A Bayesian Approach To Portfolio Analysis
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Portfolio Management under Stress
Author | : Riccardo Rebonato |
Publisher | : Cambridge University Press |
Total Pages | : 519 |
Release | : 2013 |
Genre | : Business & Economics |
ISBN | : 1107048117 |
A rigorous presentation of a novel methodology for asset allocation in financial portfolios under conditions of market distress.
A Bayesian Approach to Portfolio Selection and Revision
Author | : Robert L. Winkler |
Publisher | : |
Total Pages | : 39 |
Release | : 1973 |
Genre | : Investments |
ISBN | : |
Sequential Binary Investment Decisions
Author | : Werner Jammernegg |
Publisher | : Springer Science & Business Media |
Total Pages | : 167 |
Release | : 2012-12-06 |
Genre | : Business & Economics |
ISBN | : 364246646X |
This book describes some models from the theory of investment which are mainly characterized by three features. Firstly, the decision-maker acts in a dynamic environment. Secondly, the distributions of the random variables are only incompletely known at the beginning of the planning process. This is termed as decision-making under conditions of uncer tainty. Thirdly, in large parts of the work we restrict the analysis to binary decision models. In a binary model, the decision-maker must choose one of two actions. For example, one decision means to undertake the invest ·ment project in a planning period, whereas the other decision prescribes to postpone the project for at least one more period. The analysis of dynamic decision models under conditions of uncertainty is not a very common approach in economics. In this framework the op timal decisions are only obtained by the extensive use of methods from operations research and from statistics. It is the intention to narrow some of the existing gaps in the fields of investment and portfolio analysis in this respect. This is done by combining techniques that have been devel oped in investment theory and portfolio selection, in stochastic dynamic programming, and in Bayesian statistics. The latter field indicates the use of Bayes' theorem for the revision of the probability distributions of the random variables over time.
Modern Portfolio Optimization with NuOPTTM, S-PLUS®, and S+BayesTM
Author | : Bernd Scherer |
Publisher | : Springer Science & Business Media |
Total Pages | : 422 |
Release | : 2007-09-05 |
Genre | : Business & Economics |
ISBN | : 038727586X |
In recent years portfolio optimization and construction methodologies have become an increasingly critical ingredient of asset and fund management, while at the same time portfolio risk assessment has become an essential ingredient in risk management. This trend will only accelerate in the coming years. This practical handbook fills the gap between current university instruction and current industry practice. It provides a comprehensive computationally-oriented treatment of modern portfolio optimization and construction methods using the powerful NUOPT for S-PLUS optimizer.
Modern Portfolio Theory and Investment Analysis
Author | : Edwin J. Elton |
Publisher | : John Wiley & Sons |
Total Pages | : 754 |
Release | : 2014-01-21 |
Genre | : Business & Economics |
ISBN | : 1118469941 |
Modern Portfolio Theory and Investment Analysis, 9th Editionexamines the characteristics and analysis of individual securities, as well as the theory and practice of optimally combining securities into portfolios. It stresses the economic intuition behind the subject matter while presenting advanced concepts of investment analysis and portfolio management. The authors present material that captures the state of modern portfolio analysis, general equilibrium theory, and investment analysis in an accessible and intuitive manner.
Bayesian Methods in Finance
Author | : Svetlozar T. Rachev |
Publisher | : John Wiley & Sons |
Total Pages | : 351 |
Release | : 2008-02-13 |
Genre | : Business & Economics |
ISBN | : 0470249242 |
Bayesian Methods in Finance provides a detailed overview of the theory of Bayesian methods and explains their real-world applications to financial modeling. While the principles and concepts explained throughout the book can be used in financial modeling and decision making in general, the authors focus on portfolio management and market risk management—since these are the areas in finance where Bayesian methods have had the greatest penetration to date.
Bayesian Approach to Global Optimization
Author | : Jonas Mockus |
Publisher | : Springer Science & Business Media |
Total Pages | : 267 |
Release | : 2012-12-06 |
Genre | : Computers |
ISBN | : 9400909098 |
·Et moi ... si j'avait su comment en revcnir. One service mathematics has rendered the je o'y semis point alle.' human race. It has put common sense back Jules Verne where it beloogs. on the topmost shelf next to the dusty canister labelled 'discarded non The series is divergent; therefore we may be sense', able to do something with it. Eric T. BclI O. Heaviside Mathematics is a tool for thought. A highly necessary tool in a world where both feedback and non linearities abound. Similarly, all kinds of parts of mathematics serve as tools for other parts and for other sciences. Applying a simple rewriting rule to the quote on the right above one finds such statements as: 'One service topology has rendered mathematical physics ... '; 'One service logic has rendered com puter science .. .'; 'One service category theory has rendered mathematics .. .'. All arguably true. And all statements obtainable this way form part of the raison d'etre of this series.
Portfolio Decision Analysis
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.