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 in some way 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 the case of geometric Brownian motion 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 the pricesof assets , 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 that takes the form of a Brownian motion with random drift . 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. Alternatively, one can view the market pricing kernel as the inverse of a "benchmark" or "natural numeraire" asset, and in that case the benchmark asset is the portfolio obtained by aggregating the benchmarks assigned by the individual investors based on their private risk preferences. Remarkably, with an appropriate definition of L\'evy information one draws the same conclusion in the case of a geometric L\'evy model in which asset prices can jump. As a consequence one is lead to a rather general scheme for the management of investments in heterogeneous markets subject to jump risk.
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.
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Alternatively, one can view the market pricing kernel as the inverse of a "benchmark" or "natural numeraire" asset, and in that case the benchmark asset is the portfolio obtained by aggregating the benchmarks assigned by the individual investors based on their private risk preferences.
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