Journal articles on the topic 'Optimal portfolio strategy'
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1
Mroua, Mourad, and Fathi Abid. "Portfolio revision and optimal diversification strategy choices." International Journal of Managerial Finance 10, no. 4 (August 26, 2014): 537–64. http://dx.doi.org/10.1108/ijmf-07-2012-0085.
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Purpose – Since equity markets have a dynamic nature, the purpose of this paper is to investigate the performance of a revision procedure for domestic and international portfolios, and provides an empirical selection strategy for optimal diversification from an American investor's point of view. This paper considers the impact of estimation errors on the optimization processes in financial portfolios. Design/methodology/approach – This paper introduces the concept of portfolio resampling using Monte Carlo method. Statistical inferences methodology is applied to construct the sample acceptance regions and confidence regions for the resampled portfolios needing revision. Tracking error variance minimization (TEVM) problem is used to define the tracking error efficient frontiers (TEEF) referring to Roll (1992). This paper employs a computation method of the periodical after revision return performance level of the dynamic diversification strategies considering the transaction cost. Findings – The main finding is that the global portfolio diversification benefits exist for the domestic investors, in both the mean-variance and tracking error analysis. Through TEEF, the dynamic analysis indicates that domestic dynamic diversification outperforms international major and emerging diversification strategies. Portfolio revision appears to be of no systematic benefit. Depending on the revision of the weights of the assets in the portfolio and the transaction costs, the revision policy can negatively affect the performance of an investment strategy. Considering the transaction costs of portfolios revision, the results of the return performance computation suggest the dominance of the global and the international emerging markets diversification over all other strategies. Finally, an assessment between the return and the cost of the portfolios revision strategy is necessary. Originality/value – The innovation of this paper is to introduce a new concept of the dynamic portfolio management by considering the transaction costs. This paper investigates the performance of a revision procedure for domestic and international portfolios and provides an empirical selection strategy for optimal diversification. The originality of the idea consists on the application of a new statistical inferences methodology to define portfolios needing revision and the use of the TEVM algorithm to define the tracking error dynamic efficient frontiers.
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Kashif, Muhammad, Francesco Menoncin, and Iqbal Owadally. "Optimal portfolio and spending rules for endowment funds." Review of Quantitative Finance and Accounting 55, no. 2 (November 18, 2019): 671–93. http://dx.doi.org/10.1007/s11156-019-00856-x.
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AbstractWe investigate the role of different spending rules in a dynamic asset allocation model for university endowment funds. In particular, we consider the fixed consumption-wealth ratio (CW) rule and the hybrid rule which smoothes spending over time. We derive the optimal portfolios under these two strategies and compare them with a theoretically optimal (Merton) strategy. We show that the optimal portfolio with habit is less risky compared to the optimal portfolio without habit. A calibrated numerical analysis on U.S. data shows, similarly, that the optimal portfolio under the hybrid strategy is less risky than the optimal portfolios under both the CW and the classical Merton strategies, in typical market conditions. Our numerical analysis also shows that spending under the hybrid strategy is less volatile than the other strategies. Thus, endowments following the hybrid spending rule use asset allocation to protect spending. However, in terms of the endowment’s wealth, the hybrid strategy comparatively outperforms the conventional Merton and CW strategies when the market is highly volatile but under-performs them when there is strong stock market growth and low volatility. Overall, the hybrid strategy is effective in terms of stability of spending and intergenerational equity because, even if it allows short-term fluctuation in spending, it ensures greater stability in the long run.
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Li, Longqing. "Simulation-Based Optimal Portfolio Selection Strategy—Evidence from Asian Markets." Applied Economics and Finance 5, no. 5 (July 13, 2018): 1. http://dx.doi.org/10.11114/aef.v5i4.3376.
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Recently portfolio optimization has become widely popular in risk management, and the common practice is to use mean-variance or Value-at-Risk (VaR), despite the VaR being incoherent risk measure because of the lack of subadditivity. This has led to the emergence of the conditional value-at-risk (CVaR) approach, consequently, a gradual development of mean-CVaR portfolio optimization. To seek an optimal portfolio selection strategy and increase the robustness of the result, the paper studies the performance of portfolio optimization in Asian markets using a Monte-Carlo simulation tool, creates a variety of randomly selected portfolios that consists of Asian ADRs listed in NYSE from 2011 to 2016, and applies both optimization frameworks with different skewed fat-tailed distributions, including the Generalized Hyperbolic (GH) and skewed-T distribution. The main result shows that the Generalized Hyperbolic distribution produces the lowest risk under a given rate of return, while the skewed-T distribution creates a diversification allocation outcome similar to that of historical simulation.
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Li, Longqing. "Simulation-Based Optimal Portfolio Selection Strategy—Evidence from Asian Markets." Applied Economics and Finance 5, no. 5 (July 13, 2018): 1. http://dx.doi.org/10.11114/aef.v5i5.3376.
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Recently portfolio optimization has become widely popular in risk management, and the common practice is to use mean-variance or Value-at-Risk (VaR), despite the VaR being incoherent risk measure because of the lack of subadditivity. This has led to the emergence of the conditional value-at-risk (CVaR) approach, consequently, a gradual development of mean-CVaR portfolio optimization. To seek an optimal portfolio selection strategy and increase the robustness of the result, the paper studies the performance of portfolio optimization in Asian markets using a Monte-Carlo simulation tool, creates a variety of randomly selected portfolios that consists of Asian ADRs listed in NYSE from 2011 to 2016, and applies both optimization frameworks with different skewed fat-tailed distributions, including the Generalized Hyperbolic (GH) and skewed-T distribution. The main result shows that the Generalized Hyperbolic distribution produces the lowest risk under a given rate of return, while the skewed-T distribution creates a diversification allocation outcome similar to that of historical simulation.
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Nur Safitri, Indah Nur, Sudradjat Sudradjat, and Eman Lesmana. "STOCK PORTFOLIO ANALYSIS USING MARKOWITZ MODEL." International Journal of Quantitative Research and Modeling 1, no. 1 (February 2, 2020): 47–58. http://dx.doi.org/10.46336/ijqrm.v1i1.6.
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A common problem that often occurs in investment is the selection of the optimal portfolio according to the wishes of investors. This thesis ueds the Markowitz Model as a basis to formed a model to choose the optimal portfolio that provided the lowest risk. Efforts to minimize risk were carried out by conducting a diversification strategy. After the selection of several companies with the criteria of capitalization value and DER (Debt Equity Ratio), a combination of stocks is formed to form a portfolio. The formed portfolio was then analyzed to determine the optimal proportion of each stock. Using the Markowitz model, which is then solved by Non Linear Programming, an optimal portfolio is obtained with the proportion of each stock minimizing risk. In general, the results of this analysis indicate that portfolios with more stocks will produce lower risks compared to portfolios with fewer stocks, thus providing optimal diversification solutions, namely portfolios with members of five stocks with optimal risk of 0.886%.
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Demos, Guilherme, Thomas Pires, and Guilherme Valle Moura. "Rebalanceamento Endógeno para Portfólios de Variância Mínima." Brazilian Review of Finance 13, no. 4 (October 25, 2015): 544. http://dx.doi.org/10.12660/rbfin.v13n4.2015.49112.
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Investment managers often rebalance portfolios using it ad-hoc criteria due the trade-off between gains from updating optimal weight and costs incurred from changing the portfolio composition. A common solution for this stalemate is rebalancing the portfolio based on some exogenous criteria. By monitoring the optimal weights of the portfolio through control charts, the authors propose a portfolio rebalance strategy based solely on endogenous information. The optimal portfolio weights are thus monitored daily and if statistical significant changes are detected we either rebalance or not the portfolio thus avoiding transaction costs. The performance of the rebalancing strategy is then compared with different periodical strategies based on indicators such as Turnover and Sharpe-Ratio. Our results suggest that rebalancing strategies based on signals from control charts outperform those based solely on exogenous criteria, thus yielding economical gains to the investor.
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Gunning, Wade, and Gary van Vuuren. "Optimal omega-ratio portfolio performance constrained by tracking error." Investment Management and Financial Innovations 17, no. 3 (September 29, 2020): 263–80. http://dx.doi.org/10.21511/imfi.17(3).2020.20.
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The mean-variance framework coupled with the Sharpe ratio identifies optimal portfolios under the passive investment style. Optimal portfolio identification under active investment approaches, where performance is measured relative to a benchmark, is less well-known. Active portfolios subject to tracking error (TE) constraints lie on distorted elliptical frontiers in return/risk space. Identifying optimal active portfolios, however defined, have only recently begun to be explored. The Ω – ratio considers both down and upside portfolio potential. Recent work has established a technique to determine optimal Ω – ratio portfolios under the passive investment approach. The authors apply the identification of optimal Ω – ratio portfolios to the active arena (i.e., to portfolios constrained by a TE) and find that while passive managers should always invest in maximum Ω – ratio portfolios, active managers should first establish market conditions (which determine the sign of the main axis slope of the constant TE frontier). Maximum Sharpe ratio portfolios should be engaged when this slope is > 0 and maximum Ω – ratios when < 0.
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Maslov, Sergei, and Yi-Cheng Zhang. "Optimal Investment Strategy for Risky Assets." International Journal of Theoretical and Applied Finance 01, no. 03 (July 1998): 377–87. http://dx.doi.org/10.1142/s0219024998000217.
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We design an optimal strategy for investment in a portfolio of assets subject to a multiplicative Brownian motion. The strategy provides the maximal typical long-term growth rate of investor's capital. We determine the optimal fraction of capital that an investor should keep in risky assets as well as weights of different assets in an optimal portfolio. In this approach both average return and volatility of an asset are relevant indicators determining its optimal weight. Our results are particularly relevant for very risky assets when traditional continuous-time Gaussian portfolio theories are no longer applicable.
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Mercurio, Peter Joseph, Yuehua Wu, and Hong Xie. "Portfolio Optimization for Binary Options Based on Relative Entropy." Entropy 22, no. 7 (July 9, 2020): 752. http://dx.doi.org/10.3390/e22070752.
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The portfolio optimization problem generally refers to creating an investment portfolio or asset allocation that achieves an optimal balance of expected risk and return. These portfolio returns are traditionally assumed to be continuous random variables. In An Entropy-Based Approach to Portfolio Optimization, we introduced a novel non-parametric optimization method based on Shannon entropy, called return-entropy portfolio optimization (REPO), which offers a simple and fast optimization algorithm for assets with continuous returns. Here, in this paper, we would like to extend the REPO approach to the optimization problem for assets with discrete distributed returns, such as those from a Bernoulli distribution like binary options. Under a discrete probability distribution, portfolios of binary options can be viewed as repeated short-term investments with an optimal buy/sell strategy or general betting strategy. Upon the outcome of each contract, the portfolio incurs a profit (success) or loss (failure). This is similar to a series of gambling wagers. Portfolio selection under this setting can be formulated as a new optimization problem called discrete entropic portfolio optimization (DEPO). DEPO creates optimal portfolios for discrete return assets based on expected growth rate and relative entropy. We show how a portfolio of binary options provides an ideal general setting for this kind of portfolio selection. As an example we apply DEPO to a portfolio of short-term foreign exchange currency pair binary options from the NADEX exchange platform and show how it outperforms leading Kelly criterion strategies. We also provide an additional example of a gambling application using a portfolio of sports bets over the course of an NFL season and present the advantages of DEPO over competing Kelly criterion strategies.
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Zibri, Arben, and Agim Kukeli. "Does GMVP Strategy Reduce Risk? A Global Asset Approach." Journal of Applied Business Research (JABR) 30, no. 6 (October 29, 2014): 1873. http://dx.doi.org/10.19030/jabr.v30i6.8899.
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<p>This paper studies the out of sample risk reduction of global minimum variance portfolio. The analysis are drown from the discussions of Jagannathan and Ma (2003) regarding the risk reduction in US stock portfolios using portfolio constraints. We estimate the covariance matrix using the sample covariance matrix approach and derive optimal minimum variance portfolios considering upper/lower bounds and no restrictions. Results are shown under different revision frequency and transaction costs assumed. The data used are monthly indices of stocks, bonds, gold oil and spreads from 1996 until 2013. Unconstrained GMVPs result in the lowest out of sample variance, while unconstrained GMVPs of global bond portfolios performs the best in terms of risk reduction. Diversification through global asset classes result in a better strategy than international stock diversification regarding risk, as suggested by the literature.</p>
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Koné, N’Golo. "Regularized Maximum Diversification Investment Strategy." Econometrics 9, no. 1 (December 29, 2020): 1. http://dx.doi.org/10.3390/econometrics9010001.
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The maximum diversification has been shown in the literature to depend on the vector of asset volatilities and the inverse of the covariance matrix of the asset return covariance matrix. In practice, these two quantities need to be replaced by their sample statistics. The estimation error associated with the use of these sample statistics may be amplified due to (near) singularity of the covariance matrix, in financial markets with many assets. This, in turn, may lead to the selection of portfolios that are far from the optimal regarding standard portfolio performance measures of the financial market. To address this problem, we investigate three regularization techniques, including the ridge, the spectral cut-off, and the Landweber–Fridman approaches in order to stabilize the inverse of the covariance matrix. These regularization schemes involve a tuning parameter that needs to be chosen. In light of this fact, we propose a data-driven method for selecting the tuning parameter. We show that the selected portfolio by regularization is asymptotically efficient with respect to the diversification ratio. In empirical and Monte Carlo experiments, the resulting regularized rules are compared to several strategies, such as the most diversified portfolio, the target portfolio, the global minimum variance portfolio, and the naive 1/N strategy in terms of in-sample and out-of-sample Sharpe ratio performance, and it is shown that our method yields significant Sharpe ratio improvements.
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Deng, Liurui, Lan Yang, and Bolin Ma. "Research on the Multi-Period Optimal Fee of the Money Manager Under Cumulative Prospect Theory." Business and Management Studies 1, no. 2 (August 21, 2019): 29. http://dx.doi.org/10.11114/bms.v5i3.4468.
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We are interested in investors’ interaction with portfolio managers and investigate the manager’s optimal strategy under cumulative prospect theory. We create model to characterize the relative anxiety about investing in risk assets and trust in the manager. Besides, we research how anxiety and trust affect the manager’s fee and the investors’ portfolios under cumulative prospect theory. Compared with previous work, our main novelty is that we focus on a dynamic portfolio selection. In other words, we formulate the optimal problem under multi-period setting. Besides, relying on the sub-game perfect investment strategies, we attain an optimal fee in multi-period. Another contribution is to discuss multiple risky assets. We use elliptic distribution to reduce a high-dimensional optimal problem to a one-dimensional optimal one. We obtain the CPT-investors’ portfolio for multiple risky assets under a dynamic framework. Based on this result, we study the manager’s optimal fee. It is valuable to say that we explore the optimal strategy for the manager under cumulative prospect theory but not the classical mean-variance preferences.
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Yu, Xing, Hongguo Sun, and Guohua Chen. "The Fuzzy Optimal Portfolio Strategy with Options." Advanced Science Letters 7, no. 1 (March 30, 2012): 594–96. http://dx.doi.org/10.1166/asl.2012.2662.
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Nugroho, Sulistyo Adi, Tony Irawan SE MappEc, and Ir Aruddy, Msi. "Portfolio Analysis Using the Single Index Method in the COVID-19 Pandemic Period." International Journal of Research and Review 8, no. 6 (June 29, 2021): 215–25. http://dx.doi.org/10.52403/ijrr.20210626.
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The COVID-19 outbreak that occurred in early 2020 put pressure on economic activity in many countries, including Indonesia. The pressure on economic activity can be seen from the index movement in the capital market. The JCI as a composite index that reflects transaction activity in the Indonesian capital market has weakened due to the impact of the COVID-19 outbreak in a number of business sectors. The decline in the index is a warning for investors to rearrange the composition of assets in their portfolios so that returns can remain optimal during a pandemic. The single index model (SIM) can be used by investors to make investment decisions, including to rearrange their investment portfolios. The share price data analyzed covers the period from 2 September 2019 to 7 December 2020, where the government confirmed the first positive case of COVID-19 in Indonesia on 3 March 2020. The Single Index Model is used to select assets to form an optimal portfolio. Portfolio performance is measured using the Sharpe, Treynor and Jensen index. The sector rotation strategy results in five selected sectors whose assets will be selected to form an optimal portfolio, namely the consumption sector (JKCONS), the basic and chemical industry sector (JKBIND), the infrastructure sector (JKINFA), the mining sector (JKMING) and the financial sector (JKFINA). The listed companies for analysis were 25 out of 184 issuers in the five sectors. The Single Index Model selects 3 issuers for the pre-COVID period and 10 issuers for the COVID period. The allocation of portfolio funds for the pre-COVID period showed BTPS of 44.94%; CPIN 47.61% and BYAN 7.46%. 2.8% allocation of portfolio funds during the COVID period to BTPS issuers; PBID 22.57%; TKIM 15.96%; BYAN 5.86%; ITMG 17.89%; MYOH 1.56%; PTBA 1.76%; ADRO 12.54% and PPRE 19.05%. The portfolio's expected return is positive, which means that the portfolio formed has the potential to generate profits. The Sharpe, Treynor and Jensen indexes are positive, which means that portfolios formed using a single index model have the potential to have good performance. Keywords: investors, IHSG, portfolio performance, single index model, optimal portfolio.
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Cai, Zhiqing, Yuting Ding, Wanning Du, Yilong Hou, Yilin Zhang, and Yifang Zhao. "Portfolio Investment Strategy Based on Markowitz Model and Single Index Model." BCP Business & Management 26 (September 19, 2022): 981–94. http://dx.doi.org/10.54691/bcpbm.v26i.2060.
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Investing with the highest return and the lowest risk has always been an ideal situation for every investor in the bond markets. Therefore, financial scholars developed lots of models to estimate the optimal risk portfolios of several bonds. Markowitz Model and Single Index Model are both classical financial models used for this estimation. However, they have different advantages and disadvantages, which makes it difficult to determine which one to use under different circumstances. In this essay, the effectiveness of two regular financial models in establishing the optimal risk portfolio under 5 common constraints is assessed. Based on the data of 7 firms within twenty years, both models are applied to construct their corresponding optimal risk portfolios, and visualized the results through Excel. Then, their results are compared to determine the more suitable model in our case by assessing the expected rate of return, predicted risk, and the accuracy of results.
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Pandey, Manas. "Application of Markowitz model in analysing risk and return a case study of BSE stock." Risk Governance and Control: Financial Markets and Institutions 2, no. 1 (2012): 7–15. http://dx.doi.org/10.22495/rgcv2i1art1.
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In this paper the optimal portfolio formation using real life data subject to two different constraint sets is attempted. It is a theoretical framework for the analysis of risk return choices. Decisions are based on the concept of efficient portfolios. Markowitz portfolio analysis gives as output an efficient frontier on which each portfolio is the highest return earning portfolio for a specified level of risk. The investors can reduce their risks and can maximize their return from the investment, The Markowitz portfolio selections were obtained by solving the portfolio optimization problems to get maximum total returns, constrained by minimum allowable risk level. Investors can get lot of information knowledge about how to invest when to invest and why to invest in the particular portfolio. It basically calculates the standard deviation and returns for each of the feasible portfolios and identifies the efficient frontier, the boundary of the feasible portfolios of increasing returns.
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Deng, Liurui, Lan Yang, and Bolin Ma. "Multi-period Investment Strategies with Transaction Costs Under Cumulative Prospect Theory." Applied Finance and Accounting 5, no. 2 (August 15, 2019): 53. http://dx.doi.org/10.11114/afa.v5i2.4432.
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This paper focuses on optimal investment strategies under cumulative prospect theory (CPT). Considering transaction costs, we investigate CPT investors multi-period optimal portfolios. Our main contributions relative to previous work are expanding a single-period optimization problem to a multi-period optimization problem and investigating the impact of transaction costs on optimal portfolio selections. In a numerical analysis that applied original data on four stocks from the NASDAQ, we examine the effects of different risks on the optimal portfolio. Moreover, in contrast with the results without transaction costs, we come to conclusion that the optimal strategy with transaction costs is less sensitive to risk.
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NKEKI, CHARLES I. "OPTIMAL INVESTMENT STRATEGY WITH DIVIDEND PAYING AND PROPORTIONAL TRANSACTION COSTS." Annals of Financial Economics 13, no. 01 (March 2018): 1850001. http://dx.doi.org/10.1142/s201049521850001x.
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A Markowitz’s mean-variance investment strategy is studied in a market with a stock, a bond, dividend payment and proportional transaction costs. Two control variables, portfolio strategy and dividend are considered in this paper. The control variables are inherent with a finite time horizon. This paper aims at minimizing the investment portfolio risk and maximizing the dividend process of the investment over time subject to portfolio allocation strategy, expected net wealth and investment costs over time. The method of Lagrangian multiplier was adopted. As a result, the optimal portfolio and optimal dividend payment are obtained. We found that the optimal portfolio process depends on the optimal dividend payment over time. Also, obtained in this paper, is the optimal portfolio with no dividend payment. We found that for the investment to achieve high target, more of the fund should be invested in stock and low dividend should be declared. The region of boundedness for stock purchase and stock sale are established. We found that for the investment to break-even, the quantum amount of stock sold must be greater than the quantum amount of stock purchase over time. The efficient frontier of the investment strategy was also obtained.
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Zhang, Peng, and Hui Li Wang. "The Optimization on the Expected Utility Portfolio Selection Model without Short Sales." Advanced Materials Research 225-226 (April 2011): 1071–74. http://dx.doi.org/10.4028/www.scientific.net/amr.225-226.1071.
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A new expected utility (EU) portfolio selection model without short sales is proposed. In the model, the expected utility function is quadratic. The model is solved by the pivoting algorithm. The paper showed in the EU portfolio selection model without the short sales, the relationship between the risk preference coefficient and the expected return is not linear but more complex. The risk preference coefficient could just reflect the investors’ preference in some intervals. We wrote program to calculate the optimal portfolios with the different coefficient. Investors could choose the optimal investment strategy according to both their own risk preference and the expected return of the portfolio.
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Hamma, Wajdi, Bassem Salhi, Ahmed Ghorbel, and Anis Jarboui. "Conditional dependence structure between oil prices and international stock markets." International Journal of Energy Sector Management 14, no. 2 (July 31, 2019): 439–67. http://dx.doi.org/10.1108/ijesm-04-2019-0010.
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Purpose The purpose of this paper is to analyze the optimal hedging strategy of the oil-stock dependence structure. Design/methodology/approach The methodology consists to model the data over the daily period spanning from January 02, 2002 to May 19, 2016 by a various copula functions to better modeling the dependence between crude oil market and stock markets, and to use dependence coefficients and conditional variance to calculate optimal portfolio weights and optimal hedge ratios, and to suggest the best hedging strategy for oil-stock portfolio. Findings The findings show that the Gumbel copula is the best model for modeling the conditional dependence structure of the oil and stock markets in most cases. They also indicate that the best hedging strategy for oil price by stock market varies considerably over time, but this variation depends on both the index introduced and the model used. However, the conditional copula method with skewed student more effective than the other models to minimize the risk of oil-stock portfolio. Originality/value This research implication can be valuable for portfolio managers and individual investors who seek to make earnings by diversifying their portfolios. The findings of this study provide evidence of the importance of stock assets for making an optimal portfolio consisting of oil in the case of investments in oil and stock markets. This paper attempts to fill the voids in the literature on volatility among oil prices and stock markets in two important areas. First, it uses copulas to investigate the conditional dependence structure of the oil crude and stock markets in the oil exporting and importing countries. Second, it uses the dependence coefficients and conditional variance to calculate dynamic hedge ratios and risk-minimizing optimal portfolio weights for oil–stock.
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GRINEVA, NATALIA. "DYNAMIC OPTIMIZATION OF THE INVESTMENT PORTFOLIO MANAGEMENT TRAJECTORY." Economic Problems and Legal Practice 17, no. 3 (June 28, 2021): 73–77. http://dx.doi.org/10.33693/2541-8025-2021-17-3-73-77.
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The task of control from the position of mathematical tools application is discussed, economic statement and mathematical model of optimization problem are formulated, the sequential realization of the research aim - the mechanism of optimal portfolio management strategy formation - is presented. The results of dynamic optimization of decisions made at each step form the optimum law of the portfolio management. Scientific novelty of the study consists in the fact that the constructed portfolio takes into account the real incompleteness of the initial data on the processes of change in the yields of securities; there is no need to build a set of effective portfolios and indifference curves that characterize the risk appetite of investors; private characteristics are not used as the main criteria that determine the structure of the optimal portfolio of securities.
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Shen, Weiwei, Bin Wang, Jian Pu, and Jun Wang. "The Kelly Growth Optimal Portfolio with Ensemble Learning." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 1134–41. http://dx.doi.org/10.1609/aaai.v33i01.33011134.
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As a competitive alternative to the Markowitz mean-variance portfolio, the Kelly growth optimal portfolio has drawn sufficient attention in investment science. While the growth optimal portfolio is theoretically guaranteed to dominate any other portfolio with probability 1 in the long run, it practically tends to be highly risky in the short term. Moreover, empirical analysis and performance enhancement studies under practical settings are surprisingly short. In particular, how to handle the challenging but realistic condition with insufficient training data has barely been investigated. In order to fill voids, especially grappling with the difficulty from small samples, in this paper, we propose a growth optimal portfolio strategy equipped with ensemble learning. We synergically leverage the bootstrap aggregating algorithm and the random subspace method into portfolio construction to mitigate estimation error. We analyze the behavior and hyperparameter selection of the proposed strategy by simulation, and then corroborate its effectiveness by comparing its out-of-sample performance with those of 10 competing strategies on four datasets. Experimental results lucidly confirm that the new strategy has superiority in extensive evaluation criteria.
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Mroua, Mourad, Fathi Abid, and Wing Keung Wong. "Optimal diversification, stochastic dominance, and sampling error." American Journal of Business 32, no. 1 (April 3, 2017): 58–79. http://dx.doi.org/10.1108/ajb-04-2015-0014.
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Purpose The purpose of this paper is to contribute to the literature in three ways: first, the authors investigate the impact of the sampling errors on optimal portfolio weights and on financial investment decision. Second, the authors advance a comparative analysis between various domestic and international diversification strategies to define a stochastic optimal choice. Third, the authors propose a new methodology combining the re-sampling method, stochastic optimization algorithm, and nonparametric stochastic dominance (SD) approach to analyze a stochastic optimal portfolio choice for risk-averse American investors who care about benefits of domestic diversification relative to international diversification. The authors propose a new portfolio optimization model involving SD constraints on the portfolio return rate. The authors define a portfolio with return dominating the benchmark portfolio return in the second-order stochastic dominance (SSD) and having maximum expected return. The authors combine re-sampling procedure and stochastic optimization to establish more flexibility in the investment decision rule. Design/methodology/approach The authors apply the re-sampling procedure to consider the sampling error in the optimization process. The authors try to resolve the problem of the stochastic optimal investment strategy choice using the nonparametric SD test by Linton et al. (2005) based on sub-sampling simulated p values. The authors apply the stochastic portfolio optimization algorithm with SSD constraints to define optimal diversified portfolios beating benchmark indices. Findings First, the authors find that reducing sampling error increases the dominance relationships between different portfolios, which, in turn, alters portfolio investment decisions. Though international diversification is preferred in some cases, the study’s results show that for risk-averse US investors, in general, there is no difference between the diversification strategies; this implies that there is no increase in the expected utility of international diversification for the period before and after the 2007-2008 financial crisis. Nevertheless, the authors find that stochastic diversification in domestic, global, and Europe, Australasia, and Far East markets delivers better risk returns for the US risk averters during the crisis period. Originality/value The originality of the idea in this paper is to introduce a new methodology combining the concept of portfolio re-sampling, stochastic portfolio optimization with SSD constraints, and the nonparametric SD test by Linton et al. (2005) based on subsampling simulated p values to analyze the impact of sampling errors on optimal portfolio returns and to investigate the problem of stochastic optimal choice between international and domestic diversification strategies. The authors try to prove more coherence in the portfolio choice with the stochastically and the uncertainty characters of the paper.
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Liu, Yufang, Wei-Guo Zhang, Rongda Chen, and Junhui Fu. "Hedging Long-Term Exposures of a Well-Diversified Portfolio with Short-Term Stock Index Futures Contracts." Mathematical Problems in Engineering 2014 (2014): 1–13. http://dx.doi.org/10.1155/2014/843240.
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It is difficult for passive portfolio strategy to manage the long-term exposure of a well-diversified portfolio because stock index futures contracts have a finite life limited by their maturity. In this paper, we investigate the problem of the rollover hedge strategy for the long-term exposure of a well-diversified portfolio. First, we consider the rollover hedge strategy for the well-diversified portfolio when the portfolio is not adjusted during the period. In order to obtain the optimal solution of the proposed model, the auxiliary models are constructed using the equivalent transformation technique. Moreover, dynamic programming is employed to derive the optimal positions of stock index futures contracts for the long-term exposure of the well-diversified portfolio. In addition, we extend the result to the case of the rollover hedge strategy with transaction costs and derive the optimal number of stock index futures contracts.
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Nkeki, Charles I. "Optimal Portfolio Strategy with Discounted Stochastic Cash Inflows." Journal of Mathematical Finance 03, no. 01 (2013): 130–37. http://dx.doi.org/10.4236/jmf.2013.31012.
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Yang, Zhaoji (George), and Liang Zhong. "Towards optimal portfolio strategy to control maximum drawdown." China Finance Review International 3, no. 2 (May 10, 2013): 131–63. http://dx.doi.org/10.1108/20441391311330582.
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Ivanović, Zoran. "The strategy of financial investments in securities." Tourism and hospitality management 4, no. 2 (December 1998): 351–72. http://dx.doi.org/10.20867/thm.4.2.10.
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The paper presents the financial analysis which has to he performed by every successful financial investor while creation of the optimal portfolio of securities, with the aim to minimize or diverse financial risks. According to the limitless number of possible portfolio of securities available to investors, this paper concerns only portfolio of securities which are a part of effective series of securities.
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Худяков and S. Khudyakov. "Investment portfolio strategy formation (multiobjective optimization)." Economics of the Firm 2, no. 1 (March 19, 2013): 0. http://dx.doi.org/10.12737/303.
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In the article the transition from business process reengineering, the formation of the investment portfolio to the problems of optimization, formulated in a general form of multiobjective problems of a linear programming. The toolssupport reverse engineering on different levels of the value chain organization can justify the choice of the optimal economic strategies for the development and operation of companies.
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Faias, José Afonso, and Pedro Santa-Clara. "Optimal Option Portfolio Strategies: Deepening the Puzzle of Index Option Mispricing." Journal of Financial and Quantitative Analysis 52, no. 1 (February 2017): 277–303. http://dx.doi.org/10.1017/s0022109016000831.
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Traditional methods of asset allocation (such as mean–variance optimization) are not adequate for option portfolios because the distribution of returns is non-normal and the short sample of option returns available makes it difficult to estimate their distribution. We propose a method to optimize a portfolio of European options, held to maturity, with a myopic objective function that overcomes these limitations. In an out-of-sample exercise incorporating realistic transaction costs, the portfolio strategy delivers a Sharpe ratio of 0.82 with positive skewness. This performance is mostly obtained by exploiting mispricing between options and not by loading on jump or volatility risk premia.
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STRADI, BENITO, and EMMANUEL HAVEN. "OPTIMAL INVESTMENT STRATEGY VIA INTERVAL ARITHMETIC." International Journal of Theoretical and Applied Finance 08, no. 02 (March 2005): 185–206. http://dx.doi.org/10.1142/s0219024905002962.
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This paper studies the optimal replacement policy of an item that experiences stochastic geometric growth in maintenance costs. The model integrates corporate taxes, tax credits, depreciation, and salvage value. We extend this traditional application to cover the cost of replacement with the payout from two bonds. The two-bond portfolio is passively immunized. The intersections between the continuation and replacement boundaries are computed using the Interval-Newton Generalized-Bisection (IN/GB) method. We allow small fluctuations of the replacement boundary. With these fluctuations, multiple intersections of the two boundaries are determined. The IN/GB method finds all these intersections without the need for initial guesses of the problem variables. This is a major computational improvement over traditional single-root finding implementations that require multiple initial guesses and provide no guarantees of existence or uniqueness. We demonstrate that without fluctuations one would expect to find a single optimal replacement time. However with fluctuations, there are several intersections of the continuation and replacement boundaries and the bond weight fractions may change by more than 200% between intersection points. These large changes in portfolio wealth allocation highlight the fragility of the idealized solution in the realm of fluctuations in replacement costs.
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Pratama, Yoga Yudha, Isni Andriana, and H. M. A. Rasyid HS Umrie. "The Analysis of Optimal Stock-Bond Portfolio Strategy: Empirical Study in LQ 45 Index Companies and Government Bonds Listed on Indonesia Stock Exchange." JURNAL MANAJEMEN DAN BISNIS SRIWIJAYA 18, no. 3 (January 20, 2021): 145–60. http://dx.doi.org/10.29259/jmbs.v18i3.12642.
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This study aims to analyze the strategy in determining the optimal stocks portfolio performance through Single Index Model technique from LQ 45 Index stocks and optimal bonds portfolio performance of bonds through Buy and Hold technique from government bonds in Indonesia Stock Exchange in the 2014-2018 period. The strategy generates performance which generally consists of optimal return (yield), risk and portfolio proportion. The population used in the study are companies stock in LQ 45 Index which produced 23 samples and government bonds produced 7 samples. The methodology research in this study is descriptive analysis. The type of data used in this study is quantitative and data sources of this study is secondary data. Purposive sampling method used as the sampling method. This research found that optimal stock portfolio performance with expected return and optimal portfolio risk values at 0.01497 and 0.006395 while optimal bonds portfolio performance showed optimal portfolio yields and risk with values at 0.090063991 and -0.003063991. The proportions of fund that invested in the optimal stock portfolio are BBCA (27%), GGRM (12%), TLKM (11%), ICBP (14%), PTBA (5%), UNVR (10%), BBRI (9%), BBNI (6%), BMRI (5%) and UNTR (2%) while the optimal bonds portofolio proportions are FR0073 (90%) and FR0072 (10%).
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LI, ZHONG-FEI, KAI W. NG, KEN SENG TAN, and HAILIANG YANG. "OPTIMAL CONSTANT-REBALANCED PORTFOLIO INVESTMENT STRATEGIES FOR DYNAMIC PORTFOLIO SELECTION." International Journal of Theoretical and Applied Finance 09, no. 06 (September 2006): 951–66. http://dx.doi.org/10.1142/s0219024906003883.
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In this paper we propose a variant of the continuous-time Markowitz mean-variance model by incorporating the Earnings-at-Risk measure in the portfolio optimization problem. Under the Black-Scholes framework, we obtain closed-form expressions for the optimal constant-rebalanced portfolio (CRP) investment strategy. We also derive explicitly the corresponding mean-EaR efficient portfolio frontier, which is a generalization of the Markowitz mean-variance efficient frontier.
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Zagaglia, Paolo. "International diversification for portfolios of European fixed-income mutual funds." Managerial Finance 43, no. 2 (February 13, 2017): 242–62. http://dx.doi.org/10.1108/mf-01-2015-0026.
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Purpose The purpose of this paper is to study the scope for country diversification in international portfolios of mutual funds for the “core” EMU countries. The author uses a sample of daily returns for country indices of French, German and Italian funds to investigate the quest for international diversification. The author focuses on fixed-income mutual funds during the period of the financial market turmoil since 2007. Design/methodology/approach The author compute optimal portfolio allocations from both unconstrained and constrained mean-variance frameworks that take as input the out-of-sample forecasts for the conditional mean, volatility and correlation of country-level indices for funds returns. The author also applies a portfolio allocation model based on utility maximization with learning about the time-varying conditional moments. The author compares the out-of-sample forecasting performance of 12 multivariate volatility models. Findings The author finds that there is a “core” EMU country also for the mutual fund industry: optimal portfolios allocate the largest portfolio weight to German funds, with Italian funds assigned a lower weight in comparison to French funds. This result is remarkably robust across competing forecasting models and optimal allocation strategies. It is also consistent with the findings from a utility-maximization model that incorporates learning about time-varying conditional moments. Originality/value This is the first study on optimal country-level diversification for a mutual fund investor focused on European countries in the fixed-income space for the turmoil period. The author uses a large array of econometric models that captures the salient features of a period characterized by large changes in volatility and correlation, and compare the performance of different optimal asset allocation models.
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GAVRISHCHAKA, VALERIY V. "BOOSTING-BASED FRAMEWORK FOR PORTFOLIO STRATEGY DISCOVERY AND OPTIMIZATION." New Mathematics and Natural Computation 02, no. 03 (November 2006): 315–30. http://dx.doi.org/10.1142/s1793005706000506.
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Increasing availability of the multi-scale market data exposes limitations of the existing quantitative models such as low accuracy of the simplified analytical and statistical frameworks as well as insufficient interpretability and stability of the best machine learning algorithms. Boosting was recently proposed as a simple and robust framework for intelligent combination of the clarity and stability of the analytical and parsimonious statistical models with the accuracy of the adaptive data-driven models. Encouraging results of the boosting application to symbolic volatility forecasting have also been reported. However, accurate forecasting does not always warrant optimal decision making that leads to acceptable performance of the portfolio strategy. In this work, a boosting-based framework for a direct trading strategy and portfolio optimization is introduced. Due to inherent adaptive control of the parameter space dimensionality, this technique can work with very large pools of base strategies and financial instruments that are usually prohibitive for other portfolio optimization frameworks. Unlike existing approaches, this framework can be effectively used for the coupled optimization of the portfolio capital/asset allocation and dynamic trading strategies. Generated portfolios of trading strategies not only exhibit stable and robust performance but also remain interpretable. Encouraging preliminary results based on real market data are presented and discussed.
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Yu, Xiaojian, Siyu Xie, and Weijun Xu. "Optimal Portfolio Strategy under Rolling Economic Maximum Drawdown Constraints." Mathematical Problems in Engineering 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/787943.
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This paper deals with the problem of optimal portfolio strategy under the constraints of rolling economic maximum drawdown. A more practical strategy is developed by using rolling Sharpe ratio in computing the allocation proportion in contrast to existing models. Besides, another novel strategy named “REDP strategy” is further proposed, which replaces the rolling economic drawdown of the portfolio with the rolling economic drawdown of the risky asset. The simulation tests prove thatREDP strategycan ensure the portfolio to satisfy the drawdown constraint and outperforms other strategies significantly. An empirical comparison research on the performances of different strategies is carried out by using the 23-year monthly data of SPTR, DJUBS, and 3-month T-bill. The investment cases of single risky asset and two risky assets are both studied in this paper. Empirical results indicate that theREDP strategysuccessfully controls the maximum drawdown within the given limit and performs best in both return and risk.
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Bodnar, Taras, Mathias Lindholm, Erik Thorsén, and Joanna Tyrcha. "Quantile-based optimal portfolio selection." Computational Management Science 18, no. 3 (April 2, 2021): 299–324. http://dx.doi.org/10.1007/s10287-021-00395-8.
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AbstractIn this paper the concept of quantile-based optimal portfolio selection is introduced and a specific portfolio connected to it, the conditional value-of-return (CVoR) portfolio, is proposed. The CVoR is defined as the mean excess return or the conditional value-at-risk (CVaR) of the return distribution. The portfolio selection consists solely of quantile-based risk and return measures. Financial institutions that work in the context of Basel 4 use CVaR as a risk measure. In this regulatory framework sufficient and necessary conditions for optimality of the CVoR portfolio are provided under a general distributional assumption. Moreover, it is shown that the CVoR portfolio is mean-variance efficient when the returns are assumed to follow an elliptically contoured distribution. Under this assumption the closed-form expression for the weights and characteristics of the CVoR portfolio are obtained. Finally, the introduced methods are illustrated in an empirical study based on monthly data of returns on stocks included in the S&P index. It is shown that the new portfolio selection strategy outperforms several alternatives in terms of the final investor wealth.
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DESMETTRE, SASCHA, RALF KORN, and FRANK THOMAS SEIFRIED. "LIFETIME CONSUMPTION AND INVESTMENT FOR WORST-CASE CRASH SCENARIOS." International Journal of Theoretical and Applied Finance 18, no. 01 (February 2015): 1550004. http://dx.doi.org/10.1142/s0219024915500041.
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We investigate worst-case optimal consumption and portfolio decisions under the threat of a market crash on an infinite time horizon. We provide a closed-form solution for constant relative risk aversion and establish a rigorous verification result. More specifically, using martingale arguments we demonstrate that the optimal consumption-portfolio strategy can be characterized as the indifference strategy that achieves the best performance in the no-crash scenario. In addition, we find a dual characterization of the optimal strategy as the indifference strategy that minimizes the crash exposure. Finally, we quantify the impact of the crash on consumption and portfolio choice and analyze it in terms of the investor's risk and time preferences and prudence.
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Majdoub, Jihed, and Haykel Hamdi. "Optimal option portfolio hedging strategy with non-Gaussian fluctuations." International Journal of Entrepreneurship and Small Business 39, no. 1/2 (2020): 27. http://dx.doi.org/10.1504/ijesb.2020.10025916.
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Hamdi, Haykel, and Jihed Majdoub. "Optimal option portfolio hedging strategy with non-Gaussian fluctuations." International Journal of Entrepreneurship and Small Business 39, no. 1/2 (2020): 27. http://dx.doi.org/10.1504/ijesb.2020.104240.
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SENGUPTA, JATI K. "Mixed strategy and information theory in optimal portfolio choice." International Journal of Systems Science 20, no. 2 (February 1989): 215–27. http://dx.doi.org/10.1080/00207728908910121.
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Ahmadi, Abdollah, Mansour Charwand, and Jamshid Aghaei. "Risk-constrained optimal strategy for retailer forward contract portfolio." International Journal of Electrical Power & Energy Systems 53 (December 2013): 704–13. http://dx.doi.org/10.1016/j.ijepes.2013.05.051.
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Pratiwi, Ariani Dian, Idqan Fahmi, and Rifki Ismal. "Optimal Hajj Funds Management by Islamic Bank." ETIKONOMI 18, no. 2 (September 22, 2019): 303–14. http://dx.doi.org/10.15408/etk.v18i2.10938.
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The purpose of this paper is to find the optimal portfolio of Hajj fund management by the Islamic banks in Indonesia. BPKH, as an authority, can place the Hajj fund on Islamic bank deposits. However, Islamic banks limited the expected returns and risks set by BPKH so that the appropriate strategy is required to establish the optimal of portfolio. Islamic banks face a trade-off because of the increased level of risk constrains the intention to get higher returns. This study uses a mean-variance portfolio optimization theory to construct such an optimal portfolio. Finally, this study recommends Murabaha financing and SBIS to Islamic banks as the optimal portfolio selection. The combination of an efficient portfolio that has formed cannot be fully employed because the expectation limits them. However, Islamic banks can still select the optimal portfolio combination according to their risk preferences.JEL Classification: G11, G18
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T, Vorkut, Bilonoh O, Petunin A, Tretynychenko Y, Kharuta V, and Chechet A. "PROJECT PORTFOLIOS OPTIMISATION OF COLLECTIVE STRATEGIES IMPLEMENTATION IN SUPPLY CHAIN NETWORKS." National Transport University Bulletin 1, no. 48 (2021): 44–62. http://dx.doi.org/10.33744/2308-6645-2021-1-48-044-062.
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The actuality of the theme arises from the need to improve and further develop the methodological support of portfolio management processes in the context of the portfolio management introduction of collective strategies implementation in supply chain networks. The purpose of the study is to develop a mathematical model for determining the optimal portfolio components as a means of single system implementation of collective strategies in supply chain networks (SCNs) to meet the target value of selected criteria of efficiency and cost-effectiveness of supply chains as integral objects, taking into account the possibility of presenting these criteria as stochastic variables. The given model is described in the paper in the terms of portfolio implementation optimisation, the components of which are aimed at reducing the delivery time of orders in the supply chain. Objectives of the study: to conduct a comparative analysis of the PMI portfolio management standard versions in order to form a conceptual framework for the study and determine the knowledge base for portfolio management by the subject of the research; to formulate the problem of portfolio components optimisation for the collective strategies implementation in SCNs; to analyse and identify scientific gaps in methodological approaches to solving the problem of optimizing portfolio components of the collective strategies implementation in SCNs in the proposed formulation; to develop a mathematical model for determining the optimal portfolio components for the implementation of collective strategies in SCNs as in the case of portfolio optimisation for a collective logistics strategy implementation, the components of which are aimed at reducing the time of orders delivery in supply chain; to approve the developed mathematical model for portfolio optimisation under the operation conditions of perishable goods supply chains in Ukraine. Utilised techniques of the research. The research is based on the concept of forming, on a single system basis, the collective strategies portfolio implementation in SCNs, which foresees the spread of portfolio management, which is defined to be an effective tool for the strategy implemention of an individual organisation, in a similar way a network of organisations, if the development conditions of the given network foresee the adoption of a collective strategy. Based on a comparative analysis of the four known versions of the PMI portfolio management standard for 2020, portfolio management is identified as a knowledge basis for portfolio management of methods and models for portfolio optimisation and strategies implementation in organisations. Based on the analysis of scientific and other information sources, the objective of optimizing the portfolios composition of collective strategies in SCNs is formulated as one that foresees the single system optimisation of the supply chain portfolio to meet the targets of selected criteria of efficiency and costeffectiveness of the supply chain as a whole object, taking into account the possibility of presenting these criteria as stochastic variables. Based on the analysis of methodological approaches to solving the problem of optimizing the portfolio composition of collective strategies in SCNs, we identified a scientific gap, including the knowledge basis of portfolio management composition, in terms of lack of models for portfolio components optimisation. They would give the possibility to assess these components from a single system position of SCNs according to the established, in general case, several criteria, taking into account the possibility to present these criteria as stochastic variables. Based on the analysis of methodological approaches to solving multicriteria problems, taking into account the fact that some parameters may be stochastic, to solve the problem of portfolios components optimisation of collective strategies in SCNs in the proposed presentation we chose such an approach to solving multicriteria problems as establishing one (main) criterion transfering others to the rank of restraints. This gave grounds to apply the method of stochastic integer programming and to accept the condition about the random nature of individual parameters, i.e. the method of stochastic integer programming. As a result, the mathematical model for determining the optimal composition of portfolios was introduced as a means of implementing, on a single system basis, collective strategies in SCNs according to the requirements of achieving the target values of the selected criteria as stochastic variables. This model is described in the paper under the conditions of the portfolio optimisation of logistics strategy implementation, the components of which are aimed at reducing the time of order delivery of supply chain. The reliability of the model is confirmed by its practical approval within 2018-2020 in seven types of perishable goods supply chains, which involved companies, such as: FROZEN FRUT LLC, Handikap LLC, AIFT Ukraine LLC, Hroskhandel LLC, Olhopilske Motor Transport Enterprise LLC and Ukrainskyi Product PE. KEY WORDS: COLLECTIVE STRATEGY, SUPPLY CHAIN, LOGISTICS STRATEGY, SUPPLY CHAIN MANAGEMENT, PORTFOLIO-MANAGEMENT.
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T, Vorkut, Bilonoh O, Petunin A, Tretynychenko Y, Kharuta V, and Chechet A. "PROJECT PORTFOLIOS OPTIMISATION OF COLLECTIVE STRATEGIES IMPLEMENTATION IN SUPPLY CHAIN NETWORKS." National Transport University Bulletin 1, no. 48 (2021): 44–62. http://dx.doi.org/10.33744/2308-6645-2021-1-48-044-062.
Full textAbstract:
The actuality of the theme arises from the need to improve and further develop the methodological support of portfolio management processes in the context of the portfolio management introduction of collective strategies implementation in supply chain networks. The purpose of the study is to develop a mathematical model for determining the optimal portfolio components as a means of single system implementation of collective strategies in supply chain networks (SCNs) to meet the target value of selected criteria of efficiency and cost-effectiveness of supply chains as integral objects, taking into account the possibility of presenting these criteria as stochastic variables. The given model is described in the paper in the terms of portfolio implementation optimisation, the components of which are aimed at reducing the delivery time of orders in the supply chain. Objectives of the study: to conduct a comparative analysis of the PMI portfolio management standard versions in order to form a conceptual framework for the study and determine the knowledge base for portfolio management by the subject of the research; to formulate the problem of portfolio components optimisation for the collective strategies implementation in SCNs; to analyse and identify scientific gaps in methodological approaches to solving the problem of optimizing portfolio components of the collective strategies implementation in SCNs in the proposed formulation; to develop a mathematical model for determining the optimal portfolio components for the implementation of collective strategies in SCNs as in the case of portfolio optimisation for a collective logistics strategy implementation, the components of which are aimed at reducing the time of orders delivery in supply chain; to approve the developed mathematical model for portfolio optimisation under the operation conditions of perishable goods supply chains in Ukraine. Utilised techniques of the research. The research is based on the concept of forming, on a single system basis, the collective strategies portfolio implementation in SCNs, which foresees the spread of portfolio management, which is defined to be an effective tool for the strategy implemention of an individual organisation, in a similar way a network of organisations, if the development conditions of the given network foresee the adoption of a collective strategy. Based on a comparative analysis of the four known versions of the PMI portfolio management standard for 2020, portfolio management is identified as a knowledge basis for portfolio management of methods and models for portfolio optimisation and strategies implementation in organisations. Based on the analysis of scientific and other information sources, the objective of optimizing the portfolios composition of collective strategies in SCNs is formulated as one that foresees the single system optimisation of the supply chain portfolio to meet the targets of selected criteria of efficiency and costeffectiveness of the supply chain as a whole object, taking into account the possibility of presenting these criteria as stochastic variables. Based on the analysis of methodological approaches to solving the problem of optimizing the portfolio composition of collective strategies in SCNs, we identified a scientific gap, including the knowledge basis of portfolio management composition, in terms of lack of models for portfolio components optimisation. They would give the possibility to assess these components from a single system position of SCNs according to the established, in general case, several criteria, taking into account the possibility to present these criteria as stochastic variables. Based on the analysis of methodological approaches to solving multicriteria problems, taking into account the fact that some parameters may be stochastic, to solve the problem of portfolios components optimisation of collective strategies in SCNs in the proposed presentation we chose such an approach to solving multicriteria problems as establishing one (main) criterion transfering others to the rank of restraints. This gave grounds to apply the method of stochastic integer programming and to accept the condition about the random nature of individual parameters, i.e. the method of stochastic integer programming. As a result, the mathematical model for determining the optimal composition of portfolios was introduced as a means of implementing, on a single system basis, collective strategies in SCNs according to the requirements of achieving the target values of the selected criteria as stochastic variables. This model is described in the paper under the conditions of the portfolio optimisation of logistics strategy implementation, the components of which are aimed at reducing the time of order delivery of supply chain. The reliability of the model is confirmed by its practical approval within 2018-2020 in seven types of perishable goods supply chains, which involved companies, such as: FROZEN FRUT LLC, Handikap LLC, AIFT Ukraine LLC, Hroskhandel LLC, Olhopilske Motor Transport Enterprise LLC and Ukrainskyi Product PE. KEY WORDS: COLLECTIVE STRATEGY, SUPPLY CHAIN, LOGISTICS STRATEGY, SUPPLY CHAIN MANAGEMENT, PORTFOLIO-MANAGEMENT.
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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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Lefebvre, William, Grégoire Loeper, and Huyên Pham. "Mean-Variance Portfolio Selection with Tracking Error Penalization." Mathematics 8, no. 11 (November 1, 2020): 1915. http://dx.doi.org/10.3390/math8111915.
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This paper studies a variation of the continuous-time mean-variance portfolio selection where a tracking-error penalization is added to the mean-variance criterion. The tracking error term penalizes the distance between the allocation controls and a reference portfolio with same wealth and fixed weights. Such consideration is motivated as follows: (i) On the one hand, it is a way to robustify the mean-variance allocation in the case of misspecified parameters, by “fitting" it to a reference portfolio that can be agnostic to market parameters; (ii) On the other hand, it is a procedure to track a benchmark and improve the Sharpe ratio of the resulting portfolio by considering a mean-variance criterion in the objective function. This problem is formulated as a McKean–Vlasov control problem. We provide explicit solutions for the optimal portfolio strategy and asymptotic expansions of the portfolio strategy and efficient frontier for small values of the tracking error parameter. Finally, we compare the Sharpe ratios obtained by the standard mean-variance allocation and the penalized one for four different reference portfolios: equal-weights, minimum-variance, equal risk contributions and shrinking portfolio. This comparison is done on a simulated misspecified model, and on a backtest performed with historical data. Our results show that in most cases, the penalized portfolio outperforms in terms of Sharpe ratio both the standard mean-variance and the reference portfolio.
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Ghaemi Asl, Mahdi, and Muhammad Mahdi Rashidi. "Dynamic diversification benefits of Sukuk and conventional bonds for the financial performance of MENA region companies: empirical evidence from COVID-19 pandemic period." Journal of Islamic Accounting and Business Research 12, no. 7 (August 4, 2021): 979–99. http://dx.doi.org/10.1108/jiabr-09-2020-0306.
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Purpose This study aims to investigate the spillover between the Middle East and North Africa (MENA) stock index and several security indices, including Sukuk and conventional bond, and ultimately compare the hedge effectiveness of Sukuk and conventional bond. Design/methodology/approach The study uses VAR (1)-asymmetric Baba, Engle, Kraft and Kroner-multivariate generalized autoregressive conditional heteroskedasticity (1,1) model to analyze the volatility and shock and asymmetric shock spillover between Sukuk index and several bond indices in the MENA region including, Bond, All Bond, High Yield Bond and Bond and Sukuk and MENA stock market index and ultimately compare the hedging capabilities of Sukuk and conventional bonds by calculating the optimal portfolio weights for securities indices and stock portfolios and hedge effectiveness of security indices. Findings Results indicate that there is no shock, volatility and asymmetric shock spillover between the Sukuk index and MENA stock index, implying that Sukuk indices behave independently from MENA stock indices; however, there is shock and asymmetric shock spillover between MENA stock indices and security indices that include conventional bonds. The result of optimal portfolio weights and corresponding hedge effectiveness indicate that Sukuk is the most significant asset among other security indices in diversifying and hedging stock MENA portfolios. Moreover, the hedge effectiveness of Sukuk shows persistent trends during both the normal and crisis periods. Practical implications The study suggests that MENA stock market investors and investment managers should add Sukuk instead of the conventional bond to their portfolio to hedge their portfolio against investment risks during both normal and crisis periods. Originality/value Although many studies compare many aspects of Sukuk and conventional bonds, this is the first study that compares the hedge effectiveness of Sukuk and conventional bond based on the time-varying optimal portfolio weights strategy.
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Bakurova, Anna, Hanna Ropalo, and Elina Tereschenko. "Modeling of complex diversification for centralized pharmacy network." E3S Web of Conferences 166 (2020): 09003. http://dx.doi.org/10.1051/e3sconf/202016609003.
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The risk management of a centralized pharmacy network identifies the research object. The paper proposes a strategy of complex diversification for the pharmacy network. By constructing portfolio models for complex diversification and solving relevant multicriteria problems, multiple pareto-optimal portfolios have been found for successive risk management. Based on the fundamentals of Markowitz portfolio theory and multicriteria optimization, this paper builds four models of the optimal portfolios for centralized pharmacy network. In contrast to the classic two-criteria model (risk minimization while maximizing income), our models have been introduced to maximize entropy, which enhances the diversification effect. Matlab software has been developed for solving multicriteria problems. Model verification was performed on real data provided by one of the pharmacy networks. The modeling results will be useful for automating the business processes of any trading network, managing risk, analysing loyalty programs to improve the effectiveness of their operations.
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Fajri, Salman, Tony Irawan, and Trias Andati. "THE STUDY OF MARKET TIMING IMPLEMENTATION IN INDONESIAN STOCK MARKET." Jurnal Manajemen Indonesia 19, no. 2 (August 30, 2019): 176. http://dx.doi.org/10.25124/jmi.v19i2.1641.
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This study is intended to discuss about implementation of market timing as an investment alternative strategic in Indonesian Stock Market. Market timing is procedure for changing portfolio asset allocation to deal with changes in business cycle. The market timing indicator used in this study is interest rate of Bank Indonesia. The active portfolio consist of IHSG and bond for simple rotation strategy. Sector rotation strategy consist of cyclical and non cyclical sector index. The dissecting cycle analyse by two methods, Hamilton Filter and indicator change assumptions. The secondary data used in this study have a span of time from January 2005 - December 2017. The result showed that active strategies produced better performance than passive strategy, and sector rotation were the best performance among other alternative strategies. Optimal performance of simple rotation occurs when change of variable BI rate by ±2% and optimal performance of sector rotation occurs when change of variable BI rate by ±4%.
Keywords—Hamilton Filter; Market Timing; Sector Rotation; Simple Rotation
AbstrakPenelitian ini bertujuan untuk membahas tentang penerapan market timing sebagai tindakan strategi investasi aktif di pasar modal Indonesia. Market timing merupakan prosedur perubahan alokasi aset portfolio untuk menghadapi perubahan siklus bisnis di suatu negara. Indikator market timing yang digunakan dalam penelitian ini adalah suku bunga acuan Bank Indonesia. Portfolio aktif terdiri dari IHSG dan obligasi untuk strategi aktif rotasi sederhana dan indeks sektor siklikal dan non siklikal untuk rotasi sektoral. Pemilahan siklus dilakukan dengan dua metode yaitu Hamilton Filter dan asumsi perubahan variabel indikator. Seluruh data sekunder yang digunakan dalam penelitian ini memiliki rentang waktu dari Januari 2005 - Desember 2017. Hasil penelitian menunjukkan bahwa strategi aktif menghasilkan kinerja lebih baik relatif terhadap strategi pasif, dan strategi rotasi sektoral secara keseluruhan lebih baik dibandingkan dengan alternatif strategi lain. Strategi rotasi sederhana optimal pada penggunaan asumsi perubahan variabel ±25 bps (basis point) dan strategi rotasi sektoral optimal pada penggunaan asumsi perubahan variabel ±100 bps (basis point).
Kata kunci— Hamilton Filter, Market Timing, Rotasi Sederhana, Rotasi Sektoral
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VIGNA, ELENA. "ON TIME CONSISTENCY FOR MEAN-VARIANCE PORTFOLIO SELECTION." International Journal of Theoretical and Applied Finance 23, no. 06 (September 2020): 2050042. http://dx.doi.org/10.1142/s0219024920500429.
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This paper addresses a comparison between different approaches to time inconsistency for the mean-variance portfolio selection problem. We define a suitable intertemporal preferences-driven reward and use it to compare three common approaches to time inconsistency for the mean-variance portfolio selection problem over [Formula: see text]: precommitment approach, consistent planning or game theoretical approach, and dynamically optimal approach. We prove that, while the precommitment strategy beats the other two strategies (that is a well-known obvious result), the consistent planning strategy dominates the dynamically optimal strategy until a time point [Formula: see text] and is dominated by the dynamically optimal strategy from [Formula: see text] onwards. Existence and uniqueness of the break even point [Formula: see text] is proven.