The New Science of Asset Allocation

The New Science of Asset Allocation
Author: Thomas Schneeweis
Publisher: John Wiley & Sons
Total Pages: 422
Release: 2010-02-12
Genre: Business & Economics
ISBN: 0470608390

A feasible asset allocation framework for the post 2008 financial world Asset allocation has long been a cornerstone of prudent investment management; however, traditional allocation plans failed investors miserably in 2008. Asset allocation still remains an essential part of the investment arena, and through a new approach, you'll discover how to make it work. In The New Science of Asset Allocation, authors Thomas Schneeweis, Garry Crowder, and Hossein Kazemi first explore the myths that plague this field then quickly move on to examine how the practice of asset allocation has failed in recent years. They then propose new allocation models that employ liquidity, transparency, and real risk controls across multiple asset classes. Outlines a new approach to asset allocation in a post-2008 world, where risk seems hidden The "great manager" problem is examined with solutions on how to capture manager alpha while limiting downside risk A complete case study is presented that allocates for beta and alpha Written by an experienced team of industry leaders and academic experts, The New Science of Asset Allocation explains how you can effectively apply this approach to a financial world that continues to change.

Optimal Asset Allocation Problems Under the Discrete-time Regime-switching Model

Optimal Asset Allocation Problems Under the Discrete-time Regime-switching Model
Author:
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Release: 2005
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(Uncorrected OCR) Abstract of the thesis entitled OPTIMAL ASSET ALLOCATION PROBLEMS UNDER THE DISCRETE-TIME REGIME-SWITCHING MODEL submitted by Cheung, Ka Chun for the degree of Doctor of Philosophy at The University of Hong Kong in January 2005 Recently, academics and practitioners have started paying attention to using the Markov Regime-Switching process to model asset price dynamics. The Markov Regime-Switching model can capture the reality that the investment environment is changing over time and hence is non-stationary. Another merit of the model is that it can provide a reasonable degree of analytical tractability. In this thesis, the optimal behavior of an investor in a Markov regime-switching environment will be examined. The thesis studies the optimal dynamic asset allocation strategy, the optimal consumption strategy in the presence of default risk, and the optimal surrender strategy of an equity-linked investment product. By employing the concept of stochastic dominance and assuming that the transition matrix is stochastically monotone, where both the concept and assumption have natural and appealing financial interpretations, it was shown that the optimal behavior of the investor is consistent with our intuition. As default risk is an important subject in modern finance and actuarial science, this thesis also studies the optimal portfolio problem in which financial instruments are subject to dependent default risks. Sufficient condition to order the optimal allocations was obtained. The analysis demonstrates that in the optimal portfolio problem context, the dependency structure between the default risks is essential and cannot be ignored.

Dynamic Asset Allocation under Controlled Downside Risk

Dynamic Asset Allocation under Controlled Downside Risk
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This paper provides an analytical framework for dynamic portfolio strategies that are mean-variance efficient and subjected to a principal-guaranteed rate. Specifying a numeraire known as growth-optimal portfolio, we apply martingale method instead of dynamic programming approach to solve the optimal problem. Under the general assumptions of the price dynamics being a semi-martingale with finite expectation and variance, the efficient strategies are identified as a combination of put options on minimum norm portfolio and zero coupon bonds with the maturity of investment horizon. In the case of a single factor interest rate model, we derive the closed-form formula for optimal weights on securities. We conduct numerical simulations to illustrate the performance of the optimal strategies in the case of an economy comprising a stock index fund, a bond index fund and a money market account. In addition, for different investors with various interests like principal guaranted rate and investment horizon, we also show how investors ought to allocate their funds.

Multi-Period Trading Via Convex Optimization

Multi-Period Trading Via Convex Optimization
Author: Stephen Boyd
Publisher:
Total Pages: 92
Release: 2017-07-28
Genre: Mathematics
ISBN: 9781680833287

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.

Dynamic Asset Allocation Under VAR Constraint with Stochastic Interest Rates

Dynamic Asset Allocation Under VAR Constraint with Stochastic Interest Rates
Author: Donatien Hainaut
Publisher:
Total Pages: 20
Release: 2013
Genre:
ISBN:

This paper addresses the problem of dynamic asset allocation under a bounded shortfall risk in a market composed of three assets: cash, stocks and a zero coupon bond. The dynamics of the instantaneous short rates is driven by a Hull and White model. In this setting, we determine and compare optimal investment strategies maximizing the CRRA utility of terminal wealth with and without value at risk constraint.

A Practitioner's Guide to Asset Allocation

A Practitioner's Guide to Asset Allocation
Author: William Kinlaw
Publisher: John Wiley & Sons
Total Pages: 259
Release: 2017-05-02
Genre: Business & Economics
ISBN: 1119402425

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.