We study the problem of detecting structural instability of factor strength in asset pricing models for financial returns. We allow for strong and weaker factors, in which the sum of squared betas grows at a rate equal to and slower than the number of test assets, respectively: this growth rate...

Muir (2014) shows that the ratio of intermediary equity to GDP predicts future market returns and is a priced risk factor in the cross-section of stock returns. Here, I extend his work and show that expectations of large declines in the equity of financial institutions can also help explain...

We propose a nonparametric method to study which characteristics provide incremental information for the cross section of expected returns. We use the adaptive group LASSO to select characteristics and to estimate how they affect expected returns nonparametrically. Our method can handle a large...

We develop an Artificial Stock Market - an agent-based simulation model of the stock market with many risky assets. The ASM has three layers of heterogeneous and interacting agents, and generates prices for 150 stocks. We present the current state of the model and demonstrate its ability to...

A prominent factor used in most models predicting stock returns is firm size. Yet no consensus has emerged on the magnitude and stability of the size premium, with some researchers even questioning the usefulness of the factor. To take stock of the voluminous academic literature on the size...

We merge the literature on downside return risk and liquidity risk and introduce the concept of extreme downside liquidity (EDL) risks. The cross-section of stock returns reflects a premium if a stock's return (liquidity) is lowest at the same time when the market liquidity (return) is lowest....