Managing Transaction Costs in a Dynamic Trading Strategy

Managing Transaction Costs in a Dynamic Trading Strategy
Author: James A. Sefton
Publisher:
Total Pages: 45
Release: 2015
Genre:
ISBN:

We derive an explicit solution to a continuous time dynamic portfolio problem assuming investors maximize their welfare from a consumption stream in an incomplete market where returns to the securities are predictable but costly to trade. The solution is phrased in terms of a risk-sensitive Riccati equation. We show that the optimal trading strategy is to target a portfolio that is the optimal solution to a frictionless (or 'no-cost') dynamic portfolio problem but where the returns to the assets have been adjusted for costs; that is they have been expressed on a net rather than gross basis. The legacy portfolio (the inherited undesirable positions) are then traded away in line with a backward-looking optimal execution problem. We show that the utility gradient is a stochastic discount factor that prices the assets net returns. Thus we are able to generalise some of the results of the martingale approach to dynamic portfolio theory to market with frictions.

Dynamic Trading with Predictable Returns and Transaction Costs

Dynamic Trading with Predictable Returns and Transaction Costs
Author: Nicolae Garleanu
Publisher:
Total Pages: 0
Release: 2009
Genre: Portfolio management
ISBN:

Abstract: This paper derives in closed form the optimal dynamic portfolio policy when trading is costly and security returns are predictable by signals with different mean-reversion speeds. The optimal updated portfolio is a linear combination of the existing portfolio, the optimal portfolio absent trading costs, and the optimal portfolio based on future expected returns and transaction costs. Predictors with slower mean reversion (alpha decay) get more weight since they lead to a favorable positioning both now and in the future. We implement the optimal policy for commodity futures and show that the resulting portfolio has superior returns net of trading costs relative to more naive benchmarks. Finally, we derive natural equilibrium implications, including that demand shocks with faster mean reversion command a higher return premium

The Science of Algorithmic Trading and Portfolio Management

The Science of Algorithmic Trading and Portfolio Management
Author: Robert Kissell
Publisher: Academic Press
Total Pages: 492
Release: 2013-10-01
Genre: Business & Economics
ISBN: 0124016936

The Science of Algorithmic Trading and Portfolio Management, with its emphasis on algorithmic trading processes and current trading models, sits apart from others of its kind. Robert Kissell, the first author to discuss algorithmic trading across the various asset classes, provides key insights into ways to develop, test, and build trading algorithms. Readers learn how to evaluate market impact models and assess performance across algorithms, traders, and brokers, and acquire the knowledge to implement electronic trading systems. This valuable book summarizes market structure, the formation of prices, and how different participants interact with one another, including bluffing, speculating, and gambling. Readers learn the underlying details and mathematics of customized trading algorithms, as well as advanced modeling techniques to improve profitability through algorithmic trading and appropriate risk management techniques. Portfolio management topics, including quant factors and black box models, are discussed, and an accompanying website includes examples, data sets supplementing exercises in the book, and large projects. - Prepares readers to evaluate market impact models and assess performance across algorithms, traders, and brokers. - Helps readers design systems to manage algorithmic risk and dark pool uncertainty. - Summarizes an algorithmic decision making framework to ensure consistency between investment objectives and trading objectives.

Strategic Asset Allocation

Strategic Asset Allocation
Author: John Y. Campbell
Publisher: OUP Oxford
Total Pages: 272
Release: 2002-01-03
Genre: Business & Economics
ISBN: 019160691X

Academic finance has had a remarkable impact on many financial services. Yet long-term investors have received curiously little guidance from academic financial economists. Mean-variance analysis, developed almost fifty years ago, has provided a basic paradigm for portfolio choice. This approach usefully emphasizes the ability of diversification to reduce risk, but it ignores several critically important factors. Most notably, the analysis is static; it assumes that investors care only about risks to wealth one period ahead. However, many investors—-both individuals and institutions such as charitable foundations or universities—-seek to finance a stream of consumption over a long lifetime. In addition, mean-variance analysis treats financial wealth in isolation from income. Long-term investors typically receive a stream of income and use it, along with financial wealth, to support their consumption. At the theoretical level, it is well understood that the solution to a long-term portfolio choice problem can be very different from the solution to a short-term problem. Long-term investors care about intertemporal shocks to investment opportunities and labor income as well as shocks to wealth itself, and they may use financial assets to hedge their intertemporal risks. This should be important in practice because there is a great deal of empirical evidence that investment opportunities—-both interest rates and risk premia on bonds and stocks—-vary through time. Yet this insight has had little influence on investment practice because it is hard to solve for optimal portfolios in intertemporal models. This book seeks to develop the intertemporal approach into an empirical paradigm that can compete with the standard mean-variance analysis. The book shows that long-term inflation-indexed bonds are the riskless asset for long-term investors, it explains the conditions under which stocks are safer assets for long-term than for short-term investors, and it shows how labor income influences portfolio choice. These results shed new light on the rules of thumb used by financial planners. The book explains recent advances in both analytical and numerical methods, and shows how they can be used to understand the portfolio choice problems of long-term investors.

Dynamic Hedging

Dynamic Hedging
Author: Nassim Nicholas Taleb
Publisher: John Wiley & Sons
Total Pages: 536
Release: 1997-01-14
Genre: Business & Economics
ISBN: 9780471152804

Destined to become a market classic, Dynamic Hedging is the only practical reference in exotic options hedgingand arbitrage for professional traders and money managers Watch the professionals. From central banks to brokerages to multinationals, institutional investors are flocking to a new generation of exotic and complex options contracts and derivatives. But the promise of ever larger profits also creates the potential for catastrophic trading losses. Now more than ever, the key to trading derivatives lies in implementing preventive risk management techniques that plan for and avoid these appalling downturns. Unlike other books that offer risk management for corporate treasurers, Dynamic Hedging targets the real-world needs of professional traders and money managers. Written by a leading options trader and derivatives risk advisor to global banks and exchanges, this book provides a practical, real-world methodology for monitoring and managing all the risks associated with portfolio management. Nassim Nicholas Taleb is the founder of Empirica Capital LLC, a hedge fund operator, and a fellow at the Courant Institute of Mathematical Sciences of New York University. He has held a variety of senior derivative trading positions in New York and London and worked as an independent floor trader in Chicago. Dr. Taleb was inducted in February 2001 in the Derivatives Strategy Hall of Fame. He received an MBA from the Wharton School and a Ph.D. from University Paris-Dauphine.

Optimal Mean Reversion Trading

Optimal Mean Reversion Trading
Author: Tim Leung (Professor of industrial engineering)
Publisher: World Scientific
Total Pages: 221
Release: 2015-11-26
Genre: Business & Economics
ISBN: 9814725927

"Optimal Mean Reversion Trading: Mathematical Analysis and Practical Applications provides a systematic study to the practical problem of optimal trading in the presence of mean-reverting price dynamics. It is self-contained and organized in its presentation, and provides rigorous mathematical analysis as well as computational methods for trading ETFs, options, futures on commodities or volatility indices, and credit risk derivatives. This book offers a unique financial engineering approach that combines novel analytical methodologies and applications to a wide array of real-world examples. It extracts the mathematical problems from various trading approaches and scenarios, but also addresses the practical aspects of trading problems, such as model estimation, risk premium, risk constraints, and transaction costs. The explanations in the book are detailed enough to capture the interest of the curious student or researcher, and complete enough to give the necessary background material for further exploration into the subject and related literature. This book will be a useful tool for anyone interested in financial engineering, particularly algorithmic trading and commodity trading, and would like to understand the mathematically optimal strategies in different market environments."--

Multi-Period Trading Via Convex Optimization

Multi-Period Trading Via Convex Optimization
Author: Stephen Boyd
Publisher:
Total Pages: 92
Release: 2017-07-28
Genre: Mathematics
ISBN: 9781680833287

This monograph 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.