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Author: Ph.D. Simi (Wei) Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
During the financial crisis of 2008, the S&P 500 Implied Volatility Index (VIX), known as the “fear gauge”, jumped to 80% of the highest level it has ever reached. Portfolio managers faced tremendous pressures in these environments of such high levels market volatility. Because it is well known that asset allocation dominates portfolio performances, this paper focuses on asset allocation strategies. It develops a strategic asset allocation solution for portfolio management under all conditions and at all levels of market volatility. The approach is to derive a dynamic optimal portfolio that is based on the well-known asset allocation Black-Litterman [1991, 1992] framework. In addition, this paper proposes a methodology that considers the features of volatility regime-switching over time. This new strategic framework allows portfolio managers to derive a systematically optimal portfolio in a timely, accurate fashion.
Author: Ph.D. Simi (Wei) Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
During the financial crisis of 2008, the S&P 500 Implied Volatility Index (VIX), known as the “fear gauge”, jumped to 80% of the highest level it has ever reached. Portfolio managers faced tremendous pressures in these environments of such high levels market volatility. Because it is well known that asset allocation dominates portfolio performances, this paper focuses on asset allocation strategies. It develops a strategic asset allocation solution for portfolio management under all conditions and at all levels of market volatility. The approach is to derive a dynamic optimal portfolio that is based on the well-known asset allocation Black-Litterman [1991, 1992] framework. In addition, this paper proposes a methodology that considers the features of volatility regime-switching over time. This new strategic framework allows portfolio managers to derive a systematically optimal portfolio in a timely, accurate fashion.
Author: Sarthak Garg Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
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: Ka-Chun Cheung Publisher: ISBN: 9781361203781 Category : Languages : en Pages :
Book Description
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: Tristan Gardner Wisner Publisher: ISBN: Category : Languages : en Pages : 45
Book Description
The objective of this paper is to implement and test the multivariate regime-switching GARCH model as a potential improvement on traditional methods for estimating the covariance matrix for multiple time series. I describe the characteristics and estimation of the primary model of interest, MS-GARCH, and some competitor models. I implement and backtest a portfolio management strategy based on risk minimization using MS-GARCH forecasts and evaluate performance relative to competitors. I find MS-GARCH to be an useful tool in portfolio construction, and to offer some significant advantages over more traditional models in terms of accuracy and interpretability when describing a process.
Author: Donatien Hainaut Publisher: ISBN: Category : Languages : en Pages : 19
Book Description
This paper revisits the problem of the strategic asset allocation between stocks and bonds. The novelty of our approach is to model the influence of economic cycles on the marginal distributions of asset returns and their dependence structure by a single hidden Markov chain. After a brief review of selected statistical distributions (Student't and Weibull) and copulas (elliptic and Archimedian), we describe how the switching regime model is calibrated using two indices: the CAC 40 for stocks and the SGI Bond 10 years, for bonds. We then propose a dynamic investment policy based on the estimated probabilities of sojourn in each state of the Markov chain. Even though the Markov chain ruling the assets dynamics is hidden, a Bayesian procedure can be used to infer the probabilities of being in a certain state of the economy. The asset allocation can then adapted to provide the highest yield given the most likely state. Having calibrated and estimated the parameters of the model, the performance of static and dynamic strategies are compared by conducting Monte Carlo simulations. Our results show that dynamic strategies, which exploit the additional information relating the probable regime state, perform better than static policies with a limited risk and an acceptable number of reallocations.
Author: Monica Billio Publisher: ISBN: Category : Languages : en Pages : 31
Book Description
A new Bayesian multi-chain Markov Switching GARCH model for dynamic hedging in energy futures markets is developed by constructing a system of simultaneous equations for the return dynamics on the hedged portfolio and futures. More specifically, both the mean and variance of the hedged portfolio are assumed to be governed by two unobserved discrete state processes, while the futures dynamics is driven by a univariate hidden state process. The noise in both processes are characterized by a MS-GARCH model. This formulation has two main practical and conceptual advantages. First, the different states of the discrete processes can be identified as different volatility regimes. Secondly, the parameters can be easily interpreted as different hedging components. Our formulation also provides an avenue to analyze the contribution of the volatility dynamics and state probabilities to the optimal hedge ratio at each point in time. Moreover, the combination of the expected utility framework with regime-switching models allows the definition of a robust minimum variance hedging strategy to also account for parameter uncertainty. Evidence of changes in the optimal hedging strategies before and after the financial crisis is found when the proposed robust hedging strategy is applied to crude oil spot and futures markets.
Author: Xiaojing Xi Publisher: ISBN: Category : Languages : en Pages :
Book Description
We consider a higher-order hidden Markov models (HMM), also called weak HMM (WHMM), to capture the regime-switching and memory properties of financial time series. A technique of transforming a WHMM into a regular HMM is employed, which in turn enables the development of recursive filters. With the use of the change of reference probability measure methodology and EM algorithm, a dynamic estimation of model parameters is obtained. Several applications and extensions were investigated. WHMM is adopted in describing the evolution of asset prices and its performance is examined through a forecasting analysis. This is extended to the case when the drift and volatility components of the logreturns are modulated by two independent WHMMs that are not necessarily having the same number of states. Numerical experiment is conducted based on simulated data to demonstrate the ability of our estimation approach in recovering the true model parameters. The analogue of recursive filtering and parameter estimation to handle multivariate data is also established. Some aspects of statistical inference arising from model implementation such as the assessment of model adequacy and goodness of fit are examined and addressed. The usefulness of the WHMM framework is tested on an asset allocation problem whereby investors determine the optimal investment strategy for the next time step through the results of the algorithm procedure. As an application in the modelling of yield curves, it is shown that the WHMM, with its memory-capturing mechanism, outperforms the usual HMM. A mean-reverting interest rate model is further developed whereby its parameters are modulated by a WHMM along with the formulation of a self-tuning parameter estimation. Finally, we propose an inverse Stieltjes moment approach to solve the inverse problem of calibration inherent in an HMM-based regime-switching set-up.
Author: Tata Subba Rao Publisher: Elsevier ISBN: 0444538585 Category : Mathematics Languages : en Pages : 778
Book Description
'Handbook of Statistics' is a series of self-contained reference books. Each volume is devoted to a particular topic in statistics, with volume 30 dealing with time series.
Author: Ph.D. Simi (Wei)
Author: Ph.D. Simi (Wei)
Author: Sarthak Garg
Author: Ka-Chun Cheung
Author: Tristan Gardner Wisner
Author: Donatien Hainaut
Author: Monica Billio
Author: Xiaojing Xi
Author: Stephen E. Satchell
Author: Tata Subba Rao
Author: