Abstract
We consider the so-called optimal execution problem in algorithmic trading, which is the problem faced by an investor who has a large number of stock shares to sell over a given time horizon and whose actions have an impact on the stock price. In particular, we develop and study a price model that presents the stochastic dynamics of a geometric Brownian motion and incorporates a log-linear effect of the investor's transactions. We then formulate the optimal execution problem as a degenerate singular stochastic control problem. Using both analytic and probabilistic techniques, we establish simple conditions for the market to allow for no arbitrage or price manipulation and develop a detailed characterization of the value function and the optimal strategy. In particular, we derive an explicit solution to the problem if the time horizon is infinite.
Published Version
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