Knowledge that Transforms

Using a database of daily institutional trades, we document that a majority of short-term institutional trades lose money. In aggregate, over 23% of round-trip trades are held for less than 3 months, and the returns on these trades average -3.91% (nonannualized). These losses are pervasive across all types of stocks, with the lowest returns occurring in small stocks, value stocks, and low-momentum stocks. Short-term trades lose more in more volatile markets. Across funds, the worst short-term returns accrue to funds that do the most trading, and there is no evidence of persistent skill or disposition effect in short-term institutional trades.

We find that stock liquidity increases stock price crash risk. To identify the causal effect, we use the decimalization of stock trading as an exogenous shock to liquidity. This effect is increasing in a firm’s ownership by transient investors and nonblockholders. Liquid firms have a higher likelihood of future bad earnings news releases, which are accompanied by greater selling by transient investors, but not blockholders. Our results suggest that liquidity induces managers to withhold bad news, fearing that its disclosure will lead to selling by transient investors. Eventually, accumulated bad news is released all at once, causing a crash.

We present CoMargin, a new methodology to estimate collateral requirements in derivatives central counterparties (CCPs). CoMargin depends on both the tail risk of a given market participant and its interdependence with other participants. Our approach internalizes trading externalities and enhances the stability of CCPs, thus reducing systemic risk concerns. We assess our methodology using proprietary data from the Canadian Derivatives Clearing Corporation that include daily observations of the actual trading positions of all of its members from 2003 to 2011. We show that CoMargin outperforms existing margining systems by stabilizing the probability and minimizing the shortfall of simultaneous margin-exceeding losses.

Exchange rate models with uncertain and incomplete information predict that investors focus on a small set of fundamentals that changes frequently over time. We design a model selection rule that captures the current set of fundamentals that best predicts the exchange rate. Out-of-sample tests show that the forecasts made by this rule significantly beat a random walk for 5 out of 10 currencies. Furthermore, the currency forecasts generate meaningful investment profits. We demonstrate that the strong performance of the model selection rule is driven by time-varying weights attached to a small set of fundamentals, in line with theory.

The launch of the Single Supervisory Mechanism (SSM) was an historic event. Beginning in Nov. 2014, the most significant banks came under the direct supervision of the European Central Bank (ECB), while national supervisory authorities (NSAs) maintained direct supervision of the remaining banks. Thus, supervision is conducted on two levels, which could cause inconsistency problems. Did the behavior of the significant banks differ from that of the less significant banks during the SSM launch? We find that the significant banks reduced their lending activity more than the less significant banks did in order to shrink their balance sheets and increase their capitalization.

Price declines over the previous quarter lead to stronger reversals across the subsequent 2 months. We explain this finding based on the dual notions that liquidity provision can influence reversals and that agents who act as de facto liquidity providers may be less active in past losers. Supporting these observations, we find that active institutions participate less in losing stocks and that the magnitude of monthly return reversals fluctuates with changes in the number of active institutional investors. Thus, we argue that fluctuations in liquidity provision with past return performance account for the link between return reversals and past returns.

We show how firm-level real options lead to idiosyncratic skewness in stock returns. We then document empirically that growth option variables are positive and significant determinants of idiosyncratic skewness. The real option impact on skewness is more significant in firms with lottery-type features, small size, high volatility, distressed, low return on assets, and low book-to-market ratio. We also find that expectation on idiosyncratic skewness is associated with lower Sharpe ratios. This suggests investors are willing to sacrifice mean-variance portfolio efficiency for greater skewness deriving from real options. Furthermore, financial flexibility has a positive incremental effect, enhancing the beneficial role of asset flexibility on idiosyncratic skewness.

We use credit card data to estimate the impact of increasing minimum payments on delinquency, payments, spending, and write-offs. Our identification strategy exploits an unusual institutional feature: Borrowers can use their account to make purchases with both revolving loans (on which minimum payments increased) and term loans (on which there was no change). Payment increases by delinquent borrowers are insufficient to match increasing minimums, resulting in lower cure rates and an increase in write-offs. Affected borrowers migrate away from these accounts by decreasing charges and increasing payments, consequently lowering the interest earned by the bank.

On the day that dividends are paid, we find a significant positive mean abnormal return that is completely reversed over the following days. This dividend pay date effect has strengthened since the 1970s and is consistent with the temporary price pressure hypothesis. The pay date effect is concentrated among stocks with dividend reinvestment plans (DRIPs) and is larger for stocks with a higher dividend yield, greater DRIP participation, and greater limits to arbitrage. Over time, profits from a trading strategy that exploits this behavior are positively related to the dividend yield and spread and negatively associated with aggregate liquidity.

This paper documents an increase in the comovement between credit default swap (CDS) spread changes during the 2007–2009 crisis and investigates the source of that increase. One possible explanation is that comovement increased because fundamental values became more correlated. However, I find that changes in fundamentals account for only 23% of the increase in covariance. The remaining increase is attributed to changes in liquidity and the market price of default risk. In contrast, counterparty risk played an insignificant role. Although both contributed, the increase in covariance was driven more by variation in exposures than factor variance–covariance.