The Market Portfolio May Be Mean/Variance Efficient After All

2010 ◽  
Vol 23 (6) ◽  
pp. 2464-2491 ◽  
Author(s):  
Moshe Levy ◽  
Richard Roll
Keyword(s):  
Market Portfolio ◽  
Mean Variance

Stochastic Models for Actuarial Use: The Equilibrium Modelling of Local Markets

2009 ◽  
Vol 39 (1) ◽  
pp. 339-370 ◽  
Author(s):  
Robert J. Thomson ◽  
Dmitri V. Gott
Keyword(s):  
Local Market ◽  
Market Participants ◽  
Market Portfolio ◽  
One Year ◽  
The One ◽  
Mean Variance ◽  
Annual Time ◽  
Time Subject

AbstractIn this paper, a long-term equilibrium model of a local market is developed. Subject to minor qualifications, the model is arbitrage-free. The variables modelled are the prices of risk-free zero-coupon bonds – both index-linked and conventional – and of equities, as well as the inflation rate. The model is developed in discrete (nominally annual) time, but allowance is made for processes in continuous time subject to continuous rebalancing. It is based on a model of the market portfolio comprising all the above-mentioned asset categories. The risk-free asset is taken to be the one-year index-linked bond. It is assumed that, conditionally upon information at the beginning of a year, market participants have homogeneous expectations with regard to the forthcoming year and make their decisions in mean-variance space. For the purposes of illustration, a descriptive version of the model is developed with reference to UK data. The parameters produced by that process may be used to inform the determination of those required for the use of the model as a predictive model. Illustrative results of simulations of the model are given.

scholarly journals CAN INVESTMENT IN MICROFINANCE FUNDS IMPROVE RISK-RETURN CHARACTERISTICS OF A PORTFOLIO?

2014 ◽  
Vol 20 (4) ◽  
pp. 673-695 ◽  
Author(s):  
Karel Janda ◽  
Gordon Rausser ◽  
Barbora Svárovská
Keyword(s):  
Financial Indicators ◽  
Fixed Income ◽  
Socially Responsible ◽  
Investment Funds ◽  
Risk Return ◽  
Market Portfolio ◽  
Bond Portfolios ◽  
Capm Beta ◽  
Returns On Investment ◽  
Mean Variance

This article is concerned with contribution of microfinance investment funds to a sustainable financial portfolio. With regard to the dependence of microfinance funds’ returns on the performance of stock and fixed income markets in developed and emerging economies we find slightly negative correlation when measured by the portfolio beta measure. Our regression analysis confirms that returns on investment in microfinance investment funds exceed the returns on the market portfolio. This result together with reported near-to-zero beta estimates as a proxy for the systematic risk may be taken to be a clear financial advantage of an inclusion of microfinance assets in a portfolio compared to pure stock or bond portfolios. The results based on CAPM beta and Jensen's alpha are confirmed by mean-variance spanning test. We show that the socially responsible investors may invest into microfinance without sacrifice with respect to pure financial indicators.

scholarly journals Fundamental Indexes As Proxies For Mean-Variance Efficient Portfolios

2014 ◽  
Vol 30 (6) ◽  
pp. 1929
Author(s):  
Kathleen Hodnett ◽  
Geare Botes ◽  
Khumbudzo Daswa ◽  
Kimberly Davids ◽  
Emmanuel Che Fongwa ◽  
...  
Keyword(s):  
Firm Value ◽  
Efficient Frontier ◽  
Expected Returns ◽  
Market Capitalization ◽  
Weighted Index ◽  
Market Portfolio ◽  
Index Approach ◽  
Efficient Portfolios ◽  
Market Indexes ◽  
Mean Variance

Mean-variance efficiency was first explained by Markowitz (1952) who derived an efficient frontier comprised of portfolios with the highest expected returns for a given level of risk borne by the investor. The assumed mean-variance efficiency of the market portfolio along with the fact that it is capitalization-weighted underlies the rationale for market indexes being constructed by market capitalization weights (Mar, Bird, Casavecchia and Yeung, 2009). The pioneers of the fundamental index approach to investing, Arnott, Hsu and Moore (2005), however differ, and argue that market capitalization-weighted indexes are not mean-variance efficient due to their price-sensitivity, which leads to the overweighting of overvalued stocks and the underweighting of undervalued stocks, creating a return drag. The authors constructed an index weighted by fundamental determinants of firm value such as earnings, book value and revenue, proving that their fundamentally weighted index causes the return drag inherent in capitalization-weighted indexes to disappear. The aim of this paper is to discuss the evidence for and the arguments against fundamentally-weighted indexes as proxies for mean-variance efficient portfolios. We conclude that since the market cap-weighted index is only mean-variance efficient given the efficiency of the market, whilst the fundamental index incurs higher turnover, and may contain a value bias, its resistance to investor overreaction makes it a more valid mean-variance efficient proxy in an inefficient market.

Mean-Variance Analysis

2017 ◽  
Author(s):  
Kerry E. Back
Keyword(s):  
Global Minimum ◽  
Minimum Variance ◽  
Variance Analysis ◽  
Affine Function ◽  
Market Portfolio ◽  
Minimum Variance Portfolio ◽  
The Mean ◽  
Global Minimum Variance Portfolio ◽  
Mean Variance

The mean‐variance frontier is characterized with and without a risk‐free asset. The global minimum variance portfolio and tangency portfolio are defined, and two‐fund spanning is explained. The frontier is characterized in terms of the return defined from the SDF that is in the span of the assets. This is related to the Hansen‐Jagannathan bound. There is an SDF that is an affine function of a return if and only if the return is on the mean‐variance frontier. Separating distributions are defined and shown to imply two‐fund separation and mean‐variance efficiency of the market portfolio.

scholarly journals Second-Order Stochastic Dominance, Reward-Risk Portfolio Selection, and the CAPM

2008 ◽  
Vol 43 (2) ◽  
pp. 525-546 ◽  
Author(s):  
Enrico De Giorgi ◽  
Thierry Post
Keyword(s):  
Stock Returns ◽  
Portfolio Selection ◽  
Stochastic Dominance ◽  
Risk Model ◽  
Second Order ◽  
Order Stochastic Dominance ◽  
Market Portfolio ◽  
The Mean ◽  
Second Order Stochastic Dominance ◽  
Mean Variance

AbstractStarting from the reward-risk model for portfolio selection introduced in De Giorgi (2005), we derive the reward-risk Capital Asset Pricing Model (CAPM) analogously to the classical mean-variance CAPM. In contrast to the mean-variance model, reward-risk portfolio selection arises from an axiomatic definition of reward and risk measures based on a few basic principles, including consistency with second-order stochastic dominance. With complete markets, we show that at any financial market equilibrium, reward-risk investors' optimal allocations are comonotonic and, therefore, our model reduces to a representative investor model. Moreover, the pricing kernel is an explicitly given, non-increasing function of the market portfolio return, reflecting the representative investor's risk attitude. Finally, an empirical application shows that the reward-risk CAPM captures the cross section of U.S. stock returns better than the mean-variance CAPM does.

scholarly journals Técnicas Quantitativas de Otimização de Carteiras Aplicadas ao Mercado de Ações Brasileiro

2012 ◽  
Vol 10 (3) ◽  
pp. 369
Author(s):  
André Alves Portela Santos ◽  
Cristina Tessari
Keyword(s):  
Covariance Matrix ◽  
Minimum Variance ◽  
Short Selling ◽  
Optimization Techniques ◽  
Market Portfolio ◽  
Sample Covariance ◽  
Out Of Sample ◽  
Weighted Portfolio ◽  
Performance Statistics ◽  
Mean Variance

In this paper we assess the out-of-sample performance of two alternative quantitative portfolio optimization techniques - mean-variance and minimum variance optimization – and compare their performance with respect to a naive 1/N (or equally-weighted) portfolio and also to the market portfolio given by the Ibovespa. We focus on short selling-constrained portfolios and consider alternative estimators for the covariance matrices: sample covariance matrix, RiskMetrics, and three covariance estimators proposed by Ledoit and Wolf (2003), Ledoit and Wolf (2004a) and Ledoit and Wolf (2004b). Taking into account alternative portfolio re-balancing frequencies, we compute out-of-sample performance statistics which indicate that the quantitative approaches delivered improved results in terms of lower portfolio volatility and better risk-adjusted returns. Moreover, the use of more sophisticated estimators for the covariance matrix generated optimal portfolios with lower turnover over time.

AN ANALYTICAL FRAMEWORK FOR EXPLAINING RELATIVE PERFORMANCE OF CAPM BETA AND DOWNSIDE BETA

2009 ◽  
Vol 12 (03) ◽  
pp. 341-358 ◽  
Author(s):  
DON U. A. GALAGEDERA
Keyword(s):  
Risk Measures ◽  
Systematic Risk ◽  
Analytical Framework ◽  
Portfolio Returns ◽  
Market Portfolio ◽  
Empirical Performance ◽  
Capm Beta ◽  
Using Data ◽  
Risk Free Rate ◽  
Mean Variance

Even though investors' view of risk is generally regarded as related to the downside of the return distribution the CAPM beta is still a widely used measure of systematic risk. A number of studies compare the empirical performance of CAPM beta and downside beta in explaining the variation in portfolio returns and report mixed results. This paper provides a basis for explaining such mixed results. Using data generating processes in the mean-variance and mean-lower partial moment frameworks, analytical relationships between the CAPM beta and downside beta are derived. The derived relationships reveal that the association between the two systematic risk measures is to a great extent dependent on the volatility of the market portfolio returns and the deviation of the target rate from the risk-free rate. How the relationships derived here may be used in practice is demonstrated using empirical data.

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