Dynamic Asset Allocation Under Regime Switching. An In-sample and Out-of-sample Study Under the Copula-Opinion Pooling Framework PDF Download
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Author: Andrea Bartolucci
Publisher:
ISBN: 9783668367944
Category :
Languages : en
Pages :
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Author: Andrea Bartolucci
Publisher:
ISBN: 9783668367944
Category :
Languages : en
Pages :
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Author: Sarthak Garg
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ISBN:
Category :
Languages : en
Pages : 0
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The aim of this thesis is to develop a Markov Regime Switching framework that can be used in asset allocation in conjunction with Modern Portfolio Theory. Modern Portfolio Theory has long been a popular tool among big financial institutions. However, one of its major limitations is assumption of stationary market volatility. In this paper, we develop a single period Mean Variance Optimization model that minimizes the variance of a portfolio subject to a specified expected return by combining Modern Portfolio Theory with a Markov Regime Switching framework. Then, we extend the above developed framework to be used in conjunction with a robust optimization framework as proposed by Goldfarb Iyengar in which regards we were partially successful. The portfolios constructed by the Markov Regime-Switching framework were tested out of sample to outperform those suggested by a Simple MVO One Factor model and the Robust MVO One Factor Model.
Author: Huy Thanh Vo
Publisher:
ISBN:
Category :
Languages : en
Pages : 130
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Author: Ka-Chun Cheung
Publisher:
ISBN: 9781361203781
Category :
Languages : en
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This dissertation, "Optimal Asset Allocation Problems Under the Discrete-time Regime-switching Model" by Ka-chun, Cheung, 張家俊, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: 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-Switchingmodelcancapturetherealitythattheinvestmentenvironment 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 stochasticallymonotone, 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 mod- ern 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 analy- sis demonstrates that in the optimal portfolio problem context, the dependency structure between the default risks is essential and cannot be ignored. DOI: 10.5353/th_b3131123 Subjects: Asset allocation - Mathematical models Markov processes
Author: Massimo Guidolin
Publisher:
ISBN:
Category : Asset allocation
Languages : en
Pages : 33
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Author: Allan Timmermann
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ISBN:
Category :
Languages : en
Pages :
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This paper studies asset allocation decisions in the presence of regime switching in asset returns. We find evidence that four separate regimes - characterized as crash, slow growth, bull and recovery states - are required to capture the joint distribution of stock and bond returns. Optimal asset allocations vary considerably across these states and change over time as investors revise their estimates of the state probabilities. In the crash state, buy-and-hold investors allocate more of their portfolio to stocks the longer their investment horizon, while the optimal allocation to stocks declines as a function of the investment horizon in bull markets. The joint effects of learning about state probabilities and predictability of asset returns from the dividend yield give rise to a non-monotonic relationship between the investment horizon and the demand for stocks. Out-of-sample forecasting experiments confirm the economic importance of accounting for the presence of regimes in asset returns.
Author: Hening Liu
Publisher:
ISBN:
Category :
Languages : en
Pages : 40
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I examine a continuous-time intertemporal consumption and portfolio choice problem under ambiguity, where expected returns of a risky asset follow a hidden Markov chain. Investors with Chen and Epstein''s (2002) recursive multiple priors utility possess a set of priors for unobservable investment opportunities. We explicitly characterize optimal consumption and portfolio policies in terms of the Malliavin derivatives and stochastic integrals. When the model is calibrated to U.S. stock market data, I find that continuous Bayesian revisions under incomplete information generate ambiguity-driven hedging demands that mitigate intertemporal hedging demands. In addition, ambiguity aversion magnifies the importance of hedging demands in the optimal portfolio policies. Out-of-sample experiments demonstrate the economic importance of accounting for ambiguity.
Author: Long Kang
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ISBN:
Category :
Languages : en
Pages :
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We solve the asset allocation problem where investors choose to invest among risk-free assets, a passively managed index fund, and an actively managed fund. Asset allocation is based on the maximization of expected utility in a one-period time frame-work and the excess returns of two funds are modeled by a copula-GARCH model which captures most non-normal features of the data. Estimation risk of the copula-GARCH model is dealt with by a Bayesian approach where the posterior distributions of the parameters are drawn by the quot;Metropolis within Gibbsquot; algorithm. We apply our model to the quot;passive funds versus active fundsquot; problem with three asset categories-quot;large Capquot; funds, quot;small Capquot; funds and international stock funds, and test the models in an out-of-sample manner. Our results show significant percentage of holdings in the active fund with different risk levels of risk aversion for all the three asset groups. This implies that the actively managed funds do make a valuable contribution in the portfolio constructions for a wide range of investors. Secondly, with low risk version, the Bayesian copula model suggests very similar weights in the active fund as other classical models. However, with increasing risk aversion, the Bayesian model implies more conservative weights in the active fund. Moreover, in terms of realized returns and utilities, there is no sharp difference of performance between Bayesian and classical models as they all have some cases with the highest realized returns or utilities. However, as the risk aversion increases, the Bayesian model leads to significantly lower volatility of the realized out-of-sample returns and utilities.
Author: Giulia Dal Pra
Publisher:
ISBN:
Category :
Languages : en
Pages : 39
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We analyze the recursive, out-of-sample performance of asset allocation decisions based on financial ratio-predictability under single-state linear and regime-switching models. We adopt both a statistical perspective to analyze whether models based on the dividend-price, earning-price, and book-to-market ratios can forecast excess equity returns, and an economic approach that turns predictions into portfolio strategies. The strategies consist of a portfolio switching approach, a mean-variance framework, and a long-run dynamic model. We report an interesting disconnect between a statistical perspective, whereby the ratios yield a modest forecasting power, and a portfolio approach, by which a moderate predictability is occasionally sufficient to yield significant portfolio outperformance, especially before transaction costs and when regimes are taken into account. However, also when regimes are considered, predictability gives high payoffs only to long-horizon, highly risk-averse asset managers. Moreover, different strategies deliver different performance rankings across predictors. Finally, we find evidence inconsistent with the notion that increasing sophistication in the way portfolio decisions are modeled, delivers a superior performance.
Author: Alan O'Sullivan
Publisher:
ISBN:
Category : Business Theses
Languages : en
Pages : 0
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