Sparse models, though long preferred and pursued by social scientists, can be ineffective or unstable relative to large models, for example, in economic predictions (Giannone et al., 2021). To achieve sparsity for economic interpretation while exploiting big data for superior empirical...

We use information from over two million trading strategies that are randomly generated using real data, and from strategies that survive the publication process to infer the statistical properties of the set of strategies that could have been studied by researchers. Using this set, we compute...

I examine 468 estimates on the relationship between trading volume and stock returns reported in 44 studies. I deploy recent nonlinear techniques for detecting publication bias together with Bayesian and frequentist model averaging to evaluate the heterogeneity in the estimates. The results...

We show how the timing of financial innovation might have contributed to the mortgage boom and then to the bust of 2007-2009. We study the effect of leverage, tranching, securitization and CDS on asset prices in a general equilibrium model with collateral. We show why tranching and leverage tend...