Download or read book Applications of Forward Performance Processes in Dynamic Optimal Portfolio Management written by Xiao Han and published by . This book was released on 2017 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: The classical optimal investment models are cast in a finite or infinite horizon setting, assuming an a priori choice of a market model (or a family of models) as well as a priori choice of a utility function of terminal wealth and/or intermediate consumption. Once these choices are made, namely, the horizon, the model and the risk preferences, stochastic optimization technique yield the maximal expected utility (value function) and the optimal policies wither through the Hamilton-Jacobi-Bellman equation in Makovian models or, more generally, via duality in semi-martingale models. A fundamental property of the solution is time-consistency, which follows from the Dynamic Programming Principle (DPP). This principle provides the intuitively pleasing interpretation of the value function as the intermediate (indirect) utility. It also states that the value function is a martingale along the optimal wealth trajectory and a super-martingale along every admissible one. These properties provide a time-consistent framework of the solutions, which ``pastes" naturally one investment period to the next. Despite its mathematical sophistication, the classical expected utility framework cannot accommodate model revision, nor horizon flexibility nor adaptation of risk preferences, if one desires to retain time-consistency. Indeed, the classical formulation is by nature ``backwards" in time and, thus, it does not allow any "forward in time" changes. For example, on-line learning, which typically occurs in a non-anticipated way, cannot be implemented in the classical setting, simply because the latter evolves backwards while the former progresses forward in time. To alleviate some of these limitations while, at the same time, preserving the time-consistency property, Musiela and Zariphopoulou proposed an alternative criterion, the so-called forward performance process. This process satisfies the DPP forward in time, and generalizes the classical expected utility. For a large family of cases, forward performance processes have been explicitly constructed for general Ito-diffusion markets. While there has already been substantial mathematical work on this criterion, concrete applications to applied portfolio management are lacking. In this thesis, the aim is to focus on applied aspects of the forward performance approach and build meaningful connections with practical portfolio management. The following topics are being studied. Chapter 2 starts with providing an intuitive characterization of the underlying performance measure and the associated risk tolerance process, which are the most fundamental ingredients of the forward approach. It also provides a novel decomposition of the initial condition and, in turn, its inter-temporal preservation as the market evolves. The main steps involve a system of stochastic differential equations modeling various stochastic sensitivities and risk metrics. Chapter 3 focuses on the applications of the above results to lifecycle portfolio management. Investors are firstly classified by their individual risk preference generating measures and, in turn, mapped to different groups that are consistent with the popular practice of age-based de-leveraging. The inverse problem is also studied, namely, how to infer the individual investor-type measure from observed investment behavior. Chapter 4 provides applications of the forward performance to the classical problem of mean-variance analysis. It examines how sequential investment periods can be ``pasted together" in a time-consistent manner from one evaluation period to the next. This is done by mapping the mean-variance to a family of forward quadratic performances with appropriate stochastic and path-dependent coefficients. Quantitative comparisons with the classical approach are provided for a class of market settings, which demonstrate the superiority and flexibility of the forward approach.

Download or read book Outperformance and Tracking written by Ali Al-Aradi and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Portfolio management problems can be broadly divided into two classes of differing investing styles: active and passive. There are a number of philosophical and operational distinctions between these two investment approaches including mandate, complexity, activity level, constraints, and goals. Both forms of portfolio management, however, can involve absolute or relative goals. These goals are distinguished by the involvement (or lack thereof) of external processes in measuring an investor's performance. This thesis presents a unified framework for solving portfolio selection problems arising in both active and passive portfolio management with a focus on relative goals. We are, in particular, interested in stochastic optimization problems related to outperforming a selected benchmark and/or tracking a given portfolio, both natural and essential questions in portfolio management. In the first part of the thesis, we lay the foundation for our framework by introducing a flexible stochastic control problem that captures the range of goals we are interested in. We solve the problem, first, in a simple setting using a dynamic programming approach and derive an explicit closed-form solution for the optimal portfolio. We uncover several important features of the optimal portfolio, most notably, a decomposition result where the optimal solution is expressed in terms of the underlying benchmarks, the growth optimal portfolio, and the minimum variance portfolio. We probe the empirical performance of the optimal portfolio using historical as well as simulated market data. The latter parts of the thesis are dedicated to cases where (i) assets are driven by latent factors and general martingale noise processes, (ii) the market model and preference parameters are stochastic, and (iii) the investor has non-linear utility. These extensions are approached using variational analysis techniques which exploit the convexity of the underlying performance functionals to easily incorporate these additional features. In some instances, the optimal portfolio is characterized via forward backward stochastic differential equations (FBSDEs), and, due to the variational characterization, we establish the existence and uniqueness of solutions to those FBSDEs. The approach we take is also useful for lending interpretability to the solution of the well-known Merton problem when model parameters are stochastic. Moreover, in some special cases, we are able to extend the decomposition result established in the Brownian setting. From a practical perspective, this thesis also presents a fully implementable procedure for computing optimal portfolios for a hidden Markov model of asset prices, including parameter estimation along with filtering results for the hidden state in a general semimartingale setting. The investment performance is demonstrated with out-of-sample backtesting using historical market data.

Download or read book Dynamic Portfolio Theory and Management written by Richard E. Oberuc and published by McGraw Hill Professional. This book was released on 2004 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Publisher Description

Download or read book Robust Portfolio Optimization and Management written by Frank J. Fabozzi and published by John Wiley & Sons. This book was released on 2007-04-27 with total page 513 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for Robust Portfolio Optimization and Management "In the half century since Harry Markowitz introduced his elegant theory for selecting portfolios, investors and scholars have extended and refined its application to a wide range of real-world problems, culminating in the contents of this masterful book. Fabozzi, Kolm, Pachamanova, and Focardi deserve high praise for producing a technically rigorous yet remarkably accessible guide to the latest advances in portfolio construction." --Mark Kritzman, President and CEO, Windham Capital Management, LLC "The topic of robust optimization (RO) has become 'hot' over the past several years, especially in real-world financial applications. This interest has been sparked, in part, by practitioners who implemented classical portfolio models for asset allocation without considering estimation and model robustness a part of their overall allocation methodology, and experienced poor performance. Anyone interested in these developments ought to own a copy of this book. The authors cover the recent developments of the RO area in an intuitive, easy-to-read manner, provide numerous examples, and discuss practical considerations. I highly recommend this book to finance professionals and students alike." --John M. Mulvey, Professor of Operations Research and Financial Engineering, Princeton University

Download or read book Portfolio Optimization and Performance Analysis written by Jean-Luc Prigent and published by CRC Press. This book was released on 2007-05-07 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: In answer to the intense development of new financial products and the increasing complexity of portfolio management theory, Portfolio Optimization and Performance Analysis offers a solid grounding in modern portfolio theory. The book presents both standard and novel results on the axiomatics of the individual choice in an uncertain framework, cont

Download or read book The Complete Guide to Portfolio Performance written by Pascal François and published by John Wiley & Sons. This book was released on 2024-04-23 with total page 1095 pages. Available in PDF, EPUB and Kindle. Book excerpt: An intuitive and effective desk reference for performance measurement in asset and wealth management In The Complete Guide to Portfolio Performance: Appraise, Analyse, Act, a team of finance professors with extended practical experience deliver a hands-on desk reference for asset and wealth managers suitable for everyday use. Intuitively organized and full of concrete examples of the real-world implementation of the concepts discussed within, the book provides a comprehensive coverage of all important portfolio performance matters across 18 chapters of actionable and clearly described content. The authors have provided relevant cross-referencing where appropriate, “Key Takeaways and Equations” sections at the end of each chapter, and pointers to additional resources for anyone interested in pursuing further research. You'll also find: Discussions of more than a hundred classical and modern performance measures organized logically and with a focus on their applications Strategies for selecting appropriate performance measures based on your situation as a manager or investor Explanations of analytical techniques (statistical approaches, attribution, fund ratings...) enabling a comprehensive use of performance-related information Applications of portfolio performance criteria in concrete investment decision-making processes Highly actionable and logically organized material that's easy to find at a moment's notice A full set of pedagogical powerpoint slides and excel worksheets with all data and formulas Perfect for investors, portfolio managers, advisors, analysts, and regulators, The Complete Guide to Portfolio Performance is also a must-read reference for students and practitioners of asset and wealth management, as well as those pursuing certification such as CFA, CIPM, CIIA, and CAIA.

Download or read book Forward Optimization and Real time Model Adaptation with Applications to Portfolio Management Indifference Valuation and Optimal Liquidation written by Haoran Wang (Ph. D.) and published by . This book was released on 2018 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Stochastic Optimization Methods in Finance and Energy written by Marida Bertocchi and published by Springer Science & Business Media. This book was released on 2011-09-15 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents a collection of contributions dedicated to applied problems in the financial and energy sectors that have been formulated and solved in a stochastic optimization framework. The invited authors represent a group of scientists and practitioners, who cooperated in recent years to facilitate the growing penetration of stochastic programming techniques in real-world applications, inducing a significant advance over a large spectrum of complex decision problems. After the recent widespread liberalization of the energy sector in Europe and the unprecedented growth of energy prices in international commodity markets, we have witnessed a significant convergence of strategic decision problems in the energy and financial sectors. This has often resulted in common open issues and has induced a remarkable effort by the industrial and scientific communities to facilitate the adoption of advanced analytical and decision tools. The main concerns of the financial community over the last decade have suddenly penetrated the energy sector inducing a remarkable scientific and practical effort to address previously unforeseeable management problems. Stochastic Optimization Methods in Finance and Energy: New Financial Products and Energy Markets Strategies aims to include in a unified framework for the first time an extensive set of contributions related to real-world applied problems in finance and energy, leading to a common methodological approach and in many cases having similar underlying economic and financial implications. Part 1 of the book presents 6 chapters related to financial applications; Part 2 presents 7 chapters on energy applications; and Part 3 presents 5 chapters devoted to specific theoretical and computational issues.

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.

Download or read book Portfolio Management Toward Optimal Consumption and Terminal Wealth written by Andrew Ellett and published by . This book was released on 2005 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Missing Data Methods written by David M. Drukker and published by Emerald Group Publishing. This book was released on 2011-11-30 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: Part of the "Advances in Econometrics" series, this title contains chapters covering topics such as: Missing-Data Imputation in Nonstationary Panel Data Models; Markov Switching Models in Empirical Finance; Bayesian Analysis of Multivariate Sample Selection Models Using Gaussian Copulas; and, Consistent Estimation and Orthogonality.

Download or read book Optimizing Dynamic Portfolio Selection written by Haleh Valian and published by . This book was released on 2009 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation, a control-theoretic decision model is proposed for an agent to "optimally" allocate and deploy its financial resources over time among a dynamically changing list of opportunities (e.g., financial assets), in an uncertain market environment. This control-theoretic approach is unique in the sense that it solves the problem at distinct time epochs over a finite time horizon. The solution is a sequence of actions with the objective of optimizing a reward function over that time horizon. While the above problem is quite general, we will focus solely on the problem of dynamic financial portfolio management. The dynamic portfolio model looks at the portfolio as a moving object to achieve a maximal expected utility for a given risk level and time horizon. We tackle this problem using Semi-Markov Decision Processes and develop an efficient solution methodology based on the Q-learning algorithm. The performance of the model is analyzed, and results from the model are compared to a known market index. The "optimal" portfolio management policy is then extended to configurations whereby only incomplete information is available. Furthermore, quality of information and its impact on the decision making process is assessed. Here the market environment is characterized by its volatility and price dynamics. The existence of other agents in the market place, who can act adversarial or collaborative, further complicates the underlying price dynamics. The complexity of interactions among different agents is an important challenge for the dynamic portfolio management problem. We fully examine this challenge using a game-theoretic approach to determine the optimal actions of non-price-taking agents with and without a debt constraint.

Download or read book A Dynamic Model of Active Portfolio Management and Mutual Fund Performance Evaluation written by Yonggan Zhao and published by . This book was released on 2005 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: We analyze an optimal dynamic portfolio and asset allocation policy for investors who are concerned with the performances of their portfolios relative to a benchmark. Assuming that asset returns follow a multi-linear factor model similar to the structure of Ross (1976) and that portfolio managers adopt a mean tracking error analysis similar to Roll (1992), we develop a dynamic model of active portfolio management maximizing risk adjusted excess return over a well-diversified benchmark. Unlike the case of constant proportional portfolios for the standard utility maximization, our optimal portfolio policy is state dependent, namely a function of time to investment horizon, the return on the benchmark portfolio, and the return on the investment portfolio itself. Based on the analysis in this paper, we define a dynamic performance measure which relates portfolio's return to its risk sensitivity. Abnormal returns at each point in time are quantified as the difference between the realized and the model-fitted returns. Risk sensitivity is estimated through a dynamic matching that minimizes the total fitted error of portfolio returns. We study portfolio performances for a sample of U.S. mutual funds with the data from January 2001 to December 2003. To limit biases in the selection of a benchmark for portfolio evaluation, we assume that the benchmark portfolio is the minimum variance portfolio composed of the Dow Jones Industrial Average index and the Nasdaq 100 index components. We find that majority of the mutual funds have substantially under-performed the chosen benchmark. Our model also implies an interesting relationship between performance indices and risk sensitivities. For the three year data, the empirical analysis shows that portfolio performance indices are related to their estimated risk sensitivities in an open-upward quadratic curve.

Download or read book Outperformance and Tracking written by Ali Al-Aradi and published by . This book was released on 2019 with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt: Portfolio management problems are often divided into two types: active and passive, where the objective is to outperform and track a preselected benchmark, respectively. Here, we formulate and solve a dynamic asset allocation problem that combines these two objectives in a unified framework. We look to maximize the expected growth rate differential between the wealth of the investor's portfolio and that of a performance benchmark while penalizing risk-weighted deviations from a given tracking portfolio. Using stochastic control techniques, we provide explicit closed-form expressions for the optimal allocation and we show how the optimal strategy can be related to the growth optimal portfolio. The admissible benchmarks encompass the class of functionally generated portfolios (FGPs), which include the market portfolio, as the only requirement is that they depend only on the prevailing asset values. Finally, some numerical experiments are presented to illustrate the risk-reward profile of the optimal allocation.

Download or read book Goals Based Wealth Management written by Jean L. P. Brunel and published by John Wiley & Sons. This book was released on 2015-02-20 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Take a more active role in strategic asset allocation Goals-Based Wealth Management is a manual for protecting and growing client wealth in a way that changes both the services and profitability of the firm. Written by a 35-year veteran of international wealth education and analysis, this informative guide explains a new approach to wealth management that allows individuals to take on a more active role in the allocation of their assets. Coverage includes a detailed examination of the goals-based approach, including what works and what needs to be revisited, and a clear, understandable model that allows advisors to help individuals to navigate complex processes. The companion website offers ancillary readings, practice management checklists, and assessments that help readers secure a deep understanding of the key ideas that make goals-based wealth management work. The goals-based wealth management approach was pioneered in 2002, but has seen a slow evolution and only modest refinements largely due to a lack of wide-scale adoption. This book takes the first steps toward finalizing the approach, by delineating the effective and ineffective aspects of traditional approaches, and proposing changes that could bring better value to practitioners and their clients. Understand the challenges faced by the affluent and wealthy Examine strategic asset allocation and investment policy formulation Learn a model for dealing with the asset allocation process Learn why the structure of the typical advisory firm needs to change High-net-worth individuals face very specific challenges. Goals-Based Wealth Management focuses on how those challenges can be overcome while adhering to their goals, incorporating constraints, and working within the individual's frame of reference to drive strategic allocation of their financial assets.

Download or read book Dynamic Portfolio Management Strategies written by Anthony Seymour and published by . This book was released on 2018 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt: The performance of dynamic trading and investment strategies can be difficult to predict. Although not without its problems, analysis of the historical performance of a strategy can provide valuable insight into its general risk and return properties. Furthermore, historical analysis allows one to compare variations of a strategy and examine the impact of various parameter choices and implementation rules. Dynamic strategy applications in three areas are considered, namely derivatives, asset allocation and equity factor portfolios. Firstly, the analysis of a strategy involving single-stock derivatives is examined in which call options on certain constituents of an index portfolio are sold as an alternative method of under-weighting the underlying. Secondly, the historical performance of an optimization-based asset allocation strategy is considered. The assumed aim of the strategy is to outperform a benchmark of CPI 5 via dynamic trading in a portfolio of domestic equities, bonds, property and cash, as well as international equities and bonds. Finally, the effects of portfolio construction on factor performance are studied via an historical analysis in which portfolios corresponding to a selection of fundamental factors are managed according to a range of weighting schemes, rebalance frequencies and portfolio sizes.

Download or read book Portfolio Selection written by Harry Markowitz and published by Yale University Press. This book was released on 2008-10-01 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: Embracing finance, economics, operations research, and computers, this book applies modern techniques of analysis and computation to find combinations of securities that best meet the needs of private or institutional investors.