Optimal Portfolio Modeling
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Optimal Portfolio Modeling
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Author : Philip McDonnell
language : en
Publisher: John Wiley & Sons
Release Date : 2008-05-02
Optimal Portfolio Modeling written by Philip McDonnell and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-05-02 with Business & Economics categories.
Optimal Portfolio Modeling is an easily accessible introduction to portfolio modeling for those who prefer an intuitive approach to this discipline. While early chapters provide engaging insights on the statistical properties of markets, this book quickly moves on to illustrate invaluable trading and risk control models based on popular programs such as Excel and the statistical modeling language R. This reliable resource presents modeling formulas that will allow you to effectively maximize the performance, minimize the drawdown, and manage the risk of your portfolio.
Optimal Portfolios
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Author : Ralf Korn
language : en
Publisher: World Scientific
Release Date : 1997
Optimal Portfolios written by Ralf Korn and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Business & Economics categories.
The focus of the book is the construction of optimal investment strategies in a security market model where the prices follow diffusion processes. It begins by presenting the complete Black-Scholes type model and then moves on to incomplete models and models including constraints and transaction costs. The models and methods presented will include the stochastic control method of Merton, the martingale method of Cox-Huang and Karatzas et al., the log optimal method of Cover and Jamshidian, the value-preserving model of Hellwig etc.
Robust Equity Portfolio Management
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Author : Woo Chang Kim
language : en
Publisher: John Wiley & Sons
Release Date : 2015-11-25
Robust Equity Portfolio Management written by Woo Chang Kim and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-25 with Business & Economics categories.
A comprehensive portfolio optimization guide, with provided MATLAB code Robust Equity Portfolio Management + Website offers the most comprehensive coverage available in this burgeoning field. Beginning with the fundamentals before moving into advanced techniques, this book provides useful coverage for both beginners and advanced readers. MATLAB code is provided to allow readers of all levels to begin implementing robust models immediately, with detailed explanations and applications in the equity market included to help you grasp the real-world use of each technique. The discussion includes the most up-to-date thinking and cutting-edge methods, including a much-needed alternative to the traditional Markowitz mean-variance model. Unparalleled in depth and breadth, this book is an invaluable reference for all risk managers, portfolio managers, and analysts. Portfolio construction models originating from the standard Markowitz mean-variance model have a high input sensitivity that threatens optimization, spawning a flurry of research into new analytic techniques. This book covers the latest developments along with the basics, to give you a truly comprehensive understanding backed by a robust, practical skill set. Get up to speed on the latest developments in portfolio optimization Implement robust models using provided MATLAB code Learn advanced optimization methods with equity portfolio applications Understand the formulations, performances, and properties of robust portfolios The Markowitz mean-variance model remains the standard framework for portfolio optimization, but the interest in—and need for—an alternative is rapidly increasing. Resolving the sensitivity issue and dramatically reducing portfolio risk is a major focus of today's portfolio manager. Robust Equity Portfolio Management + Website provides a viable alternative framework, and the hard skills to implement any optimization method.
Advanced Stochastic Models Risk Assessment And Portfolio Optimization
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Author : Svetlozar T. Rachev
language : en
Publisher: Wiley
Release Date : 2008-02-25
Advanced Stochastic Models Risk Assessment And Portfolio Optimization written by Svetlozar T. Rachev and has been published by Wiley this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-02-25 with Business & Economics categories.
This groundbreaking book extends traditional approaches of risk measurement and portfolio optimization by combining distributional models with risk or performance measures into one framework. Throughout these pages, the expert authors explain the fundamentals of probability metrics, outline new approaches to portfolio optimization, and discuss a variety of essential risk measures. Using numerous examples, they illustrate a range of applications to optimal portfolio choice and risk theory, as well as applications to the area of computational finance that may be useful to financial engineers.
Financial Risk Modelling And Portfolio Optimization With R
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Author : Bernhard Pfaff
language : en
Publisher: John Wiley & Sons
Release Date : 2016-08-16
Financial Risk Modelling And Portfolio Optimization With R written by Bernhard Pfaff and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-16 with Mathematics categories.
Financial Risk Modelling and Portfolio Optimization with R, 2nd Edition Bernhard Pfaff, Invesco Global Asset Allocation, Germany A must have text for risk modelling and portfolio optimization using R. This book introduces the latest techniques advocated for measuring financial market risk and portfolio optimization, and provides a plethora of R code examples that enable the reader to replicate the results featured throughout the book. This edition has been extensively revised to include new topics on risk surfaces and probabilistic utility optimization as well as an extended introduction to R language. Financial Risk Modelling and Portfolio Optimization with R: Demonstrates techniques in modelling financial risks and applying portfolio optimization techniques as well as recent advances in the field. Introduces stylized facts, loss function and risk measures, conditional and unconditional modelling of risk; extreme value theory, generalized hyperbolic distribution, volatility modelling and concepts for capturing dependencies. Explores portfolio risk concepts and optimization with risk constraints. Is accompanied by a supporting website featuring examples and case studies in R. Includes updated list of R packages for enabling the reader to replicate the results in the book. Graduate and postgraduate students in finance, economics, risk management as well as practitioners in finance and portfolio optimization will find this book beneficial. It also serves well as an accompanying text in computer-lab classes and is therefore suitable for self-study.
Robust Portfolio Optimization And Management
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Author : Frank J. Fabozzi
language : en
Publisher: John Wiley & Sons
Release Date : 2007-04-27
Robust Portfolio Optimization And Management written by Frank J. Fabozzi and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-04-27 with Business & Economics categories.
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
Linear And Mixed Integer Programming For Portfolio Optimization
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Author : Renata Mansini
language : en
Publisher: Springer
Release Date : 2015-06-10
Linear And Mixed Integer Programming For Portfolio Optimization written by Renata Mansini and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-10 with Business & Economics categories.
This book presents solutions to the general problem of single period portfolio optimization. It introduces different linear models, arising from different performance measures, and the mixed integer linear models resulting from the introduction of real features. Other linear models, such as models for portfolio rebalancing and index tracking, are also covered. The book discusses computational issues and provides a theoretical framework, including the concepts of risk-averse preferences, stochastic dominance and coherent risk measures. The material is presented in a style that requires no background in finance or in portfolio optimization; some experience in linear and mixed integer models, however, is required. The book is thoroughly didactic, supplementing the concepts with comments and illustrative examples.
Statistical And Algorithm Aspects Of Optimal Portfolios
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Author : Howard Howan Stephen Shek
language : en
Publisher: Stanford University
Release Date : 2011
Statistical And Algorithm Aspects Of Optimal Portfolios written by Howard Howan Stephen Shek and has been published by Stanford University this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.
We address three key aspects of optimal portfolio construction: expected return, variance-covariance modeling and optimization in presence of cardinality constraints. On expected return modeling, we extend the self-excited point process framework to model conditional arrival intensities of bid and ask side market orders of listed stocks. The cross-excitation of market orders is modeled explicitly such that the ask side market order size and bid side probability weighted order book cumulative volume can affect the ask side order intensity, and vice versa. Different variations of the framework are estimated by using method of maximum likelihood estimation, based on a recursive application of the log-likelihood functions derived in this thesis. Results indicate that the self-excited point process framework is able to capture a significant amount of the underlying trading dynamics of market orders, both in-sample and out-of-sample. A new framework is introduced, Realized GARCH, for the joint modeling of returns and realized measures of volatility. A key feature is a measurement equation that relates the realized measure to the conditional variance of returns. The measurement equation facilitates a simple modeling of the dependence between returns and future volatility. Realized GARCH models with a linear or log-linear specification have many attractive features. They are parsimonious, simple to estimate, and imply an ARMA structure for the conditional variance and the realized measure. An empirical application with DJIA stocks and an exchange traded index fund shows that a simple Realized GARCH structure leads to substantial improvements in the empirical fit over standard GARCH models. Finally we describe a novel algorithm to obtain the solution of the optimal portfolio problem with NP-hard cardinality constraints. The algorithm is based on a local relaxation that exploits the inherent structure of the objective function. It solves a sequence of small, local, quadratic-programs by first projecting asset returns onto a reduced metric space, followed by clustering in this space to identify sub-groups of assets that best accentuate a suitable measure of similarity amongst different assets. The algorithm can either be cold started using the centroids of initial clusters or be warm started based on the output of a previous result. Empirical result, using baskets of up to 3,000 stocks and with different cardinality constraints, indicates that the algorithm is able to achieve significant performance gain over a sophisticated branch-and-cut method. One key application of this local relaxation algorithm is in dealing with large scale cardinality constrained portfolio optimization under tight time constraint, such as for the purpose of index tracking or index arbitrage at high frequency.
Construction Of Dynamic Portfolio Modeling Based On Order Impact Coefficient And Its Empirical Analysis
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Author : Li Chenggang
language : en
Publisher:
Release Date : 2015
Construction Of Dynamic Portfolio Modeling Based On Order Impact Coefficient And Its Empirical Analysis written by Li Chenggang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
The fund flow reflects investors' choosing stocks, and contains investors' trading information. Order flow is one of core variables of financial market microstructure theory, and it can characterize the fund flow. In order to capture the information of the fund flow, this paper introduces order flow indicator to measure net inflows, and puts forward order impact coefficient to characterize fund inflow and its change rate. From the perspective of investors' expected utility maximization, this paper determines portfolio weight according to order impact coefficient, and constructs the dynamic portfolio model with order impact coefficient. Using the optimization theory and methods, by constructing Lagrange function, this paper gains the optimal portfolio weights of the dynamic portfolio model. This paper arbitrarily selects weekly data of six stocks listed on Chinese Shenzhen Stock Exchange to do an empirical analysis. The empirical results show that weekly return of dynamic portfolio based on order impact coefficient is higher than both mean-variance portfolio return and Shenzhen composite index return. Accumulative return of dynamic portfolio based on order impact coefficient is higher than the latter two by 8.47% and 11.46% respectively. This indicates that the dynamic portfolio model based on order impact coefficient can obtain better investment return.
Applications Of Optimal Portfolio Management
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Author : Dimitrios Bisias
language : en
Publisher:
Release Date : 2015
Applications Of Optimal Portfolio Management written by Dimitrios Bisias and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
This thesis revolves around applications of optimal portfolio theory. In the first essay, we study the optimal portfolio allocation among convergence trades and mean reversion trading strategies for a risk averse investor who faces Value-at-Risk and collateral constraints with and without fear of model misspecification. We investigate the properties of the optimal trading strategy, when the investor fully trusts his model dynamics. Subsequently, we investigate how the optimal trading strategy of the investor changes when he mistrusts the model. In particular, we assume that the investor believes that the data will come from an unknown member of a set of unspecified alternative models near his approximating model. The investor believes that his model is a pretty good approximation in the sense that the relative entropy of the alternative models with respect to his nominal model is small. Concern about model misspecification leads the investor to choose a robust optimal portfolio allocation that works well over that set of alternative models. In the second essay, we study how portfolio theory can be used as a framework for making biomedical funding allocation decisions focusing on the National Institutes of Health (NIH). Prioritizing research efforts is analogous to managing an investment portfolio. In both cases, there are competing opportunities to invest limited resources, and expected returns, risk, correlations, and the cost of lost opportunities are important factors in determining the return of those investments. Can we apply portfolio theory as a systematic framework of making biomedical funding allocation decisions? Does NIH manage its research risk in an efficient way? What are the challenges and limitations of portfolio theory as a way of making biomedical funding allocation decisions? Finally in the third essay, we investigate how risk constraints in portfolio optimization and fear of model misspecification affect the statistical properties of the market returns. Risk sensitive regulation has become the cornerstone of international financial regulations. How does this kind of regulation affect the statistical properties of the financial market? Does it affect the risk premium of the market? What about the volatility or the liquidity of the market?