2008 Jun 15 - Sun

Adaptive Arrival Price

A keynote lecture at the April 7th Algorithmic Trading Conference in London was by Mr. Julian Lorenz of ETH Zurich. The abstract for his lecture reads as follows:

Electronic trading of equities and other securities makes heavy use of "arrival price" algorithms, that balance the market impact cost of rapid execution against the volatility risk of slow execution. In the standard formulation, mean-variance optimal trading strategies are static: they donot modify the execution speed in response to price motions observed during trading. We show that with a more realistic formulation of the mean-variance tradeoff, with no momentum or mean reversion in the price process, substantial improvements are possible by using dynamic trading strategies. We develop a technique for computing optimal dynamic strategies to any desired degree of precision. The asset price process is observed on a discrete tree with a arbitrary number of levels. We introduce a novel dynamic programming technique in which the control variables are not only the shares traded at each time step, but also the maximum expected cost for the remainder of the program; the value function is the variance ofthe remaining program. The resulting adaptive strategies are"aggressive-in-the-money": they accelerate the execution when the price moves in the trader's favor, spending parts of the trading gains to reduce risk. The improvement is larger for large initial positions.

I think I'll add 'arrival price algorithms' to my key word searches. The above extract was from a search on 'mean reversion trading system algorithms'.