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Consumption optimization for recursive utility in a jump-diffusion model

机译:跳扩散模型中递归效用的消费优化

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In this paper, we consider a market model with prices and consumption following a jump-diffusion dynamics. In this setting, we first characterize the optimal consumption plan for an investor with recursive stochastic differential utility on the basis of his/her own beliefs, then we solve the inverse problem to find what beliefs make a given consumption plan optimal. The problem is viewed in general for a class of homogeneous recursive utility, and later we choose a logarithmic model for the utility aggregator as an explicitly computable example. When beliefs, represented via Girsanov's theorem, get incorporated into the model, the change of measure gives rise, up to a transformation, to a backward stochastic differential equation whose generator exhibits a quadratic behavior in the Brownian component and a locally Lipschitz one in the jump component, which is solvable on the basis of some recent results.
机译:在本文中,我们考虑了具有跳跃扩散动力学的价格和消费的市场模型。在这种情况下,我们首先根据自己的信念来描述具有递归随机差分效用的投资者的最优消费计划,然后解决反问题,以找出哪些信念使给定的消费计划最优。对于一类齐次递归效用,通常会考虑该问题,随后,我们为效用聚合器选择对数模型作为可明确计算的示例。当通过吉尔萨诺夫定理表示的信念被纳入模型时,测度的变化将导致转换,最后是向后随机微分方程,该方程的生成器在布朗分量中表现出二次行为,在跳跃中表现出局部Lipschitz行为。成分,根据最近的一些结果可以解决。

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