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On Drawdown-Modulated Feedback Control in Stock Trading
Preprint

On Drawdown-Modulated Feedback Control in Stock Trading

Chung-Han Hsieh and B. Ross Barmish
arXiv.org
04/10/2017

Abstract

Mathematics - Optimization and Control Quantitative Finance - Portfolio Management Quantitative Finance - Risk Management
IFAC-PapersOnLine Volume 50, Issue 1, 2017 Control of drawdown, that is, the control of the drops in wealth over time from peaks to subsequent lows, is of great concern from a risk management perspective. With this motivation in mind, the focal point of this paper is to address the drawdown issue in a stock trading context. Although our analysis can be carried out without reference to control theory, to make the work accessible to this community, we use the language of feedback systems. The takeoff point for the results to follow, which we call the Drawdown Modulation Lemma, characterizes any investment which guarantees that the percentage drawdown is no greater than a prespecified level with probability one. With the aid of this lemma, we introduce a new scheme which we call the drawdown-modulated feedback control. To illustrate the power of the theory, we consider a drawdown-constrained version of the well-known Kelly Optimization Problem which involves maximizing the expected logarithmic growth of the trader's account value. As the drawdown parameter dmax in our new formulation tends to one, we recover existing results as a special case. This new theory leads to an optimal investment strategy whose application is illustrated via an example with historical stock-price data.

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Title
On Drawdown-Modulated Feedback Control in Stock Trading
Creators
Chung-Han Hsieh - University of Wisconsin–Madison
B. Ross Barmish - University of Wisconsin–Madison
Resource Type
Preprint
Publication Details
arXiv.org
Language
English
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