Multi-Period Trading via Convex Optimization

Boyd, Stephen

ISBN 10: 1680833286 ISBN 13: 9781680833287
Published by Now Publishers Inc 2017-07, 2017
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Multi-Period Trading via Convex Optimization considers a basic model of multi-period trading, which can be used to evaluate the performance of a trading strategy. It describes a framework for single-period optimization, where the trades in each period are found by solving a convex optimization problem that trades off expected return, risk, transaction cost and holding cost such as the borrowing cost for shorting assets. It then describes a multi-period version of the trading method, where optimization is used to plan a sequence of trades, with only the first one executed, using estimates of future quantities that are unknown when the trades are chosen. The single period method traces back to Markowitz; the multi-period methods trace back to model predictive control. This monograph addresses the single-period and multi-period methods in one simple framework, giving a clear description of the development and the approximations made. The methods described can be thought of as good ways to exploit predictions, no matter how they are made. Multi-Period Trading via Convex Optimization collects in one place the basic definitions, a careful description of the model, and discussion of how convex optimization can be used in multi-period trading, all in a common notation and framework. It provides the reader with a unified, self-contained treatment, focusing on the practical issues that arise in multi-period trading. It will benefit anyone interested in the study of these methods and is also an ideal reference for a quantitative trader, or someone who works with or for, or employs, one.

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Bibliographic Details

Title: Multi-Period Trading via Convex Optimization
Publisher: Now Publishers Inc 2017-07
Publication Date: 2017
Binding: PF
Condition: New

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Boyd, Stephen; Busseti, Enzo; Diamond, Steven; Kahn, Ronald N; Koh, Kwangmoo; Nystrup, Peter; Speth, Jan
Published by Now Publishers, 2017
ISBN 10: 1680833286 ISBN 13: 9781680833287
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