We suggest a simple practical method to combine the human and artificial intelligence to both learn best investment practices of fund managers, and provide recommendations to improve them. Our approach is based on a combination of Inverse Reinforcement Learning (IRL) and RL. First, the IRL...

Increases in investor exposure to prominent systematic trading strategies such as momentum correlate with lower returns to these strategies. A 1 percentage point increase in gross momentum exposure as a percentage of market capitalization corresponds with a permanent 1.1 percentage point decline...

We attempt to reconcile Gabaix and Koijen's (GK) recent Inelastic Market Hypothesis (IMH) with the order-driven view of markets that emerged within the microstructure literature in the past 20 years. We review the most salient empirical facts and arguments that give credence to the idea that...

This paper derives ex-ante standard errors of risk premium predictions from neural networks (NNs). Considering standard errors, I provide improved investment strategies and ex-post out-of-sample (OOS) statistical inferences relative to existing literature. The equal-weighted (value-weighted)...

We investigate both theoretically and empirically how unemployment level and its growth affect future stock returns. We find that both a higher unemployment rate and higher growth of unemployment positively predict future stock market returns. In our model, the effects come through their...

We estimate asset pricing models with multiple risks: long-run growth, long-run volatility, habit, and a residual. The Bayesian estimation accounts for the entire likelihood of consumption, dividends, and the price-dividend ratio. We find that the residual represents at least 80% of the variance...

In the past year, generative AI, led by Chat GPT by Open AI and Bard, a language experiment by Google, generated tremendous attention amongst the public. Their impact on finance, law and general productivity are difficulty to articulate with words. This paper aims to strengthen the...

The publication of the Black-Scholes formula in 1973 appeared for the first time to put the pricing of financial options onto a rational and objective basis. While earlier option-pricing models relied on a subjective estimate of the stock’s uncertain future growth rate, the Black-Scholes model...

I assume that a market maker selects a buy and a sell price at her exchange to maximize profits. Up to first-order approximation, this problem is equivalent to a social planner’s problem and the problem of maximizing trader participation in the exchange. The optimal market maker rule has...

We propose a class of execution algorithms that consists of a strategic layer and a speculative layer. The strategic layer is an optimal trading schedule that encodes the trader's objective, her tolerance to risk, and the impact of her own trades in the market. The schedule of the strategic...