Portfolio Process Research Articles

Finite-time ruin probability of a risk model with perturbation and subexponential main claims and by-claims

The paper considers a nonstandard risk model with stochastic return and perturbation, in which the price process of the investment portfolio is described as a geometric Lévy process and each main claim may induce a delayed by-claim. When the main claims and by-claims have subexponential distributions, we obtain some asymptotic estimations of the finite-time ruin probability.

ESG integration strategy with a multivariate normal distribution

Purpose: The paper aims to present a new framework for ESG integration strategies in portfolio optimization problems. The optimization in the new structure focuses on the portfolio level, and the procedure is not focused on utility functions or on preliminary weights applied to the asset level. It applies the resampling technique, and all the portfolios are optimal portfolios in the mean-variance space. It uses a filtering process where only optimal portfolios with lower ESG risks are considered. Therefore, this technique works only with optimized portfolios, avoids concentration bias, and considers estimation errors in the expected returns and in the covariance matrix. Design/methodology/approach: The sample mean returns and covariance matrices generated by a multivariate normal distribution are applied in mean-variance optimization to generate several portfolios in the efficient frontiers. An ESG filtering process is used to select portfolios with lower ESG risks from a sample of 42 companies listed on the Brazilian stock exchange with returns from the period of 2018/01/01 to 2024/04/22.Findings: Integration strategy costs may be lower than the best-in-class strategy costs and may be similar to the costs of a negative screening strategy. Social implications: The paper presents a framework that considers social, environmental, and governance factors in the portfolio optimization process.Originality: The main contribution of this paper is to present a new framework that combines resampling of returns’ mean and covariance based on a multivariate normal distribution with an ESG portfolio filtering process.

Optimal trade execution under small market impact and portfolio liquidation with semimartingale strategies

We consider an optimal liquidation problem with instantaneous price impact and stochastic resilience for small instantaneous impact factors. Within our modelling framework, the optimal portfolio process converges to the solution of an optimal liquidation problem with general semimartingale controls when the instantaneous impact factor converges to zero. Our results provide a unified framework within which to embed the two most commonly used modelling frameworks in the liquidation literature and provide a foundation for the use of semimartingale liquidation strategies and the use of portfolio processes of unbounded variation. Our convergence results are based on novel convergence results for BSDEs with singular terminal conditions and novel representation results of BSDEs in terms of uniformly continuous functions of forward processes.

Enhancing portfolio management using artificial intelligence: literature review.

Building an investment portfolio is a problem that numerous researchers have addressed for many years. The key goal has always been to balance risk and reward by optimally allocating assets such as stocks, bonds, and cash. In general, the portfolio management process is based on three steps: planning, execution, and feedback, each of which has its objectives and methods to be employed. Starting from Markowitz's mean-variance portfolio theory, different frameworks have been widely accepted, which considerably renewed how asset allocation is being solved. Recent advances in artificial intelligence provide methodological and technological capabilities to solve highly complex problems, and investment portfolio is no exception. For this reason, the paper reviews the current state-of-the-art approaches by answering the core question of how artificial intelligence is transforming portfolio management steps. Moreover, as the use of artificial intelligence in finance is challenged by transparency, fairness and explainability requirements, the case study of post-hoc explanations for asset allocation is demonstrated. Finally, we discuss recent regulatory developments in the European investment business and highlight specific aspects of this business where explainable artificial intelligence could advance transparency of the investment process.

Practical Analysis of Stock Market Under ESG

In today's era, climate change brought about by the greenhouse effect is gradually bringing more and more economic losses and natural disasters. In order to mitigate the negative impact of climate change, many countries have jointly formulated a 1.5°C climate scenario, which has brought a lot of impact on the global economy and industry development (Henderson et al., 2020). At the same time, my client commissioned me to build a portfolio that complies with the 1.5°C climate scenario, and the shares must be included in the S&P 500 Net Zero 2050 Climate Transition ESG Index as of 30/09/2022. The total portfolio is $100,000, and the benchmark designates the S&P 500 Net Zero 2050 Climate Transition ESG Index. Because the investment horizon is short and only six weeks, I chose semi-active management in my portfolio management process, and the rebalancing method was selected as percentage rebalancing. Finally, based on macro and industry analysis and relative valuation and technical analysis of the corresponding stocks, I selected ten stocks: Starbucks Corporation, Tesla, Inc., Amgen Inc., Cisco Systems, Inc., Eversource Energy, The Coca-Cola Company, and Expeditors International of Washington, Inc., Trans Digm Group Incorporated， Netflix, Inc., S&P Global Inc. I calculated their respective shares using the Markowitz model and bought and rebalanced, but unfortunately, my portfolio did not work as expected. The sector index fell by 4.87% in the week of the investment term, but my portfolio fell by 7.45% and performed poorly. Among them, the collapse of Tesla due to special events and my previous judgment of Tesla were greatly affected, and although its share price was only 9.94%, its share price fell by 33.74%. Although the late-stage rebalancing gave me hope for the better, the short investment horizon became a significant obstacle to the improvement of my portfolio.

Implementation of value-oriented project portfolio management for the development of complex system

ObjectivesThe aim of the article is to set the problem of forming the optimal value-oriented portfolio of the development of a complex system, taking into account the mutual influence of the components of the portfolio on each other.Material and methodsThe research used: project portfolio management methods; systems theory and system analysis (for the formalization of value-oriented management processes); mathematical modeling tools (for the formation of basic models of portfolio management).ResultsThis article provides a basic methodological framework for portfolio management of organizational development. The conceptual framework for portfolio management has been formalized, where portfolio management processes are considered as a means of implementing strategic decisions.ConclusionsThe success of development portfolio management should not only be measured by the economic component, but also by the values that influence the sustainable development of the region. The current legal framework for the design and implementation of public projects in Ukraine is not up to date, as confirmed by the findings of international experts and domestic scientists.

Stock portfolio optimization for risk-averse investors: A novel hybrid possibilistic and flexible robust approach

This study proposes stock portfolio optimization models for risk-averse investors under uncertain conditions. To accomplish this, the study measures risk based on the conditional drawdown-at-risk (CDaR) measure, which can prevent major declines in investment as a conservative investment strategy. Given the uncertain character of the input parameters of the problem, the study first proposes a hybrid possibilistic and flexible model by considering the CDaR measure (CDaR-HPFM) to handle uncertainty. Furthermore, to offer more robust outcomes, the study constructs a hybrid possibilistic and flexible robust model by considering the CDaR measure (CDaR-HPFRM), in the forms of a non-linear and a linear mathematicalprogramming problem. The CDaR-HPFRM can process the robustness of output decisions while dealing with uncertain parameters. The real stock exchange data of 100 companies registered on the Tehran Stock Exchange are investigated to validate the functionality of the proposed models. The results reveal that, when various penalty costs are factored in, the CDaR-HPFRM yields more efficient and more robust results than the CDaR-HPFM. Comparative results also indicate that the proposed models almost always outperform existing methods, in terms of both CDaR and rate of return measures. Proposed models can be used for all types of stock market investments (including micro-investing and investment funds) and can handle portfolio optimization and selection processes in project-based organizations.

Optimal asset allocation for DC pension subject to allocation and terminal wealth constraints under a remuneration scheme

. We investigate the optimal investment problem faced by a defined contribution (DC) pension fund manager under simultaneous allocation and expected shortfall (ES) constraints. Under a non concave utility, a Value-at-Risk (VaR) constraint does not lead to the full prevention of moral hazard. As a widely employed risk management tool, whether an ES constraint can provide a more effective protection than a VaR constraint has been a focus point of research. We apply a dual control approach and a concavification technique to solve the ES-constrained optimization problem for a DC pension plan under an incentive scheme and derive the closed-form representations of the optimal wealth and portfolio processes. Furthermore, we compare the effect of an ES constraint on the optimal investment behavior with that under a VaR constraint in the presence of an option-like scheme for the DC pension members. Theoretical and numerical results show that for a relatively low protection level, a joint VaR and an ES constraints induce the same structure of the optimal solution, which implies that for a non concave optimization problem, the ES-based risk management has lost its advantage over the VaR-based risk management. Therefore, it needs to design a more efficient risk measure to improve the risk management for a DC pension plan.

Portfolio optimization based on the pre-selection of stocks by the Support Vector Machine model

This study aims to analyze the performance of an investment portfolio using the Markowitz model, which maximizes the Sharpe ratio from a set of assets preselected through the Support Vector Machine (SVM) model using fundamental indicators in the Brazilian stock market. With an accuracy of 61% for the SVM model, the results indicate that preselecting assets based on fundamental indicators and subsequently optimizing them by maximizing the Sharpe ratio showed a superior return and faster recovery after drawdown periods compared to the benchmark or SVM (1/n) strategy. These results suggest the relevance of including the SVM in the optimization portfolio process.

Improved Hedge Fund Portfolio Optimization Using 2-Step Covariance Matrix and Fund Transaction Costs

This study focuses on fund portfolio investments in the Chinese market. The application of classic portfolio optimization methods encounters several issues when applied to fund portfolios. For example, issues such as the non-normal distribution of returns on funds or fund portfolios, turnover rate limitations in fund investments, and liquidity constraints of fund assets, which can lead to transaction costs and opportunity costs, are prevalent challenges. The existence of these issues can compromise the effectiveness of classic portfolio optimization methods like Mean-Variance Optimization. This may result in a reduction of accuracy in determining the portfolios optimal weights, a deviation of actual trading results from the models optimal expectation, and may even render the optimal weights impractical in real-world scenarios. To address these challenges, this paper integrates the 2-Step covariance matrix method (2-Step method) and the measurement of fund transaction costs into the portfolio optimization process. The paper finds that the 2-Step method, compared to the baseline, can indeed improve the risk-return indicators of the potimal fund portfolio. The inclusion of the transaction cost can effectively control the turnover frequency of the portfolio. Even after accounting for these costs, the 2-Step method continues to exhibit a significant improvement effect compared to the baseline.

Toward Project Portfolio Selection Applying Game Theory: A Colombian Case Study

The project portfolio selection process aims to maximize synergy among chosen projects while delivering significant value to the parent organization. Due to the complexity of this decision, several approaches to project portfolio selection have been developed. In this paper, we adopt a cooperative and static game with complete information and implement the Shapley Value to determine the optimal mix of projects in a case study of a Colombian project portfolio. The application of the Shapley Value demonstrates its equitable nature, as it fairly distributes benefits considering the number of coalitions and the agreements made by each project within these coalitions.

Decision Support Systems in Stock Investment Problems

This study compiles decision support systems that aim to optimize financial decision processes by examining the literature studies targeting stock investments. The review encompasses a range of methodologies and applications, from traditional approaches such as Markowitz’s Modern Portfolio Theory, Black-Litterman, and Single Index models to artificial intelligence-based techniques. In detail, the contributions of Decision Support Systems to stock portfolio construction and portfolio optimization processes along with comparative analyses between these systems are scrutinized. The review also aims to enable researchers and practitioners to be engaged in portfolio optimization with a framework for future investigations in areas such as historical data analysis, future price movement prediction, assessment of risk factors, and determination of optimal portfolio distribution. Furthermore, it seeks to enhance the understanding of decision support systems employed in portfolio optimization, facilitating a more comprehensive grasp of their utility within stock investments.

Project portfolio management in telecommunication company: A stage-gate approach for effective portfolio governance

In today's fast-paced business environment, implementing strategies through programs, projects, and business-as-usual activities can be challenging for companies. The telecommunication industry, in particular, faces these challenges as it experiences the effects of digital transformation and fast-changing markets. It requires a flexible and adaptive approach to project portfolio management (PPM) to optimize investments and deliver value. This article presents a successful case study of a PPM process using the Stage-Gate model in a prominent telecommunications company that operates in a dynamic and fast-growing environment. The Stage-Gate PPM model comprises four stages: Proposal Selection, Selection of Nominated Demands, Prioritization, and Categorization of Projects. The model is unique as it can be adapted to different projects and incorporates elements of Agile approaches, such as Portfolio Sprint meetings and artefacts. The study demonstrates the importance of a well-defined PPM process in coordinating short-term and long-term activities and effectively allocating time, money, and resources. The Stage-Gate PPM model can potentially enhance project success rates and bring greater value to companies by ensuring the realization of suitable projects. This article contributes significantly to the existing literature on portfolio management, providing valuable insights and lessons applicable to other companies in the industry to enhance their portfolio management processes. Furthermore, this study can interest scholars and researchers seeking to explore effective portfolio management in other complex and dynamic environments.

Portfolio Optimization Using Markowitz Model on Sri-Kehati Index

This thesis investigates the portfolio optimization process using the Markowitz model on the SRI-KEHATI index, an esteemed sustainable investment index. The study aims to explore the potential advantages of incorporating environmental, social, and governance (ESG) factors into portfolio construction. By leveraging historical financial data and reliable ESG metrics, this research develops optimized portfolios that strike a balance between risk and return while adhering to the sustainability criteria of the SRIKEHATI index. The methodology encompasses the collection of credible ESG data and financial information for the constituents of the SRIKEHATI index. The Markowitz model is subsequently employed to analyze the risk and return characteristics of each asset within the portfolio. Through the application of optimization algorithms, the study seeks to identify the optimal asset allocation that maximizes risk-adjusted returns, taking into account the ESG criteria outlined by the SRI-KEHATI index. The outcomes of this research provide valuable insights into the effectiveness of portfolio optimization techniques within the realm of sustainable investing. By considering both financial metrics and ESG factors, investors can construct portfolios that align with their sustainability objectives while optimizing risk and return. The findings shed light on the performance of the optimized portfolios and compare them with conventional approaches, thereby demonstrating the potential benefits of integrating ESG considerations into portfolio decision-making. Additionally, this study examines the practical implications associated with implementing sustainable portfolio strategies based on the SRI-KEHATI index. Overall, this thesis contributes to the expanding body of knowledge on sustainable investing and portfolio optimization, specifically focusing on the SRI-KEHATI index. It provides valuable insights for investors, asset managers, and policymakers interested in sustainable investment strategies. Furthermore, it offers a framework for incorporating ESG considerations into the portfolio construction process using the Markowitz model, thereby aiding in the development of more robust and sustainable investment portfolios.

A digital financial advisory standardization framework for client success in Nigeria

The growing complexity of Nigeria's financial landscape necessitates a more structured and standardized approach to financial advisory services. This paper proposes a Digital Financial Advisory Standardization Framework aimed at improving client success in wealth management and financial planning. The framework focuses on enhancing consistency, transparency, and accessibility through technology-driven solutions. By integrating digital tools such as artificial intelligence (AI) and data analytics, the framework enables financial advisors to deliver personalized, data-driven recommendations. It also introduces standardized risk assessment and portfolio management processes, ensuring that clients receive tailored advice based on uniform best practices. The lack of standardization in Nigeria's financial advisory sector has led to inconsistencies in service quality, limiting consumer trust and market participation. This framework addresses these gaps by promoting regulatory compliance, professional ethics, and continuous advisor education. Additionally, the integration of digital platforms expands access to underserved populations, particularly in rural areas, enabling financial inclusion. By providing a centralized system for managing client information, monitoring compliance, and streamlining advisory operations, the framework improves both advisor efficiency and client outcomes. This standardized approach is expected to result in increased client satisfaction, higher investment participation, and improved financial literacy. Moreover, the framework fosters long-term wealth creation by promoting informed decision-making and reducing exposure to fraudulent schemes. The model ultimately supports economic growth by aligning financial advisory practices with global standards and improving the overall trust in Nigeria's financial system.

UNCERTAINTY MANAGEMENT IN PRODUCT DEVELOPMENT PORTFOLIOS: THE IMPACT OF GLOBAL SUSTAINABILITY AGENDAS

AbstractIncreased focus on sustainability significantly impacts product development portfolio management in organizations. This paper focuses on the significant unaccommodated uncertainty caused by the green transition for current mid- and long-term portfolio management processes. These uncertainties arise in areas such as the regulatory environment, market demands, and technical capabilities. This paper makes four contributions: First, current product portfolio management literature is mostly employing deterministic practices. Uncertainties are incompletely addressed, and current methods fail to address the deep uncertainties of the green transition. Second, building a literature-based conceptual framework of the sources of uncertainty in 6 areas: Business Models, Technology, Regulation and Legislation, Finance and Insurance, Market and Consumer, and Organizational Context. Third, preliminary empirical evidence supports the usefulness of our model for product development portfolio management. Fourth, concluding with a suggested empirical research agenda to develop a deeper understanding of challenges towards method and theory development to support the green transition on the portfolio management level.

A framework of robust project portfolio selection problem under strategic objectives considering the risk propagation

PurposeThe consideration of the substitution phenomenon in the project portfolio selection problem can improve the robustness of project portfolio selection and help enterprises better achieve their strategic objectives. However, the existence of inter-project risk propagation will have a negative impact on project substitution. This paper proposes a new framework for project portfolio selection and constructs a risk propagation model based on strategic objectives to study the impact of risk propagation on substitution in the project portfolio.Design/methodology/approachThe authors first construct a risk propagation model based on strategic objectives to describe the risk propagation between projects. Then the project substitution phenomenon based on risk propagation is put forward, and the calculation method of substitution loss is given. Finally, a robust project portfolio selection framework based on strategic objectives considering risk propagation is constructed.FindingsThe analysis of a case study demonstrates that (1) With the increase of risk intensity, the strategic loss of the same project portfolio increases linearly, and under the same risk intensity, the more projects in the portfolio, the stronger the robustness. (2) Considering risk propagation, the effect of project substitution is significantly weakened, and the strategic loss rate of the project portfolio is significantly increased compared with that of a direct attack.Originality/valueThis study is the first to take the project substitution into account in the project portfolio selection process. Moreover, the authors describe inter-project risk propagation and analyze the impact of risk propagation on the project substitution phenomenon. Finally, the authors extend the evaluation index of robustness. This paper puts forward a new way to solve the problem of project portfolio selection.

Resourcing a Technological Portfolio: How Fairtown Hospital Preserved Results While Degrading Its Older Surgical Robot

Here I theorize about a common challenge that research on technology and organizing has not yet considered: how organizations preserve results given the challenges of managing increasingly heterogeneous technological portfolios. I do so via a study of how a top-tier hospital allocated scarce resources across two surgical robots. After acquiring its second robot, the hospital divided resources between the older and newer robots to build its surgical capacity: it allocated the best available infrastructure to the new robot, and it prioritized assigning inexperienced talent to the new technology to facilitate use and skill development. The hospital then adjusted its resources to build on initial successes, committing both the best available maintenance and more-complex surgical cases to the newer robot. These dynamics inadvertently degraded the older robot, making it increasingly difficult to use. In response, more-experienced surgeons and staff made do with the degrading system: they developed and mastered workarounds, and they developed a venting cycle with management. Their actions reduced concerns about the older technology and stabilized the situation for the hospital, such that for years this portfolio resourcing process facilitated satisfactory outcomes on organizational goals such as growth, new capability, and patient care. But by shunting scarce resources away from the older technology, this process also stressed the experienced talent (even as it built their resilience) and limited exploration of changes that could benefit the hospital.

Risk‐return optimised energy asset allocation in transmission‐distribution system using tangency portfolio and Black–Litterman model

AbstractThe application of Markowitz and tangency portfolio and Black–Litterman models is extended by the authors to energy portfolio selection in transmission‐distribution environments with high penetration of renewable energy. As Transmission System Operator (TSO) and Distribution System Operator (DSO) contextually take mutualistic or conflicting positions in their portfolio selection process, their risk‐return interactions and behaviours depend on their subjective views on generation and operation. Here, the financial portfolio allocation tool Black–Litterman Model is adapted to incorporate subjective views of the operators to arrive at more intuitive portfolios. The best portfolios are searched within the acceptable risk‐return search space of each operator defined by their Markowitz efficient frontiers (EF), for Pareto‐optimising their profits. The tangency portfolio approach, which is generally used to determine the portfolio of risky and risk‐free assets in finance, is used here to determine the portfolio of renewable (energy‐risky) and fuel‐based sources (energy‐risk‐free). The proposed methodology is adopted in an HV–MV interconnected test system operated by one TSO and two DSOs, having wind, solar, coal, gas and nuclear generation technologies. It is observed that completely customisable portfolios can be constructed for TSO and DSO based on their inherent financial and energy risk‐return behaviours and posterior views.

OPTIMISATION OF TARGET INDICATORS OF THE PROJECT PORTFOLIO FOR TRANSPORT AND LOGISTICS SUPPORT OF TOURIST CENTRES

The subject of the study is modelling the optimal target indicators of the portfolio of projects for transport and logistics support of tourist centres. The aim of the study is to improve the efficiency of portfolio management processes for the development of transport and logistics support for tourist centres. Tasks: 1) to develop a conceptual model for harmonising targets / parameters of project products for the portfolio of projects for the transport and logistics support of tourist centres; 2) to determine the mathematical description of the main indicators as functions of the parameters of transport and logistics support of tourist centres; 3) to develop a mathematical model for determining optimal and consistent targets for the portfolio of transport and logistics support of tourist centres. Research methods are: methodology and methods of system analysis, methods of operations research. The following results were obtained: the concept of "hierarchy of tourist centres" was introduced, which is a logistics system that is linked to the relevant transport hubs. To manage transport and logistics projects as part of the portfolio, a conceptual and appropriate mathematical model has been developed to determine the optimal and consistent target indicators of the portfolio of transport and logistics projects for tourism centres as part of the hierarchy. The coordination is formed at the level of tourist flows, taking into account their possible distribution among tourist centres, as well as a single source of funding. The model's control parameters are the necessary indicators of the increase in the capacity and quality of service of transport and logistics systems of tourist centres of the same hierarchy. The objective function of the model reflects the maximisation of the economic effect of implementing projects to improve capacity and quality. The constraints take into account funding opportunities, investment efficiency, goals for the development of tourist flows in each centre, and the conditions for coordinating tourist flows in the centres of the same hierarchy (or part of it). The results obtained take into account the peculiarities of forming economic indicators for the hierarchy of tourist centres and form the basis for assessing the value of transport and logistics projects for tourist centres. Conclusions: The results of the study are a conceptual and appropriate mathematical model that allows to form optimal and consistent parameters of the products of projects for the integrated development of transport and logistics support for tourist centres. The model takes into account the peculiarity of the parameters of transport and logistics support, but its structure and construction principle can be used to form models for optimising and coordinating the target indicators of portfolio projects whose products are interdependent.