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Journal articles on the topic 'Portfolio theory'

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Author: Grafiati

Published: 4 June 2021

Last updated: 11 March 2023

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1

MADAN, DILIP B. "CONIC PORTFOLIO THEORY." International Journal of Theoretical and Applied Finance 19, no. 03 (April 21, 2016): 1650019. http://dx.doi.org/10.1142/s0219024916500199.

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Portfolios are designed to maximize a conservative market value or bid price for the portfolio. Theoretically this bid price is modeled as reflecting a convex cone of acceptable risks supporting an arbitrage free equilibrium of a two price economy. When risk acceptability is completely defined by the risk distribution function and bid prices are additive for comonotone risks, then these prices may be evaluated by a distorted expectation. The concavity of the distortion calibrates market risk attitudes. Procedures are outlined for observing the economic magnitudes for diversification benefits reflected in conservative valuation schemes. Optimal portfolios are formed for long only, long short and volatility constrained portfolios. Comparison with mean variance portfolios reflects lower concentration in conic portfolios that have comparable out of sample upside performance coupled with higher downside outcomes. Additionally the optimization problems are robust, employing directionally sensitive risk measures that are in the same units as the rewards. A further contribution is the ability to construct volatility constrained portfolios that attractively combine other dimensions of risk with rewards.

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2

Best, Michael J., and Robert R. Grauer. "Humans, Econs and Portfolio Choice." Quarterly Journal of Finance 07, no. 02 (September 2, 2016): 1750001. http://dx.doi.org/10.1142/s201013921750001x.

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We compare the portfolio choices of Humans — prospect theory investors — to the portfolio choices of Econs — power utility and mean-variance (MV) investors. In a numerical example, prospect theory portfolios are decidedly unreasonable. In an in-sample asset allocation setting, the prospect theory results are consistent with myopic loss aversion. However, the portfolios are extremely unstable. The power utility and MV results are consistent with traditional finance theory, where the portfolios are stable across decision horizons. In an out-of-sample asset allocation setting, the power utility and portfolios outperform the prospect theory portfolios. Nonetheless the prospect theory portfolios with loss aversion coefficients of 2.25 and 2 perform well.

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3

Širůček, Martin, and Lukáš Křen. "Application of Markowitz Portfolio Theory by Building Optimal Portfolio on the US Stock Market." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 63, no. 4 (2015): 1375–86. http://dx.doi.org/10.11118/actaun201563041375.

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This paper is focused on building investment portfolios by using the Markowitz Portfolio Theory (MPT). Derivation based on the Capital Asset Pricing Model (CAPM) is used to calculate the weights of individual securities in portfolios. The calculated portfolios include a portfolio copying the benchmark made using the CAPM model, portfolio with low and high beta coefficients, and a random portfolio. Only stocks were selected for the examined sample from all the asset classes. Stocks in each portfolio are put together according to predefined criteria. All stocks were selected from Dow Jones Industrial Average (DJIA) index which serves as a benchmark, too. Portfolios were compared based on their risk and return profiles. The results of this work will provide general recommendations on the optimal approach to choose securities for an investor’s portfolio.

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Micán, Camilo, Gabriela Fernandes, and Madalena Araújo. "Disclosing the Tacit Links between Risk and Success in Organizational Development Project Portfolios." Sustainability 14, no. 9 (April 26, 2022): 5235. http://dx.doi.org/10.3390/su14095235.

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Project portfolios aim to impact organizational strategic goals, influencing both the organization’s business model and its processes. Nonetheless, the actual impact is dependent on the portfolio’s success, which is affected by the materialization of risk factors. This study aims to examine the tacit conceptualization of project portfolio risk as a risk measure explicitly based on project portfolio success itself. In order to focus on the portfolios of organizational development projects, Social Representation Theory was adopted to analyze empirical evidence from twenty-eight semi-structured interviews conducted with project portfolio practitioners. Findings showed that strategic fit, future preparedness, and stakeholder satisfaction were dimensions of success within which project portfolio risk could be conceptualized. Additionally, results evidenced that risk factors influenced project portfolio success through systematic and non-systematic impacts on project portfolio outputs, and also had direct impacts on project portfolio outcomes. This paper provides empirical evidence to back up the conceptualization of project portfolio risk explicitly oriented to portfolio success as a multidimensional risk measure. It represents a new avenue for conducting portfolio risk analysis for both practitioners and academics, orienting the decision-making process based on the portfolio success rather than only on the success of each project.

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Harzallah, Amen Aissi, and Mouna Boujelbene Abbes. "The Impact of Financial Crises on the Asset Allocation: Classical Theory Versus Behavioral Theory." Journal of Interdisciplinary Economics 32, no. 2 (September 17, 2019): 218–36. http://dx.doi.org/10.1177/0260107919848629.

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The aim of this article is to compare the portfolio optimization generated by the behavioral portfolio theory (BPT) and the mean variance theory (MVT) by investigating the impact of the global financial crisis on the asset allocation. We use data from the Canadian Stock Exchange over the 2002–2015 period. By comparing both approaches, we show that for any level of aspiration and admissible failure, the BPT optimal portfolio will always contain a part of the mean–variance frontier. Thus, in the case of higher degree of risk aversion induced by typical BPT investors, the security set is located on the upper right of the Markowitz frontier. However, even if the optimal portfolios of MVT and BPT may coincide, MVT investors associated with an extremely low degree of risk aversion will not systematically choose BPT optimal portfolios. Our results also indicate the period of financial crisis generate huge losses in MVT portfolio values that implies a lower expected return and a higher level of risk. Furthermore, we point out the absence of the BPT optimal portfolio when potential losses are higher during the 2008 global financial crisis. JEL: G11, G17, G40

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6

Jones, C. Kenneth. "Modern Portfolio Theory, Digital Portfolio Theory and Intertemporal Portfolio Choice." American Journal of Industrial and Business Management 07, no. 07 (2017): 833–54. http://dx.doi.org/10.4236/ajibm.2017.77059.

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7

Kiyko, S., L. Deineha, M. Basanets, D. Kamienskyi, and A. Didenko. "PORTFOLIO MANAGEMENT OF ENERGY SAVING PROJECTS BASED ON THE MARKOVITS THEORY." Integrated Technologies and Energy Saving, no. 3 (November 9, 2021): 79–91. http://dx.doi.org/10.20998/2078-5364.2021.3.08.

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The goal of the work was to identify research and compare methods of portfolio management of energy saving projects and to develop software for optimizing portfolio investments using several methods. The key elements and strategies of creating an effective investment portfolio are considered: diversification, rebalancing, active portfolio management, passive portfolio management. Given the basic principles of investment theory, the task of portfolio investment is to form an investment portfolio with known shares of certain assets to maximize returns and minimize risk. To solve this problem, the method of Harry Markowitz, known as modern portfolio theory, was chosen. This is the theory of financial investment, in which statistical methods are used to make the most profitable risk distribution of the securities portfolio and income valuation, its components are asset valuation, investment decisions, portfolio optimization, evaluation of results. From a mathematical point of view, the problem of forming an optimal portfolio is the problem of optimizing a quadratic function (finding the minimum) with linear constraints on the arguments of the function. Methods of optimization of portfolios of energy saving projects taking into account the specifics of the subject area are analyzed. According to the results of the analysis, the methods of finding the maximum Sharpe’s ratio and the minimum volatility from randomly generated portfolios were chosen. A software application has been developed that allows you to download data, generate random portfolios and optimize them with selected methods. A graphical display of portfolio optimization results has also been implemented. The program was tested on data on shares of energy saving companies. The graphs built by the program allow the operator to better assess the created portfolio of the energy saving project.

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8

Lord, Mimi. "University Endowment Committees, Modern Portfolio Theory and Performance." Journal of Risk and Financial Management 13, no. 9 (September 3, 2020): 198. http://dx.doi.org/10.3390/jrfm13090198.

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University endowments with broad portfolio diversification have been correlated with performance, but committees’ decision-making process has received relatively little attention. This study is unique in postulating that the committee’s learning commitment and open-mindedness are significant contributors to a decision process that is based on the principles of Modern Portfolio Theory (or, simply, Portfolio Theory). The use of Portfolio Theory as a decision-making framework leads to greater portfolio diversification, which, in turn, leads to higher risk-adjusted returns. This study also demonstrates that greater committee expertise across multiple asset classes contributes to more diversified portfolios.

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Majewski, Sebastian. "The Maslowian Portfolio Theory Versus the Pyramid Portfolio." Folia Oeconomica Stetinensia 14, no. 1 (June 1, 2014): 91–101. http://dx.doi.org/10.2478/foli-2014-0107.

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Abstract This article refers to De Brouwer’s modification of portfolio selection from 2009. He modified the existing portfolio’s theories so that they could take into account the Maslov’s hierarchy of needs. This proposal could be also an alternative concept to the behavioural portfolio theory. Another theoretical concept which includes not only the hierarchy of needs but the pyramid portfolio is presented in this paper as well. The base point in this case is Markowitz’s model and the safety-first criterion by Roy. Such a construction should be a starting point for building an application in this field.

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Abdul Hali, Nurfadhlina, and Ari Yuliati. "Markowitz Model Investment Portfolio Optimization: a Review Theory." International Journal of Research in Community Services 1, no. 3 (October 4, 2020): 14–18. http://dx.doi.org/10.46336/ijrcs.v1i3.104.

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In the face of investment risk, investors generally diversify and form an investment portfolio consisting of several assets. The problem is the fiery proportion of funds that must be allocated to each asset in the formation of investment portfolios. This paper aims to study the optimization of the Markowitz investment portfolio. In this study, the Markowitz model discussed is that which considers risk tolerance. Optimization is done by using the Lagrangean Multiplier method. From the study, an equation is obtained to determine the proportion (weight) of fund allocation for each asset in the formation of investment portfolios. So by using these equations, the determination of investment portfolio weights can be determined by capital.

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11

Brasley, Richard A. "Portfolio Theory Versus Portfolio Practice." Journal of Portfolio Management 16, no. 4 (July 31, 1990): 6–10. http://dx.doi.org/10.3905/jpm.1990.6.

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12

ISHII, Hiroaki. "Portfolio Theory." Journal of Japan Society for Fuzzy Theory and Systems 10, no. 2 (1998): 236–41. http://dx.doi.org/10.3156/jfuzzy.10.2_56.

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13

Zhao, Daping, Yong Fang, Chaoliang Zhang, and Zongrun Wang. "Portfolio Selection Based on Bayesian Theory." Mathematical Problems in Engineering 2019 (October 20, 2019): 1–11. http://dx.doi.org/10.1155/2019/4246903.

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The traditional portfolio selection model seriously overestimates its theoretic optimal return. Aiming at this problem, two portfolio selection models are proposed to modify the parameters and enhance portfolio performance based on Bayesian theory. Firstly, a Bayesian-GARCH(1,1) model is built. Secondly, Markov Chain is applied to curve the parameters’ state transfer, and a Bayesian Markov regime-Switching-GARCH(1,1) model is constructed. Both the two models can handle the overestimation problem and can obtain self-financing portfolios. In the numerical experiments, both the models are examined with data from China stock market, and their performances are compared and analyzed. The results show that BMS-GARCH(1,1) model is superior to the Bayesian-GARCH(1,1) model.

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Mittal, Saksham, Sujoy Bhattacharya, and Satrajit Mandal. "Characteristics analysis of behavioural portfolio theory in the Markowitz portfolio theory framework." Managerial Finance 48, no. 2 (November 3, 2021): 277–88. http://dx.doi.org/10.1108/mf-05-2021-0208.

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PurposeIn recent times, behavioural models for asset allocation have been getting more attention due to their probabilistic modelling for scenario consideration. Many investors are thinking about the trade-offs and benefits of using behavioural models over conventional mean-variance models. In this study, the authors compare asset allocations generated by the behavioural portfolio theory (BPT) developed by Shefrin and Statman (2000) against the Markowitz (1952) mean-variance theory (MVT).Design/methodology/approachThe data used have been culled from BRICS countries' major index constituents from 2009 to 2019. The authors consider a single period economy and generate future probable outcomes based on historical data in order to determine BPT optimal portfolios.FindingsThis study shows that a fair number of portfolios satisfy the first entry constraint of the BPT model. BPT optimal portfolio exhibits high risk and higher returns as compared to typical Markowitz optimal portfolio.Originality/valueThe BRICS countries' data were used because the dynamics of the emerging markets are significantly different from the developed markets, and many investors have been considering emerging markets as their new investment avenues.

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15

Zinkhan, F. Christian. "Forestry Projects, Modern Portfolio Theory, and Discount Rate Selection." Southern Journal of Applied Forestry 12, no. 2 (May 1, 1988): 132–35. http://dx.doi.org/10.1093/sjaf/12.2.132.

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Abstract According to modern portfolio theory, only that portion of risk that cannot be diversified away by investors is relevant. Given this assumption, this paper illustrates that timberland investments can offer substantial risk-reduction benefits for investors holding diversified portfolios. With the opportunity for these benefits, it is found that the current required rate of return on an investment in southern timberland is less than the rate on U.S. Treasury bills. Utilizing one of the foundations of modern portfolio theory, an approach is presented for selecting a discount rate for long-term forestry projects undertaken either by individuals with diversified portfolios or by corporations with shareholders owning diversified portfolios. South J. Appl. For. 12(2):132-135

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16

Yang, Hyunjun, Hyeonjun Park, and Kyungjae Lee. "A Selective Portfolio Management Algorithm with Off-Policy Reinforcement Learning Using Dirichlet Distribution." Axioms 11, no. 12 (November 23, 2022): 664. http://dx.doi.org/10.3390/axioms11120664.

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Existing methods in portfolio management deterministically produce an optimal portfolio. However, according to modern portfolio theory, there exists a trade-off between a portfolio’s expected returns and risks. Therefore, the optimal portfolio does not exist definitively, but several exist, and using only one deterministic portfolio is disadvantageous for risk management. We proposed Dirichlet Distribution Trader (DDT), an algorithm that calculates multiple optimal portfolios by taking Dirichlet Distribution as a policy. The DDT algorithm makes several optimal portfolios according to risk levels. In addition, by obtaining the pi value from the distribution and applying importance sampling to off-policy learning, the sample is used efficiently. Furthermore, the architecture of our model is scalable because the feed-forward of information between portfolio stocks occurs independently. This means that even if untrained stocks are added to the portfolio, the optimal weight can be adjusted. We also conducted three experiments. In the scalability experiment, it was shown that the DDT extended model, which is trained with only three stocks, had little difference in performance from the DDT model that learned all the stocks in the portfolio. In an experiment comparing the off-policy algorithm and the on-policy algorithm, it was shown that the off-policy algorithm had good performance regardless of the stock price trend. In an experiment comparing investment results according to risk level, it was shown that a higher return or a better Sharpe ratio could be obtained through risk control.

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17

Dubrovin, Valerii, Larysa Deineha, and Valerii Laktionov. "Energy saving at energy-intensive enterprises." Electrical Engineering and Power Engineering, no. 2 (June 30, 2022): 58–68. http://dx.doi.org/10.15588/1607-6761-2022-2-6.

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Purpose. Investigate the methods of decision-making in the project portfolio management, as well as perform their software implementation as part of the system of the portfolio management optimization of energy saving projects at energy-intensive enterprises. Methodology. To achieve this goal, Markovitz's portfolio theory was chosen - the theory of financial investment, in which the methods of optimization are the most profitable distribution of the risk of the securities portfolio and income valuation. In combination with portfolio theory, methods were used to find the maximum Sharpe coefficient and minimum volatility according to randomly generated portfolios. Findings. Methods of portfolio management of energy saving projects are considered through their generalization to the methods of optimization of investment portfolios, but taking into account the specifics of the subject area. A software application has been developed and tested that automatically downloads data for certain stocks for a certain period from an electronic resource, generates random portfolios and optimizes them by maximizing the Sharpe ratio and minimizing portfolio volatility. Composing a portfolio of investments from four stocks traded on the stock exchange, the return and risk of the portfolio with different types of optimization were calculated. The application implements graphical display of portfolio optimization results in the form of tables and graphs. The first graph shows the changes in each stock over a given period of time. The following is a graph of daily profitability instead of actual prices, where you can see the volatility of shares. The simulated portfolio optimization based on the effective limit is graphically presented - the line along which the points will give the least risk to the target return and the calculated optimization of the portfolio based on the effective limit. The graphs and tables built by the program allow the user to better assess the created portfolio of the energy saving project. Originality. The approach proposed in this paper is a combination of methods for optimizing the investment portfolio according to Markovitz's portfolio theory and methods for finding the maximum Sharpe coefficient and minimum volatility in one software application to solve a wide range of problems. Practical value. The completed development has significant practical value, as it allows you to optimize quickly the financial portfolio for any assets, which allows, among other things, to use the system to optimize the management of portfolios of energy saving projects in energy-intensive enterprises. In addition, it can be the basis or model for a similar development.

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Famara Badji, Cherif, Cristiane Benetti, and Renato Guimaraes. "Diversification Benefits of European REIT, Equities and Bonds." New Challenges in Accounting and Finance 6 (November 2021): 31–49. http://dx.doi.org/10.32038/ncaf.2021.06.03.

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This study aims to demonstrate the benefits related to the inclusion of European REIT in a portfolio of stocks and bonds traded on European markets. Major studies of the portfolio’s diversification those considered REIT was carried out on the American real estate market. Therefore, this research project aims to extend the work to the European scale by forming a mixed pan‐European REIT portfolio. The database is composed of monthly dividend‐adjusted closing prices, over the past 11 years, from different stock indexes collected during eleven years of different European market indexes. Four hypothetic portfolios were constructed to test our hypothesis. Descriptive statistics and correlations were presented. Therefore, the results have shown that European REIT has reduced the risk of a mixed portfolio even if the risk reduction is very limited. The same is true for the portfolio’s return, which was slightly improved. The study showed that European REIT remains a factor of diversification that should not be overlooked in building an asset portfolio. These findings contribute to the existing portfolio theory arguing that using REITs in portfolio diversification helps investors dilute their risk and improve their returns. Our results also have practical implications. They can be useful to investors and financial analysts in their investment decisions by shedding light on this type of asset.

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Potrykus, Marcin. "ASSESSMENT OF GOLD AND/OR CRUDE OIL AS INVESTMENTS FOR PORTFOLIO DIVERSIFICATION. A WARSAW STOCK EXCHANGE CASE STUDY." Acta Scientiarum Polonorum. Oeconomia 18, no. 4 (December 30, 2019): 77–84. http://dx.doi.org/10.22630/aspe.2019.18.4.47.

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The purpose of the study is to assess whether the inclusion of investments in gold and/or crude oil improves an investment portfolio consisting of shares of enterprises included in the WIG20 index (traditional investments). All possible combinations of investment portfolios with minimal risk and maximum efficiency were tested. The portfolios were determined based on Markowitz’s portfolio theory. All results were compared with a naive strategy. In total, nearly 55,000 investment portfolios consisting of three, four or five investments were constructed. The study showed that the application of portfolio theory contributes to obtaining better results than a naive strategy. The minimum risk portfolios that included gold and crude oil showed a risk reduction of 0.39 p.p. on average and a maximum cumulative loss of 7.85 p.p. on average. Portfolios with maximum efficiency achieved an average increase in the rate of return of the investment portfolio of 0.024 p.p. and an average increase in efficiency of 0.0256.

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van Bilsen, Servaas, Ilja A. Boelaars, and A. Lans Bovenberg. "The Duration Puzzle in Life-Cycle Investment*." Review of Finance 24, no. 6 (March 17, 2020): 1271–311. http://dx.doi.org/10.1093/rof/rfaa009.

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Abstract By analyzing the portfolio allocations of target date funds (TDFs), we document that the observed durations of TDF portfolios are inconsistent with the durations predicted by classical portfolio theory. We call this stylized fact the duration puzzle. We investigate to what extent several extensions of classical portfolio theory can explain the duration puzzle. More specifically, we consider the impact of human capital, inflation risk, and portfolio restrictions on the duration of the optimal portfolio. We find that it is difficult to explain the duration puzzle, especially for individuals aged between 35 and 65 years.

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Ćosić, Karlo, and Anita Čeh Časni. "The impact of cryptocurrency on the efficient frontier of emerging markets." Croatian Review of Economic, Business and Social Statistics 5, no. 2 (December 1, 2019): 64–75. http://dx.doi.org/10.2478/crebss-2019-0012.

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AbstractCryptocurrencies are a sweltering topic in modern times of investment strategies. Since the cryptocurrency market is classified as an emerging market, in this paper a portfolio of emerging markets is compiled from the indices of four European Union (EU) countries and one cryptocurrency. The aim of this paper is to investigate how the incorporation of the Bitcoin cryptocurrency into the portfolio affects the performance of the portfolios of these countries. Moreover, by drawing an efficient frontier, the paper identifies where Bitcoin stands relative to other indices in the portfolio. The countries whose indices were used in the analysis are: Croatia, Hungary, Romania and Poland during the period from July 13, 2018 to June 07, 2019. The method used for an efficient frontier formation is Markowitz’s Modern Portfolio Theory (MPT). By applying this theory, the minimum variance portfolio at the efficient frontier was created for the portfolio with and without the cryptocurrency. The empirical analysis indicates that Bitcoin improves the effectiveness of the portfolio in emerging markets of the selected EU countries, where the expected risks of a portfolio that includes the cryptocurrency are smaller and with higher returns than those of portfolios without Bitcoin. From the Markowitz’s theory point of view, the results of the empirical analysis also indicate that Bitcoin is on the efficient frontier. Since all instruments on the efficient frontier according to the modern portfolio theory are efficient, it can be concluded that investments in such instruments depend on investor’s risk aversion.

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BAYAT, Fikret, and Şule Yüksel YİĞİTER. "COMPARISON OF DOWN-SIDE RISK MEASUREMENTS AND MODERN PORTFOLIO THEORY: THE EXAMPLE OF BORSA ISTANBUL." Kafkas Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi 13, no. 25 (June 29, 2022): 1–23. http://dx.doi.org/10.36543/kauiibfd.2022.001.

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The concept of risk entered the portfolio world with the work of Harry Markowitz. By considering risk and return together, Markowitz accepts the return distribution symmetrically to create optimal portfolios so that investors can obtain the least risk (variance) and the highest return. When the return distribution is symmetrical, variance can give accurate results as an indicator of risk. But what if the returns show an asymmetrical distribution, can this be the case? Based on this question, the purpose of our research is to compare the portfolio return, risk and covariances of 10 different stocks traded in BIST100 between 1.1.2011-31.4.2021 according to Modern Portfolio theory and Downside risk criteria. In our study, it has been found that Modern Portfolio does not diversify sufficiently, creates portfolios from stocks with high return-risk features, and when the returns do not show a symmetrical distribution, it is insufficient. On the contrary, it has been understood that portfolios created against downside risk measures contain less risk and that more accurate results can be achieved with downside risk measures in asymmetric return distribution.

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Huang, Zi’an. "Investment Portfolio Management Based on Realistic US’s Stock Data with Two Models." BCP Business & Management 26 (September 19, 2022): 929–36. http://dx.doi.org/10.54691/bcpbm.v26i.2055.

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Portfolio theory is widely used in the financial field. Let us Suppose we combine the modern investment portfolio theory and diversify the investment portfolio. In that case, we can reduce investment risks and increase the possibility of satisfying all kinds of investors to obtain investment returns. In this article, we mainly consider applying the Markowitz model and the index model in portfolio theory, trying to explore its rate of return in the US market. We found that in the constructed investment portfolio, the portfolio’s return and Sharpe ratio constructed by the Markowitz model are consistent with the performance of the index model. This provides investors with a new investment perspective for portfolio construction.

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MÜLLER, Heinz H. "Modern Portfolio Theory." ASTIN Bulletin 19, no. 3 (November 1, 1989): 9–27. http://dx.doi.org/10.2143/ast.19.3.2014899.

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Shefrin, Hersh, and Meir Statman. "Behavioral Portfolio Theory." Journal of Financial and Quantitative Analysis 35, no. 2 (June 2000): 127. http://dx.doi.org/10.2307/2676187.

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Madan, Dilip B. "Instantaneous portfolio theory." Quantitative Finance 18, no. 8 (February 13, 2018): 1345–64. http://dx.doi.org/10.1080/14697688.2017.1420210.

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Kitt, R., and J. Kalda. "Leptokurtic portfolio theory." European Physical Journal B 50, no. 1-2 (February 20, 2006): 141–45. http://dx.doi.org/10.1140/epjb/e2006-00062-8.

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Shipway, I. "Modern Portfolio Theory." Trusts & Trustees 15, no. 2 (January 27, 2009): 66–71. http://dx.doi.org/10.1093/tandt/ttn129.

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Fu, Yufen, and George W. Blazenko. "Normative portfolio theory." International Review of Financial Analysis 52 (July 2017): 240–51. http://dx.doi.org/10.1016/j.irfa.2017.07.002.

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Jiang, Wei Na, Bin Shan Ju, Guang Hua Zhai, Ya Qiang Chen, and Liang Wei. "Study on Application of Markowitz’s Portfolio Selection Theory in Overseas Petroleum Venture Investment Decision." Advanced Materials Research 1051 (October 2014): 1045–50. http://dx.doi.org/10.4028/www.scientific.net/amr.1051.1045.

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Markowitz’s portfolio selection theory was applied in overseas petroleum venture capital investment, the mean of each project’s AT cash was used as the portfolio’s return, the fluctuate rate return of project was used to reflect portfolio’s risk, the combination of minimum risk portfolio optimization decision model was established. A variety of risk definition method were explored, efficient frontier under variety of risk-defined were developed, according to different risk preferences, the investment decision-makers can choose optimal portfolio to maximize investment, so as to reduce and avoid undue loss.

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Sheng, Jiliang, Jian Wang, and Jun Yang. "Regret Theory and Equilibrium Asset Prices." Mathematical Problems in Engineering 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/912652.

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Regret theory is a behavioral approach to decision making under uncertainty. In this paper we assume that there are two representative investors in a frictionless market, a representative active investor who selects his optimal portfolio based on regret theory and a representative passive investor who invests only in the benchmark portfolio. In a partial equilibrium setting, the objective of the representative active investor is modeled as minimization of the regret about final wealth relative to the benchmark portfolio. In equilibrium this optimal strategy gives rise to a behavioral asset priciting model. We show that the market beta and the benchmark beta that is related to the investor’s regret are the determinants of equilibrium asset prices. We also extend our model to a market with multibenchmark portfolios. Empirical tests using stock price data from Shanghai Stock Exchange show strong support to the asset pricing model based on regret theory.

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Leković, Miljan. "Historical development of portfolio theory." Tehnika 76, no. 2 (2021): 220–27. http://dx.doi.org/10.5937/tehnika2102220l.

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Portfolio theory occupies an essential place in modern finance, while portfolio management grounded on its achievements has been recognized as one of the main tasks of financial experts worldwide. Taking into account the previous, the research aims to understand the development process of portfolio theory profoundly and to familiarize the investment community with the basic features of each of its phases: traditional, modern, and post-modern portfolio theory, with inevitable comparative analysis of these theories and presentation of their positive and negative aspects. The rationale of implementing an analysis of the evolutionary process of portfolio theory lies in the intention to provide a systematic overview of the development of theoretical thought within this area and grounded on the belief that accumulated knowledge in the field of portfolio theory and portfolio management is one of the most valuable knowledge assets of contemporary society.

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Wise, A. J. "Matching and portfolio selection: Part 1." Journal of the Institute of Actuaries 114, no. 1 (June 1987): 113–33. http://dx.doi.org/10.1017/s0020268100019028.

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1.1 My paper entitled ‘The Matching of Assets to Liabilities’ described a new study of the subject of matching. The paper outlined the mathematical framework, showed some calculations, and suggested various applications in the field of actuarial valuation.1.2 Subsequently A. D. Wilkie published a note entitled ‘Portfolio Selection in the Presence of Fixed Liabilities: a Comment on “The Matching of Assets to Liabilities”’. Wilkie's note appears to represent a new extension of portfolio selection theory which enables him to encompass the conventional portfolio theory and to show where my approach to matching fits into the picture.1.3 This paper is in the nature of a reply to that of Wilkie. My objective at the stage of the first draft was to re-examine the matching portfolio, as defined in relation to specified liabilities, in view of the wide range of alternative portfolios which Wilkie has described. The scope of this work progressed well beyond my original plans when I found a most interesting mathematical relationship between the ‘matching portfolios’ described in my earlier paper and the ‘efficient portfolios’ described in Wilkie's.

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Weng, Y. H., K. A. Crowe, W. H. Parker, D. Lindgren, M. S. Fullarton, and K. J. Tosh. "Using portfolio theory to improve yield and reduce risk in black spruce family reforestation." Silvae Genetica 62, no. 1-6 (December 1, 2013): 232–38. http://dx.doi.org/10.1515/sg-2013-0028.

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AbstractFamily forestry, defined as the deployment of families in mixture into plantations, is becoming an attractive option for black spruce (Picea mariana (Mill.) BSP) in New Brunswick, Canada. With many elite families of black spruce being available, there is a knowledge gap regarding how to compose a mixture of families that optimally balances the objectives of increased yield and reduced risk. This study, based on real field test data, investigates the application of a model based on the modern portfolio theory to optimally balance yield and risk when selecting a portfolio (mixture) of black spruce families to deploy in reforestation. The risk was expressed as the variance of the family portfolio, an effective indicator of yield stability. This is an innovative approach in forestry and it is compared to the currently used method, truncation-deployment, defined as the equal deployment of seed of selected families. Results show that the portfolio theory searched for the combination of yield and stability and produced family portfolios maximizing yield at a given stability or minimizing yield instability at a given yield. The portfolio theory was never inferior in maximizing yield to the truncation- deployment approach when yield stability is a concern. We recommend using portfolio theory to determine family portfolios for family forestry. While this study targets to family forestry, the results may be relevant to other deployment strategies where stability is a concern, such as clonal forestry.

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Campbell, Steven, and Ting-Kam Leonard Wong. "Functional Portfolio Optimization in Stochastic Portfolio Theory." SIAM Journal on Financial Mathematics 13, no. 2 (May 5, 2022): 576–618. http://dx.doi.org/10.1137/21m1417715.

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Bowman, H. Woods. "Toward a Theory of Membership Association Finance." Nonprofit and Voluntary Sector Quarterly 46, no. 4 (March 1, 2017): 772–93. http://dx.doi.org/10.1177/0899764016685860.

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This article explores patterns in membership associations’ portfolios. It compares and contrasts portfolio theory, which predicts variety in revenue portfolios, with a newer benefits theory, which postulates that revenue options are constrained by the balance between the member benefits and societal benefits they produce. The research makes use of a new database that more accurately measures dues and program service revenue of associations than other databases. The weight of the evidence supports benefits theory more strongly than revenue portfolio theory. This research incidentally finds that revenue concentration increases with size and decreases with real estate ownership. The article introduces the concepts of one-off entry and exit costs on members (tariffs), which tend to reduce members’ sensitivity to the level of dues. Indeed, dues are often dominant among the associations having presumptively high tariffs, such as trade unions and certain recreational clubs.

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Jones, C. Kenneth. "Portfolio Size in Stochastic Portfolio Networks Using Digital Portfolio Theory." Journal of Mathematical Finance 03, no. 02 (2013): 280–90. http://dx.doi.org/10.4236/jmf.2013.32028.

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Cuchiero, Christa, Walter Schachermayer, and Ting‐Kam Leonard Wong. "Cover's universal portfolio, stochastic portfolio theory, and the numéraire portfolio." Mathematical Finance 29, no. 3 (October 2018): 773–803. http://dx.doi.org/10.1111/mafi.12201.

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Giemza, Dawid. "Ranking of optimal stock portfolios determined on the basis of expected utility maximization criterion." Journal of Economics and Management 43 (2021): 154–78. http://dx.doi.org/10.22367/jem.2021.43.08.

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Aim/purpose – The aim of the paper is to rank the optimal portfolios of shares of com- panies listed on the Warsaw Stock Exchange, taking into account the investor’s propen- sity to risk. Design/methodology/approach – Investment portfolios consisting of varied number of companies selected from WIG 20 index were built. Next, the weights of equity holdings of these companies in the entire portfolio were determined, maximizing portfolio’s expected (square) utility function, and then the obtained structures were compared between investors with various levels of risk propensity. Using Hellwig’s taxonomic development measure, a ranking of optimum stock portfolios depending on the inves- tor’s risk propensity was prepared. The research analyzed quotations from 248 trading sessions. Findings – The findings indicated that whilst there are differences in the weight struc- tures of equity holdings in the entire portfolio between the investor characterized by aversion to risk at the level of γ = 10 and the investor characterized by aversion to risk at the level of γ = 100, the rankings of the constructed optimum portfolios demonstrate strong similarity. The study validated, in conformity with the literature, that with the increase in the number of equity holdings in the portfolio, the portfolio risk initially decreases and then becomes stable at a certain level. Research implications/limitations – The study used data from the past as for which there is no guarantee that they will be adequate for the future. There is sensitivity to the selection of the period from which the historic data come. When changing the period of the analyzed historic data by a small time unit it may prove that the portfolio composi- tion will become totally different. Originality/value/contribution – The paper compares the composition of optimum stock portfolios depending on the investor’s propensity to risk. Their ranking was cre- ated using the taxonomic method for this purpose. Taking advantage of this method also additional variables can be taken into account, which describe and differentiate the port- folio and they can be assigned relevant significance depending on the investor’s prefer- ences. Keywords: optimal portfolio, expected rate of return on the portfolio, portfolio standard deviation, expected utility theory, multidimensional comparative analysis. JEL Classification: G10, G11.

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Choi, Jay Pil, and Heiko Gerlach. "A Theory of Patent Portfolios." American Economic Journal: Microeconomics 9, no. 1 (February 1, 2017): 315–51. http://dx.doi.org/10.1257/mic.20150003.

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This paper develops a theory of patent portfolios in which firms accumulate an enormous amount of related patents, which makes it impractical to develop new products that avoid inadvertent infringement. We show that patent peace arises if product market competition is weak and patent portfolios are either sufficiently weak or sufficiently strong with comparable size. An increase in one firm's patent portfolio reduces the innovation incentives of its rivals but does not necessarily increase its own. Firms with larger patent portfolios have stronger incentives to acquire additional patents, while consumers may be better off if firms with weaker portfolios acquire them. (JEL D43, K11, L13, O34)

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Назарова, Elena Nazarova, Жданова, and O. Zhdanova. "Theories of Investment Portfolio Optimization." Economics of the Firm 5, no. 4 (December 18, 2016): 51–57. http://dx.doi.org/10.12737/24442.

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The article presents an analysis of the theories of the investment portfolio optimization, characterizes diversification strategies, gives the evaluation of the Russian theory of optimization of investment portfolios.

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De Brouwer, Philippe J. S. "Maslowian Portfolio Theory: An alternative formulation of the Behavioural Portfolio Theory." Journal of Asset Management 9, no. 6 (February 2009): 359–65. http://dx.doi.org/10.1057/jam.2008.35.

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Cochrane, John H. "Portfolios for Long-Term Investors." Review of Finance 26, no. 1 (December 27, 2021): 1–42. http://dx.doi.org/10.1093/rof/rfab038.

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Abstract How should long-term investors form portfolios in our time-varying, multi-factor and friction-filled world? Two conceptual frameworks may help: first, look directly at the stream of payments that a portfolio and payout policy can produce. Second, include a general equilibrium view of the markets’ economic purpose, and the nature of investors’ different preferences, risk-taking ability, and function in that equilibrium. These perspectives can rationalize some of investors’ behaviors, suggest substantial revisions to standard portfolio theory, and help us to apply portfolio theory in a way that is useful in practice.

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Beresford‐Smith, Bryan, and Colin J. Thompson. "An info‐gap approach to managing portfolios of assets with uncertain returns." Journal of Risk Finance 10, no. 3 (May 22, 2009): 277–87. http://dx.doi.org/10.1108/15265940910959393.

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PurposeThe purpose of this paper is to provide a quantitative methodology based on information‐gap decision theory for dealing with (true) Knightian uncertainty in the management of portfolios of assets with uncertain returns.Design/methodology/approachPortfolio managers aim to maximize returns for given levels of risk. Since future returns on assets are uncertain the expected return on a portfolio of assets can be subject to significant uncertainty. Information‐gap decision theory is used to construct portfolios that are robust against uncertainty.FindingsUsing the added dimensions of aspirational parameters and performance requirements in information‐gap theory, the paper shows that one cannot simultaneously have two robust‐optimal portfolios that outperform a specified return and a benchmark portfolio unless one of the portfolios has arbitrarily large long and short positions.Research limitations/implicationsThe paper has considered only one uncertainty model and two performance requirements in an information‐gap analysis over a particular time frame. Alternative uncertainty models could be introduced and benchmarking against proxy portfolios and competitors are examples of additional performance requirements that could be incorporated in an information‐gap analysis.Practical implicationsAn additional methodology for applying information‐gap modeling to portfolio management has been provided.Originality/valueThis paper provides a new and novel approach for managing portfolios in the face of uncertainties in future asset returns.

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Nyang'iye, Samson Akumu, Cyrus Iraya, and Duncan Elly Ochieng. "Residential Mortgage Portfolio, Product Innovation and Performance of Commercial Banks in Kenya." European Journal of Business and Management Research 7, no. 3 (June 2, 2022): 184–93. http://dx.doi.org/10.24018/ejbmr.2022.7.3.1439.

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This study sought to investigate the relationship between residential mortgage portfolios, product innovation, and performance of commercial banks in Kenya. The study was anchored on the Modern Portfolio Theory, Agency Theory, and Asymmetric Information Theory. The study adopted a correlational descriptive research design and data collected from the annual residential mortgage surveys conducted by the central bank of Kenya (CBK) on commercial banks covering a 13-year period from 2006 to 2018. Further, the financial statements of commercial banks and Kenya Bankers Association database were used as a source of secondary data. Data were analyzed via panel data approaches. The Baron and Kenny (1986) approach was used to test the hypothesis. The results revealed that residential mortgage portfolio attributes, namely: portfolio quality and mortgage interest return significantly influence bank performance. The effect of mortgage terms on the relationship between mortgage portfolio quality and performance was negative and statistically significant. Loan to value (LTV) ratio was however found not to significantly intervene in the relationship between residential mortgage portfolios and the performance of banks operating in Kenya. From the findings, the study suggested that bank managers pay attention to the institutional environment and product characteristics in designing their mortgage loan portfolios.

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Maier-Paape, Stanislaus, and Qiji Zhu. "A General Framework for Portfolio Theory. Part II: Drawdown Risk Measures." Risks 6, no. 3 (August 7, 2018): 76. http://dx.doi.org/10.3390/risks6030076.

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The aim of this paper is to provide several examples of convex risk measures necessary for the application of the general framework for portfolio theory of Maier-Paape and Zhu (2018), presented in Part I of this series. As an alternative to classical portfolio risk measures such as the standard deviation, we, in particular, construct risk measures related to the “current” drawdown of the portfolio equity. In contrast to references Chekhlov, Uryasev, and Zabarankin (2003, 2005), Goldberg and Mahmoud (2017), and Zabarankin, Pavlikov, and Uryasev (2014), who used the absolute drawdown, our risk measure is based on the relative drawdown process. Combined with the results of Part I, Maier-Paape and Zhu (2018), this allows us to calculate efficient portfolios based on a drawdown risk measure constraint.

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Boloș, Marcel-Ioan, Ioana-Alexandra Bradea, and Camelia Delcea. "Neutrosophic Portfolios of Financial Assets. Minimizing the Risk of Neutrosophic Portfolios." Mathematics 7, no. 11 (November 3, 2019): 1046. http://dx.doi.org/10.3390/math7111046.

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This paper studies the problem of neutrosophic portfolios of financial assets as part of the modern portfolio theory. Neutrosophic portfolios comprise those categories of portfolios made up of financial assets for which the neutrosophic return, risk and covariance can be determined and which provide concomitant information regarding the probability of achieving the neutrosophic return, both at each financial asset and portfolio level and also information on the probability of manifestation of the neutrosophic risk. Neutrosophic portfolios are characterized by two fundamental performance indicators, namely: the neutrosophic portfolio return and the neutrosophic portfolio risk. Neutrosophic portfolio return is dependent on the weight of the financial assets in the total value of the portfolio but also on the specific neutrosophic return of each financial asset category that enters into the portfolio structure. The neutrosophic portfolio risk is dependent on the weight of the financial assets that enter the portfolio structure but also on the individual risk of each financial asset. Within this scientific paper was studied the minimum neutrosophic risk at the portfolio level, respectively, to establish what should be the weight that the financial assets must hold in the total value of the portfolio so that the risk is minimum. These financial assets weights, after calculations, were found to be dependent on the individual risk of each financial asset but also on the covariance between two financial assets that enter into the portfolio structure. The problem of the minimum risk that characterizes the neutrosophic portfolios is of interest for the financial market investors. Thus, the neutrosophic portfolios provide complete information about the probabilities of achieving the neutrosophic portfolio return but also of risk manifestation probability. In this context, the innovative character of the paper is determined by the use of the neutrosophic triangular fuzzy numbers and by the specific concepts of financial assets, in order to substantiating the decisions on the financial markets.

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Cenci, Marisa, Massimiliano Corradini, and Andrea Gheno. "Dynamic Portfolio Selection in a Dual Expected Utility Theory Framework." ASTIN Bulletin 36, no. 02 (November 2006): 505–20. http://dx.doi.org/10.2143/ast.36.2.2017932.

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In this paper the dynamic portfolio selection problem is studied for the first time in a dual utility theory framework. The Wang transform is used as distortion function and well diversified optimal portfolios result both with and without short sales allowed.

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Cenci, Marisa, Massimiliano Corradini, and Andrea Gheno. "Dynamic Portfolio Selection in a Dual Expected Utility Theory Framework." ASTIN Bulletin 36, no. 2 (November 2006): 505–20. http://dx.doi.org/10.1017/s0515036100014616.

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In this paper the dynamic portfolio selection problem is studied for the first time in a dual utility theory framework. The Wang transform is used as distortion function and well diversified optimal portfolios result both with and without short sales allowed.

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Prastiwi, Muji Sri, Badrun Kartowagiran, and Endang Susantini. "Assessing Using Technology: Is Electronic Portfolio Effective To Assess the Scientific Literacy on Evolution Theory." International Journal of Emerging Technologies in Learning (iJET) 15, no. 12 (June 26, 2020): 230. http://dx.doi.org/10.3991/ijet.v15i12.12227.

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This study used a sequential exploratory mixed method to examine the effectiveness of using an electronic portfolio to assess the scientific literacy of evolution theory. As much as 135 university students majoring in biology education were involved as research participants. They were asked to create the electronic portfolio by using any learning artifacts produced during the classroom activities including direct and virtual practicums, reading activities, direct and online discussions, quizzes, and formative examinations. Evolutionary Scientific Literacy by electronic portfolio consists of Scientific Literacy skills namely Nominal, Functional, Conceptual, Multidimensional levels, and electronic portfolios skills namely beginner, intermediate, proficient and advanced level. The results depicted that the Evolutionary Scientific Literacy skills of students were at the beginner-nominal level (71.4%) and the advanced-multidimensional level (9.5%). Another finding disclosed was that students showed a positive response to the electronic portfolio creation. This study suggests that an electronic portfolio can be used as an assessment tool of the scientific literacy of evolution theory relevant to industrial revolution 4.0.

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