Download or read book Portfolio Optimization a Combined Regime switching and Black Litterman Model written by Edwin O. Fischer and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multi period Portfolio Optimization with Investor Views Under Regime Switching written by Razvan Gabriel Oprisor and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose a novel multi-period trading model that allows portfolio managers to perform optimal portfolio allocation while incorporating their interpretable investment views. This model's significant advantage is its incorporation of the latest asset return regimes to quantitatively solve managers' question: how certain should one be that a given investment view is occurring? First, we describe a framework for multi-period portfolio allocation formulated as a convex optimization problem that trades off expected return, risk and transaction costs. Second, we use the Black-Litterman model to combine investment views specified in a simple linear combination based format with the market portfolio. A data-driven method to adjust the confidence in the manager's views by comparing them to dynamically updated regime-switching forecasts is proposed. Our contribution is to incorporate both multi-period trading and interpretable investment views into one efficient framework and offer a novel method of using regime-switching to determine each view's confidence.
Download or read book Asset Allocation Using Regime Switching Methods written by Sarthak Garg and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Application of Regime Switching and Random Matrix Theory for Portfolio Optimization written by Javed Iqbal and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Optimal Portfolio Selection in a Regime Switching Model written by Xudong Zeng and published by . This book was released on 2006 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Regime Switching Factor Model for Mean Variance Optimization written by Giorgio Costa and published by . This book was released on 2020 with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt: We formulate a novel Markov regime-switching factor model to describe the cyclical nature of asset returns in modern financial markets. Maintaining a factor model structure allows us to easily derive the asset expected returns and their corresponding covariance matrix. By design, these two parameters are calibrated to better describe the properties of the different market regimes. In turn, these regime-dependent parameters serve as the inputs during mean-variance optimization, thereby constructing portfolios adapted to the current market environment. Through this formulation, the proposed model allows for the construction of large, realistic portfolios at no additional computational cost during optimization. Moreover, the viability of this model can be significantly improved by periodically re-balancing the portfolio, ensuring proper alignment between the estimated parameters and the transient market regimes. An out-of-sample computational experiment over a long investment horizon shows that the proposed regime-dependent portfolios are better aligned with the market environment, yielding a higher ex post rate of return and lower volatility than competing portfolios.
Download or read book Portfolio Optimization in the Financial Market with Regime Switching Under Constraints Transaction Costs and Different Rates for Borrowing and Lending written by Vladimir Dombrovskii and published by . This book was released on 2014 with total page 8 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this work, we consider the optimal portfolio selection problem under hard constraints on trading amounts, transaction costs and different rates for borrowing and lending when the dynamics of the risky asset returns are governed by a discrete-time approximation of the Markov-modulated geometric Brownian motion. The states of Markov chain are interpreted as the states of an economy. The problem is stated as a dynamic tracking problem of a reference portfolio with desired return. Our approach is tested on a set of a real data from Russian Stock Exchange MICEX.
Download or read book Multi Period Trading Via Convex Optimization written by Stephen Boyd and published by . This book was released on 2017-07-28 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph collects in one place the basic definitions, 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.
Download or read book Strategic Asset Allocation and Markov Regime Switch with GARCH Model written by Ph.D. Simi (Wei) and published by . This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Convex Duality in Constrained Mean variance Portfolio Optimization Under a Regime switching Model written by Catherine Donnelly and published by . This book was released on 2008 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, we solve a mean-variance portfolio optimization problem with portfolio constraints under a regime-switching model. Specifically, we seek a portfolio process which minimizes the variance of the terminal wealth, subject to a terminal wealth constraint and convex portfolio constraints. The regime-switching is modeled using a finite state space, continuous-time Markov chain and the market parameters are allowed to be random processes. The solution to this problem is of interest to investors in financial markets, such as pension funds, insurance companies and individuals. We establish the existence and characterization of the solution to the given problem using a convex duality method. We encode the constraints on the given problem as static penalty functions in order to derive the primal problem. Next, we synthesize the dual problem from the primal problem using convex conjugate functions. We show that the solution to the dual problem exists. From the construction of the dual problem, we find a set of necessary and sufficient conditions for the primal and dual problems to each have a solution. Using these conditions, we can show the existence of the solution to the given problem and characterize it in terms of the market parameters and the solution to the dual problem. The results of the thesis lay the foundation to find an actual solution to the given problem, by looking at specific examples. If we can find the solution to the dual problem for a specific example, then, using the characterization of the solution to the given problem, we may be able to find the actual solution to the specific example. In order to use the convex duality method, we have to prove a martingale representation theorem for processes which are locally square-integrable martingales with respect to the filtration generated by a Brownian motion and a finite state space, continuous-time Markov chain. This result may be of interest in problems involving regime-switching models which require a martingale representation theorem.
Download or read book Black Litterman Model for Continuous Distributions written by Jan Palczewski and published by . This book was released on 2018 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Black-Litterman methodology of portfolio optimization, developed at the turn of the 1990s, combines statistical information on asset returns with investor's views within the Markowitz mean-variance framework. The main assumption underlying the Black-Litterman model is that asset returns and investor's views are multivariate normally distributed. However, empirical research demonstrates that the distribution of asset returns has fat tails and is asymmetric, which contradicts normality. Recent advances in risk measurement advocate replacing the variance by risk measures that take account of tail behavior of the portfolio return distribution. This paper extends the Black-Litterman model into general continuous distributions and deviation measures of risk. Using ideas from the Black-Litterman methodology, we design numerical methods (with variance reduction techniques) for the inverse portfolio optimization that extracts statistical information from historical data in a stable way. We introduce a quantitative model for stating investor's views and blending them consistently with the market information. The theory is complemented by efficient numerical methods with the implementation distributed in the form of publicly available R packages. We conduct practical tests, which demonstrate significant impact of the choice of distributions on optimal portfolio weights to the extent that the classical Black-Litterman procedure cannot be viewed as an adequate approximation.
Download or read book Optimal Portfolio Choice Under Regime Switching Skew and Kurtosis Preferences written by Allan Timmermann and published by . This book was released on 2003 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper proposes a new tractable approach to solving multi-period asset allocation problems. We assume that investor preferences are defined over moments of the terminal wealth distribution such as its skew and kurtosis. Time-variations in investment opportunities are driven by a regime switching process that can capture bull and bear states. We develop analytical methods that only require solving a small set of difference equations and thus are very convenient to use. These methods are applied to a simple portfolio selection problem involving choosing between a stock index and a risk-free asset in the presence of bull and bear states in the return distribution. If the market is in a bear state, investors increase allocations to stocks the longer their time horizon. Conversely, in bull markets it is optimal for investors to decrease allocations to stocks the longer their investment horizon.
Download or read book Black Litterman Portfolio Optimization Model written by Jaka Gogala and published by . This book was released on 2010 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Application of Regime Switching Model to Equity Market and Portfolio Selection written by Zijian Yang and published by . This book was released on 2010 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multi Asset Portfolio Optimization and Out of Sample Performance written by Wolfgang Bessler and published by . This book was released on 2014 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Black-Litterman model aims to enhance asset allocation decisions by overcoming the problems of mean-variance portfolio optimization. We propose a sample based version of the Black-Litterman model and implement it on a multi-asset portfolio consisting of global stocks, bonds, and commodity indices, covering the period from January 1993 to December 2011. We test its out-of-sample performance relative to other asset allocation models and find that Black-Litterman optimized portfolios significantly outperform naïve-diversified portfolios (1/N-rule and strategic weights), and consistently perform better than mean-variance, Bayes-Stein, and minimum-variance strategies in terms of out-of-sample Sharpe ratios, even after controlling for different levels of risk aversion, investment constraints, and transaction costs. The BL model generates portfolios with lower risk, less extreme asset allocations, and higher diversification across asset classes. Sensitivity analyses indicate that these advantages are due to more stable mixed return estimates that incorporate the reliability of return predictions, smaller estimation errors, and lower turnover.
Download or read book Is Regime Switching in Stock Returns Important in Portfolio Decisions written by Jun Tu and published by . This book was released on 2013 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt: The stock market displays regime switching between upturns and downturns. This paper provides a Bayesian framework for making portfolio decisions that takes this regime switching into account, together with asset pricing model uncertainty and parameter uncertainty. The findings reveal that the economic value of accounting for regimes is substantially independent of whether or not model and parameter uncertainties are incorporated: the certainty-equivalent losses associated with ignoring regime switching are generally above 2% per year, and can be as high as 10%. These results suggest that the more realistic regime switching model is fundamentally different from the commonly used single-state model, and hence should be employed instead in portfolio decisions irrespective of concerns about model or parameter uncertainty.
Download or read book An Improvement of the Global Minimum Variance Portfolio Using a Black Litterman Approach written by Maximilian Adelmann and published by . This book was released on 2016 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: Asset management companies are constantly searching for portfolio optimization models that are on the one hand clear and intuitive and on the other provide high and reliable returns. This paper presents a modified version of the well-known Black-Litterman portfolio optimization approach. Unlike in the original model, the intuitive global minimum variance (GMV) portfolio serves as the reference portfolio. The introduction of a general rule for investors' views in combination with a simplification of the original Black-Litterman approach facilitates the implementation of the model and enables us to remove so-called dead assets from the GMV portfolio. As an additional advantageous feature our model is only based on variance-covariance estimations, and relative return estimations for our general rule. A numerical application of our modified Black-Litterman model to empirical data sets demonstrates that portfolios based on the model clearly outperform the GMV portfolio and the 1/N portfolio in terms of compound annual returns and out-of-sample Sharpe ratios.
