327,534 research outputs found
A MODEL OF CONSTRUCTION OF A MINIMUM RISK PORTFOLIO BASED ON MARKOWITZ PORTFOLIO THEORY. APPLICATION ON BUCHAREST STOCK EXCHANGE
No full textIn this paper, the authors test a model of an efficient portfolio with minimum risk, starting from the analysis of one year portfolio payoff and risk of ten securities from Bucharest Stock Exchange. In accordance with the modern portfolio theory, maximization of returns at minimal risk should be the main objective of every investor. We show, using a mathematical methodology based on Markowitz portfolio theory and on Lagrange function, which is the exact amount of stocks to be purchased from a Bucharest Stock Exchange sample of securities in order to have an efficient portfolio with minimum risk at a given return.efficient portfolio, risk, return, Markowitz portfolio theory, Bucharest Stock Exchange
Aplicação da teoria de Markowitz em um plano de benefício definido – caso ELOS
No full textTCC (graduação) - Universidade Federal de Santa Catarina. Centro Sócio-Econômico. Economia.As Entidades Fechadas de Previdência Complementar vêm apresentando déficits crescentes desde 2010 até os dias atuais. Na prática, os déficits representam um grande problema para os Fundos de Pensão, pois estes não irão conseguir cumprir com o seu principal objetivo que é complementar a perda de renda ocasionada pela aposentadoria. Na literatura moderna há diversas teorias de otimização de carteiras que podem auxiliar os gestores da Fundação a minimizar estes impactos. O modelo escolhido foi o de Markowitz, já que é o primeiro a tratar de otimização de carteiras e é apresentado como o mais conhecido de otimização. Resumidamente, o modelo propõe encontrar a máxima rentabilidade média para um determinado nível de risco. O presente estudo visa avaliar a aplicabilidade do modelo de Markowitz em um Plano de Benefício Definido e consequentemente dar suporte ao gestor nas decisões. Foram utilizadas três estratégias e, todas tiveram resultados satisfatórios tanto em retorno absoluto quanto melhor relação risco/retorno
Prospect and Markowitz stochastic dominance
No full textProspect stochastic dominance, Markowitz stochastic dominance, Risk seeking, Risk averse, S-shaped utility function, Reverse S-shaped utility function, D81, C91,
Risk forecasting models and optimal portfolio selection.
No full textThis study analyses, from an investor's perspective, the performance of several risk forecasting models in obtaining optimal portfolios. The plausibility of the homoscedastic hypothesis implied in the classical Markowitz model is dicussed and more general models which take into account assymetry and time varying risk are analysed. Specifically, it studies whether ARCH-type based models obtain portfolios whose risk-adjusted returns exceed those of the classical Markowitz model. The same analysis is performed with models based on the Lower Partial Moment (LPM) which take into account the assymetry in the distribution of returns. The results suggest that none of the models achieve a clearly superior average performance. It is also found that models based on semivariance perform as well as those based on the variance, but not better than, even if the evaluation criterion is based on the Reward-to-Semivariance ratio. When attention turns to the analysis of worst case performance, the results are clearly different. Models which employ LPM with a high degree of risk aversion (n>2) as the risk measure are consistently superior to those which employ a symmetric measure, either homoscedastic or heteroscedastic.
Bayesian Portfolio Selection with Gaussian Mixture Returns
No full textMarkowitz portfolio selection is challenged by huge implementation barriers. This paper addresses the parameter uncertainty and deviation from normality in a Bayesian framework. The non-normal asset returns are modeled as finite Gaussian mixtures. Gibbs sampler is employed to obtain draws from the posterior predictive distribution of asset returns. Optimal portfolio weights are then constructed so as to maximize agents’ expected utility. Simple experiment suggests that our Bayesian portfolio selection procedure performs exceedingly well.portfolio selection; Gaussian mixtures; Bayesian
Teoría de Markowitz en portafolios del S&P 500
No full textThe objective of this article was to analyze Markowitz\u27s Theory to identify its impact on performance because investors require optimizing the balance between risk and return. Methodologically, the study used the type of basic research with a quantitative approach; in addition, a non-experimental design of a retrospective type and a descriptive and explanatory scope. Regarding the sample, the monthly historical price of the shares of the companies listed in the S&P 500 stock index was used, covering a period from January 2023 to August 2024 and processed through the Solver program. As findings, it was found that the efficient frontier was useful to identify portfolios with the same level of risk and different returns, the lower dispersion of data and the lower beta coefficient allowed to obtain a return higher than the risk. In this sense, it was concluded that Markowitz\u27s theory favorably affects the performance of a portfolio since it allowed to identify investment alternatives that simultaneously minimize risk and maximize return.En el presente artículo se propuso como objetivo analizar la Teoría de Markowitz para identificar su incidencia en el rendimiento debido a que los inversionistas requieren optimizar el equilibrio entre riesgo y rendimiento. Metodológicamente, el estudio empleó el tipo de investigación básica con enfoque cuantitativo; además, un diseño no experimental de tipo retrospectivo y un alcance descriptivo y explicativo. En cuanto a la muestra, se utilizó la cotización histórica mensual de las acciones de las empresas listadas en el índice bursátil S&P 500 abarcando un periodo comprendido entre enero del 2023 hasta agosto 2024 y procesados a través del programa Solver. Como hallazgos se encontró que la frontera eficiente fue útil para identificar portafolios con el mismo nivel de riesgo y rendimientos diferentes, la menor dispersión de datos y el menor coeficiente beta permitieron obtener un rendimiento superior al riesgo. En ese sentido, se concluyó que la teoría de Markowitz incide favorablemente en el rendimiento de un portafolio ya que permitió identificar alternativas de inversión que simultáneamente minimizan el riesgo y maximizan el rendimiento
Markowitz Models of Portfolio Selection: The Inverse Problem
No full textPredictions about investor portfolio holdings can provide powerful tests of asset pricing theories. In the context of Markowitz portfolio selection problem, this paper develops an algorithm which determines the structural parameters in both the investor's return-generating process and the utility function based upon the actual portfolio choices made by each investor. We refe
Decisão de investimento: uma proposta de adequação da teoria moderna de portfólio e Life Cycle Investing na previdência complementar
No full textDissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Sócio Econômico, Programa de Pós-Graduação em Administração, Florianópolis, 2013.O paradigma econômico mundial não é mais o mesmo desde a última crise financeira em 2008. Os prejuízos causados para a sociedade são inúmeros e refletem em todos os setores da economia mundial e nacional. Os impactos dessa crise foram enormes para o setor de previdência complementar, uma vez que as Entidades Fechadas de Previdência Complementar aplicam os recursos de seus participantes nos mercados financeiros. Esse contexto de mudanças e riscos aponta para um realinhamento equilibrado e diversificado das carteiras de investimento dos fundos de pensão brasileiros, no intuito de diminuir os riscos e maximizar os retornos. Em seu estudo, Portfolio Selection, Markowitz demonstra como os investidores devem aplicar seus recursos levando em conta a relação risco e retorno esperado. (Teoria Moderna de Portfólio). Enquanto a teoria de Markowitz trata da diversificação dos investimentos em uma carteira, os princípios de Life Cycle Investing propõe essa diversificação também ao longo do tempo. A junção do modelo de Markowitz com Life Cycle Investing demonstrou em seus testes que pode trazer benefícios para as Entidades Fechadas de Previdência Complementar, quando tratamos de seus investimentos. Por meio da análise de dados estatísticos do mercado financeiro brasileiro, juntamente com modelagem e simulações, demonstrou-se a eficácia do modelo proposto para os fundos de pensão brasileiros embasado na Teoria Moderna de Portfólio e os princípios de Life Cycle Investing. <br
Prospect and Markowitz Stochastic Dominance
No full textLevy and Levy (2002, 2004) develop the Prospect and Markowitz stochastic dominance theory with S-shaped and reverse S-shaped utility functions for investors. In this paper, we extend Levy and Levy's Prospect Stochastic Dominance theory (PSD) and Markowitz Stochastic Dominance theory (MSD) to the first three orders and link the corresponding S-shaped and reverse S-shaped utility functions to the first three orders. We also provide experiments to illustrate each case of the MSD and PSD to the first three orders and demonstrate that the higher order MSD and PSD cannot be replaced by the lower order MSD and PSD. Prospect theory has been regarded as a challenge to the expected utility paradigm. Levy and Levy (2002) prove that the second order PSD and MSD satisfy the expected utility paradigm. In our paper we take Levy and Levy's results one step further by showing that both PSD and MSD of any order are consistent with the expected utility paradigm. Furthermore, we formulate some other properties for the PSD and MSD including the hierarchy that exists in both PSD and MSD relationships; arbitrage opportunities that exist in the first orders of both PSD and MSD; and that for any two prospects under certain conditions, their third order MSD preference will be ???the opposite??? of or ???the same??? as their counterpart third order PSD preference. By extending Levy and Levy's work, we provide investors with more tools for empirical analysis, with which they can identify the first order PSD and MSD prospects and discern arbitrage opportunities that could increase his/her utility as well as wealth and set up a zero dollar portfolio to make huge profit. Our tools also enable investors to identify the third order PSD and MSD prospects and make better choices.Prospect stochastic dominance, Markowitz stochastic dominance, risk seeking, risk averse, S-shaped utility function, reverse S-shaped utility function
Robust Portfolio Optimization with a Hybrid Heuristic Algorithm
No full textEstimation errors in both the expected returns and the covariance matrix hamper the constructing of reliable portfolios within the Markowitz framework. Robust techniques that incorporate the uncertainty about the unknown parameters are suggested in the literature. We propose a modification as well as an extension of such a technique and compare both with another robust approach. In order to eliminate oversimplifications of Markowitz’ portfolio theory, we generalize the optimization framework to better emulate a more realistic investment environment. Because the adjusted optimization problem is no longer solvable with standard algorithms, we employ a hybrid heuristic to tackle this problem. Our empirical analysis is conducted with a moving time window for returns of the German stock index DAX100. The results of all three robust approaches yield more stable portfolio compositions than those of the original Markowitz framework. Moreover, the out-of-sample risk of the robust approaches is lower and less volatile while their returns are not necessarily smaller.Hybrid heuristic algorithm, Markowitz, Robust optimization, Uncertainty sets.
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