Abstract
This article shows the execution performance of the risk-averse institutional trader with constant absolute risk aversion (CARA) type utility by using the condition of no price manipulation defined in the risk neutral sense. From two linear price impact models both satisfying that condition, we have derived the unique explicit optimal execution strategy calculated backwardly with dynamic programming equations. And our study shows that the optimal execution strategy exists in the static class. The derived solution can be decomposed into mainly two components, each giving an explanation of the property of optimal execution volume. Moreover we propose two conditions in order to compare the performance of these two price models, and illustrate that the performances of the two models are surprisingly different under certain conditions.
Highlights
In the competitive market paradigm, it is assumed that security markets are perfectly elastic and all orders can be executed instantaneously
In the equidistance discrete trading time grid setting, we show that the optimal execution strategy of the risk-averse large trader with each price model exists in the static class by deriving backwardly the explicit solution with the dynamic programming equation
We show that the optimal execution strategy exists in the static class by deriving the explicit solution with a dynamic programming equation
Summary
In the competitive market paradigm, it is assumed that security markets are perfectly elastic and all orders can be executed instantaneously. Ohnishi ration of trade information to the price which derives the gradual price recovery, and a permanent impact which affects the prices of all subsequent trades of an agent These price changes may enable the large trader to manipulate the market. In the equidistance discrete trading time grid setting, we show that the optimal execution strategy of the risk-averse large trader with each price model exists in the static class by deriving backwardly the explicit solution with the dynamic programming equation. Calculations and proofs are complicated but can be proved in a straightforward way
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