L\'evy Information and the Aggregation of Risk Aversion

TL;DR

This paper explores how market pricing kernels aggregate in markets with heterogeneous risk attitudes, using Le9vy processes to model jumps and information flow, revealing the harmonic mean as the key aggregation method.

Contribution

It introduces a novel framework for understanding risk aversion aggregation using Le9vy information, extending previous models to include jump processes.

Findings

Market pricing kernel is the harmonic mean of individual kernels.

Le9vy information allows for jump risk modeling in heterogeneous markets.

Provides a general scheme for investment management under jump risk.

Abstract

When investors have heterogeneous attitudes towards risk, it is reasonable to assume that each investor has a pricing kernel, and that these individual pricing kernels are aggregated to form a market pricing kernel. The various investors are then buyers or sellers depending on how their individual pricing kernels compare to that of the market. In Brownian-based models, we can represent such heterogeneous attitudes by letting the market price of risk be a random variable, the distribution of which corresponds to the variability of attitude across the market. If the flow of market information is determined by the movements of prices, then neither the Brownian driver nor the market price of risk are directly visible: the filtration is generated by an "information process" given by a combination of the two. We show that the market pricing kernel is then given by the harmonic mean of the individual pricing kernels associated with the various market participants. Remarkably, with an appropriate definition of L\'evy information one draws the same conclusion in the case when asset prices can jump. As a consequence we are led to a rather general scheme for the management of investments in heterogeneous markets subject to jump risk.