Knowledge that Transforms

Modern mutual fund families include more than active mutual funds (AMFs). AMFs in families with greater index mutual fund (IMF) presence generate higher category-adjusted gross returns. Performance is positively related to the levels of passive and active fees, suggesting moral hazard. Intrafamily competition from IMFs in the same Morningstar category incentivizes managers to exert effort. Financial resources do not contribute to the performance effect. Cross-trading with IMFs occurs with some positive effect on performance. ETFs have no impact on performance. IMFs reduce flow-performance sensitivity and flow volatility of AMFs in the family. IMFs and ETFs uniquely contribute to expense pressure.

We present and test a model to understand the puzzling fact that characteristics-sorted stock portfolios tend to earn opposite-signed overnight and intraday expected returns. Heterogeneous arbitrageurs – “fast” arbitrageurs with informational advantages and “slow” arbitrageurs with low inventory costs – compete to determine the price of liquidity. High information asymmetry around market open allows fast arbitrageurs to demand large price deviations for absorbing order imbalances, as cream-skimming risk discourages competition from slow arbitrageurs. Despite persistent order imbalances, these deviations attenuate when cream-skimming risk subsides, leading to opposite-signed overnight and intraday returns. Our model identifies novel determinants that empirically explain substantial variations in predictable overnight-minus-intraday returns.

We measure a stock’s exposure to fire sale risk through its ownership links to mutual funds that anticipate significant outflows during periods of systematic outflows from the fund industry. We find that stocks with higher exposure to this risk earn higher average returns: a portfolio that buys (shorts) stocks with the highest (lowest) exposure outperforms by 3-7% annually. Our findings cannot be explained by several known determinants of average returns and support the ex-ante pricing of the risk of fire sales. We conclude that stocks’ exposures to risks inherited from the constraints of shareholders have important implications for stock prices.

Revaluations of industry peers around horizontal acquisitions are negative when targets are private, but positive when they are public. We posit this “revaluation spread” arises because acquiring managers favor private targets when public firms are overvalued. Targets’ ownership status thus conveys information about industry assets’ misvaluation and triggers predictable revaluations. Supporting this idea, private acquisitions occur when private targets appear “cheaper” than public firms based on valuation multiples or the trading activity of industry insiders. The revaluation spread varies with overall market misvaluation, predicts future industry returns, and is unrelated to peers’ and industries’ fundamentals.

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.

We study the importance of financial markets for (un)employment fluctuations in a model with matching frictions where firms borrow under limited enforcement. Borrowing affects employment through a ‘debt bargaining channel’: higher debt improves the bargaining position of employers with workers and increases the incentive to hire. We estimate the model structurally and find that the debt bargaining channel accounts for 26 percent of unemployment fluctuations. We find empirical support for the channel at the micro level using firm level data from Compustat.

This paper uncovers a novel component for exchange rate predictability based on the price difference between sovereign credit default swaps denominated in different currencies. This new forecasting variable – the credit-implied risk premium – captures the expected currency depreciation conditional on a severe but rare credit event. Using data for 16 Eurozone countries, we find that the credit-implied risk premium positively forecasts the dollar-euro exchange rate return at various horizons. Moreover, a currency strategy that exploits the informative content of our predictor generates substantial out-of-sample economic value against the naïve random walk benchmark.

We show, using machine learning, that fund characteristics can consistently differentiate high from low-performing mutual funds, before and after fees. The outperformance persists for more than three years. Fund momentum and fund flow are the most important predictors of future risk-adjusted fund performance, while characteristics of the stocks that funds hold are not predictive. Returns of predictive long-short portfolios are higher following a period of high sentiment. Our estimation with neural networks enables us to uncover novel and substantial interaction effects between sentiment and both fund flow and fund momentum.

We consider a market where large investors do not only trade on information about asset fundamentals. When they trade more aggressively, the price becomes less informative. Other investors who learn from prices, in turn, are less concerned about adverse selection and provide more liquidity, causing large investors to trade even more aggressively. This trading complementarity can engender three unconventional results: i) increased competition among large investors makes all investors worse off, ii) more precise private information reduces price informativeness, creating complementarities in information acquisition, and iii) multiple equilibria emerge. Our results have implications for competition and transparency policies in financial markets.

Using a dynamic real-option model of litigation, we show that the increasingly popular practice of third-party litigation financing has ambiguous implications for total ex-post litigant surplus. A defendant and a plaintiff bargain over a settlement payment. The defendant takes costly actions to avoid deadweight losses associated with large transfers to the plaintiff. Litigation financing bolsters the plaintiff, leading to larger deadweight losses. However, by endogenously deterring the defendant from taking costly actions, litigation financing can nonetheless improve the joint surplus of the plaintiff and defendant. In contrast to popular opinion, litigation financing does not necessarily encourage high-risk frivolous lawsuits.