects all stocks; more fragmented stocks have lower transactions costs and faster execution speeds; and fragmentation is associated with higher short-term volatility but greater market efficiency, in that prices are closer to being a random walk. Our results that fragmentation does not appear to harm market quality are consistent with US markets being a single virtual market with multiple points of entry.

To prevent issuers from inflating their share prices, SEC Rule 10b-18 sets price ceilings on share repurchases through open markets. We find that market-structure reforms in the 1990s and 2000s dramatically increased share repurchases because they relaxed constraints on issuers competing with other buyers under price ceilings. The Tick Size Pilot Program, a controlled experiment that partially reversed previous reforms, significantly reduced share repurchases. We estimate that price ceilings and reduced market-structure frictions explain 18% of the secular increase in share repurchases. Meanwhile, these two frictions still exist, which explains why share repurchases have not crowded out dividends entirely.

The Regulation National Market System (Reg NMS) links fragmented stock exchanges by routing orders to the National Best Bid and Offer (NBBO). As the NBBO ignores exchange fees, 62% of routings lead to worse net prices. An increase in fee differences increases the market share captured by orders that refuse Reg NMS routings, particularly for stocks whose fees account for a large portion of transaction costs. Heterogeneous opportunity costs rationalize routing choices: non-routable orders entail lower non-execution costs than routable orders. Our results indicate that fees and clientele segmentation drive the proliferation of order types in the Reg NMS era.

This paper examines post-revision return drift, or PRD, following analysts’ revisions of their stock recommendations. PRD refers to the finding that the analysts’ recommendation changes predict future long-term returns in the same direction as the change (i.e., upgrades are followed by positive returns, and downgrades are followed by negative returns). During the high-frequency algorithmic trading period of 2003–2010, average PRD is no longer significantly different from zero. The new findings agree with improved market efficiency after declines in real trading cost inefficiencies. They are consistent with a reduced information production role for analysts in the supercomputer era.

We provide a spatial framework to study competition between banks and fintechs in the lending market and examine the impact on investment and welfare. Based on the key differences between banks and fintechs, we derive results consistent with the empirical evidence available. We find that fintechs with inferior monitoring efficiency can successfully enter because of their superior flexibility in pricing and that higher bank concentration leads to higher fintech loan volume. If fintechs and banks have similar funding costs, fintech borrowers pay lower loan rates and have higher default rates than bank borrowers with similar characteristics; however, the result will flip if fintechs have much higher funding costs than banks. The advantage of fintechs in offering convenience can also induce them to charge higher loan rates than banks. Fintech entry will improve welfare if fintechs have high monitoring efficiency and inter-fintech competition intensity is intermediate. Fintech entry may induce banks’ exit and reduce investment; however, it will increase investment if inter-fintech competition is intense enough.

Using a structural model, we estimate the liquidity multiplier of an interbank network and banks’ contributions to systemic risk. To provide payment services, banks hold reserves. Their equilibrium holdings can be strategic complements or substitutes. The former arises when payment velocity and multiplier are high. The latter prevails when the opportunity cost of liquidity is large, incentivising banks to borrow neighbors’ reserves instead of holding their own. Consequently, the network can amplify or dampen shocks to individual banks. Empirically, network topology explains cross-sectional heterogeneity in banks’ systemic-risk contributions while changes in the equilibrium type drive time-series variation.

We examine the performance impact of the relative quality of a Chief Executive Officer (CEO)’s compensation peers (peers to determine a CEO's overall compensation) and bonus peers (peers to determine a CEO's relative-performance-based bonus). We use the fraction of peers with greater managerial ability scores (Demerjian, Lev, and McVay, 2012) than the reporting firm to measure this CEO's relative peer quality (RPQ). We find that firms with higher RPQ earn higher stock returns and experience higher profitability growth than firms with lower RPQ. Learning among peers and the increased incentive to work harder induced by the peer-based tournament contribute to RPQ's performance effect.

We model competition for liquidity provision between high-frequency traders (HFTs) and slower execution algorithms (EAs) designed to minimize investors’ transaction costs. Under continuous pricing, EAs dominate liquidity provision by using aggressive limit orders to stimulate HFTs’ market orders. Under discrete pricing, HFTs dominate liquidity provision if the bid-ask spread is binding at one tick. If the tick size (minimum price variation) is not binding, EAs choose between stimulating HFTs and providing liquidity to non-HFTs. Transaction costs increase with the tick size but can be negatively correlated with the bid-ask spread when all traders can provide liquidity.