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Book Multiperiod Portfolio Optimization with Many Risky Assets and General Transaction Costs

Download or read book Multiperiod Portfolio Optimization with Many Risky Assets and General Transaction Costs written by Victor DeMiguel and published by . This book was released on 2014 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: We analyze the optimal portfolio policy for a multiperiod mean-variance investor facing a large number of risky assets in the presence of general transaction cost. For proportional transaction costs, we give a closed-form expression for a no-trade region, shaped as a multi-dimensional parallelogram, and show how the optimal portfolio policy can be efficiently computed by solving a single quadratic program. For market impact costs, we show that at each period it is optimal to trade to the boundary of a state-dependent rebalancing region. Finally, we show empirically that the utility loss associated with ignoring transaction costs may be large.

Book Multi Period Trading Via Convex Optimization

Download or read book Multi Period Trading Via Convex Optimization written by Stephen Boyd and published by . This book was released on 2017-07-28 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Multi Dimensional Portfolio Optimization with Proportional Transaction Costs

Download or read book Multi Dimensional Portfolio Optimization with Proportional Transaction Costs written by Kumar Muthuraman and published by . This book was released on 2004 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt: We provide a computational study of the problem of optimally allocating wealth among multiple stocks and a bank account, in order to maximize the infinite horizon discounted utility of consumption. We consider the situation where the transfer of wealth from one asset to another involves transaction costs that are proportional to the amount of wealth transferred. Our model allows for correlation between the price processes, which in turn gives rise to interesting hedging strategies. This results in a stochastic control problem with both drift-rate and singular controls, that can be recast as a free boundary problem in partial differential equations. Adapting the finite element method and using an iterative procedure that converts the free-boundary problem into a sequence of fixed boundary problems, we provide an efficient numerical method for solving this problem. We present computational results that describe the impact of volatility, risk aversion of the investor, level of transaction costs and correlation among the risky assets on the structure of the optimal policy. Finally we suggest and quantify some heuristic approximations.

Book Multiperiod Portfolio Optimization in the Presence of Transaction Costs

Download or read book Multiperiod Portfolio Optimization in the Presence of Transaction Costs written by Efthalia Chryssikou and published by . This book was released on 1998 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Multi period Portfolio Optimization in the Presence of Transaction Costs

Download or read book Multi period Portfolio Optimization in the Presence of Transaction Costs written by Husnu Kipeak and published by . This book was released on 2001 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Portfolio Optimization with Concave Transaction Costs

Download or read book Portfolio Optimization with Concave Transaction Costs written by and published by . This book was released on 2002 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Parameter Uncertainty in Multiperiod Portfolio Optimization with Transaction Costs

Download or read book Parameter Uncertainty in Multiperiod Portfolio Optimization with Transaction Costs written by Victor DeMiguel and published by . This book was released on 2014 with total page 45 pages. Available in PDF, EPUB and Kindle. Book excerpt: We study the impact of parameter uncertainty on the expected utility of a multiperiod investor subject to quadratic transaction costs. We characterize the utility loss associated with ignoring parameter uncertainty, and show that it is equal to the product between the single-period utility loss and another term that captures the effects of the multiperiod mean-variance utility and transaction cost losses. To mitigate the impact of parameter uncertainty, we propose two multiperiod shrinkage portfolios and demonstrate with simulated and empirical datasets that they substantially outperform portfolios that ignore parameter uncertainty, transaction costs, or both.

Book Numerical Solution of Dynamic Portfolio Optimization with Transaction Costs

Download or read book Numerical Solution of Dynamic Portfolio Optimization with Transaction Costs written by Yongyang Cai and published by . This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We apply numerical dynamic programming to multi-asset dynamic portfolio optimization problems with proportional transaction costs. Examples include problems with one safe asset plus two to six risky stocks, and seven to 360 trading periods in a finite horizon problem. These examples show that it is now tractable to solve such problems.

Book Multi period Portfolio Optimization with Investor Views Under Regime Switching

Download or read book Multi period Portfolio Optimization with Investor Views Under Regime Switching written by Razvan Gabriel Oprisor and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose a novel multi-period trading model that allows portfolio managers to perform optimal portfolio allocation while incorporating their interpretable investment views. This model's significant advantage is its incorporation of the latest asset return regimes to quantitatively solve managers' question: how certain should one be that a given investment view is occurring? First, we describe a framework for multi-period portfolio allocation formulated as a convex optimization problem that trades off expected return, risk and transaction costs. Second, we use the Black-Litterman model to combine investment views specified in a simple linear combination based format with the market portfolio. A data-driven method to adjust the confidence in the manager's views by comparing them to dynamically updated regime-switching forecasts is proposed. Our contribution is to incorporate both multi-period trading and interpretable investment views into one efficient framework and offer a novel method of using regime-switching to determine each view's confidence.

Book Portfolio Optimization with Transaction Costs and Capital Gain Taxes

Download or read book Portfolio Optimization with Transaction Costs and Capital Gain Taxes written by and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Across various sets of parameters, duality gaps between lower and upper bounds are smaller than 3% in most examples. We are able to solve the problem up to the size of 20 risky assets and a 30-year-long horizon.

Book Skewed Target Range Strategy for Multiperiod Portfolio Optimization Using a Two Stage Least Squares Monte Carlo Method

Download or read book Skewed Target Range Strategy for Multiperiod Portfolio Optimization Using a Two Stage Least Squares Monte Carlo Method written by Rongju Zhang and published by . This book was released on 2019 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, we propose a novel investment strategy for portfolio optimization problems. The proposed strategy maximizes the expected portfolio value bounded within a targeted range, composed of a conservative lower target representing a need for capital protection and a desired upper target representing an investment goal. This strategy favorably shapes the entire probability distribution of returns, as it simultaneously seeks a desired expected return, cuts off downside risk and implicitly caps volatility and higher moments. To illustrate the effectiveness of this investment strategy, we study a multiperiod portfolio optimization problem with transaction costs and develop a two-stage regression approach that improves the classical least squares Monte Carlo (LSMC) algorithm when dealing with difficult payoffs, such as highly concave, abruptly changing or discontinuous functions. Our numerical results show substantial improvements over the classical LSMC algorithm for both the constant relative risk-aversion (CRRA) utility approach and the proposed skewed target range strategy (STRS). Our numerical results illustrate the ability of the STRS to contain the portfolio value within the targeted range. When compared with the CRRA utility approach, the STRS achieves a similar mean-variance efficient frontier while delivering a better downside risk-return trade-off.

Book Single  and Multi Period Portfolio Optimization with Cone Constraints and Discrete Decisions

Download or read book Single and Multi Period Portfolio Optimization with Cone Constraints and Discrete Decisions written by Ümit Saglam and published by . This book was released on 2019 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt: Portfolio optimization literature has come quite far in the decades since the first publication, and many modern models are formulated using second-order cone constraints and take discrete decisions into consideration. In this study, we consider both single-period and multi-period portfolio optimization problems based on the Markowitz (1952) mean/variance framework, where there is a trade-off between expected return and the risk that the investor may be willing to take on. Our model is aggregated from current literature. In this model, we have included transaction costs, conditional value-at-risk (CVaR) constraints, diversification-by-sector constraints, and buy-in-thresholds. Our numerical experiments are conducted on portfolios drawn from 20 to 400 different stocks available from the S&P 500 for the single period-model. The multi-period portfolio optimization model is obtained using a binary scenario tree that is constructed with monthly returns of the closing price of the stocks from the S&P 500. We solve these models with a MATLAB based Mixed Integer Linear and Nonlinear Optimizer (MILANO). We provide a substantial improvement in runtimes using warmstarts in both branch-and-bound and outer approximation algorithms.

Book Performance Bounds and Suboptimal Policies for Multi period Investment

Download or read book Performance Bounds and Suboptimal Policies for Multi period Investment written by Stephen P. Boyd and published by . This book was released on 2014 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt: We consider dynamic trading of a portfolio of assets in discrete periods over a finite time horizon, with arbitrary time-varying distribution of asset returns. The goal is to maximize the total expected revenue from the portfolio, while respecting constraints on the portfolio such as a required terminal portfolio and leverage and risk limits. The revenue takes into account the gross cash generated in trades, transaction costs, and costs associated with the positions, such as fees for holding short positions. Our model has the form of a stochastic control problem with linear dynamics and convex cost function and constraints. While this problem can be tractably solved in several special cases, such as when all costs are convex quadratic, or when there are no transaction costs, our focus is on the more general case, with nonquadratic cost terms and transaction costs. We show how to use linear matrix inequality techniques and semidefinite programming to produce a quadratic bound on the value function, which in turn gives a bound on the optimal performance. This performance bound can be used to judge the performance obtained by any suboptimal policy. As a by-product of the performance bound computation, we obtain an approximate dynamic programming policy that requires the solution of a convex optimization problem, often a quadratic program, to determine the trades to carry out in each step. While we have no theoretical guarantee that the performance of our suboptimal policy is always near the performance bound (which would imply that it is nearly optimal) we observe that in numerical examples the two values are typically close.

Book Uncertain Portfolio Optimization

Download or read book Uncertain Portfolio Optimization written by Zhongfeng Qin and published by Springer. This book was released on 2016-09-16 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a new modeling approach for portfolio optimization problems involving a lack of sufficient historical data. The content mainly reflects the author’s extensive work on uncertainty portfolio optimization in recent years. Considering security returns as different variables, the book presents a series of portfolio optimization models in the framework of credibility theory, uncertainty theory and chance theory, respectively. As such, it offers readers a comprehensive and up-to-date guide to uncertain portfolio optimization models.

Book Financial Decision Aid Using Multiple Criteria

Download or read book Financial Decision Aid Using Multiple Criteria written by Hatem Masri and published by Springer. This book was released on 2018-01-17 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume highlights recent applications of multiple-criteria decision-making (MCDM) models in the field of finance. Covering a wide range of MCDM approaches, including multiobjective optimization, goal programming, value-based models, outranking techniques, and fuzzy models, it provides researchers and practitioners with a set of MCDM methodologies and empirical results in areas such as portfolio management, investment appraisal, banking, and corporate finance, among others. The book addresses issues related to problem structuring and modeling, solution techniques, comparative analyses, as well as combinations of MCDM models with other analytical methodologies.

Book Convex Optimization

Download or read book Convex Optimization written by Stephen P. Boyd and published by Cambridge University Press. This book was released on 2004-03-08 with total page 744 pages. Available in PDF, EPUB and Kindle. Book excerpt: Convex optimization problems arise frequently in many different fields. This book provides a comprehensive introduction to the subject, and shows in detail how such problems can be solved numerically with great efficiency. The book begins with the basic elements of convex sets and functions, and then describes various classes of convex optimization problems. Duality and approximation techniques are then covered, as are statistical estimation techniques. Various geometrical problems are then presented, and there is detailed discussion of unconstrained and constrained minimization problems, and interior-point methods. The focus of the book is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. It contains many worked examples and homework exercises and will appeal to students, researchers and practitioners in fields such as engineering, computer science, mathematics, statistics, finance and economics.

Book Performance Bounds and Suboptimal Policies for Multi Period Investment

Download or read book Performance Bounds and Suboptimal Policies for Multi Period Investment written by Stephen Boyd and published by Now Pub. This book was released on 2013-11 with total page 94 pages. Available in PDF, EPUB and Kindle. Book excerpt: Examines dynamic trading of a portfolio of assets in discrete periods over a finite time horizon, with arbitrary time-varying distribution of asset returns. The goal is to maximize the total expected revenue from the portfolio, while respecting constraints on the portfolio such as a required terminal portfolio and leverage and risk limits.