Knowledge that Transforms

Rational models claim “trading to learn” explains widespread excessive speculative trading and challenge behavioral explanations of excessive trading. We argue rational learning models do not explain speculative trading by studying day traders in Taiwan. Consistent with previous studies of learning, unprofitable day traders are more likely than profitable traders to quit. Consistent with models of overconfidence and biased learning (but not with rational learning), the aggregate performance of day traders is negative; 74% of day trading volume is generated by traders with a history of losses; and 97% of day traders are likely to lose money in future day trading. Received: March 4, 2019; Editorial decision: May 16, 2019 by Editor: Jeffrey Pontiff.

We investigate the impact of monetary policy shocks on excess corporate bonds returns. We obtain a significant negative response of bond returns to policy shocks, which is especially strong among low-grading bonds. The largest portion of this response is related to higher expected bond returns (risk premium news), while the impact on expectations of future interest rates (interest rate news) plays a secondary role. However, the interest rate channel is dominant among high-grading bonds and Treasury bonds. Looking at the two components of bond premium news, we find that the dominant channel for high-rating (low-rating) bonds is term premium (credit premium) news. (JEL 44, E52, G10, G12) Received: March 25, 2019: Editorial decision: March 27, 2020 by Editor: Hui Chen.

I test a number of well-known asset pricing models using regression-based managed portfolios that capture nonlinearity in the cross-sectional relation between firm characteristics and expected stock returns. Although the average portfolio returns point to substantial nonlinearity in the data, none of the asset pricing models successfully explain the estimated nonlinear effects. Indeed, the estimated expected returns produced by the models display almost no variation across portfolios. Because the tests soundly reject every model considered, it is apparent that nonlinearity in the relation between firm characteristics and expected stock returns poses a formidable challenge to asset pricing theory.

Contrary to the predictions of traditional life-cycle models, household consumption is excessively sensitive to current income. Similarly, weak evidence of income hedging runs against standard portfolio theory. We link these two puzzles by modifying the theoretical framework of Viceira (2001) to study how consumption-income sensitivities generated by income in the utility function affect households' portfolio choices. Empirically, we find that consumption-income sensitivities affect asset allocation through the income hedging channel. In particular, we show that the interaction between consumption-income sensitivity and the correlation of income growth to stock market returns is an important explanatory variable for households' stock market holdings. Received October 20, 2016; editorial decision April 25, 2018 by Editor Wayne Ferson.

We study the workup protocol, an important size discovery mechanism in the U.S. Treasury market. We find that workup order flow shocks explain 6%–8% of the variation of returns on benchmark notes and, across maturities, 10% of the variation of the yield curve level factor. Information related to proprietary client order flow is more likely to show up in workup trades, whereas information derived from public announcements tends to come through preworkup trades. Our findings highlight how the nature of information affects the trade-off between speed and execution price when informed traders choose between the lit and workup channels. Received May 3, 2017; Editorial decision August 1, 2018 by Editor Thierry Foucault. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online. Internet Appendix tables are numbered with “IA” prefix.

Since the introduction of its quantitative and qualitative easing program in 2013, the Bank of Japan has been increasing its holdings of Japanese equity through large-scale purchases of index-linked ETFs, to lower risk premiums. We exploit the cross-sectional heterogeneity of the supply shock to identify a positive and persistent impact on stock prices, consistent with a portfolio balance channel. The evidence suggests that long-run demand curves for stocks are downward sloping with unitary price elasticity. We show that the purchases of ETFs tracking the price-weighted Nikkei 225 generate pricing distortions relative to a value-weighted benchmark. Received April 13, 2018; editorial decision July 18, 2019 by Editor Thierry Foucault.

I assess time-series return predictability using a weighted least squares estimator that is around 25% more efficient than ordinary least squares (OLS) because it incorporates timevarying volatility into its point estimates. Traditional predictors, such as the dividend yield, perform better in-and out-of-sample when using my estimator, indicating the insignificant OLS estimates may be false negatives driven by a lack of power. Some newer predictors, such as the variance risk premium and the president's political party, are insignificant when using my estimator, indicating the significant OLS estimates may be false positives driven by a few periods with high expected volatility.

We construct a traded funding liquidity measure from stock returns. Guided by a model, we extract the measure as the return spread between two beta-neutral portfolios constructed using stocks with high and low margins, to control for their sensitivity to the aggregate funding shocks. Our measure of funding liquidity is correlated with other funding liquidity proxies. It delivers a positive risk premium that cannot be explained by existing risk factors. A model augmented by our funding liquidity measure has superior pricing performance for various portfolios. Despite evident comovement, this measure contains additional information that is not subsumed by market liquidity.

We identify the causal effects of short-selling bans on stock prices using regression discontinuity (RD). We exploit three threshold-based rules that determine a stock’s short-selling eligibility on the Hong Kong Stock Exchange. Short-selling bans have a large effect on short-selling volume at all thresholds. Despite this, bans do not affect stock prices. Stock returns, volatility, and crash risk are not different for banned versus unrestricted stocks when appropriate counterfactual stocks are used to measure a ban’s effects. Our findings suggest that short-selling bans are not as costly as previously argued, but are ineffective at reducing volatility or buttressing prices. Received September 13, 2017; editorial decision April 29, 2018 by Editor Jeffrey Pontiff.

We study whether mutual funds systematically manage the downside risk of their portfolios in ways that improve their performance. We find that actively managed mutual funds on average possess positive downside-risk-timing ability. Managers adjust funds’ downside risk exposure in response to macroeconomic information; however, downside-risk-timing skills remain strong even after controlling for macro variables. Funds more skilled in timing downside risk outperform those that are not by 14.3 bp per month (or 1.73% annualized) unconditionally and by 39.9 bp per month (or 4.89% annualized) during recessions; they also attract larger flows. Received September 11, 2016; editorial decision Januaruy 08, 2018 by Editor Wayne Ferson.