The existing replication policies at top finance journals are far weaker than the policies at top economics journals. This paper explores both the costs and benefits of having a stronger replication policy in the context of my failed 2010 initiative to develop a unified policy across all top...

We now know that research findings favorable to the sponsor of the research should be discounted on the grounds of conflict of interest (e.g., tobacco companies or pharma companies). Incentives distort research findings. Is the same true in the field of finance? I argue that economic incentives...

Incentives distort research findings. We now know that research findings favorable to the sponsor of the research should be discounted on the grounds of conflict of interest (e.g., tobacco companies or pharma companies). Is the same true in the field of finance? I argue that economic incentives...

We provide practical insights for investors seeking exposure to the growing cryptocurrency space. Today, crypto is much more than just bitcoin, which historically dominated the space but accounted for just a 21% share of total crypto trading volume in 2021. We discuss a wide variety of tokens,...

Our paper explores the link between cross-sectional fund return dispersion and performance evaluation. The foundation of our model is the simple intuition that in periods of high return dispersion, which is associated with high levels of idiosyncratic risk for zero-alpha funds, it is easier for...

In the late stages of long bull markets, a popular question arises: What steps can an investor take to mitigate the impact of the inevitable large equity correction? However, hedging equity portfolios is notoriously difficult and expensive. We analyze the performance of different tools that...

Machine learning offers a set of powerful tools that holds considerable promise for investment management. As with most quantitative applications in finance, the danger of misapplying these techniques can lead to disappointment. One crucial limitation involves data availability. Many of machine...

We apply state-of-the-art Bayesian machine learning to test whether we can extract valuable information from analysts' recommendations of stock performance. We use a probabilistic model for independent Bayesian classifier combination that has been successfully applied in both the physical and...