We show that the conventional procedure of risk adjustment by running full-sample time-series Fama–French three-factor regressions is not appropriate for momentum portfolios because the procedure fails to allow for the systematic dynamics of momentum portfolio factor loadings. We propose a simple procedure to adjust risks associated with the Fama–French three factors for momentum portfolios. Using our proposed method, the Fama–French three factors can explain approximately 40% of momentum profits generated by individual stocks and nearly all of momentum returns from style portfolios.

This paper investigates whether stock-price indexes of seventeen emerging markets can be characterized as random walk (unit root) or mean reversion processes. We implement a test that can account for structural breaks in the underlying series and is more powerful than standard tests. We find that for fourteen countries, stock prices exhibit structural breaks. Furthermore, for ten countries, the null hypothesis of a random walk can be rejected at the one or 5% significance level. Our results indicate that ignoring structural breaks that arise from the liberalization of emerging markets can lead to incorrect inference that these indices are characterized by random walks, and are consistent with the points made by Bekaert et al. [J. Int. Money Finan. 21 (2002) 295]. Our findings hold true regardless of whether stock indexes are denominated in US dollar terms, in local currencies terms, or in real terms.

This paper studies the impact of sovereign debt rating changes on liquidity for stocks from 40 countries for the period 1990–2009. We find that sovereign rating changes significantly affect stock liquidity. The impact is stronger for downgrades than for upgrades, and is nonlinear in event size. The loss of investment grade has a particularly strong negative impact on stock liquidity. We also find that some stock characteristics and country legal and macroeconomic environment are important in explaining the differences in the impact of sovereign credit rating changes on stock liquidity across countries.

We propose a new methodology to provide fair prices of international mutual funds by adjusting prices at the individual security level using a comprehensive and economically relevant information set. Stepwise regressions are used to endogenously determine the stock-specific optimal set of factors. Using 16 synthetic funds whose characteristics are extracted from 16 corresponding actual US-based Japanese mutual funds, we demonstrate that our method estimates fund prices significantly more accurately than existing methods. Although existing fair-pricing methods provide an improvement over the current practice of simply using Japanese market closing prices, they are still highly vulnerable to exploitation by market-timers. By contrast, our method is the most successful in preventing such strategic exploitation since no competing method can profit from our stated prices.

For U.S. stock prices, evidence of mean reversion over long horizons is mixed, possibly due to lack of a reliable long time series. Using additional cross‐sectional power gained from national stock index data of 18 countries during the period 1969 to 1996, we find strong evidence of mean reversion in relative stock index prices. Our findings imply a significantly positive speed of reversion with a half‐life of three to three and one‐half years. This result is robust to alternative specifications and data. Parametric contrarian investment strategies that fully exploit mean reversion across national indexes outperform buy‐and‐hold and standard contrarian strategies.

Using a GARCH approach, we estimate a time-varying two-factor international asset pricing model for weekly equity index returns of 16 OECD countries. A trade-weighted basket of exchange rates and the MSCI world market index are used as risk factors. We find significant currency risk exposures in country equity index returns. We then explain these currency betas using several country-specific macroeconomic variables with a panel approach. We find that imports, exports, credit ratings, and tax revenues significantly affect currency risks in a way that is consistent with some economic hypotheses. Similar conclusions are obtained by using lagged explanatory variables, and thus these macroeconomic variables may be useful as predictors of currency risk exposures. Our results are robust to a number of alternative specifications.

This paper documents significant cross-return predictability of news variables, derived from textual analysis of news articles, for a broad cross-section of currencies. By employing forecasts based on the Least Absolute Shrinkage and Selection Operator (LASSO) that incorporate both news variables and forward discounts, we develop a notably profitable trading strategy. This strategy proves robust against transaction costs, risk adjustments, and controls for currency characteristics. Further analyses indicate that both risks and market frictions contribute to the profitability of the trading strategy, highlighting the crucial role of news in financial markets.

We use the advent of new credit default swap (CDS) trading conventions in April 2009—the CDS Big Bang—to study how a shock to funding liquidity impacts market liquidity. After the Big Bang, traders are required to pay upfront fees to execute CDS transactions, with the size of the fees depending on the level of CDS spreads. While CDS bid-ask spreads decline in aggregate after the Big Bang, they do so less for contracts that require larger fees. Furthermore, the funding effect is stronger for smaller and riskier firms and for noncentrally cleared contracts. The effect also becomes stronger after Deutsche Bank's exit.