We investigate why spreads on corporate bonds are so much larger than expected losses from default. Systematic factors make very little contribution to spreads, even if higher moments or downside effects are taken into account. Instead we find that sizes of spreads are strongly related to idiosyncratic-risk factors: not only to idiosyncratic equity volatility, but even more to idiosyncratic bond volatility and idiosyncratic bond value-at-risk. Idiosyncratic bond volatility helps to explain spreads because it reflects not just the distribution of firm value but is also a proxy for liquidity risk. Idiosyncratic bond value-at-risk adds to this by capturing the left-skewness of the firm-value distribution. We confirm our results both for the initial 1997–2004 sample period and also out of sample for 2005–2009, which includes the sub-prime crisis. Overall, credit spreads are large because they incorporate a large risk premium related to investors’ fears of extreme losses.

Gruber (1996) and Zheng (1999) report that investors channel money toward mutual funds that subsequently perform well. Sapp and Tiwari (2004) find that this “smart money” effect no longer holds after controlling for stock return momentum. While prior work uses quarterly U.S. data, we employ a British data set of monthly fund inflows and outflows differentiated between individual and institutional investors. We document a robust smart money effect in the United Kingdom. The effect is caused by buying (but not selling) decisions of both individuals and institutions. Using monthly data available post‐1991 we show that money is comparably smart in the United States.

Using data on the universe of U.S. based mutual funds, we find that two out of five fund families hold corporate bonds of firms in which they also own an equity stake. We show that the greater the fraction of debt a fund family holds in a given firm, the greater its propensity to vote in line with the interests of firm debtholders at shareholder meetings, even when against Institutional Shareholder Services (ISS) recommendation. Voting has direct policy consequences as firms that receive more votes in favor of creditors make corporate decisions more in line with the interests of debtholders.

We compare the long run reaction to anticipated and surprise information announcements using stock splits. Although there is underreaction in both cases, anticipated splits are treated differently to those that are unforeseen. After anticipated splits, cumulative abnormal returns peak at one-and-a-half times the level observed after unanticipated splits although the time taken for the announcement to be absorbed into prices is the same. We explain the difference in underreaction by the degree to which split announcements are believed and hence invested in. The favorable signal conveyed in forecast splits is more credible owing to their better pre-split performance, resulting in a far more pronounced underreaction effect.

We use a new data set to study the determinants of the performance of open–end actively managed equity mutual funds in 27 countries. We find that mutual funds underperform the market overall. The results show important differences in the determinants of fund performance in the USA and elsewhere in the world. The US evidence of diminishing returns to scale is not a universal truth as the performance of funds located outside the USA and funds that invest overseas is not negatively affected by scale. Our findings suggest that the adverse scale effects in the USA are related to liquidity constraints faced by funds that, by virtue of their style, have to invest in small and domestic stocks. Country characteristics also explain fund performance. Funds located in countries with liquid stock markets and strong legal institutions display better performance.

We study how culture influences mutual funds around the world. Uncertainty Avoidance (UA), which is related to ambiguity aversion, is negatively associated with flow-performance sensitivity, deviation from the fund benchmark, fund alpha, and the fraction of active management across the 25 countries in our sample. This is true even when controlling for an exhaustive set of fund- and country-level characteristics. We also find that a fund's deviation from its benchmark is not only affected by the UA of its domicile country but also by the UA of its fund family's country of origin. Our results highlight the importance of considering cultural characteristics, and UA in particular, when studying mutual funds across countries.

We use a new dataset to study how mutual fund flows depend on past performance across 28 countries. We show that there are marked differences in the flow-performance relationship across countries, suggesting that US findings concerning its shape do not apply universally. We find that mutual fund investors sell losers more and buy winners less in more developed countries. This is because investors in more developed countries are more sophisticated and face lower costs of participating in the mutual fund industry. Higher country-level convexity is positively associated with higher levels of risk taking by fund managers.