Local, Regional, or Global Asset Pricing?
研究了全球、区域和本地因子模型对134个横截面异象的解释能力，发现全球和区域模型产生的平均绝对阿尔法值显著高于本地模型，表明国际分散化仍有很大潜力。
Abstract Analyzing several developed and emerging international markets, I test the ability of global, regional, and local models to explain a large set of 134 cross-sectional anomalies. My main finding is that both global and regional factor models create substantially larger average absolute alphas than local factor models. Annual (absolute) anomaly portfolio alphas are on average 1.7 and 1.1 percentage points higher, respectively, with global and regional than with local factor models. Even for the most recent period, there is no evidence of a catch-up of global and regional factor models. There is substantial potential for international diversification of anomaly strategies.