Risk aversion and the dynamics of optimal liquidation strategies in illiquid markets

We consider the infinite-horizon optimal portfolio liquidation problem for a von Neumann–Morgenstern investor in the liquidity model of Almgren (Appl. Math. Finance 10:1–18, 2003). Using a stochastic control approach, we characterize the value function and the optimal strategy as classical solutions of nonlinear parabolic partial differential equations. We furthermore analyze the sensitivities of the value function and the optimal strategy with respect to the various model parameters. In particular, we find that the optimal strategy is aggressive or passive in-the-money, respectively, if and only if the utility function displays increasing or decreasing risk aversion. Surprisingly, only few further monotonicity relations exist with respect to the other parameters. We point out in particular that the speed by which the remaining asset position is sold can be decreasing in the size of the position but increasing in the liquidity price impact.

[1]  Alexander Fadeev,et al.  Optimal execution for portfolio transactions , 2006 .

[2]  A. Kyle Continuous Auctions and Insider Trading , 1985 .

[3]  D. Bertsimas,et al.  Optimal control of execution costs , 1998 .

[4]  Robert Kissell,et al.  Optimal Trading Strategies: Quantitative Approaches for Managing Market Impact and Trading Risk , 2003 .

[5]  A. Tversky,et al.  Prospect Theory : An Analysis of Decision under Risk Author ( s ) : , 2007 .

[6]  Robert Almgren,et al.  Optimal execution with nonlinear impact functions and trading-enhanced risk , 2003 .

[7]  Roberto Malamut,et al.  Understanding the Profit and Loss Distribution of Trading Algorithms , 2005 .

[8]  B. Rosenow,et al.  Order book approach to price impact , 2003, cond-mat/0311457.

[9]  Jean-Philippe Bouchaud,et al.  More Statistical Properties of Order Books and Price Impact , 2002, cond-mat/0210710.

[10]  Alexander Schied,et al.  Optimal execution strategies in limit order books with general shape functions , 2007, 0708.1756.

[11]  J. Bouchaud,et al.  Fluctuations and Response in Financial Markets: The Subtle Nature of 'Random' Price Changes , 2003, cond-mat/0307332.

[12]  Duane J. Seppi,et al.  Episodic Liquidity Crises: Cooperative and Predatory Trading , 2007 .

[13]  A. Tversky,et al.  Prospect theory: an analysis of decision under risk — Source link , 2007 .

[14]  Robert Kissell,et al.  Algorithmic Decision-Making Framework , 2005, Algorithmic Trading Methods.

[15]  Alexander Schied,et al.  Liquidation in the Face of Adversity: Stealth vs. Sunshine Trading , 2007 .

[16]  Hua He,et al.  Dynamic Trading Policies with Price Impact , 2001 .

[17]  Alexander Schied,et al.  Optimal basket liquidation with finite time horizon for CARA investors , 2008 .

[18]  Ajay Subramanian,et al.  The Liquidity Discount , 2001 .

[19]  L. Rogers,et al.  THE COST OF ILLIQUIDITY AND ITS EFFECTS ON HEDGING , 2010 .

[20]  L. Rogers,et al.  MODELING LIQUIDITY EFFECTS IN DISCRETE TIME , 2007 .

[21]  Alexander Schied,et al.  Optimal Portfolio Liquidation for CARA Investors , 2007 .

[22]  Maureen O'Hara,et al.  PRICE, TRADE SIZE, AND INFORMATION IN SECURITIES MARKETS* , 1987 .