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Optimum utilization of investments has always been considered one of the most crucial aspects of capital markets. Investment into various securities is the subject of portfolio optimization intent to maximize return at minimum risk. In this series, a population-based evolutionary approach, stochastic fractal search (SFS), is derived from the natural growth phenomenon. This study aims to develop portfolio selection model using SFS approach to construct an efficient portfolio by optimizing the Sharpe ratio with risk budgeting constraints.

This paper proposes a constrained portfolio optimization model using the SFS approach with risk-budgeting constraints. SFS is an evolutionary method inspired by the natural growth process which has been modeled using the fractal theory. Experimental analysis has been conducted to determine the effectiveness of the proposed model by making comparisons with state-of-the-art from domain such as genetic algorithm, particle swarm optimization, simulated annealing and differential evolution. The real datasets of the Indian stock exchanges and datasets of global stock exchanges such as Nikkei 225, DAX 100, FTSE 100, Hang Seng31 and S&P 100 have been taken in the study.

The study confirms the better performance of the SFS model among its peers. Also, statistical analysis has been done using SPSS 20 to confirm the hypothesis developed in the experimental analysis.

In the recent past, researchers have already proposed a significant number of models to solve portfolio selection problems using the meta-heuristic approach. However, this is the first attempt to apply the SFS optimization approach to the problem.

The purpose of this paper is to explore how organizations manage and integrate exploration and exploitation across the innovation project portfolio. Such ambidextrous capabilities are required for organizations to innovate and succeed in today's rapidly changing competitive environment. Understanding how exploration and exploitation projects are integrated can illustrate ways to enhance ambidexterity and boost learning for the benefit of both approaches.

A multiple-case study approach was used to explore innovation portfolio management in six large organizations that emphasize innovation in their strategies.

The findings draw upon concepts of paradox and contingency to reveal that the inherent tension between formality and flexibility in managing innovation project portfolios is aligned with the need for organizational ambidexterity that maintains effective exploitative innovation while supporting explorative innovation capabilities. Four integration mechanisms are identified that enhance ambidexterity across the innovation portfolio by embedding processes for transition from exploration to exploitation and cross-fertilizing knowledge to build innovation capability across both exploration and exploitation.

Managers may find inspiration on ways to enhance learning by bridging exploration and exploitation projects from the four types of integration mechanisms. Recognizing the paradoxical nature of the tension between formality and flexibility in project and portfolio management may also help guide organizations to effectively develop ambidextrous approaches to enhance overall innovation outcomes.

In contrast to perspectives which suggest that paradox and contingency approaches represent disparate perspectives, the authors demonstrate how they can complement each other and work together through innovation portfolio management to support ambidexterity at the portfolio and project levels.

This chapter presents the survey of selected linear and mixed integer programming multi-objective portfolio optimization. The definitions of selected percentile risk measures are presented. Some contrasts and similarities of the different types of portfolio formulations are drawn out. The survey of multi-criteria methods devoted to portfolio optimization such as weighting approach, lexicographic approach, and reference point method is also presented. This survey presents the nature of the multi-objective portfolio problems focuses on a compromise between the construction of objectives, constraints, and decision variables in a portfolio and the problem complexity of the implemented mathematical models. There is always a trade-off between computational time and the size of an input data, as well as the type of mathematical programming formulation with linear and/or mixed integer variables.

There has been a burgeoning interest in exploring the impact of uncertainty factors on share returns. However, studies on the influence of global financial uncertainties on emerging market sectoral indices are scarce. Thus, there is a need to have a thorough investigation of the connection between global financial uncertainties and emerging market sectoral indices. To fill this gap, using the theoretical framework of international portfolio diversification (IPD) and utilizing data from 2008 to 2021, this study examines the spillover connection between global uncertainty indices (GUIs) and leading sectoral indices of 28 emerging markets.

The authors employ the quantile spillover-based connectedness approach and minimum connectedness portfolio approach to explore the dynamic connectedness among sectoral indices and global uncertainty indices (GUIs) as well as portfolio implication.

The study found high connectedness among all indices, especially at higher and lower quantiles. Among GUIs, the authors find that stock market volatility (VIX) and oil volatility index (OVX) are strongly interconnected with all leading emerging markets' sectoral indices. Among sectoral indices, the linkage between the financial (F-Index), information technology (IT-Index), and consumer discretionary (CD-Index) sectors shows moderate interconnectedness. In contrast, the communication services (CS-Index) sector has low interconnectedness with the system. In terms of spillover effects, the authors find EVZ, OVX, and the IT sectors to be net recipients for the entire period. The authors also explored portfolio diversification benefits by employing a minimum connectedness portfolio approach. The cumulative returns' findings show a slight decline in the portfolio's value after 2010; during 2012, the pattern remained stable; from 2014 to 2020, the portfolio performed negatively, that is, underperformance due to different events in that period, including COVID-19. The Consumer Discretionary sector is found to be significant because of having the largest weight, 51%, in the portfolio during the study period.

The study suggests that investors should invest in the communication services sector as it is the least connected. However, the connectedness increases during COVID-19, which implies that it may be difficult for investors to benefit from IPD in a crisis period. Hence, to obtain the benefits from IPD, the evidence suggests that investors need to consider Consumer Discretionary sector while considering assets for investment.

The study's uniqueness is that the authors have investigated spillover between GUIs and 28 emerging markets sectoral indices by employing a quantile spillover-based connectedness approach and minimum connectedness portfolio approach with a special focus on portfolio implication.

In addition to the seminal approach of Markowitz (1952) that is based on finding the optimal budget shares for minimizing risk, the authors also make use of the approach developed by Hatemi-J and El-Khatib (2015), which is built on finding the weights as budget shares for maximizing the risk-adjusted return of the underlying portfolio. For testing the stability of the portfolio benefits, the asymmetric interaction between oil, equity and bonds is tested.

Oil is a major investment commodity. The literature shows mixed results regarding oils' ability to provide diversification benefits. This paper re-examines this issue by applying a new portfolio optimization approach.

The authors find that oil still yields portfolio diversification benefits; contrary to the traditional Markowitz portfolio approach, the asymmetric causality test results show that oil does not cause bonds for either positive or negative changes; however, oil does cause stocks but only for stocks' negative changes. Hence, oil can still make the returns of a portfolio of stocks and bonds unstable through oil's effect on stocks.

This is the first attempt to investigate the potential portfolio diversification benefits of stocks, bonds and oil by using the combination of risk and return explicitly in the optimization problem. The new insights provided by this article might be valuable to the investors, financial institutions and policy makers.

New methods of integrated risk modeling play an important role in determining the efficiency of bank portfolio management. The purpose of this paper is to suggest a systematic approach for risk strategies formulation based on risk‐return optimized portfolios, which applies different methodologies of risk measurement in the context of actual regulatory requirements.

Optimization problems to illustrate different levels of integrated bank portfolio management has been set up. It constrains economic capital allocation using different risk aggregation methodologies. Novel methods of financial engineering to relate actual bank capital regulations to recently developed methods of risk measurement value‐at‐risk (VaR) and conditional value‐at‐risk (CVaR) deviation are applied. Optimization problems with the portfolio safeguard package by American Optimal Decision (web site: www.AOrDA.com) are run.

This paper finds evidence that risk aggregation in Internal Capital Adequacy Assessment Process (ICAAP) should be based on risk‐adjusted aggregation approaches, resulting in an efficient use of economic capital. By using different values of confidence level α in VaR and CVaR, deviation, it is possible to obtain optimal portfolios with similar properties. Before deciding to insert constraints on VaR or CVaR, one should analyze properties of the dataset on which computation are based, with particular focus on the model for the tails of the distribution, as none of them is “better” than the other.

This study should further be extended by an inclusion of simulation‐based scenarios and copula approaches for integrated risk measurements.

The suggested optimization models support a systematic generation of risk‐return efficient target portfolios under the ICAAP. However, issues of practical implementation in risk aggregation and capital allocation still remain unsolved and require heuristic implementations.

Purpose – This chapter considers the question whether firms can contribute to poverty alleviation through engaging in ‘inclusive business’, thereby linking the macro concept of ‘inclusive growth’ to the micro concept of ‘inclusive business’. A key element in this approach is how to take so-called cross-sector partnerships into account. Partnerships are one way of bundling non-market resources in the internationalisation strategies of multinational enterprises (MNEs).

Design/methodology/approach – This chapter is largely exploratory and primarily aimed at validating a general taxonomy of inclusive business. The creation of a multi-level taxonomy of business models of MNEs towards inclusive business takes into account the role of cross-sector partnership portfolios. The taxonomy makes it possible to come to a first comparison of the strategies of MNEs across national and cultural boundaries, distinguish some patterns and discuss determinants of strategies in which partnerships play a role in the inclusive growth strategies of MNEs.

Findings – A first application of this taxonomy on the business and partnership models adopted by the first 100 Global Fortune companies shows that in general firms still adopt very reactive strategies when integrating inclusive business strategies in their cross-sector partnership portfolios.

Originality/value of chapter – This chapter takes a company-specific level of analysis for the relationship between Foreign Direct Investment and development, which is habitually researched at the macro level of analysis. It documents business models as well as the related cross-sector partnerships. Cross-sector partnership portfolios of companies are not yet researched at any systematic level. They form the meso-level link between micro-level business models and macro-level national development strategies.

The purpose of this paper is the development of a patent-based supplier portfolio that can be used to evaluate and select suppliers on account of their technological competencies.

In addition to traditional approaches, the authors develop a supplier portfolio that characterizes suppliers according to the similarity between supplier's and OEM's technological competencies as well as their technological broadness. These variables are measured on the basis of patents, which constitute a valuable source of information in technology-driven industries. Contrary to existing binary measurement approaches, the authors’ portfolio uses semantic analyses to make use of the specific information provided in the patents' texts. The authors test this method in the field of gearings, which is a key driver for the automotive industry.

The authors identify six generic positions, characterizing specific risks for an OEM to become either technologically dependent or dependent on suppliers' production capacities. For each position the authors develop specific management strategies in face of the aforementioned risks. The approach helps OEMs navigate in the competitive landscape based on the most recent and publicly available information medium.

This work explicitly applies the construct of technological competencies to supplier evaluation and selection on the basis of portfolio approaches. Furthermore, the authors improve the use of patents for supplier evaluation in two respects: First, the authors analyze OEMs and upstream suppliers on an organizational level. Second, the authors utilize advanced semantic analysis to generate variables for the measurement of the criteria mentioned above.

Marketing/finance interface and application of its new insights in marketing decisions have recently found great interest among marketing researchers and practitioners. There is a relatively large body of marketing literature about incorporating modern portfolio theory (MPT) into customer portfolio context and taking advantage of it in marketing resource allocation decisions. Previous studies have modelled customer portfolio risk in the form of historical return/profitability volatility of customer base. However, the risk is a future-oriented measure, and deals with future volatility associated with return stream. This study aims to address this research problem.

The well-known Pareto/non-binomial distribution (NBD) approach is used to model customer purchases in a non-contractual setting of research practice. Then, the results were used to simulate the customers’ future buying behaviour and associated returns via the Monte Carlo simulation approach. Subsequently, the mean-variance portfolio optimization model was applied to find the optimal customer portfolio mix.

The results illustrated the better performance of the proposed efficient portfolio versus the current customer portfolio. These results are applicable in analyzing customer portfolio composition, and can be used as a guidance to make decisions about marketing resource allocation in different segments.

This study proposes a new approach to analyze customer portfolio by using the customers’ future buying behaviour. Taking advantage of rich marketing literature about statistical assumptions describing the customers’ buying behaviour, this study tries to take some steps forward in the application of the MPT theory in customer portfolio management context.

An event portfolio is a vital part of economic and socio-cultural processes designed around the use of public events in cities and destinations around the world. The purpose of this paper is to suggest a new research framework for comparative studies of diverse event portfolio strategies.

The discussion in this paper is based on a review of the literature and content analysis of event strategies from two New Zealand cities: Auckland and Dunedin.

The paper suggests an empirically tested framework for exploring event portfolios. It entails such dimensions as the event portfolio strategy, event portfolio focus, portfolio objectives and evaluation tools and event portfolio configuration.

This exploratory research provides a comparative analysis of diverse portfolio contexts and offers insights on developing sustainable event strategies while considering diverse local contexts. Core conditions and processes shaping event portfolio design and management are evaluated and strategic factors articulated.