Author: Cong LiuPublisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Asset Allocation and Portfolio Optimization with Small Transaction Costs
Author: Cong LiuA Practitioner's Guide to Asset Allocation
Author: William KinlawPublisher: John Wiley & Sons
ISBN: 111940245X
Category : Business & Economics
Languages : en
Pages : 271
Book Description
Since the formalization of asset allocation in 1952 with the publication of Portfolio Selection by Harry Markowitz, there have been great strides made to enhance the application of this groundbreaking theory. However, progress has been uneven. It has been punctuated with instances of misleading research, which has contributed to the stubborn persistence of certain fallacies about asset allocation. A Practitioner's Guide to Asset Allocation fills a void in the literature by offering a hands-on resource that describes the many important innovations that address key challenges to asset allocation and dispels common fallacies about asset allocation. The authors cover the fundamentals of asset allocation, including a discussion of the attributes that qualify a group of securities as an asset class and a detailed description of the conventional application of mean-variance analysis to asset allocation.. The authors review a number of common fallacies about asset allocation and dispel these misconceptions with logic or hard evidence. The fallacies debunked include such notions as: asset allocation determines more than 90% of investment performance; time diversifies risk; optimization is hypersensitive to estimation error; factors provide greater diversification than assets and are more effective at reducing noise; and that equally weighted portfolios perform more reliably out of sample than optimized portfolios. A Practitioner's Guide to Asset Allocation also explores the innovations that address key challenges to asset allocation and presents an alternative optimization procedure to address the idea that some investors have complex preferences and returns may not be elliptically distributed. Among the challenges highlighted, the authors explain how to overcome inefficiencies that result from constraints by expanding the optimization objective function to incorporate absolute and relative goals simultaneously. The text also explores the challenge of currency risk, describes how to use shadow assets and liabilities to unify liquidity with expected return and risk, and shows how to evaluate alternative asset mixes by assessing exposure to loss throughout the investment horizon based on regime-dependent risk. This practical text contains an illustrative example of asset allocation which is used to demonstrate the impact of the innovations described throughout the book. In addition, the book includes supplemental material that summarizes the key takeaways and includes information on relevant statistical and theoretical concepts, as well as a comprehensive glossary of terms.
Portfolio Management with Heuristic Optimization
Author: Dietmar G. MaringerPublisher: Springer Science & Business Media
ISBN: 0387258531
Category : Business & Economics
Languages : en
Pages : 238
Book Description
Portfolio Management with Heuristic Optimization consist of two parts. The first part (Foundations) deals with the foundations of portfolio optimization, its assumptions, approaches and the limitations when "traditional" optimization techniques are to be applied. In addition, the basic concepts of several heuristic optimization techniques are presented along with examples of how to implement them for financial optimization problems. The second part (Applications and Contributions) consists of five chapters, covering different problems in financial optimization: the effects of (linear, proportional and combined) transaction costs together with integer constraints and limitations on the initital endowment to be invested; the diversification in small portfolios; the effect of cardinality constraints on the Markowitz efficient line; the effects (and hidden risks) of Value-at-Risk when used the relevant risk constraint; the problem factor selection for the Arbitrage Pricing Theory.
Portfolio Optimization with Transaction Costs and Preconceived Portfolio Weights
Author: Jeremy Dale MyersPublisher:
ISBN:
Category :
Languages : en
Pages : 88
Book Description
In the financial world, many quantitative investment managers have developed sophisticated statistical techniques to generate signals about expected returns from previous market data. However, the manner in which they apply this information to rebalancing their portfolios is often ad-hoc, trading off between rebalancing their assets into an allocation that generates the greatest expected return based on the generated signals and the incurred transaction costs that the reallocation will require. In this thesis, we develop an approximation to our investor's true value function which incorporates both return predictability and transaction costs. By optimizing our approximate value function at each time step, we will generate a portfolio strategy that closely emulates the optimal portfolio strategy, which is based on the true value function. In order to determine the optimal set of parameters for our approximate function which will generate the best overall portfolio performance, we develop a simulation-based method. Our computational implementation is verified against well-known base cases. We determine the optimal parameters for our approximate function in the single stock and bond case. In addition, we determine a confidence level on our simulation results. Our approximate function gives us useful insight into the optimal portfolio allocation in complex higher dimensional cases. Our function derivation and simulation methodology extend easily to portfolio allocation in higher dimensional cases, and we implement the modifications required to run these simulations. Simple cases are tested and more complex tests are specified for testing when appropriate dedicated computing resources are available.
Efficient Asset Management
Author: Richard O. MichaudPublisher: Oxford University Press
ISBN: 0199715793
Category : Business & Economics
Languages : en
Pages : 145
Book Description
In spite of theoretical benefits, Markowitz mean-variance (MV) optimized portfolios often fail to meet practical investment goals of marketability, usability, and performance, prompting many investors to seek simpler alternatives. Financial experts Richard and Robert Michaud demonstrate that the limitations of MV optimization are not the result of conceptual flaws in Markowitz theory but unrealistic representation of investment information. What is missing is a realistic treatment of estimation error in the optimization and rebalancing process. The text provides a non-technical review of classical Markowitz optimization and traditional objections. The authors demonstrate that in practice the single most important limitation of MV optimization is oversensitivity to estimation error. Portfolio optimization requires a modern statistical perspective. Efficient Asset Management, Second Edition uses Monte Carlo resampling to address information uncertainty and define Resampled Efficiency (RE) technology. RE optimized portfolios represent a new definition of portfolio optimality that is more investment intuitive, robust, and provably investment effective. RE rebalancing provides the first rigorous portfolio trading, monitoring, and asset importance rules, avoiding widespread ad hoc methods in current practice. The Second Edition resolves several open issues and misunderstandings that have emerged since the original edition. The new edition includes new proofs of effectiveness, substantial revisions of statistical estimation, extensive discussion of long-short optimization, and new tools for dealing with estimation error in applications and enhancing computational efficiency. RE optimization is shown to be a Bayesian-based generalization and enhancement of Markowitz's solution. RE technology corrects many current practices that may adversely impact the investment value of trillions of dollars under current asset management. RE optimization technology may also be useful in other financial optimizations and more generally in multivariate estimation contexts of information uncertainty with Bayesian linear constraints. Michaud and Michaud's new book includes numerous additional proposals to enhance investment value including Stein and Bayesian methods for improved input estimation, the use of portfolio priors, and an economic perspective for asset-liability optimization. Applications include investment policy, asset allocation, and equity portfolio optimization. A simple global asset allocation problem illustrates portfolio optimization techniques. A final chapter includes practical advice for avoiding simple portfolio design errors. With its important implications for investment practice, Efficient Asset Management 's highly intuitive yet rigorous approach to defining optimal portfolios will appeal to investment management executives, consultants, brokers, and anyone seeking to stay abreast of current investment technology. Through practical examples and illustrations, Michaud and Michaud update the practice of optimization for modern investment management.
Dynamic Portfolio Theory and Management
Author: Richard E. OberucPublisher: McGraw Hill Professional
ISBN: 9780071426695
Category : Business & Economics
Languages : en
Pages : 344
Book Description
Publisher Description
Multi-Period Trading Via Convex Optimization
Author: Stephen BoydPublisher:
ISBN: 9781680833287
Category : Mathematics
Languages : en
Pages : 92
Book Description
This monograph collects in one place the basic deļ¬nitions, 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.
Investments: Portfolio theory and asset pricing
Author: Edwin J. EltonPublisher: MIT Press
ISBN: 9780262050593
Category : Business enterprises
Languages : en
Pages : 452
Book Description
This collection of articles in investment and portfolio management spans the thirty-five-year collaborative effort of two key figures in finance. Each of the nine sections begins with an overview that introduces the main contributions of the pieces and traces the development of the field. Each volume contains a foreword by Nobel laureate Harry Markowitz. Volume I presents the authors' groundbreaking work on estimating the inputs to portfolio optimization, including the analysis of alternative structures such as single and multi-index models in forecasting correlations; portfolio maximization under alternative specifications for return structures; the impact of CAPM and APT in the investment process; and taxes and portfolio composition. Volume II covers the authors' work on analysts' expectations; performance evaluation of managed portfolios, including commodity, stock, and bond portfolios; survivorship bias and performance persistence; debt markets; and immunization and efficiency.
Large-scale Portfolio Allocation Under Transaction Costs and Model Uncertainty
Author: Nikolaus HautschPublisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
We theoretically and empirically study large-scale portfolio allocation problems when transaction costs are taken into account in the optimization problem. We show that transaction costs act on the one hand as a turnover penalization and on the other hand as a regularization, which shrinks the covariance matrix. As an empirical framework, we propose a flexible econometric setting for portfolio optimization under transaction costs, which incorporates parameter uncertainty and combines predictive distributions of individual models using optimal prediction pooling. We consider predictive distributions resulting from highfrequency based covariance matrix estimates, daily stochastic volatility factor models and regularized rolling window covariance estimates, among others. Using data capturing several hundred Nasdaq stocks over more than 10 years, we illustrate that transaction cost regularization (even to small extent) is crucial in order to produce allocations with positive Sharpe ratios. We moreover show that performance differences between individual models decline when transaction costs are considered. Nevertheless, it turns out that adaptive mixtures based on high-frequency and low-frequency information yield the highest performance. Portfolio bootstrap reveals that naive 1=N-allocations and global minimum variance allocations (with and without short sales constraints) are significantly outperformed in terms of Sharpe ratios and utility gains.
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