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Markowitz</title> <meta name="description" content="Search results for: Markowitz"> <meta name="keywords" content="Markowitz"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler ml-auto" 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id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="Markowitz"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 18</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: Markowitz</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18</span> Efficient Frontier: Comparing Different Volatility Estimators</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tea%20Poklepovi%C4%87">Tea Poklepović</a>, <a href="https://publications.waset.org/abstracts/search?q=Zdravka%20Aljinovi%C4%87"> Zdravka Aljinović</a>, <a href="https://publications.waset.org/abstracts/search?q=Mario%20Matkovi%C4%87"> Mario Matković</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Modern Portfolio Theory (MPT) according to Markowitz states that investors form mean-variance efficient portfolios which maximizes their utility. Markowitz proposed the standard deviation as a simple measure for portfolio risk and the lower semi-variance as the only risk measure of interest to rational investors. This paper uses a third volatility estimator based on intraday data and compares three efficient frontiers on the Croatian Stock Market. The results show that range-based volatility estimator outperforms both mean-variance and lower semi-variance model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=variance" title="variance">variance</a>, <a href="https://publications.waset.org/abstracts/search?q=lower%20semi-variance" title=" lower semi-variance"> lower semi-variance</a>, <a href="https://publications.waset.org/abstracts/search?q=range-based%20volatility" title=" range-based volatility"> range-based volatility</a>, <a href="https://publications.waset.org/abstracts/search?q=MPT" title=" MPT"> MPT</a> </p> <a href="https://publications.waset.org/abstracts/20229/efficient-frontier-comparing-different-volatility-estimators" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/20229.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">513</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17</span> Markowitz and Implementation of a Multi-Objective Evolutionary Technique Applied to the Colombia Stock Exchange (2009-2015)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Feijoo%20E.%20Colomine%20Duran">Feijoo E. Colomine Duran</a>, <a href="https://publications.waset.org/abstracts/search?q=Carlos%20E.%20Pe%C3%B1aloza%20Corredor"> Carlos E. Peñaloza Corredor</a> </p> <p class="card-text"><strong>Abstract:</strong></p> There modeling component selection financial investment (Portfolio) a variety of problems that can be addressed with optimization techniques under evolutionary schemes. For his feature, the problem of selection of investment components of a dichotomous relationship between two elements that are opposed: The Portfolio Performance and Risk presented by choosing it. This relationship was modeled by Markowitz through a media problem (Performance) - variance (risk), ie must Maximize Performance and Minimize Risk. This research included the study and implementation of multi-objective evolutionary techniques to solve these problems, taking as experimental framework financial market equities Colombia Stock Exchange between 2009-2015. Comparisons three multiobjective evolutionary algorithms, namely the Nondominated Sorting Genetic Algorithm II (NSGA-II), the Strength Pareto Evolutionary Algorithm 2 (SPEA2) and Indicator-Based Selection in Multiobjective Search (IBEA) were performed using two measures well known performance: The Hypervolume indicator and R_2 indicator, also it became a nonparametric statistical analysis and the Wilcoxon rank-sum test. The comparative analysis also includes an evaluation of the financial efficiency of the investment portfolio chosen by the implementation of various algorithms through the Sharpe ratio. It is shown that the portfolio provided by the implementation of the algorithms mentioned above is very well located between the different stock indices provided by the Colombia Stock Exchange. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=finance" title="finance">finance</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=portfolio" title=" portfolio"> portfolio</a>, <a href="https://publications.waset.org/abstracts/search?q=Markowitz" title=" Markowitz"> Markowitz</a>, <a href="https://publications.waset.org/abstracts/search?q=evolutionary%20algorithms" title=" evolutionary algorithms"> evolutionary algorithms</a> </p> <a href="https://publications.waset.org/abstracts/56680/markowitz-and-implementation-of-a-multi-objective-evolutionary-technique-applied-to-the-colombia-stock-exchange-2009-2015" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/56680.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">302</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">16</span> Contrasted Mean and Median Models in Egyptian Stock Markets</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mai%20A.%20Ibrahim">Mai A. Ibrahim</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammed%20El-Beltagy"> Mohammed El-Beltagy</a>, <a href="https://publications.waset.org/abstracts/search?q=Motaz%20Khorshid"> Motaz Khorshid</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Emerging Markets return distributions have shown significance departure from normality were they are characterized by fatter tails relative to the normal distribution and exhibit levels of skewness and kurtosis that constitute a significant departure from normality. Therefore, the classical Markowitz Mean-Variance is not applicable for emerging markets since it assumes normally-distributed returns (with zero skewness and kurtosis) and a quadratic utility function. Moreover, the Markowitz mean-variance analysis can be used in cases of moderate non-normality and it still provides a good approximation of the expected utility, but it may be ineffective under large departure from normality. Higher moments models and median models have been suggested in the literature for asset allocation in this case. Higher moments models have been introduced to account for the insufficiency of the description of a portfolio by only its first two moments while the median model has been introduced as a robust statistic which is less affected by outliers than the mean. Tail risk measures such as Value-at Risk (VaR) and Conditional Value-at-Risk (CVaR) have been introduced instead of Variance to capture the effect of risk. In this research, higher moment models including the Mean-Variance-Skewness (MVS) and Mean-Variance-Skewness-Kurtosis (MVSK) are formulated as single-objective non-linear programming problems (NLP) and median models including the Median-Value at Risk (MedVaR) and Median-Mean Absolute Deviation (MedMAD) are formulated as a single-objective mixed-integer linear programming (MILP) problems. The higher moment models and median models are compared to some benchmark portfolios and tested on real financial data in the Egyptian main Index EGX30. The results show that all the median models outperform the higher moment models were they provide higher final wealth for the investor over the entire period of study. In addition, the results have confirmed the inapplicability of the classical Markowitz Mean-Variance to the Egyptian stock market as it resulted in very low realized profits. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Egyptian%20stock%20exchange" title="Egyptian stock exchange">Egyptian stock exchange</a>, <a href="https://publications.waset.org/abstracts/search?q=emerging%20markets" title=" emerging markets"> emerging markets</a>, <a href="https://publications.waset.org/abstracts/search?q=higher%20moment%20models" title=" higher moment models"> higher moment models</a>, <a href="https://publications.waset.org/abstracts/search?q=median%20models" title=" median models"> median models</a>, <a href="https://publications.waset.org/abstracts/search?q=mixed-integer%20linear%20programming" title=" mixed-integer linear programming"> mixed-integer linear programming</a>, <a href="https://publications.waset.org/abstracts/search?q=non-linear%20programming" title=" non-linear programming"> non-linear programming</a> </p> <a href="https://publications.waset.org/abstracts/42897/contrasted-mean-and-median-models-in-egyptian-stock-markets" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/42897.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">315</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">15</span> The Impact of Transaction Costs on Rebalancing an Investment Portfolio in Portfolio Optimization</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=B.%20Marasovi%C4%87">B. Marasović</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Pivac"> S. Pivac</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20V.%20Vukasovi%C4%87"> S. V. Vukasović</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Constructing a portfolio of investments is one of the most significant financial decisions facing individuals and institutions. In accordance with the modern portfolio theory maximization of return at minimal risk should be the investment goal of any successful investor. In addition, the costs incurred when setting up a new portfolio or rebalancing an existing portfolio must be included in any realistic analysis. In this paper rebalancing an investment portfolio in the presence of transaction costs on the Croatian capital market is analyzed. The model applied in the paper is an extension of the standard portfolio mean-variance optimization model in which transaction costs are incurred to rebalance an investment portfolio. This model allows different costs for different securities, and different costs for buying and selling. In order to find efficient portfolio, using this model, first, the solution of quadratic programming problem of similar size to the Markowitz model, and then the solution of a linear programming problem have to be found. Furthermore, in the paper the impact of transaction costs on the efficient frontier is investigated. Moreover, it is shown that global minimum variance portfolio on the efficient frontier always has the same level of the risk regardless of the amount of transaction costs. Although efficient frontier position depends of both transaction costs amount and initial portfolio it can be concluded that extreme right portfolio on the efficient frontier always contains only one stock with the highest expected return and the highest risk. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Croatian%20capital%20market" title="Croatian capital market">Croatian capital market</a>, <a href="https://publications.waset.org/abstracts/search?q=Markowitz%20model" title=" Markowitz model"> Markowitz model</a>, <a href="https://publications.waset.org/abstracts/search?q=fractional%20quadratic%20programming" title=" fractional quadratic programming"> fractional quadratic programming</a>, <a href="https://publications.waset.org/abstracts/search?q=portfolio%20optimization" title=" portfolio optimization"> portfolio optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=transaction%20costs" title=" transaction costs"> transaction costs</a> </p> <a href="https://publications.waset.org/abstracts/21383/the-impact-of-transaction-costs-on-rebalancing-an-investment-portfolio-in-portfolio-optimization" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21383.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">385</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">14</span> Portfolio Risk Management Using Quantum Annealing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Thomas%20Doutre">Thomas Doutre</a>, <a href="https://publications.waset.org/abstracts/search?q=Emmanuel%20De%20Meric%20De%20Bellefon"> Emmanuel De Meric De Bellefon</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper describes the application of local-search metaheuristic quantum annealing to portfolio opti- mization. Heuristic technics are particularly handy when Markowitz’ classical Mean-Variance problem is enriched with additional realistic constraints. Once tailored to the problem, computational experiments on real collected data have shown the superiority of quantum annealing over simulated annealing for this constrained optimization problem, taking advantages of quantum effects such as tunnelling. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=optimization" title="optimization">optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=portfolio%20risk%20management" title=" portfolio risk management"> portfolio risk management</a>, <a href="https://publications.waset.org/abstracts/search?q=quantum%20annealing" title=" quantum annealing"> quantum annealing</a>, <a href="https://publications.waset.org/abstracts/search?q=metaheuristic" title=" metaheuristic"> metaheuristic</a> </p> <a href="https://publications.waset.org/abstracts/40564/portfolio-risk-management-using-quantum-annealing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/40564.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">383</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">13</span> Optimization of Black-Litterman Model for Portfolio Assets Allocation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20Hidalgo">A. Hidalgo</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Desportes"> A. Desportes</a>, <a href="https://publications.waset.org/abstracts/search?q=E.%20Bonin"> E. Bonin</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Kadaoui"> A. Kadaoui</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20Bouaricha"> T. Bouaricha</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Present paper is concerned with portfolio management with Black-Litterman (B-L) model. Considered stocks are exclusively limited to large companies stocks on US market. Results obtained by application of the model are presented. From analysis of collected Dow Jones stock data, remarkable explicit analytical expression of optimal B-L parameter τ, which scales dispersion of normal distribution of assets mean return, is proposed in terms of standard deviation of covariance matrix. Implementation has been developed in Matlab environment to split optimization in Markovitz sense from specific elements related to B-L representation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Black-Litterman" title="Black-Litterman">Black-Litterman</a>, <a href="https://publications.waset.org/abstracts/search?q=Markowitz" title=" Markowitz"> Markowitz</a>, <a href="https://publications.waset.org/abstracts/search?q=market%20data" title=" market data"> market data</a>, <a href="https://publications.waset.org/abstracts/search?q=portfolio%20manager%20opinion" title=" portfolio manager opinion"> portfolio manager opinion</a> </p> <a href="https://publications.waset.org/abstracts/6712/optimization-of-black-litterman-model-for-portfolio-assets-allocation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/6712.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">260</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">12</span> Multi-Criteria Based Robust Markowitz Model under Box Uncertainty</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pulak%20Swain">Pulak Swain</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20K.%20Ojha"> A. K. Ojha</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Portfolio optimization is based on dealing with the problems of efficient asset allocation. Risk and Expected return are two conflicting criteria in such problems, where the investor prefers the return to be high and the risk to be low. Using multi-objective approach we can solve those type of problems. However the information which we have for the input parameters are generally ambiguous and the input values can fluctuate around some nominal values. We can not ignore the uncertainty in input values, as they can affect the asset allocation drastically. So we use Robust Optimization approach to the problems where the input parameters comes under box uncertainty. In this paper, we solve the multi criteria robust problem with the help of E- constraint method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=portfolio%20optimization" title="portfolio optimization">portfolio optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-objective%20optimization" title=" multi-objective optimization"> multi-objective optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=%CF%B5%20-%20constraint%20method" title=" ϵ - constraint method"> ϵ - constraint method</a>, <a href="https://publications.waset.org/abstracts/search?q=box%20uncertainty" title=" box uncertainty"> box uncertainty</a>, <a href="https://publications.waset.org/abstracts/search?q=robust%20optimization" title=" robust optimization"> robust optimization</a> </p> <a href="https://publications.waset.org/abstracts/118411/multi-criteria-based-robust-markowitz-model-under-box-uncertainty" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/118411.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">139</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">11</span> Meaningful General Education Reform: Integrating Core Curricula and Institutional Values </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Michael%20W.%20Markowitz">Michael W. Markowitz</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A central element of higher education today is the “core” or “general education” curriculum: that configuration of courses that often encompasses the essence of liberal arts education. Ensuring that such offerings reflect the mission and values of the institution is a challenge faced by most college and universities, often more than once. This paper presents an action model of program planning designed to structure the processes of developing, implementing and revising core curricula in a manner consistent with key institutional goals and objectives. Through presentation of a case study from a university in the United States, the elements of needs assessment, stakeholder investment and collaborative compromise are shown as key components of a planning strategy that can produce a general education program that is comprehensive, academically rigorous, assessable and mission consistent. The paper concludes with recommendations for both the implementation and evaluation of such programs in practice. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=academic%20assessment" title="academic assessment">academic assessment</a>, <a href="https://publications.waset.org/abstracts/search?q=academic%20program%20planning" title=" academic program planning"> academic program planning</a>, <a href="https://publications.waset.org/abstracts/search?q=curriculum%20development" title=" curriculum development"> curriculum development</a>, <a href="https://publications.waset.org/abstracts/search?q=general%20education%20reform" title=" general education reform"> general education reform</a> </p> <a href="https://publications.waset.org/abstracts/20694/meaningful-general-education-reform-integrating-core-curricula-and-institutional-values" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/20694.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">320</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10</span> Financial Portfolio Optimization in Electricity Markets: Evaluation via Sharpe Ratio</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=F.%20G%C3%B6kg%C3%B6z">F. Gökgöz</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20E.%20Atmaca"> M. E. Atmaca</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Electricity plays an indispensable role in human life and the economy. It is a unique product or service that must be balanced instantaneously, as electricity is not stored, generation and consumption should be proportional. Effective and efficient use of electricity is very important not only for society, but also for the environment. A competitive electricity market is one of the best ways to provide a suitable platform for effective and efficient use of electricity. On the other hand, it carries some risks that should be carefully managed by the market players. Risk management is an essential part in market players’ decision making. In this paper, risk management through diversification is applied with the help of Markowitz’s Mean-variance, Down-side and Semi-variance methods for a case study. Performance of optimal electricity sale solutions are measured and evaluated via Sharpe-Ratio, and the optimal portfolio solutions are improved. Two years of historical weekdays’ price data of the Turkish Day Ahead Market are used to demonstrate the approach. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=electricity%20market" title="electricity market">electricity market</a>, <a href="https://publications.waset.org/abstracts/search?q=portfolio%20optimization" title=" portfolio optimization"> portfolio optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=risk%20management%20in%20electricity%20market" title=" risk management in electricity market"> risk management in electricity market</a>, <a href="https://publications.waset.org/abstracts/search?q=sharpe%20ratio" title=" sharpe ratio"> sharpe ratio</a> </p> <a href="https://publications.waset.org/abstracts/52925/financial-portfolio-optimization-in-electricity-markets-evaluation-via-sharpe-ratio" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/52925.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">365</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">9</span> Random Matrix Theory Analysis of Cross-Correlation in the Nigerian Stock Exchange</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chimezie%20P.%20Nnanwa">Chimezie P. Nnanwa</a>, <a href="https://publications.waset.org/abstracts/search?q=Thomas%20C.%20Urama"> Thomas C. Urama</a>, <a href="https://publications.waset.org/abstracts/search?q=Patrick%20O.%20Ezepue"> Patrick O. Ezepue</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper we use Random Matrix Theory to analyze the eigen-structure of the empirical correlations of 82 stocks which are consistently traded in the Nigerian Stock Exchange (NSE) over a 4-year study period 3 August 2009 to 26 August 2013. We apply the Marchenko-Pastur distribution of eigenvalues of a purely random matrix to investigate the presence of investment-pertinent information contained in the empirical correlation matrix of the selected stocks. We use hypothesised standard normal distribution of eigenvector components from RMT to assess deviations of the empirical eigenvectors to this distribution for different eigenvalues. We also use the Inverse Participation Ratio to measure the deviation of eigenvectors of the empirical correlation matrix from RMT results. These preliminary results on the dynamics of asset price correlations in the NSE are important for improving risk-return trade-offs associated with Markowitz’s portfolio optimization in the stock exchange, which is pursued in future work. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=correlation%20matrix" title="correlation matrix">correlation matrix</a>, <a href="https://publications.waset.org/abstracts/search?q=eigenvalue%20and%20eigenvector" title=" eigenvalue and eigenvector"> eigenvalue and eigenvector</a>, <a href="https://publications.waset.org/abstracts/search?q=inverse%20participation%20ratio" title=" inverse participation ratio"> inverse participation ratio</a>, <a href="https://publications.waset.org/abstracts/search?q=portfolio%20optimization" title=" portfolio optimization"> portfolio optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=random%20matrix%20theory" title=" random matrix theory"> random matrix theory</a> </p> <a href="https://publications.waset.org/abstracts/68007/random-matrix-theory-analysis-of-cross-correlation-in-the-nigerian-stock-exchange" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/68007.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">344</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8</span> Investments in Petroleum Industry Abnormally Normal: A Case Study Based on Petroleum and Natural Gas Companies in India</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Radhika%20Ramanchi">Radhika Ramanchi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The oil market during 2014-2015 in India with large price fluctuations is very confusing to individual investor. The drop in oil prices supported stocks of some oil marketing companies (OMCs) like Bharat Petroleum Corporation, Hindustan Petroleum Corporation (HPCL) and Indian Oil Corporation etc their shares rose 84.74%, 128.63% and 59.16%, respectively. Lower oil prices, and lower current account, a smaller subsidy burden are the reasons for outperformance. On the other hand, lower crude prices giving downward pressure on upstream companies like Oil and Natural Gas Corp. Ltd (ONGC) and Reliance Petroleum (RIL) Oil India Ltd (OIL). Not having clarity on a subsidy sharing mechanism is the reason for downward trend on these stocks. Shares of ONGC and RIL have underperformed so far in 2015. When the oil price fall profits of the companies will effect, generate less money and may cut their dividends in Long run. In this situation this paper objective is to study investment strategies in oil marketing companies, by applying CAPM and Security Market Line. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=petrol%20industry" title="petrol industry">petrol industry</a>, <a href="https://publications.waset.org/abstracts/search?q=price%20fluctuations" title=" price fluctuations"> price fluctuations</a>, <a href="https://publications.waset.org/abstracts/search?q=sharp%20single%20index%20model" title=" sharp single index model"> sharp single index model</a>, <a href="https://publications.waset.org/abstracts/search?q=SML" title=" SML"> SML</a>, <a href="https://publications.waset.org/abstracts/search?q=Markowitz%20model" title=" Markowitz model"> Markowitz model</a> </p> <a href="https://publications.waset.org/abstracts/46771/investments-in-petroleum-industry-abnormally-normal-a-case-study-based-on-petroleum-and-natural-gas-companies-in-india" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/46771.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">223</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7</span> Challenge of Baseline Hydrology Estimation at Large-Scale Watersheds</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Can%20Liu">Can Liu</a>, <a href="https://publications.waset.org/abstracts/search?q=Graham%20Markowitz"> Graham Markowitz</a>, <a href="https://publications.waset.org/abstracts/search?q=John%20Balay"> John Balay</a>, <a href="https://publications.waset.org/abstracts/search?q=Ben%20Pratt"> Ben Pratt</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Baseline or natural hydrology is commonly employed for hydrologic modeling and quantification of hydrologic alteration due to manmade activities. It can inform planning and policy related efforts for various state and federal water resource agencies to restore natural streamflow flow regimes. A common challenge faced by hydrologists is how to replicate unaltered streamflow conditions, particularly in large watershed settings prone to development and regulation. Three different methods were employed to estimate baseline streamflow conditions for 6 major subbasins the Susquehanna River Basin; those being: 1) incorporation of consumptive water use and reservoir operations back into regulated gaged records; 2) using a map correlation method and flow duration (exceedance probability) regression equations; 3) extending the pre-regulation streamflow records based on the relationship between concurrent streamflows at unregulated and regulated gage locations. Parallel analyses were perform among the three methods and limitations associated with each are presented. Results from these analyses indicate that generating baseline streamflow records at large-scale watersheds remain challenging, even with long-term continuous stream gage records available. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=baseline%20hydrology" title="baseline hydrology">baseline hydrology</a>, <a href="https://publications.waset.org/abstracts/search?q=streamflow%20gage" title=" streamflow gage"> streamflow gage</a>, <a href="https://publications.waset.org/abstracts/search?q=subbasin" title=" subbasin"> subbasin</a>, <a href="https://publications.waset.org/abstracts/search?q=regression" title=" regression"> regression</a> </p> <a href="https://publications.waset.org/abstracts/62920/challenge-of-baseline-hydrology-estimation-at-large-scale-watersheds" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/62920.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">324</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6</span> Assessment of Korea's Natural Gas Portfolio Considering Panama Canal Expansion</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Juhan%20Kim">Juhan Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Jinsoo%20Kim"> Jinsoo Kim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> South Korea cannot import natural gas in any form other than LNG because of the division of South and North Korea. Further, the high proportion of natural gas in the national energy mix makes this resource crucial for energy security in Korea. Expansion of Panama Canal will allow for reducing the cost of shipping between the Far East and U.S East. Panama Canal expansion can have significant impacts on South Korea. Due to this situation, we review the natural gas optimal portfolio by considering the uniqueness of the Korean Natural gas market and expansion of Panama Canal. In order to assess Korea’s natural gas optimal portfolio, we developed natural gas portfolio model. The model comprises two steps. First, to obtain the optimal long-term spot contract ratio, the study examines the price level and the correlation between spot and long-term contracts by using the Markowitz, portfolio model. The optimal long-term spot contract ratio follows the efficient frontier of the cost/risk level related to this price level and degree of correlation. Second, by applying the obtained long-term contract purchase ratio as the constraint in the linear programming portfolio model, we determined the natural gas optimal import portfolio that minimizes total intangible and tangible costs. Using this model, we derived the optimal natural gas portfolio considering the expansion of Panama Canal. Based on these results, we assess the portfolio for natural gas import to Korea from the perspective of energy security and present some relevant policy proposals. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=natural%20gas" title="natural gas">natural gas</a>, <a href="https://publications.waset.org/abstracts/search?q=Panama%20Canal" title=" Panama Canal"> Panama Canal</a>, <a href="https://publications.waset.org/abstracts/search?q=portfolio%20analysis" title=" portfolio analysis"> portfolio analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=South%20Korea" title=" South Korea"> South Korea</a> </p> <a href="https://publications.waset.org/abstracts/67569/assessment-of-koreas-natural-gas-portfolio-considering-panama-canal-expansion" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/67569.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">291</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5</span> The Changing Role of the Chief Academic Officer in American Higher Education: Causes and Consequences</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Michael%20W.%20Markowitz">Michael W. Markowitz</a>, <a href="https://publications.waset.org/abstracts/search?q=Jeffrey%20Gingerich"> Jeffrey Gingerich</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The landscape of higher education in the United States has undergone significant changes in the last 25 years. What was once a domain of competition among prospective students for a limited number of college and university seats has become a marketplace in which institutions vie for the enrollment of educational consumers. A central figure in this paradigm shift has been the Chief Academic Officer (CAO), whose institutional role has also evolved beyond academics to include such disparate responsibilities as strategic planning, fiscal oversight, student recruitment, fundraising and personnel management. This paper explores the scope and impact of this transition by, first, explaining its context: the intersection of key social, economic and political factors in neo-conservative, late 20th Century America that redefined the value and accountability of institutions of higher learning. This context, in turn, is shown to have redefined the role and function of the CAO from a traditional academic leader to one centered on the successful application of corporate principles of organizational and fiscal management. Information gathered from a number of sitting Provosts, Vice-Presidents of Academic Affairs and Deans of Faculty is presented to illustrate the parameters of this change, as well as the extent to which today’s academic officers feel prepared and equipped to fulfill this broader institutional role. The paper concludes with a discussion of the impact of this transition on the American academy and whether it serves as a portend of change to come in higher education systems around the globe. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=academic%20administration" title="academic administration">academic administration</a>, <a href="https://publications.waset.org/abstracts/search?q=higher%20education" title=" higher education"> higher education</a>, <a href="https://publications.waset.org/abstracts/search?q=leadership" title=" leadership"> leadership</a>, <a href="https://publications.waset.org/abstracts/search?q=organizational%20management" title=" organizational management"> organizational management</a> </p> <a href="https://publications.waset.org/abstracts/73786/the-changing-role-of-the-chief-academic-officer-in-american-higher-education-causes-and-consequences" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/73786.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">220</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">4</span> Portfolio Optimization with Reward-Risk Ratio Measure Based on the Mean Absolute Deviation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Wlodzimierz%20Ogryczak">Wlodzimierz Ogryczak</a>, <a href="https://publications.waset.org/abstracts/search?q=Michal%20Przyluski"> Michal Przyluski</a>, <a href="https://publications.waset.org/abstracts/search?q=Tomasz%20Sliwinski"> Tomasz Sliwinski</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In problems of portfolio selection, the reward-risk ratio criterion is optimized to search for a risky portfolio with the maximum increase of the mean return in proportion to the risk measure increase when compared to the risk-free investments. In the classical model, following Markowitz, the risk is measured by the variance thus representing the Sharpe ratio optimization and leading to the quadratic optimization problems. Several Linear Programming (LP) computable risk measures have been introduced and applied in portfolio optimization. In particular, the Mean Absolute Deviation (MAD) measure has been widely recognized. The reward-risk ratio optimization with the MAD measure can be transformed into the LP formulation with the number of constraints proportional to the number of scenarios and the number of variables proportional to the total of the number of scenarios and the number of instruments. This may lead to the LP models with huge number of variables and constraints in the case of real-life financial decisions based on several thousands scenarios, thus decreasing their computational efficiency and making them hardly solvable by general LP tools. We show that the computational efficiency can be then dramatically improved by an alternative model based on the inverse risk-reward ratio minimization and by taking advantages of the LP duality. In the introduced LP model the number of structural constraints is proportional to the number of instruments thus not affecting seriously the simplex method efficiency by the number of scenarios and therefore guaranteeing easy solvability. Moreover, we show that under natural restriction on the target value the MAD risk-reward ratio optimization is consistent with the second order stochastic dominance rules. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=portfolio%20optimization" title="portfolio optimization">portfolio optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=reward-risk%20ratio" title=" reward-risk ratio"> reward-risk ratio</a>, <a href="https://publications.waset.org/abstracts/search?q=mean%20absolute%20deviation" title=" mean absolute deviation"> mean absolute deviation</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20programming" title=" linear programming"> linear programming</a> </p> <a href="https://publications.waset.org/abstracts/61665/portfolio-optimization-with-reward-risk-ratio-measure-based-on-the-mean-absolute-deviation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/61665.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">407</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3</span> Optimization of a High-Growth Investment Portfolio for the South African Market Using Predictive Analytics</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mia%20Fran%C3%A7oise">Mia Françoise</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This report aims to develop a strategy for assisting short-term investors to benefit from the current economic climate in South Africa by utilizing technical analysis techniques and predictive analytics. As part of this research, value investing and technical analysis principles will be combined to maximize returns for South African investors while optimizing volatility. As an emerging market, South Africa offers many opportunities for high growth in sectors where other developed countries cannot grow at the same rate. Investing in South African companies with significant growth potential can be extremely rewarding. Although the risk involved is more significant in countries with less developed markets and infrastructure, there is more room for growth in these countries. According to recent research, the offshore market is expected to outperform the local market over the long term; however, short-term investments in the local market will likely be more profitable, as the Johannesburg Stock Exchange is predicted to outperform the S&P500 over the short term. The instabilities in the economy contribute to increased market volatility, which can benefit investors if appropriately utilized. Price prediction and portfolio optimization comprise the two primary components of this methodology. As part of this process, statistics and other predictive modeling techniques will be used to predict the future performance of stocks listed on the Johannesburg Stock Exchange. Following predictive data analysis, Modern Portfolio Theory, based on Markowitz's Mean-Variance Theorem, will be applied to optimize the allocation of assets within an investment portfolio. By combining different assets within an investment portfolio, this optimization method produces a portfolio with an optimal ratio of expected risk to expected return. This methodology aims to provide a short-term investment with a stock portfolio that offers the best risk-to-return profile for stocks listed on the JSE by combining price prediction and portfolio optimization. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=financial%20stocks" title="financial stocks">financial stocks</a>, <a href="https://publications.waset.org/abstracts/search?q=optimized%20asset%20allocation" title=" optimized asset allocation"> optimized asset allocation</a>, <a href="https://publications.waset.org/abstracts/search?q=prediction%20modelling" title=" prediction modelling"> prediction modelling</a>, <a href="https://publications.waset.org/abstracts/search?q=South%20Africa" title=" South Africa"> South Africa</a> </p> <a href="https://publications.waset.org/abstracts/168328/optimization-of-a-high-growth-investment-portfolio-for-the-south-african-market-using-predictive-analytics" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/168328.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">97</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2</span> Market Solvency Capital Requirement Minimization: How Non-linear Solvers Provide Portfolios Complying with Solvency II Regulation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abraham%20Castellanos">Abraham Castellanos</a>, <a href="https://publications.waset.org/abstracts/search?q=Christophe%20Durville"> Christophe Durville</a>, <a href="https://publications.waset.org/abstracts/search?q=Sophie%20Echenim"> Sophie Echenim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this article, a portfolio optimization problem is performed in a Solvency II context: it illustrates how advanced optimization techniques can help to tackle complex operational pain points around the monitoring, control, and stability of Solvency Capital Requirement (SCR). The market SCR of a portfolio is calculated as a combination of SCR sub-modules. These sub-modules are the results of stress-tests on interest rate, equity, property, credit and FX factors, as well as concentration on counter-parties. The market SCR is non convex and non differentiable, which does not make it a natural optimization criteria candidate. In the SCR formulation, correlations between sub-modules are fixed, whereas risk-driven portfolio allocation is usually driven by the dynamics of the actual correlations. Implementing a portfolio construction approach that is efficient on both a regulatory and economic standpoint is not straightforward. Moreover, the challenge for insurance portfolio managers is not only to achieve a minimal SCR to reduce non-invested capital but also to ensure stability of the SCR. Some optimizations have already been performed in the literature, simplifying the standard formula into a quadratic function. But to our knowledge, it is the first time that the standard formula of the market SCR is used in an optimization problem. Two solvers are combined: a bundle algorithm for convex non- differentiable problems, and a BFGS (Broyden-Fletcher-Goldfarb- Shanno)-SQP (Sequential Quadratic Programming) algorithm, to cope with non-convex cases. A market SCR minimization is then performed with historical data. This approach results in significant reduction of the capital requirement, compared to a classical Markowitz approach based on the historical volatility. A comparative analysis of different optimization models (equi-risk-contribution portfolio, minimizing volatility portfolio and minimizing value-at-risk portfolio) is performed and the impact of these strategies on risk measures including market SCR and its sub-modules is evaluated. A lack of diversification of market SCR is observed, specially for equities. This was expected since the market SCR strongly penalizes this type of financial instrument. It was shown that this direct effect of the regulation can be attenuated by implementing constraints in the optimization process or minimizing the market SCR together with the historical volatility, proving the interest of having a portfolio construction approach that can incorporate such features. The present results are further explained by the Market SCR modelling. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=financial%20risk" title="financial risk">financial risk</a>, <a href="https://publications.waset.org/abstracts/search?q=numerical%20optimization" title=" numerical optimization"> numerical optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=portfolio%20management" title=" portfolio management"> portfolio management</a>, <a href="https://publications.waset.org/abstracts/search?q=solvency%20capital%20requirement" title=" solvency capital requirement"> solvency capital requirement</a> </p> <a href="https://publications.waset.org/abstracts/127464/market-solvency-capital-requirement-minimization-how-non-linear-solvers-provide-portfolios-complying-with-solvency-ii-regulation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/127464.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">117</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1</span> Study Protocol: Impact of a Sustained Health Promoting Workplace on Stock Price Performance and Beta - A Singapore Case</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Wee%20Tong%20Liaw">Wee Tong Liaw</a>, <a href="https://publications.waset.org/abstracts/search?q=Elaine%20Wong%20Yee%20Sing"> Elaine Wong Yee Sing</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Since 2001, many companies in Singapore have voluntarily participated in the bi-annual Singapore HEALTH Award initiated by the Health Promotion Board of Singapore (HPB). The Singapore HEALTH Award (SHA), is an industry wide award and assessment process. SHA assesses and recognizes employers in Singapore for implementing a comprehensive and sustainable health promotion programme at their workplaces. The rationale for implementing a sustained health promoting workplace and participating in SHA is obvious when company management is convinced that healthier employees, business productivity, and profitability are positively correlated. However, performing research or empirical studies on the impact of a sustained health promoting workplace on stock returns are not likely to yield any interests in the absence of a systematic and independent assessment on the comprehensiveness and sustainability of a health promoting workplace in most developed economies. The principles of diversification and mean-variance efficient portfolio in Modern Portfolio Theory developed by Markowitz (1952) laid the foundation for the works of many financial economists and researchers, and among others, the development of the Capital Asset Pricing Model from the work of Sharpe (1964), Lintner (1965) and Mossin (1966), and the Fama-French Three-Factor Model of Fama and French (1992). This research seeks to support the rationale by studying whether there is a significant relationship or impact of a sustained health promoting workplace on the performance of companies listed on the SGX. The research shall form and test hypotheses pertaining to the impact of a sustained health promoting workplace on company’s performances, including stock returns, of companies that participated in the SHA and companies that did not participate in the SHA. In doing so, the research would be able to determine whether corporate and fund manager should consider the significance of a sustained health promoting workplace as a risk factor to explain the stock returns of companies listed on the SGX. With respect to Singapore’s stock market, this research will test the significance and relevance of a health promoting workplace using the Singapore Health Award as a proxy for non-diversifiable risk factor to explain stock returns. This study will examine the significance of a health promoting workplace on a company’s performance and study its impact on stock price performance and beta and examine if it has higher explanatory power than the traditional single factor asset pricing model CAPM (Capital Asset Pricing Model). To study the significance there are three key questions pertinent to the research study. I) Given a choice, would an investor be better off investing in a listed company with a sustained health promoting workplace i.e. a Singapore Health Award’s recipient? II) The Singapore Health Award has four levels of award starting from Bronze, Silver, Gold to Platinum. Would an investor be indifferent to the level of award when investing in a listed company who is a Singapore Health Award’s recipient? III) Would an asset pricing model combining FAMA-French Three Factor Model and ‘Singapore Health Award’ factor be more accurate than single factor Capital Asset Pricing Model and the Three Factor Model itself? <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=asset%20pricing%20model" title="asset pricing model">asset pricing model</a>, <a href="https://publications.waset.org/abstracts/search?q=company%27s%20performance" title=" company's performance"> company's performance</a>, <a href="https://publications.waset.org/abstracts/search?q=stock%20prices" title=" stock prices"> stock prices</a>, <a href="https://publications.waset.org/abstracts/search?q=sustained%20health%20promoting%20workplace" title=" sustained health promoting workplace"> sustained health promoting workplace</a> </p> <a href="https://publications.waset.org/abstracts/81251/study-protocol-impact-of-a-sustained-health-promoting-workplace-on-stock-price-performance-and-beta-a-singapore-case" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/81251.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">369</span> </span> </div> </div> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a href="https://waset.org/page/support#legal-information">Legal</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/WASET-16th-foundational-anniversary.pdf">WASET celebrates its 16th foundational 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