We provide an economic model of a decentralized exchange (DEX) that allows investors to concentrate liquidity within exogenously specified price intervals (e.g., Uniswap V3). We demonstrate that providing liquidity for a risky vs. risk-free asset pair within any price interval is analogous to...

Prices and investors' behavior are heavily influenced by risk aversion. As it is unobservable, estimating risk aversion has been challenging for a long time. This paper proposes using a Machine Learning approach (a combination of Autoencoder and Long-Short Term Memory) to estimate the...

This paper proposes an alternative model to Brownian-type models for high frequency market price processes which is much closer to reality and thus more appropriate for use in process behavior and optimization research. The proposed model is a modified Poisson process

This paper addresses questions regarding the dimensionality of the stochastic discount factor and the selection of the best factors that enter it. We analyze these questions theoretically and empirically with a novel methodology which performs both (i) estimation of factor loadings and (ii) best...

We propose a price impact model where changes in prices are purely driven by the order flow in the market. The stochastic price impact of market orders and the arrival rates of limit and market orders are functions of the market liquidity process which reflects the balance of the demand and...

This presentation introduces the rough path-dependent volatility model (RPDVM). After defining the model and its different components, the presentation focuses on various specifications of the RPDVM that already exist in the literature. Finally, a Markovian approximation of the model is presented

Time horizon dimensions are added to asset pricing theory. Single period, static, arbitrage pricing theory (APT) describes single period risk with long horizon contributions in the frequency domain. Mean-reversion risks correspond to horizon variances. Mean-reversion risk is measured using the...

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...