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Aggregate corporate savings, economic uncertainty, and future stock returns
Government debt management and inflation with real and nominal bonds
Picking partners: Manager selection in private markets
Investor expertise and private investment selection
Flying below the radar: Insider trading by executives below the top
To enforce insider trading laws, financial regulators require top executives to make their own-company trades public. One implication of this regulatory focus is that executives below the top fly under the radar. We use administrative register data from Norway to examine whether executives below the top in listed companies earn abnormal returns on purchases in own-company stock. We find evidence of abnormal returns on such trades, about 50 to 100 basis points at the 1-month horizon. The abnormal returns on purchases in other stocks are negative, making high investor ability an unlikely explanation.
Glass box machine learning and corporate bond returns
Dirty air and green investments: The impact of pollution information on portfolio allocations
Board connections, firm profitability, and product market actions
The co-pricing factor zoo
We analyze 18 quadrillion models for the joint pricing of corporate bond and stock returns. Strikingly, we find that equity and nontradable factors alone suffice to explain corporate bond risk premia once their Treasury term structure risk is accounted for, rendering the extensive bond factor literature largely redundant for this purpose. While only a handful of factors, behavioral and nontradable, are likely robust sources of priced risk, the true latent stochastic discount factor is dense in the space of observable factors. Consequently, a Bayesian Model Averaging Stochastic Discount Factor explains risk premia better than all low-dimensional models, in- and out-of-sample, by optimally aggregating dozens of factors that serve as noisy proxies for common underlying risks, yielding an out-of-sample Sharpe ratio of 1.5 to 1.8. This SDF, as well as its conditional mean and volatility, are persistent, track the business cycle and times of heightened economic uncertainty, and predict future asset returns.