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1 – 10 of over 8000Mourad Mroua, Fathi Abid and Wing Keung Wong
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…
Abstract
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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A. Can Inci and Rachel Lagasse
This study investigates the role of cryptocurrencies in enhancing the performance of portfolios constructed from traditional asset classes. Using a long sample period covering not…
Abstract
Purpose
This study investigates the role of cryptocurrencies in enhancing the performance of portfolios constructed from traditional asset classes. Using a long sample period covering not only the large value increases but also the dramatic declines during the beginning of 2018, the purpose of this paper is to provide a more complete analysis of the dynamic nature of cryptocurrencies as individual investment opportunities, and as components of optimal portfolios.
Design/methodology/approach
The mean-variance optimization technique of Merton (1990) is applied to develop the risk and return characteristics of the efficient portfolios, along with the optimal weights of the asset class components in the portfolios.
Findings
The authors provide evidence that as a single investment, the best cryptocurrency is Ripple, followed by Bitcoin and Litecoin. Furthermore, cryptocurrencies have a useful role in the optimal portfolio construction and in investments, in addition to their original purposes for which they were created. Bitcoin is the best cryptocurrency enhancing the characteristics of the optimal portfolio. Ripple and Litecoin follow in terms of their usefulness in an optimal portfolio as single cryptocurrencies. Including all these cryptocurrencies in a portfolio generates the best (most optimal) results. Contributions of the cryptocurrencies to the optimal portfolio evolve over time. Therefore, the results and conclusions of this study have no guarantee for continuation in an exact manner in the future. However, the increasing popularity and the unique characteristics of cryptocurrencies will assist their future presence in investment portfolios.
Originality/value
This is one of the first studies that examine the role of popular cryptocurrencies in enhancing a portfolio composed of traditional asset classes. The sample period is the largest that has been used in this strand of the literature, and allows to compare optimal portfolios in early/recent subsamples, and during the pre-/post-cryptocurrency crisis periods.
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The purpose of this paper is to examine whether corporate governance has an impact on portfolio selection within the usual mean‐variance framework, the idea being that by reducing…
Abstract
Purpose
The purpose of this paper is to examine whether corporate governance has an impact on portfolio selection within the usual mean‐variance framework, the idea being that by reducing agency conflicts, corporate governance increases the value of the firm.
Design/methodology/approach
Using a sample of 460 American firms between 1995 and 2004, the authors first determine the optimal mean‐variance portfolio. The authors then test whether governance characteristics explain the optimal portfolio weights.
Findings
The results show that the optimal portfolio weights are sensitive to internal control mechanisms, ownership concentration, managerial entrenchment and incentive compensation.
Originality/value
The results are relevant to academicians and investors concerned with portfolio selection. In fact, they underline the importance of including governance characteristics in their portfolio selection.
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This article provides a general introduction to using catastrophe models to optimally manage the risk of a portfolio of Property & Casualty (P&C) liabilities. There is increasing…
Abstract
This article provides a general introduction to using catastrophe models to optimally manage the risk of a portfolio of Property & Casualty (P&C) liabilities. There is increasing emphasis on the enterprise‐wide allocation of risk capacity for all financial intermediaries, e.g. banks, pensions, investment funds, as well as life and P&C insurers. The optionality (the skewness, kurtosis, and correlation with asset risk) of liability risks contribute substantially to earnings volatility. The severity of low‐probability events, i.e. natural catastrophes (e.g. hurricanes, earthquakes), combined with increases in geographic concentrations of wealth can adversely affect the diversification of the liability risk at the portfolio level. Since in both finance and insurance, optimally allocating risk at the portfolio level is generally based on (linear) combinations of nonlinear risks, finding an optimal allocation is not always tractable. The author describes a well‐established optimization algorithm and produces a reasonable approximation for an optimal solution.
The purpose of this paper is to research the optimal portfolio proportion for the optimal investment model and the optimal consumption investment strategies for the optimal…
Abstract
Purpose
The purpose of this paper is to research the optimal portfolio proportion for the optimal investment model and the optimal consumption investment strategies for the optimal consumption investment model under compound‐jump processes.
Design/methodology/approach
Traditionally, the price of risky security or asset is often modeled as geometric Brownian motion. However, the analysis of stock price evolution reveals sudden and rare breaks logically accounted for by exogenous events on information. It is natural to model such behavior by means of a point process, or, more simply, by a Poisson process, which has jumps of constant size occurring at rare and unpredictable intervals. Assume that the price of risky security stock is modeled by a compound‐jump process, the renew process theory is chosen to solve the optimal investment model, the HJB equation is chosen for the optimal consumption investment model.
Findings
Derive the analytical optimal portfolio proportion for the reduction model of optimal investment. The optimal consumption investment strategies are given by some equations for the optimal consumption investment model.
Research limitations/implications
Accessibility and availability of data are the main limitations which model will be applied.
Practical implications
The results obtained in this paper could be used as a guide to actual portfolio management.
Originality/value
The new approach for the optimal portfolio model under compound‐jump processes. The paper is aimed at actual portfolio managers.
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Wajdi Hamma, Bassem Salhi, Ahmed Ghorbel and Anis Jarboui
The purpose of this paper is to analyze the optimal hedging strategy of the oil-stock dependence structure.
Abstract
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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Fabio Filipozzi and Kersti Harkmann
This paper aims to investigate the efficiency of different hedging strategies for an investor holding a portfolio of foreign currency bonds.
Abstract
Purpose
This paper aims to investigate the efficiency of different hedging strategies for an investor holding a portfolio of foreign currency bonds.
Design/methodology/approach
The simplest strategies of no hedge and fully hedged are compared with the more sophisticated strategies of the ordinary least squares (OLS) approach and the optimal hedge ratios found by the dynamic conditional correlation-generalised autoregressive conditional heteroskedasticity approach.
Findings
The sophisticated hedging strategies are found to be superior to the simple strategies because they lower the portfolio risk in domestic currency terms and improve the Sharpe ratios for multi-asset portfolios. The analyses also show that both the OLS and dynamic hedging strategies imply holding a limited carry position by being long in high-yielding currencies but short in low-yielding currencies.
Originality/value
The performance of multi-currency portfolios is examined using more realistic assumptions than in the previous literature, including a weekly frequency and a constraint of no short selling. Furthermore, carry trades are shown to be part of an optimal portfolio.
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Stanley McGreal, Alastair Adair, James N. Berry and James R. Webb
Few countries have sufficiently long and detailed returns data for real estate to permit sophisticated analysis. This paper aims to examine the potential diversification of…
Abstract
Purpose
Few countries have sufficiently long and detailed returns data for real estate to permit sophisticated analysis. This paper aims to examine the potential diversification of private real estate investments using returns data for major regional centres in Ireland and the UK.
Design/methodology/approach
Optimal real estate‐only portfolios are constructed using total returns, income returns and appreciation returns for office and retail real estate in ten cities within Ireland and the UK. The analysis uses IPD data for the period 1984 to 2002. Total return, income return and appreciation returns are treated as separate asset streams in the modelling of portfolios.
Findings
The results show different risk levels; in particular the income stream carries low risk, whereas the capital appreciation element is much more volatile and risky. Optimal portfolios, office or retail, whether income, appreciation or total returns, indicate that provincial markets perform well and are capable of pushing London out of the optimised portfolios.
Research limitations/implications
Limitations stem from the optimal portfolios being based on return series without a consideration of market depth. Future research will seek to construct weighted portfolios.
Originality/value
The paper constructs optimal portfolios for three scenarios: low return; medium return; and high return across sectors, return streams and major regional centres in Ireland and the UK. The results show that regional centres perform well and can exclude London real estate from optimal portfolios.
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David Camilleri, Mohammad Iqbal Tahir and Samuel Wang
The purpose of this study is to provide further evidence on the importance of international diversification, and to determine the optimal allocation of assets in a portfolio…
Abstract
The purpose of this study is to provide further evidence on the importance of international diversification, and to determine the optimal allocation of assets in a portfolio comprising domestic (Australian) and international assets. The study focuses on stock index futures contracts in five countries ‐ Australia, USA, UK, Hong Kong and Japan. Daily data for the five selected contracts over the period from 1 January 1990 to 31 December 2000 is employed in the study. Consistent with previous studies, the results confirm the importance of international diversification and indicate that the portfolio risk is reduced considerably when more international assets are added sequentially to the portfolio. Empirical analysis also shows that the optimal asset allocation results in higher risk reduction and better returns when compared with an equally weighted portfolio.
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Stephen Lee and Simon Stevenson
The use of modern portfolio theory (MPT) in the construction real estate portfolios has two serious limitations when used in an ex ante framework: the intertemporal instability of…
Abstract
Purpose
The use of modern portfolio theory (MPT) in the construction real estate portfolios has two serious limitations when used in an ex ante framework: the intertemporal instability of the portfolio weights; and the sharp deterioration in performance of the optimal portfolios outside the sample period used to estimate asset mean returns. Both problems can be traced to wide fluctuations in sample means. Aims to prove that the use of a procedure that ignores the estimation risk due to the uncertain in mean returns is likely to produce sub‐optimal results in subsequent periods.
Design/methodology/approach
This study extends previous ex ante‐based studies by evaluating ex post optimal portfolio allocations in subsequent test periods by using methods that have been proposed to reduce the effect of measurement error on optimal portfolio allocations.
Findings
While techniques designed to handle estimation risk in capital market studies have yielded promising results, they are not completely successful in improving out‐of‐sample performance in this case. It is hypothesised that such results are due to the cyclical nature of property and that the contrarian and mean‐reversion effects picked up in studies of stocks and bonds are not captured when an asset such as direct property is examined. This conclusion is also supported by the strong performance of the tangency portfolios, and in particular the classical unadjusted Sharpe portfolio, over the shorter horizons, which would be consistent with a cyclical momentum effect.
Originality/value
The results suggest that the consideration of the issue of estimation risk is crucial in the use of MPT in developing a successful real estate portfolio strategy.
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