We develop a dynamic asset pricing model of cryptocurrencies/tokens that allows users to conduct peer-to-peer transactions on digital platforms. The equilibrium value of tokens is determined by aggregating heterogeneous users' transactional demand rather than discounting cash flows, as is done...

We develop a new class of tree-based models (P-Tree) for analyzing (unbalanced) panel data utilizing global (instead of local) split criteria that incorporate economic guidance to guard against overfitting while preserving interpretability. We grow a P-Tree top-down to split the cross section of...

We develop a dynamic asset-pricing model of cryptocurrencies/tokens that allow users to conduct peer-to-peer transactions on digital platforms. The equilibrium value of tokens is determined by aggregating heterogeneous users' transactional demand rather than discounting cashflows as in standard...

We predict asset returns and measure risk premia using a prominent technique from artificial intelligence -- deep sequence modeling. Because asset returns often exhibit sequential dependence that may not be effectively captured by conventional time series models, sequence modeling offers a...

We model financial innovations such as Exchange-Traded Funds, smart beta products, and many index-based vehicles as composite securities that facilitate trading common factors in assets' liquidation values. Through accessing a larger basket of assets in endogenously-chosen proportions, composite...

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 introduce a class of interpretable tree-based models (P-Tree) for analyzing (unbalanced) panel data, with iterative and global (instead of recursive and local) split criteria. We apply P-Tree to split the cross section of asset returns under the no-arbitrage condition, generating a stochastic...