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The paper seeks to introduce a method based on the Markowitz mean‐variance portfolio approach to outline a theory of future firm, its environment, and management accounting systems (MASs). The approach is based on the target to choose propositions for the theory to maximise expected credibility.

A conceptual approach with mathematical modelling is presented. It is illustrated by a set propositions extracted from a survey presented previously. The survey results are used to design a theory of future MASs by choosing an efficient sub‐set of propositions with the help of combinatory optimisation.

When maximising the credibility of a theory of future MAS, the trade‐off between the mean and the variance of expert judgments should be considered. The resulting theory depends on the level for disagreement aversion by the theory builder. The approach is a useful tool to design a theory of future MASs.

How to select the level of trade‐off between the mean and the variance of judgments should be analysed further. The methods to design propositions for a theory should be researched in more detail. Possible instrumentation and response biases should be assessed.

This approach provides a practical method to analyse judgments to form a consistent set (portfolio) of propositions. It can be applied to any theory building where propositions cannot be tested (such as in futures research) but only assessed by experts.

The paper includes a new approach for researchers, consultants, and teachers to form a theory of future phenomena such as future MASs.

The purpose of this paper is to prove the effectiveness of minimum semi‐absolute deviations (MSAD) method in dynamic portfolio investment.

In financial investment, the classical static portfolio theory of Markowitz type lacks the dynamic adaptability to the changing market situations. This paper proposes a dynamic portfolio theory which uses MSAD criterion on a moving window to replace the Markowitz mean‐variance analysis.

Two specific models are developed to test the validity of the MSAD method: the first model constructs a portfolio consisting of Shanghai‐Shenzhen 300 Index and a national debt as two contrarian assets; the second model constructs a portfolio consisting of a complete set of 18 Chinese stock sector indices and a national debt. The empirical results of the test using six‐year monthly data (2005 to 2010) provide significant evidence that the MSAD method is valid, producing superior returns of investment over the stock index during the test period.

The findings in this study clearly highlight the validity of the MSAD method in determining the weights of assets in Chinese stock markets.

In order to resolve the problem of portfolio investment in Chinese stock markets, the MSAD method with stop loss control strategy can be used for investors to obtain the weights of assets and control the risk.

This study analyzes and verifies the effectiveness of the MSAD method in dynamic portfolio investment. The stop loss control strategy designed and used in the MSAD method is a pioneering and exploratory experiment.

Reviews the previous research on the management of portfolio investment and compares the performance of a typical small investor’s portfolio of nine popular stocks (optimized portfolio) with a value‐weighted portfolio (VW), using 1992‐1997 US data. Explains how the portfolios were derived on a rolling basis from the previous 30 months’ data, using four risk levels for the optimized portfolios (OPs). Shows that as risk aversion increases for OPs, minimum returns tend to decrease but average returns increase; but that VW provides superior returns with less volatility. Considers the underlying reasons for the results, concludes that diversification is important even when small numbers of stocks are involved; and suggests some avenues for further research.

This issue of Managerial Finance is devoted to modern portfolio theory which has evolved since the pioneering work of Markowitz in 1952. Before the development of modern portfolio theory investors and their advisers used the “traditional approach” to investment management and portfolio selection.

This paper aims to identify a possible mismatch between the theory found in academic research and the practices of investment managers in Brazil.

The chosen approach is a field survey. This paper considers 78 survey responses from 274 asset management companies. Data obtained are analyzed using independence tests between two variables and multiple regressions.

The results show that most Brazilian investment managers have not adopted current best practices recommended by the financial academic literature and that there is a significant gap between academic recommendations and asset management practices. The modern portfolio theory is still more widely used than the post-modern portfolio theory, and quantitative portfolio optimization is less often used than the simple rule of defining a maximum concentration limit for any single asset. Moreover, the results show that the normal distribution is used more than parametrical distributions with asymmetry and kurtosis to estimate value at risk, among other findings.

This study may be considered a pioneering work in portfolio construction, risk management and performance evaluation in Brazil. Although academia in Brazil and abroad has thoroughly researched portfolio construction, risk management and performance evaluation, little is known about the actual implementation and utilization of this research by Brazilian practitioners.

This paper aims to give a brief review on behavioral economics and behavioral finance and discusses some of the previous research on agents' utility functions, applicable risk measures, diversification strategies and portfolio optimization.

The authors also cover related disciplines such as trading rules, contagion and various econometric aspects.

While scholars could first develop theoretical models in behavioral economics and behavioral finance, they subsequently may develop corresponding statistical and econometric models, this finally includes simulation studies to examine whether the estimators or statistics have good power and size. This all helps us to better understand financial and economic decision-making from a descriptive standpoint.

The research paper is original.

This study aims to advance both theory and praxis for event portfolio management in cities and destinations. An experiment has been conducted with professional event practitioners in a city to determine their opinions and strategies for balancing value and risk within their event portfolio. The first objective is to rank 14 of the city's recurring events in terms of both value and risk. Second, the events are plotted in a two-dimensional chart of value versus risk with the objective to differentiate between the 14 events. The third objective is to describe the event characteristics that event professionals associate with value and risk.

Results derive from an experiment involving the forced Q-sort procedure and professional event managers from a city renowned as an “event capital”. Empirical evidence is analysed by the constant comparative method of how events are being evaluated by ten professionals working for a DMO.

Economic impact and image effects are characteristics of high-value events as is an opportunity to create relations with event owners for future collaboration. Local community involvement is important for all events. The issue of portfolio fit was a common argument for weak-value events.

Results are based on the opinions of ten DMO employees in one large city. Conclusions help build event portfolio theory.

The results and methods are useful for event strategists and evaluators. In particular, the management of event portfolios and policies covering events in cities and destinations can benefit from the documented method for explicitly balancing risks with perceived value.

A portfolio perspective is also suggested as an approach to analyse the total tourist attractions portfolio of a destination.

Opinions regarding public value and risk by civil servants who work with events have not been studied before. The constant comparative method produces results that can be applied to policies governing events. In terms of theory development, concepts from financial portfolio management, product portfolio management and risk management are used to develop event portfolio design and management, and insights are gained on trade-offs in the process. The plot of the events in a two-dimensional chart of value versus risk clearly differentiated the 14 events and is an original contribution.

This study aims to propose the Shapley value that originates from the game theory to quantify the relative risk of a security in an optimal portfolio.

Systematic risk as expressed by the relative covariance of stock returns to market returns is an essential measure in pricing risky securities. Although very much in use, the concept has become marginalized in recent years because of the difficulties that arise estimating beta. The idea is that portfolios can be viewed as cooperative games played by assets aiming at minimizing risk. With the Shapley value, investors can calculate the exact contribution of each risky asset to the joint payoff. For a portfolio of three stocks, this study exemplifies the Shapley value when risk is minimized regardless of portfolio return.

This study computes the Shapley value of stocks and indices for optimal mean-variance portfolios by using daily returns for the years 2016–2019. This results in the risk attributes allocated to securities in optimal portfolios. The Shapley values are analyzed and compared to the standard beta estimates to determine the ranking of assets with respect to pertinent risk and return.

An alternative approach to value risk and return in optimal portfolios is presented in this study. The logic and the mechanics of Shapley value theory in portfolio analysis have been explained, and its advantages relative to standard beta analysis are presented. Hence, financial analysts when adding or removing specific assets from present positions will have the true and exact impact of their actions by using the Shapley value instead of the beta.

When computing the Shapley value, portfolio risk is decomposed exactly among its assets because it considers all possible coalitions of portfolios. In that sense, financial analysts when adding or removing specific securities from present holdings will be able to predict the true and exact impact of their transactions by using the Shapley value instead of the beta. The main implication for investors is that risk is ultimately priced relative to their holdings. This prevents the subjective mispricing of securities, as standard beta is not used and might allow investors to gain from arbitrage conditions.

The logic and the methodology of Shapley value theory in portfolio analysis have been explained as an alternative to value risk and return in optimal portfolios by presenting its advantages relative to standard beta analysis. The conclusion is that the Shapley value theory contributes much more financial optimization than to standard systematic risk analysis because it enables looking at the contribution of each security to all possible coalitions of portfolios.

The purpose of this research is to investigate the combination of relational and organizational resource factors that influence small‐to‐medium‐sized firm satisfaction with their supply chain portfolio performance.

This research employs two complementary theoretical lenses frequently used in the explanation of relationship performance, resource‐based view of the firm and strategic behavior theory. The authors then used an international survey based in three Northern European countries to test their hypotheses with hierarchical linear regression.

The quantitative analysis supports all three hypotheses indicating that supply chain portfolio flexibility is an important determinant for small‐to‐medium‐sized firm satisfaction with supply chain portfolio performance. Additionally, firm alliance orientation and entrepreneurial orientation both significantly influence the relationship between supply chain flexibility and performance satisfaction.

This research is limited by the categorization of the supply chain portfolio flexibility types as high and low resource linkages by the researchers. Future research may look at additional ways to measure individual agreements and have firms categorize them according to resource requirements. However, the findings of this research provide a theoretical and empirical foundation through the application of resource‐based view of the firm and strategic behavior theory for future research in the area of small‐to‐medium‐sized firms and their satisfaction with supply chain portfolios.

Important managerial implications are found for small to medium‐sized firms and larger firms that work with them when managing portfolio satisfaction. This research indicates that it makes sense for managers to consider categorizing supply chain relationships similar to the way they categorize their end‐user relationships. This allows small‐to‐medium‐sized firms across the portfolio to be segmented into groups where appropriate relationship maintenance can take place and where more suitable satisfaction goals can be defined in terms of operational metrics.

The framework developed in this paper provides insights on small‐to‐medium‐sized firm satisfaction with supply chain portfolio performance. This research stimulates a new research stream towards an integrated theory of supply chain portfolio management.

Although the modern portfolio theory (MPT) asset allocation framework can be adopted to enable decision making for international and direct real estate investing, and that many institutional investors adopt it to support their decision making, this framework can be enhanced to capture the multi‐causal factors influencing international and direct real estate investing. The purpose of this paper is to explain how a fuzzy decision‐making approach is a more intuitive, yet rigorous alternative in this regard.

This paper is concerned with the model formation and estimation of a unique fuzzy tactical asset allocation (FTAA), which in turn comprises the FTAA flexible programming model and the FTAA robust programming model.

Both these FTAA models enhance the classical, Markowitz MPT portfolio theory on asset allocation through making it more intuitively appropriate for decision making in international and direct real estate investing.

These two FTAA models achieve the benefits of intuitively greater risk diversification by city or real estate sector and enable effective risk management. These two short‐run fuzzy models would be accepted and more such models would emerge as an effective extension of quadratic programming optimization, as more computable software programs of this kind are widespread.

Fuzzy approaches to asset allocation in the short run, are limited by some drawbacks. Fuzzy models possess the common feature of converting the equality function under quadratic programming optimization into inequality functions. Such inequality optimization replaces the point solution of the MPT TAA optimization problem, obtained through the rigid intersection of all functions, via a generalized or intuitive answer over a defined space of alternatives. The product of the fuzzy process with fuzzy inputs, in the form of fuzzy outcome is in actual fact a more natural and intuitive approach to asset optimization.