We show that if true returns are independently distributed and a manager fully reports gains but delays reporting losses, then reported returns will feature conditional serial correlation. We use conditional serial correlation as a measure of conditional return smoothing. We estimate conditional serial correlation in a large sample of hedge funds. We find that the probability of observing conditional serial correlation is related to the volatility and magnitude of investor cash flows, consistent with conditional return smoothing in response to the risk of capital flight. We also present evidence that conditional serial correlation is a leading indicator of fraud.
This paper examines how industry structure affects corporate investment patterns. Real options theory shows that deferring irreversible investment in the face of uncertainty is valuable. Theory also shows that the value of waiting to invest falls if investment opportunities are contestable. Consistent with these theories, we find that firms in monopolistic industries exhibit lower investment-q sensitivity and are slower to invest than firms in competitive industries. However, we find that investment-q sensitivity and investment speed are highest in oligopolistic industries, suggesting that the value of investing strategically can outweigh the value of waiting. Indeed, oligopolistic industries experience less entry and more exit than other industries.
This paper studies the estimation of asset pricing model regressions with conditional alphas and betas, focusing on the joint effects of data snooping and spurious regression. We find that the regressions are reasonably well specified for conditional betas, even in settings where simple predictive regressions are severely biased. However, there are biases in estimates of the conditional alphas. When time-varying alphas are suppressed and only time-varying betas are considered, the betas become biased. Previous studies overstate the significance of time-varying alphas.
This paper examines time-series forecast errors of expected returns from conditional and unconditional asset pricing models for portfolio and individual firm equity returns. A new result that increases predictive precision concerning model specification and forecasting is introduced. Conditional versions of the models generally produce higher mean squared errors than unconditional versions for step ahead prediction. This holds for individual firm data when the instruments are firm specific. Mean square forecast error decompositions indicate that the asset pricing models produce relatively unbiased predictions, but the variance is severe enough to ruin the step ahead predictive ability beyond that of a constant benchmark.
We examine the effect of poison pill adoptions on firm value, controlling for the adopting firm’s preexisting corporate governance structure. We find that only companies with the most democratic governance structures, defined as those with the fewest preexisting protective governance provisions, experience significantly positive abnormal stock returns and significantly positive abnormal revisions in five-year earnings growth rate forecasts. Moreover, regression results indicate that abnormal returns and forecast revisions are significantly related to governance structure and not to board composition or subsequent merger activity.
Standard tests of portfolio efficiency neglect the existence of illiquid wealth. The most important illiquid asset in household portfolios is housing: if housing stock adjustments are infrequent, optimal portfolios in periods of no adjustment are affected by housing price risk through a hedge term and tests for portfolio efficiency of financial assets must be run conditionally upon housing wealth. We use Italian household portfolio data and time series on financial assets and housing stock returns to assess whether actual portfolios are efficient. We find that housing wealth plays a key role in determining whether portfolios chosen by homeowners are efficient.
Using a unique insurance dataset for a sample of Chinese publicly listed companies for the period 1997 through 2003, this study tests the simultaneous linkages between debt capacity, cost of debt, and corporate property insurance. Our results suggest that, on the one hand, a higher cost of debt appears to motivate the use of more property insurance, but high leverage alone does not lead to the purchase of more property insurance. The latter finding might reflect the unique institutional setting of China, for example, where there is a low chance of legally enforced company liquidation. Also, there is evidence that leverage can interact with tangible assets intensity and exert a positive conjoint effect on the corporate purchase of property insurance. On the other hand, we find evidence that supports that property insurance helps expand insuring firms’ debt capacity and helps lower their borrowing costs. However, the moderate evidence on the cost reduction effect suggests that lowering the borrowing cost is likely to be a concern secondary to facilitating corporate borrowing and thereby expanding debt capacity in corporate property insurance decisions in China. Overall, we conclude that debt capacity, cost of debt, and corporate insurance appear to be simultaneously related.
In textbook models of exchange rate determination, the news contained in public information announcements is directly impounded into prices with there being no role for trading in this process of information assimilation. This paper directly tests this theoretical result using transaction level exchange rate return and trading data and a sample of scheduled macroeconomic announcements. The main result of the paper is that even information that is publicly and simultaneously released to all market participants is partially impounded into prices via the key micro level price determinant—order flow. We quantify the role that order flow plays and find that approximately one third of price-relevant information is incorporated via the trading process.
To the extent that investors diversify internationally, large-cap stocks receive the dominant share of fund allocation. Increasingly, however, returns to large-cap stocks or stock market indices tend to comove, mitigating the benefits from international diversification. In contrast, stocks of locally oriented, small companies do not exhibit the same tendency. In this paper, we assess the potential of small-cap stocks as a vehicle for international portfolio diversification during the period 1980–1999. We show that the extra gains from the augmented diversification with small-cap funds are statistically significant for both in-sample and out-of-sample periods and remain robust to the consideration of market frictions.
Starting from the reward-risk model for portfolio selection introduced in De Giorgi (2005), we derive the reward-risk Capital Asset Pricing Model (CAPM) analogously to the classical mean-variance CAPM. In contrast to the mean-variance model, reward-risk portfolio selection arises from an axiomatic definition of reward and risk measures based on a few basic principles, including consistency with second-order stochastic dominance. With complete markets, we show that at any financial market equilibrium, reward-risk investors’ optimal allocations are comonotonic and, therefore, our model reduces to a representative investor model. Moreover, the pricing kernel is an explicitly given, non-increasing function of the market portfolio return, reflecting the representative investor’s risk attitude. Finally, an empirical application shows that the reward-risk CAPM captures the cross section of U.S. stock returns better than the mean-variance CAPM does.