Average skewness in global equity markets

This paper examines the predictive power of average skewness, defined as the average of monthly skewness values across stocks, documented by the prior literature for US market returns in an international setting. First, we confirm the validity of the results in the original study and show that the intertemporal relation between average skewness and aggregate returns becomes weaker in an alternative sample period. Second, when we repeat the analysis in 22 developed non-US markets, we find that average skewness has no robust predictive power for future market returns. The loss of forecasting power in the international sample does not depend on the method used to calculate average skewness or the regression specification and is supported by additional out-of-sample tests and subsample analysis.     

Initial credit ratings and earnings management

Credit rating agencies assert that they rely on financial information provided by issuers and that they value rating stability as well as accuracy. In an environment where rating agencies depend on issuer-reported information and are reluctant to adjust ratings promptly, managers of issuing firms can utilize the discretion afforded by GAAP to obtain the most favorable credit ratings. Consistent with our expectations, we find that current accruals are unusually positive and high around initial credit ratings. The increase in abnormally high accruals leading up to the initial credit rating year is followed by a reversal in the subsequent years. Multivariate regression analyses suggest that accounting accruals, abnormal current accruals in particular, are significantly positively related to initial credit ratings after controlling for several issue- and issuer-related characteristics indicative of default risk. Our results are robust to additional tests that account for endogeneity between credit ratings and earnings management, adjust for performance, and account for firms issuing debt and equity simultaneously.     

Probability Forecasts of Macroaggregates in the Turkish Economy

We provide probability forecasts of key Turkish macroeconomic variables such as inflation and output growth. The probability forecasts are derived from a core vector error correction model of the Turkish economy and its several variants. We use model and window averaging to address uncertainties arising from estimated models and possible structural breaks. The performances of the different models and their combinations are evaluated using relevant forecast accuracy tests in different pseudo out-of-sample settings. The results indicate that successful directional forecasts can be obtained for output growth and inflation. Averaging over both the models and the estimation windows improves the level of accuracy of the forecasts.