This paper examines a canonical stochastic overlapping generations model with dynamically complete markets. Belief differences lead agents to place bets against each other and so wealth shifts across agents and across generations. Such changes in the wealth distribution strongly affect prices of...

We model the dynamics of asset prices and associated derivatives by consideration of the dynamics of the conditional probability density process for the value of an asset at some specified time in the future. In the case where the asset is driven by Brownian motion, an associated "master...

Many bond portfolio managers argue that bond laddering tends to outperform other bond investment strategies because it reduces both market price risk and reinvestment risk for a bond portfolio in the presence of interest rate uncertainty. Despite the popularity of bond ladders as a strategy for...

In this paper we examine the quantitative effects of margin regulation on volatility in asset markets. We consider a general equilibrium in finite-horizon economy with heterogeneous agents and collateral constraints. There are two assets in the economy which can be used as collateral for...

Replicating portfolios have recently emerged as an important tool in the life insurance industry, used for the valuation of companies' liabilities. This paper presents a replicating portfolio (RP) model for approximating life insurance liabilities as closely as possible. We minimize the L1 error...

We assess the quantitative implications of the re-use of collateral on financial market leverage, volatility, and welfare within an infinite-horizon asset-pricing model with heterogeneous agents. In our model, the ability of agents to re-use frees up collateral that can be used to back more...

We introduce a simulation method for dynamic portfolio valuation and risk management building on machine learning with kernels. We learn the dynamic value process of a portfolio from a finite sample of its cumulative cash flow. The learned value process is given in closed form thanks to a...

We present a general framework for portfolio risk management in discrete time, based on a replicating martingale. This martingale is learned from a finite sample in a supervised setting. The model learns the features necessary for an effective low-dimensional representation, overcoming the curse...