Inverse Problems In Portfolio Selection
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| Author | : Kaushiki Bhowmick |
| Publisher | : |
| Total Pages | : 116 |
| Release | : 2011 |
| Genre | : |
| ISBN | : |
A number of researchers have proposed several Bayesian methods for portfolio selection, which combine statistical information from financial time series with the prior beliefs of the portfolio manager, in an attempt to reduce the impact of estimation errors in distribution parameters on the portfolio selection process and the effect of these errors on the performance of 'optimal' portfolios in out-of-sample-data. This thesis seeks to reverse the direction of this process, inferring portfolio managers' probabilistic beliefs about future distributions based on the portfolios that they hold. We refer to the process of portfolio selection as the forward problem and the process of retrieving the implied probabilities, given an optimal portfolio, as the inverse problem. We attempt to solve the inverse problem in a general setting by using a finite set of scenarios. Using a discrete time framework, we can retrieve probabilities associated with each of the scenarios, which tells us the views of the portfolio manager implicit in the choice of a portfolio considered optimal. We conduct the implied views analysis for portfolios selected using expected utility maximization, where the investor's utility function is a globally non-optimal concave function, and in the mean-variance setting with the covariance matrix assumed to be given. We then use the models developed for inverse problem on empirical data to retrieve the implied views implicit in a given portfolio, and attempt to determine whether incorporating these views in portfolio selection improves portfolio performance out of sample.
| Author | : Leonard C. MacLean |
| Publisher | : World Scientific |
| Total Pages | : 941 |
| Release | : 2013 |
| Genre | : Business & Economics |
| ISBN | : 9814417351 |
This handbook in two parts covers key topics of the theory of financial decision making. Some of the papers discuss real applications or case studies as well. There are a number of new papers that have never been published before especially in Part II.Part I is concerned with Decision Making Under Uncertainty. This includes subsections on Arbitrage, Utility Theory, Risk Aversion and Static Portfolio Theory, and Stochastic Dominance. Part II is concerned with Dynamic Modeling that is the transition for static decision making to multiperiod decision making. The analysis starts with Risk Measures and then discusses Dynamic Portfolio Theory, Tactical Asset Allocation and Asset-Liability Management Using Utility and Goal Based Consumption-Investment Decision Models.A comprehensive set of problems both computational and review and mind expanding with many unsolved problems are in an accompanying problems book. The handbook plus the book of problems form a very strong set of materials for PhD and Masters courses both as the main or as supplementary text in finance theory, financial decision making and portfolio theory. For researchers, it is a valuable resource being an up to date treatment of topics in the classic books on these topics by Johnathan Ingersoll in 1988, and William Ziemba and Raymond Vickson in 1975 (updated 2 nd edition published in 2006).
| Author | : Seppo Pohjolainen |
| Publisher | : Springer |
| Total Pages | : 247 |
| Release | : 2016-07-14 |
| Genre | : Mathematics |
| ISBN | : 3319278363 |
This book provides a thorough introduction to the challenge of applying mathematics in real-world scenarios. Modelling tasks rarely involve well-defined categories, and they often require multidisciplinary input from mathematics, physics, computer sciences, or engineering. In keeping with this spirit of modelling, the book includes a wealth of cross-references between the chapters and frequently points to the real-world context. The book combines classical approaches to modelling with novel areas such as soft computing methods, inverse problems, and model uncertainty. Attention is also paid to the interaction between models, data and the use of mathematical software. The reader will find a broad selection of theoretical tools for practicing industrial mathematics, including the analysis of continuum models, probabilistic and discrete phenomena, and asymptotic and sensitivity analysis.
| Author | : Cheng-Few Lee |
| Publisher | : Elsevier |
| Total Pages | : 222 |
| Release | : 2001-02-02 |
| Genre | : Business & Economics |
| ISBN | : 9780762306589 |
- Desarrolla una metodología que permite compaginar la adquisición de los objetivos y el trabajo en competencias básicas. - Asume un compromiso con la educación en valores que se refleja en el tratamiento de los contenidos, de la ilustración y de las propuestas de trabajo. - Otorga un papel destacado a las nuevas tecnologías. - Favorece la adecuación de la exposición y la profundidad de los contenidos con el grado de maduración del alumnado. - Confiere a las ilustraciones un papel didáctico de primer orden. - Proporciona una rica oferta en actividades, tanto en el plano cuantitativo como en el cualitativo. - Ofrece materiales que fomentan la autoevaluación del alumnado.
| Author | : Dominick John Samperi |
| Publisher | : |
| Total Pages | : 610 |
| Release | : 1998 |
| Genre | : |
| ISBN | : |
We study an inverse problem from derivative security pricing theory in finance: on the basis of a finite number of observed option prices the problem is to hack out a consistent risk-neutralized diffusion price process for the underlying security. Each choice of volatility coefficient leads to a complete market model and consequently this inverse problem call be viewed as a model selection problem.
| Author | : Nicolas Chapados |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 107 |
| Release | : 2011-07-12 |
| Genre | : Computers |
| ISBN | : 1461405777 |
This brief offers a broad, yet concise, coverage of portfolio choice, containing both application-oriented and academic results, along with abundant pointers to the literature for further study. It cuts through many strands of the subject, presenting not only the classical results from financial economics but also approaches originating from information theory, machine learning and operations research. This compact treatment of the topic will be valuable to students entering the field, as well as practitioners looking for a broad coverage of the topic.
| Author | : Sigrid Källblad |
| Publisher | : |
| Total Pages | : 31 |
| Release | : 2016 |
| Genre | : |
| ISBN | : |
We consider the problem of optimal portfolio selection using forward investment and consumption criteria. Such criteria were introduced in and allow the investor to consider utility from both investment and consumption also when investing over unspecified or infinite horizons. Our focus is on criteria which satisfy a specific dynamic property in that their volatility component is identically zero. We provide an explicit characterization of those criteria and explicit formulae for the associated optimal investment and consumption strategies. We further show that an important class of criteria may be decomposed into a combination of pure forward investment and infinite horizon Merton criteria. Our second contribution is that we provide the solution to a specific inverse investment problem proposed by Black. While this result is of independent interest, it also allows us to obtain further results on the adaptedness of non-volatile forward criteria, and provides key insights on the relation between the notion of forward criteria and this inverse investment problem.
| Author | : Ahti Salo |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 410 |
| Release | : 2011-08-12 |
| Genre | : Business & Economics |
| ISBN | : 1441999434 |
Portfolio Decision Analysis: Improved Methods for Resource Allocation provides an extensive, up-to-date coverage of decision analytic methods which help firms and public organizations allocate resources to 'lumpy' investment opportunities while explicitly recognizing relevant financial and non-financial evaluation criteria and the presence of alternative investment opportunities. In particular, it discusses the evolution of these methods, presents new methodological advances and illustrates their use across several application domains. The book offers a many-faceted treatment of portfolio decision analysis (PDA). Among other things, it (i) synthesizes the state-of-play in PDA, (ii) describes novel methodologies, (iii) fosters the deployment of these methodologies, and (iv) contributes to the strengthening of research on PDA. Portfolio problems are widely regarded as the single most important application context of decision analysis, and, with its extensive and unique coverage of these problems, this book is a much-needed addition to the literature. The book also presents innovative treatments of new methodological approaches and their uses in applications. The intended audience consists of practitioners and researchers who wish to gain a good understanding of portfolio decision analysis and insights into how PDA methods can be leveraged in different application contexts. The book can also be employed in courses at the post-graduate level.
| Author | : Robert Dochow |
| Publisher | : Springer |
| Total Pages | : 207 |
| Release | : 2016-05-24 |
| Genre | : Business & Economics |
| ISBN | : 365813528X |
Robert Dochow mathematically derives a simplified classification structure of selected types of the portfolio selection problem. He proposes two new competitive online algorithms with risk management, which he evaluates analytically. The author empirically evaluates online algorithms by a comprehensive statistical analysis. Concrete results are that follow-the-loser algorithms show the most promising performance when the objective is the maximization of return on investment and risk-adjusted performance. In addition, when the objective is the minimization of risk, the two new algorithms with risk management show excellent performance. A prototype of a software tool for automated evaluation of algorithms for portfolio selection is given.
| Author | : Michael Zabarankin |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 254 |
| Release | : 2013-12-16 |
| Genre | : Business & Economics |
| ISBN | : 1461484715 |
Statistical Decision Problems presents a quick and concise introduction into the theory of risk, deviation and error measures that play a key role in statistical decision problems. It introduces state-of-the-art practical decision making through twenty-one case studies from real-life applications. The case studies cover a broad area of topics and the authors include links with source code and data, a very helpful tool for the reader. In its core, the text demonstrates how to use different factors to formulate statistical decision problems arising in various risk management applications, such as optimal hedging, portfolio optimization, cash flow matching, classification, and more. The presentation is organized into three parts: selected concepts of statistical decision theory, statistical decision problems, and case studies with portfolio safeguard. The text is primarily aimed at practitioners in the areas of risk management, decision making, and statistics. However, the inclusion of a fair bit of mathematical rigor renders this monograph an excellent introduction to the theory of general error, deviation, and risk measures for graduate students. It can be used as supplementary reading for graduate courses including statistical analysis, data mining, stochastic programming, financial engineering, to name a few. The high level of detail may serve useful to applied mathematicians, engineers, and statisticians interested in modeling and managing risk in various applications.
