The out-of-sample R2 is designed to measure forecasting performance without look-ahead bias. However, researchers can hack this performance metric even without multiple tests by constructing a prediction model using the intuition derived from empirical properties that appear only in the test...

For optimal asset allocation, mean-variance investors must learn about the joint dynamics of new and existing asset classes, not only their profitability. Bitcoin's digital gold narrative provides a unique laboratory to test this hypothesis. We find that a decrease in investors' estimate on...

We theoretically and empirically analyze information generation by stock markets on economic prospects of innovations and the resultant feedback effect on firm-level innovation-related investment (IRI). By modeling the unique aspects of firm-specific and systematic drivers of innovation profits,...

Using a large sample of U.S. acquiring and non-acquiring firms and covering a broad sample of transactions, we examine the effects of mergers and acquisitions (M&A) on CEO compensation during 1993-2006, a period of intense M&A activity. We alleviate endogeneity concerns through dynamic panel...

We examine the effects of estimation risk and Bayesian learning on equilibrium asset prices when there is uncertainty about both the first and second moments of consumption and dividend growth rates. For the 1891-2007 period, our model generates a sizable average annual equity premium,...

Building on the theoretical asset pricing literature, we examine the role of market risk and the size, book-to-market (BTM), and volatility anomalies in the cross-section of unlevered equity returns. Compared with levered (stock) returns, the unlevered market beta plays a more important role in...