Abstract This paper uses style analysis to investigate whether Euro-zone equity returns are driven by country or industry effects over the 1990–2008 period. We find that before the introduction of the Euro, country effects dominate, while industry effects prevail after 1999. This reversal is driven mainly by the countries that were least integrated in the Economic and Monetary Union (EMU) and world markets in the early 1990s and for which the EMU convergence process led to rapid strengthening of linkages with the core Euro-zone. For markets with stronger economic linkages, industry effects dominate both before and after the introduction of the Euro.

Review of Finance, 2017, 21, 2169–2197. doi:10.1093/rof/rfw040 It has been brought to our attention that the distribution proposed in “A simple skewed distribution with asset pricing application” (Review of Finance, 2017) is not only a special case of Hansen’s (1994) skewed t distribution, as explained in our paper, but that it has also previously been introduced in other fields.1 The distribution has been known under different names in the literature such as “two-piece normal distribution” and “split normal distribution,” and it was first proposed by the psychologist Carl Gustav Fechner in Fechner (1897). As discussed in Wallis (2014), the distribution has since then been rediscovered in physics, statistics, and meteorology.2 While the contribution of our paper in terms of understanding skewness and its effects on value at risk, expected shortfall, portfolio weights, and asset pricing, and the closed-form parameterization of the distribution in our Appendix B is unaffected by this omission, our distribution is not new and should be correctly attributed to Fechner (1897).

Abstract Recent research has identified skewness and downside risk as one of the most important features of risk. We present a new distribution which makes modeling skewed risks no more difficult than normally distributed (symmetric) risks. Our distribution is a combination of the “downside” and “upside” half of two normal distributions, and its parameters can be calculated in closed form to match a given mean, variance, and skewness. Value at risk, expected shortfall, portfolio weights, and risk premia have simple expressions for our distribution and show economically meaningful deviations from the normal case already for very modest levels of skewness. An empirical application suggests that our distribution fits the data well.

This study investigates the announcement effects of offerings of convertible bond loans and warrant-bond loans using data for the Dutch market. The event study analysis shows that announcement effects of convertible bonds are associated with positive but insignificant abnormal returns and that announcements of warrant-bonds are associated with significant positive abnormal returns. These findings are similar to the results for Japanese hybrid debt, as reported by Kang et al. (1995) (Kang, J.K., Kim, Y.C., Park, K.J., Stulz, R.M., 1995. Journal of Financial and Quantitative Analysis, pp. 257–270) and Kang and Stulz (1996) (Kang, J.K., Stulz, R.M., 1996. Review of Financial Studies, pp. 109–139), but they contrast with studies for the United States that generally find significant negative abnormal returns for convertible bond loans and insignificant negative abnormal returns for warrant-bond loans. Our results cannot be attributed to differences in the corporate governance structures of the Netherlands and the United States. We find that the positive abnormal returns for the warrant-bond loans are caused by the packaging of the announcements with other (good) firm-specific news.

One-period expected returns on futures contracts with different maturities differ because of risk premia in the spreads between futures and spot prices. We analyze the expected returns for futures contracts with different maturities using the information that is present in the current term structure of futures prices. A simple affine one-factor model that implies a constant covariance between the pricing kernel and the cost-of-carry cannot be rejected for heating oil and German Mark futures contracts. For gold and soybean futures, the risk premia depend on the slope of the current term structure of futures prices, while for live cattle futures, the evidence is mixed.

We present a simple model implying that futures risk premia depend on both own‐market and cross‐market hedging pressures. Empirical evidence from 20 futures markets, divided into four groups (financial, agricultural, mineral, and currency) indicates that, after controlling for systematic risk, both the futures own hedging pressure and cross‐hedging pressures from within the group significantly affect futures returns. These effects remain significant after controlling for a measure of price pressure. Finally, we show that hedging pressure also contains explanatory power for returns on the underlying asset, as predicted by the model.

We test whether hedging currency risk improves the performance of international stock portfolios.We show that an auxiliary regression provides a wealth of information about the optimal portfolio holdings for non-mean–variance investors, analogous to the information provided by the Jensen regression about optimal portfolio holdings for the mean–variance case. We find that static hedging with currency forwards does not lead to significant improvements in portfolio performance for a US-Dollar based stock portfolio from the G5 countries, whereas dynamic hedges that are conditional on the interest rate spread do. These conclusions hold for both mean–variance and power utility investors and show up both in-sample and out-of-sample. However, the optimal forward positions can differ significantly for both types of investors.

ABSTRACT We identify two types of risk premia in commodity futures returns: spot premia related to the risk in the underlying commodity, and term premia related to changes in the basis. Sorting on forecasting variables such as the futures basis, return momentum, volatility, inflation, hedging pressure, and liquidity results in sizable spot premia between 5% and 14% per annum and term premia between 1% and 3% per annum. We show that a single factor, the high‐minus‐low portfolio from basis sorts, explains the cross‐section of spot premia. Two additional basis factors are needed to explain the term premia.

ABSTRACT We propose regression‐based tests for mean‐variance spanning in the case where investors face market frictions such as short sales constraints and transaction costs. We test whether U.S. investors can extend their efficient set by investing in emerging markets when accounting for such frictions. For the period after the major liberalizations in the emerging markets, we find strong evidence for diversification benefits when market frictions are excluded, but this evidence disappears when investors face short sales constraints or small transaction costs. Although simulations suggest that there is a possible small‐sample bias, this bias appears to be too small to affect our conclusions.

We show that inflation risk is priced in stock returns and that inflation risk premia in the cross-section and the aggregate market vary over time, even changing sign as in the early 2000s. This time variation is due to both price and quantities of inflation risk changing over time. Using a consumption-based asset pricing model, we argue that inflation risk is priced because inflation predicts real consumption growth. The historical changes in this predictability and in stocks’ inflation betas can account for the size, variability, predictability, and sign reversals in inflation risk premia.