Mean-variance analysis

Çalışmanın ilk bölümünde, portföy​ seçiminde önemli iki faktör olan Beklenen Getiri ve Risk değerleri incelenmiştir. İkinci bölümünde, portföy riskinin dağıtılmasında Geleneksel Portföy Yönetimi Yaklaşımı ve Modern Portföy Teorisi sözel ve matematiksel olarak ifade edilmekle beraber Modern Portföy Teorisinin riskin dağıtılmasındaki üstünlüğü vurgulanmıştır. Üçüncü ve son bölümde uygulamaya geçilmiştir. Uygulama bölümünün ilk yarısında Borsa İstanbul'da işlem gören çimento sektöründeki firmaların günlük kapanış fiyatlarıyla Excel Programı kullanılarak her bir hisse senedinin Yıllık Beklenen Getiri ve Risk Oranları hesaplanmıştır. Elde edilen veriler, Harry Markowitz tarafından ileri sürülen varlıklara ait getiri oranları arasındaki kovaryans ve/veya korelasyon katsayılarının yorumlandığı Ortalama-Varyans Yaklaşımı üzerinden değerlendirilmiş ve portföyü oluşturacak hisse senetleri belirlenmiştir. Belirlenen hisse senetlerinin farklı oranlarda bir araya getirilmesi ile meydana gelen portföyler arasından belirli bir risk oranında en yüksek getiriye sahip portföyler Markowitz Etkinlik Sınırını oluşturmaktadır. Seçilen hisse senetlerine ait veriler ile MATLAB Programında Markowitz Etkinlik Sınırı elde edilmiştir. Çalışmanın uygulama bölümünün diğer yarısında Ağırlıklı Ortalama Mevduat Faiz Oranları verilerinden TÜFE Enflasyon Oranları çıkarılarak Reel faiz oranları elde edildikten sonra Vadeli Mevduat Yatırımına ait Yıllık Beklenen Getiri ve Risk Oranları hesaplanmıştır.  Elde edilen veriler alternatif yatırım fonksiyonu olarak daha önce çimento sektöründeki firmalara ait hisse senetlerinden elde edilen Markowitz Etkinlik Sınırı ile aynı Beklenen Getiri - Risk grafiğinde işaretlenerek iki yatırım seçeneği arasında kıyaslama yapılmıştır.

Mean-variance analysis in the form of risk programming has a long, productive history in agricultural economics research. And risk programming continues to be used despite well known theoretical results that choices based on mean-variance analysis are not consistent with choices based on expected utility maximization. This paper demonstrates that the multivariate distribution of returns used in risk programming must be elliptically symmetric in order for mean-variance analysis to be consistent with expected utility choices. Then a statistical test for elliptical symmetry is developed and demonstrated. This test enables researchers to determine when data will produce significant differences between risk programming choices and expected utility choices.

The main goal of investors is to minimize risk at any point of a given returns or/and maximize returns at any given risk. Asset allocation involves allotting investments among different assets. Optimal asset allocation minimizes risk of portfolio to the barest level and maximizes returns better. The aim of this paper is to investigate the two asset allocations; Black Litterman model (BLM) and Mean Variance model (MVM) and examine the model that minimizes risk better and maximizes return optimally. The data used are monthly data of groundnut oil, palm oil and palm kernel. The study shows that the BLM minimizes risk of portfolio better and maximizes return optimally than MVM.

With globalization, an understanding of country risk (political risk (PR), financial risk (FR), and economic risk (ER)) and its impact on stock market return volatility and predictability is important for evaluating direct investment and country selection decisions in globally and regionally ...

This paper studies an application of a Darwinian theory of portfolio selection to stocks listed in the Dow Jones Industrial Average (DJIA). We analyze numerically the long-run outcome of the competition of fix-mix portfolio rules in a stock market with actual DJIA dividends. In the model seemingly rational strategies can do very poorly against seemingly irrational strategies. Moreover, the interaction of strategies can lead to stochastic time series of asset prices that do not converge. The simulations also show that the evolutionary portfolio rule dis

Mean-variance analysis in the form of risk programming has a long, productive history in agricultural economics research. And risk programming continues to be used despite well known theoretical results that choices based on mean-variance analysis are not consistent with choices based on expected utility maximization. This paper demonstrates that the multivariate distribution of returns used in risk programming must be elliptically symmetric in order for mean-variance analysis to be consistent with expected utility choices. Then a statistical test for elliptical symmetry is developed and demonstrated. This test enables researchers to determine when data will produce significant differences between risk programming choices and expected utility choices.

In this chapter we introduce the theory and the application of the computer program of modern portfolio theory. The notion of diversification is age-old: “don’t put your eggs in one basket,” obviously predates economic theory. However, a formal model showing how to make the most of the power of diversification was not devised until 1952, a feat for which Harry Markowitz eventually won the Nobel Prize in economics. Markowitz portfolio shows that as you add assets to an investment portfolio the total risk of that portfolio – as measured by the variance (or standard deviation) of total return – declines continuously, but the expected return of the portfolio is a weighted average of the expected returns of the individual assets. In other words, by investing in portfolios rather than in individual assets, investors could lower the total risk of investing without sacrificing return. In the second part we introduce the mean–variance spanning test that follows directly from the portfolio optimization problem.

This paper generalizes the notion of mean-variance spanning as de- ned in the seminal paper of Huberman & Kandel (1987) in three di- mensions.It is shown how regression techniques can be used to test for spanning for more general classes of utility functions, in case some as- sets are nontraded, and in case some of the assets are zero-investment securities such as futures contracts.We then implement these tech- niques to test whether a basic set of three international stock indices, the S&P 500, the FAZ (Germany), and the FTSE (UK), span a set of commodity and currency futures contracts.Depending on whether mean-variance, logarithmic, or power utility functions are considered, the hypothesis of spanning can be rejected for most futures contracts considered.If an investor has a position in a nontraded commodity, then the hypothesis of spanning can almost always be rejected for fu- tures contracts on that commodity for all utility functions considered.For currency futures this is only...

This paper compares two different types of annuity providers, i.e. defined benefit pension funds and life insurance companies. One of the key differences is that the residual risk in pension funds is collectively borne by the beneficiaries and the sponsor while in the case of life insurers, it is borne by the external shareholders. This paper employs a contingent claim

The major concentration of this study is to describe the structure of a C++/MEX solution for robust detection and delineation of arterial blood pressure (ABP) signal events. Toward this objective, the original ABP signal was pre-processed by application of à trous discrete wavelet transform (DWT) to extract several dyadic scales. Then, a sliding window with fixed length was moved on the appropriately selected scale. In each slid, mean, variance, Skewness and Kurtosis values of the excerpted segment were superimposed to generate a newly defined multiple higher order moments (MHOM) metric to be used as the detection decision statistic (DS). Then, after application of an adaptive-nonlinear transformation for making the DS baseline static, the histogram parameters of the enhanced DS were used for regulation of the α-level Neyman–Pearson classifier aimed for false alarm probability (FAP)-bounded delineation of the ABP events. The proposed method was applied to all 18 subjects of the MIT-...

This paper introduces a new technique to solve financial allocation in Distribution System Expansion Planning (DSEP) problem. The proposed technique will be formulated by using mean-variance analysis (MVA) approach in the form of mixed-integer programming (MIP) problem. It consist the hybridization of Hopfield Neural Network (HNN) and Boltzmann Machine (BM) in first and second phase respectively. During the execution at the first phase, this model will select the feasible units meanwhile the second phase will restructured until it finds the best solution from all the feasible solution. Due to this feature, the proposed model has a fast convergence and the accuracy of the obtained solution. This model can help planners in decision-making process since the solutions provide a better allocation of limited financial resources and offer the planners with the flexibility to apply different options to increase the profit. 1. INTRODUCTION As per present, scenario demand of electric power generation is increasing. Due to the increasing demands, several power supply failures might cause major social losses. Failures are caused by many factors such as type, design, weather condition or geographical location. The distribution system is the most extensive part of the electrical system, and consequently, it is the mainly responsible for energy losses [1-3]. Thus, a meticulous distribution system expansion planning (DSEP) must be provided to supply reliable electricity to consumers. Power system planning is defined as a process of determining a minimum cost strategy for long-range expansion of the generation, transmission and distribution systems so that it is sufficient enough to supply the load forecast within a set of technical, economic and political constraint [4]. As for DSEP, the goal is to fulfill electricity load increment at the lowermost cost and consumer's reliability desires with a level of satisfaction [5]. One of the important factors in the DSEP is included with well-calculated or analyzed investment planning that allowed by the planners. The planners plan a strategic decision related to a whole power system network and also particular individual simultaneously. Nevertheless, planners faced a problem in deciding on how much a portfolio to allocate to the different type of assets. In this case, financial allocation plays a crucial role in solving the planner's problem. Its aim is to balance risk and reward by apportioning a portfolio asset according to an individual goals, risk tolerance and investment horizon [6, 7]. In real situations, financial allocation problems are complicated and non-linear programming problem which is hard to solve. One of the ways of tackling this problem is by using the artificial neural network (ANN) since it is a useful

This paper tests whether hedging currency risk improves the performance of international stock portfolios. We use a generalized performance measure which allows for investor-dependencies such as different utility functions and the presence of nontraded risks. In addition we show that an auxiliary regression, similar to the Jensen regression, provides a wealth of information about the optimal portfolio holdings for investors for the non mean-variance case. This is analogous to the information provided by the Jensen regression about optimal portfolio holdings for the mean-variance case. Our empirical results show that static hedging with currency forwards does not lead to improvements in portfolio performance for a US investor that holds a stock portfolio from the G5 countries. On the other hand, hedges that are conditional on the current interest rate spread do lead to significant performance improvements. Also, when an investor has a substantial exogenous exposure to one of the curr...

In this article we propose two new methods of portfolio allocation which are applicable for all return distributions. The properties of these new methods are compared with that of Markowitz's mean-variance method using extensive simulation. It is found that the new ...

An outcrossed canine pedigree was developed for quantitative trait locus (QTL) mapping of hip dysplasia by breeding dysplastic Labrador retrievers to trait-free greyhounds. Measured susceptibility traits included age at onset of femoral capital chondroepiphyseal ossification (OSS), maximum hip distraction (laxity) index (DI), and the dorsolateral subluxation (DLS) score. The pedigrees consisted of 147 dogs representing four generations. For 59 dogs genotyped with 65 microsatellites, the median heterozygosity and polymorphic information content (PIC) values of the F(1) generation were 0.82 and 0.68, respectively. Seventy-seven percent of microsatellites had a PIC greater than 0.59 in the F(1)s. Ninety-six percent of alleles showed Mendelian inheritance. Based on marker informativeness, approximately 350 randomly selected markers would be required for genome-wide screening to obtain an average interval between informative markers of 10 cM. Heritability was estimated as 0.43, 0.5, and ...

ABSTRACT. In a famous and controversial paper, BH Slater has argued against the possibility of paraconsistent logics. Our reply is centred on the distinction between two aspects of the meaning of a logical constant ∗c∗ in a given logic: its operational meaning, given by the ...

This paper examines the benefits of diversifying into real estate and other assets that typify the wealth held by Japanese investors by examining movements in mean variance frontiers. We employ spanning tests to assess statistical significance of frontier shifts without specifying a benchmark asset pricing model. We also examine the impact of shifts in mean variance frontiers before and after the precipitous decline in Japanese real estate and stock market values in the 90s. Spanning tests show that real estate, short, and long-term bonds provide diversification benefits while domestic and US equities do not. Significant shifts in mean variance frontiers are detected during the 90s. Residential property as opposed to commercial and industrial properties proves to be a more robust diversifier. Statistically significant shifts are also economically significant as measured by Sharpe ratio changes. Although significant, the portfolio weights on real estate are small compared to their co...