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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.

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.

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.

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.

Electric Utility Diversification and Efficient Capital Markets Over 60% of investor owned electric utilities have experimented with diversification into lines of business other than the traditional generation, transmission, and distribution of electricity. They diversify for a variety of reasons, but a primary goal is to improve their overall financial performance. Existing studies have found that diversified utilities outperform non‐diversified utilities. Measures of performance have included EPS growth, price‐earnings multiples, market‐book ratios and internal rates of return. However, many of these studies do not compare performance on a risk‐adjusted basis nor indicate whether differences are statistically significant. In contrast, this study compares performance using the efficient market hypothesis. Regression results indicate that there is no significant difference in risk between portfolios comprised of diversified utilities and non‐diversified utilities. Furthermore, no significant difference in return was observed. The performance of the two portfolios does not appear to differ in risk or return. These results tend to support the efficient market hypothesis concerning stockholders' inability to gain an advantage from publicly available information. Differences in company performance that are anticipated and already reflected in stock price do not result in differences in returns to stockholders.

This study investigates the diversification benefits of multiple cryptocurrencies and their usefulness as investment assets, individually or combined, in enhancing the performance of a well-diversified portfolio of traditional assets before and during the pandemic COVID-19.

This paper uses two optimization techniques, namely the mean-variance and the maximum Sharpe ratio. The naïve diversification rules are used for comparison. Besides, the Sharpe and the Sortino ratios are used as performance measures.

The results show that cryptocurrencies diversification benefits occur more during the COVID-19 pandemic rather than before it, with the maximum Sharpe ratio portfolio presenting its highest performance. Furthermore, the results suggest that, during COVID-19, the diversification benefits are slightly better when using a combination of cryptocurrencies to an already well-diversified portfolio of traditional assets rather than individual ones. This serves to improve the performance of the maximum Sharpe ratio portfolio, and to some extent, the naïve portfolio. Yet, cryptocurrencies, whether added individually or combined to a well-diversified portfolio of traditional assets, don't fit in the minimum variance portfolio. Besides, the efficient frontier during COVID-19 pandemic dominates the one before COVID-19 pandemic, giving the investor a better risk-return trade-off.

To the best of the author's knowledge, this is the first study that examines the diversification benefits of multiple cryptocurrencies both as individual investments and as additional asset classes, before and during COVID-19 pandemic. The paper covers all analyses performed separately in previous studies, which brings new evidence regarding the potential for cryptocurrencies in portfolio diversification under different portfolio strategies.

This paper aims to construct and compare various total‐return world stock indices based on daily data.

Because of diversification, these indices are noticeably similar. A diversification theorem identifies any diversified portfolio as a proxy for the growth optimal portfolio.

The paper constructs a diversified world stock index that outperforms a number of other indices and argues that it is a good proxy for the growth optimal portfolio.

The diversified world stock index has applications to derivative pricing and investment management.

Modern portfolio theory demonstrates that a well‐diversified portfolio will minimize unsystematic risk. It may be impractical to achieve a well‐diversified portfolio of venture capital (VC) investments due to market imperfections, leading to the decision to specialize. The purpose of this paper is to determine the implications of choosing a strategy of specialization versus diversification in venture investing.

Using a dataset of US VC funds across a 20‐year time period, this paper verifies that there has been a tendency for venture capitalists to pursue a specialization strategy in both industry and stage of development of portfolio firms. A multivariate two‐limit tobit model is constructed to determine the effects of these decisions on venture success rates.

It is found that venture capitalists that diversify across portfolio company stage of development have greater success in bringing companies public and exiting their investments via acquisition. Industry specialization has no significant impact on venture fund success rates.

Success rates may be less important than returns to investors in VC. Future research should examine the effects of specialization on investor returns.

It may be beneficial to increase the level of diversification of VC investments across portfolio company stage of development. The lack of diversification across industry has not significantly affected success rates across funds, thus the tendency to specialize in particular industries over the sample period is not necessarily a poor decision.

Prior research demonstrates a tendency for specialization in VC investing. This paper examines the implications of adopting this strategy.

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.

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.

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.

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.

This study seeks to examine the effectiveness of controlling the currency risk for international diversified mixed‐asset portfolios via two different hedge instruments, currency forwards and currency options. So far, currency forward has been the most common hedge tool, which will be compared here with currency options to control the foreign currency exposure risk. In this regard, several hedging strategies are evaluated and compared with one another.

Owing to the highly skewed return distributions of options, the application of the traditional mean‐variance framework for portfolio optimization is doubtful. To account for this problem, a mean lower partial moment model is employed. An in‐the‐sample as well as an out‐of‐the sample context is used. With in‐sample analyses, a block bootstrap test has been used to statistically test the existence of any significant performance improvement. Following that, to investigate the consistency of the results, the out‐of‐sample evaluation has been checked. In addition, currency trends are also taken into account to test the time‐trend dependence of currency movements and, therefore, the relative potential gains of risk‐controlling strategies.

Results show that European put‐in‐the‐money options have the potential to substitute the optimally forward‐hedged portfolios. Considering the composition of the portfolio in using in‐the‐money options and forwards shows that using any of these hedge tools brings a much more diversified selection of stock and bond markets than no hedging strategy. The optimal option weights imply that a put‐in‐the‐money option strategy is more active than at‐the‐money or out‐of‐the‐money put options, which implies the dependency of put strategies on the level of strike price. A very interesting point is that, just by dedicating a very small part of the investment in options, the same amount of currency risk exposure can be hedged as when one uses the optimal forward hedging. In the out‐of‐sample study, the optimally forward‐hedged strategy generally presents a much better performance than any types of put policies.

The research shows the risk and return implications of different currency hedging strategies. The finding could be of interest for asset managers of internationally diversified portfolios.

Considering the findings in the out‐of‐sample perspective, the optimally forward‐hedged minimum risk portfolio dominates all other strategies, while, in the depreciation of the local currency, this, together with the forward‐hedged tangency portfolio selection, would characterize the dominant portfolio strategies.

Although real estate represents a substantial proportion of the UK investment market, research in this area is extremely limited. This is particularly true of the performance and construction of portfolios. This paper deals with one of the major issues which confronts both investor and advisor; namely, how effective is the diversification of a real estate portfolio as more properties are included. The analysis is undertaken at an empirical level and draws on similar research developed in the stock market. The main findings are that the low correlation between returns on individual properties enable high levels of risk reduction to be achieved. This correlation structure does, however, impose a penalty making it extremely difficult to construct highly diversified portfolios. The problem is exacerbated by the indivisibility of real estate assets.

The authors in this paper aim to investigate the performance of different portfolios of REITs which specialise by property type compared to the performance of a diversified free-float market capitalisation-weighted benchmark index to determine whether superior risk-adjusted returns can be achieved.

First, the authors examine the performance of portfolios constructed using the criteria of equal weight, minimum variance, maximum Sharpe and risk parity rather than free-float market capitalisation. Second, the authors apply an automated trading strategy of trend following to see if this filter will improve risk-adjusted returns.

The two-step process of forming combinations of REIT sectors with the subsequent addition of a trend following overlay can offer clear benefits relative to a passive benchmark investment.

Although three of the four strategies were shown to outperform the benchmark index on a risk-adjusted basis, one issue was that the efficient portfolios tended to have large weightings to relatively few sectors. The authors also found that maximum drawdowns (losses) of the strategies tended to be rather high, as was the benchmark.

The methods outlined in this paper can be applied to construct superior risk-adjusted REIT portfolios globally.

Although studies have been undertaken separately on REIT specialisation and trend following in equity and commodity markets, this paper is the first to combine the two topics, and therefore has particular value for real estate fund managers globally.