Portfolio Level Research Articles

Contagion network, portfolio credit risk, and financial crisis

We develop a network-based nonlinear dynamical system model to study credit exposure risk at the portfolio level. This model captures the complex characteristics of contagion arising from the microstructural interdependencies among firms, especially looping effects. We find that when contagion features are not adequately modeled, portfolio credit risk is generally underestimated, but becomes overestimated during a crisis. This can partly explain the outbreak and subsequent intensification of a crisis such as the 2008 financial crisis. We also derive an expression for the portfolio loss of a regular network, which has implications for measurement and pricing of portfolio credit risk.

The Portfolio‐Driven Disposition Effect

ABSTRACTThe disposition effect for a stock significantly weakens if the portfolio is at a gain, but is large when it is at a loss. We find this portfolio‐driven disposition effect (PDDE) in four independent settings: U.S. and Chinese archival data, as well as U.S. and Chinese experiments. The PDDE is robust to a variety of controls in regression specifications and is not explained by extreme returns, portfolio rebalancing, tax considerations, or investor heterogeneity. Our evidence suggests that investors form mental frames at both the stock and the portfolio levels and that these frames combine to generate the PDDE.

Towards a comprehensive framework for risk assessment of organizational development project portfolios

The benefits of risk management in the context of project portfolios have been widely recognized in the literature. However, approaches that assess the risk of organizational development project portfolios from the perspective of how the portfolio delivers value to the parent organization remain largely unexplored. To address this gap, our research takes a constructivist approach and an organizational perspective on project portfolios. We conducted twenty-eight semi-structured interviews and used thematic analysis to identify and relate four themes of a comprehensive project portfolio risk assessment (PPRA) framework: "project portfolio as the organizational unit for PPRA"; "organizational capabilities as portfolio outcomes in which PPR can be assessed"; "project portfolio levels as sources of risk factors in PPRA"; and "balance between project portfolio attributes complexity". Within the framework of organizational development project portfolios, this study contributes to our understanding of PPRA by providing two propositions: (1) The capabilities to be generated by the project portfolio can be used as the portfolio primary results on which PPRA can assess the risk of the project portfolio, establishing the impact of PPR on the project portfolio value delivering to the parent organization, and (2) The risk factors that impact the project portfolio expected results can be represented into PPRA as ‘output-related’ risk factors and ‘outcome-related’ risk factors.

Effect of Investment Decisions on Efficiency of Deposit Taking Savings and Credit Cooperative Societies in Nairobi County, Kenya

With growing competition globally, SACCOs are directing their energies on investments to enhance their efficiency and so as to survive extreme competition. However, the decision to invest is subjective and a wrong investment decision can lead companies even to bankruptcy. Investment choices can also be made in compliance with the conditions in the markets, the portfolio level divergence, the results of fundamental and technical analysis, along with what the investors and managers expect and prefer. This study’s intent was to determine how investment decisions impact the efficiency of deposit taking SACCOs in Nairobi. The study’s population was all the 43 DT-SACCOs in Nairobi County, Kenya. The independent variable for the study was investment decisions with four measures; investment in real estate, investment in government securities, investment in fixed deposit and investment in shares. The control variables were liquidity, firm size and liquidity. Firm efficiency was the response variable which was the primary focus of the study. The study utilized secondary data from 2014 to 2018 (5 years) on annual basis. A descriptive cross-sectional design together with the multiple linear regression model were used for the analysis of the variables. For this analysis the researcher used the SPSS version 21 software. The findings gave an R-square value of 0.317 meaning that 31.7 percent changes in the efficiency of DT-SACCOs in Nairobi, Kenya can be attributed to the seven selected predictor variables while 68.3 percent changes of efficiency of DT-SACCOs was attributable to other factors outside the scope of the study. It was further revealed that the predictor variables showed a strong correlation with efficiency (R=0.563). ANOVA results show that the F statistic was substantial at 5% level with a p=0.000. This shows the model was suitable for the study to provide an explanation of the variables. The results also showed that investment in real estate, investment in government securities and investment in shares produced positive and statistically substantial values for this study while investment in fixed deposits, liquidity, firm size and age were found to be statistically insignificant determiners of efficiency. This study recommends that measures should be put in place to enhance investment in government securities, real estate and shares as these three have a substantial influence on efficiency of DT-SACCOs in Nairobi. Keywords: Investment decisions, firm efficiency, liquidity, firm size, firm age

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.

A portfolio-level, sum-of-the-parts approach to return predictability

Existing research on return predictability traditionally employs aggregate, market-level information. To investigate the applicability of return predictability at a finer level, we examine out-of-sample time-series return predictability at the characteristic-based portfolio level, using predictive regressions with portfolio-level predictors and a sum-of-the-parts approach. In addition to rejecting the null of no predictability at the market level, we detect statistically and economically significant out-of-sample predictability amongst particular portfolios. Notably, we show that large growth portfolios exhibit return predictability, consistent with predictions drawn from prior literature, while we fail to consistently detect predictability for all remaining size and book-to-market portfolios. Our results reveal a significant (relative) forecast error R-squared of 0.65 % for large-growth stocks, translating into an annualised certainty equivalent gain of 1.37 %.

An Examination of the Relationship between Volatility, Liquidity and Trading Activity

We investigate the influence of the firm value on the relationship between equity trading activity, market liquidity and return volatility at the portfolio level. For the different firmvalue portfolio, we find that trading activity is negatively associated with liquidity but it is positively associated with volatility so higher trading activity leads to more volatile returns. For the very largest firm-value portfolio, the volatility-liquidity relationship is negative. However, this relationship is positive for other portfolios.

Is accumulation risk in cyber methodically underestimated?

Many insurers have started to underwrite cyber in recent years. In parallel, they developed their first actuarial models to cope with this new type of risk. On the portfolio level, two major challenges hereby are the adequate modelling of the dependence structure among cyber losses and the lack of suitable data based on which the model is calibrated. The purpose of this article is to highlight the importance of taking a holistic approach to cyber. In particular, we argue that actuarial modelling should not be viewed stand-alone, but rather as an integral part of an interconnected value chain with other processes such as cyber-risk assessment and cyber-claims settlement. We illustrate that otherwise, i.e. if these data-collection processes are not aligned with the actuarial (dependence) model, naïve data collection necessarily leads to a dangerous underestimation of accumulation risk. We illustrate the detrimental effects on the assessment of the dependence structure and portfolio risk by using a simple mathematical model for dependence through common vulnerabilities. The study concludes by highlighting the practical implications for insurers.

Risk-return Portfolio Level Trade-off for Czech Banks

Risk-return Portfolio Level Trade-off for Czech Banks

Driving Organizational Effectiveness: Implementing Safe Agile Framework for Team Alignment in Large Organisations

Implementing the Scaled Agile Framework (SAFe) in large organizations is crucial for achieving organizational effectiveness, especially as they expand globally. The SAFe framework, initially designed for software development, has evolved to cater to diverse industries like health, manufacturing, engineering, and financial services. The study elaborates the significance of implementing SAFe agile framework for team alignment in large organisations. SAFe operates at four levels: Team, Program, Large Solution, and Portfolio. Efficient collaboration, communication, and coordination, the three Cs of SAFe Agile, are essential for synergy across these levels. To practically implement SAFe and achieve team alignment, organizations should follow ten SAFe principles. These principles include taking an economic view, applying systems thinking, assuming variability, building incrementally with fast learning cycles, basing milestones on objective evaluation, ensuring uninterrupted value flow, applying cadence, unlocking intrinsic motivation, embracing decentralized decision-making, and organizing around value. Balancing bottom-up and top-down approaches through a middle-out method ensures effective SAFe implementation. This approach combines the strengths of methods, fostering cross-functional collaboration and effective communication channels from teams to the portfolio level. In conclusion, large-scale businesses may enhance organizational success through the transformational process of applying the SAFe framework for team alignment, which improves alignment, cooperation, efficiency, flexibility, and continuous improvement.

Managing public real estate and the trade-off between supporting user activities and sustainable development: case of the Netherlands police

PurposeCorporate real estate management (CREM) is complex due to an increasing number of real estate (RE) added values and the tensions between them. RE managers are faced with trade-offs: to choose a higher performance for one added value at the cost of another. CREM research mainly deals with trade-offs in a hypothetical sense, without looking at the characteristics of the RE portfolio nor the specific context in which trade-offs are made. The purpose of this paper is to further develop the concept of real estate value (REV) optimisation with regard to tensions between decreasing CO2 emissions and supporting user activities.Design/methodology/approachMixed method study. REV optimisation between user activities and energy efficiency for police stations in the Netherlands built between 2000 and 2020 is analysed. This is complemented by interviews with an RE manager and senior user of police stations and analysis of policy documents.FindingsThe characteristics of the police station portfolio indicate no correlation between user activities and energy efficiency for the case studied. This is complemented by interviews, from which it becomes clear that there was in fact little tension between supporting user activities and energy efficiency. The performances of these two different added values were optimised separately.Originality/valueThis study combines different scales (building and portfolio level) with different types of data: portfolio analysis, document analysis and interviews. This creates a comprehensive image of whether and how the Netherlands police optimised the two RE values.

Exchange complexity: a multi-method analysis of firm configurations

PurposeThe purpose of this study is to investigate if a firm's exchange complexity profile (that is, the linkages between the firm and its environment) influences investor behavior at the negotiation table where a firm valuation is derived.Design/methodology/approachThe authors utilize Qualitative Comparative Analysis (QCA). Specifically, the authors utilize fuzzy-set Qualitative Comparative Analysis (fsQCA), a QCA variant that allows the researcher to assign graduated membership in sets.FindingsWhen the authors dichotomize their positions as either higher stakes that favor the seller (high capital, low equity, high valuation) or lower stakes that favor the buyer (low capital, high equity, low valuation), and when the authors focus primarily on the equity outcome, the authors find that investors adopt a reductionist stance that adheres to a transaction cost economics logic under conditions of lower stakes and higher complexity as well as higher stakes and lower complexity conditions. The authors interpret this to mean that equity serves as a counter-balancing lever for a firm's exchange complexity configuration.Originality/valueOn a theoretical level, the authors showcase the exchange complexity framework and differentiate its position within the extant frameworks that address a firm's competitive advantage. More generally, the authors note that this framework brings the discipline of micro-economics and the field of strategic management closer together, providing scholars with a new tool enabling research across industries for the portfolio level of analysis.

Reporting on the Development of a Web-Based Prototype Dashboard for Construction Design Managers, Achieved through Design Science Research Methodology (DSRM)

Construction Design Management (DM) involves the coordination of design processes and activities to ensure quality project design, yet it involves many challenges. This study reports on a collaborative Knowledge Transfer Partnership (KTP) project with a Case Study Organization (CSO) that tackled several issues faced by construction design managers. Employing a design science research methodology (DSRM), qualitative analysis of semi-structured interviews with purposefully identified design managers uncovered real-world concerns around design co-ordination and performance monitoring. To address these concerns, a web-based design management prototype dashboard was developed using typical project data to aid in the management of design coordination, task prioritization, and reporting functionalities. The web-based Design Management prototype dashboard enhances design management productivity in construction firms by monitoring design production, assessing designer performance trends, and focusing on Technical Queries (TQs) and Requests for Information (RFIs). Digitalizing selected design management processes improves efficiency and productivity. The visual reporting of the dashboard enables design production monitoring at project and portfolio levels, assesses trends in designer performance, and maintains focus on TQs and RFIs. Demonstrating how web-based Design Management dashboards can enhance productivity, this study emphasizes practical solutions derived from employing a design science research methodology. The development and application of the web-based dashboard contribute to the growing evidence that employing design science research methodology in construction can yield tangible solutions to address real-world construction concerns.

Going beyond probability of success: Opportunities for statisticians to influence quantitative decision-making at the portfolio level.

The pharmaceutical industry is plagued with long, costly development and high risk. Therefore, a company's effective management and optimisation of a portfolio of projects is critical for success. Project metrics such as the probability of success enable modelling of a company's pipeline accounting for the high uncertainty inherent within the industry. Making portfolio decisions inherently involves managing risk, and statisticians are ideally positioned to champion not only the derivation of metrics for individual projects, but also advocate decision-making at a broader portfolio level. This article aims to examine the existing different portfolio decision-making approaches and to suggest opportunities for statisticians to add value in terms of introducing probabilistic thinking, quantitative decision-making, and increasingly advanced methodologies.

Trade fragmentation and volatility-of-volatility networks

We assess the impact of trade fragmentation in equity markets using volatility networks following the volatility-of-volatility (VoV) approach. VoV networks offer an original method for measuring and visualizing the common component of volatilities. We use topological distance and connectivity indicators describing their structure as alternative proxies of VoV. Further, we use panel tests to apply threshold effects regression models on French equity market data after the introduction of MiFID, both at portfolio level and asset level. We show that market fragmentation yields a reduction in VoV, corresponding to both a contraction of volatility networks and a change in their structure. This effect strengthens in the stabilizing fragmentation regime compared to the increased fragmentation regime. Since VoV has been shown to predict stock markets returns, this original finding is widely relevant to market operators, regulators and public authorities.

Comparing two mathematical approaches to aggregate individual climate performances at the portfolio level

Comparing two mathematical approaches to aggregate individual climate performances at the portfolio level

Design Principles for Portfolio Agility – A Delphi Study

The complexities inherent in modern business environments require enterprises to develop agile capabilities to manage their IT investments. While agile delivery practices at the team level have become ubiquitous, enterprises struggle to scale agility to the strategic level. This paper presents a set of design principles to foster agility at the portfolio level. We conducted a qualitative Delphi study to elicit insights from expert practitioners and derive nine design principles for portfolio agility through a consensus approach. These design principles describe how agile portfolios address the flow of value, information, and capital (resources) within their organizational context. Our results form the basis for creating a comprehensive design theory around portfolio agility and represent guidance rooted in practice to develop a portfolio capability that senses, assesses, responds to, and learns from environmental changes. In addition to identifying principles fostering portfolio-level agility, this study makes a unique contribution through its view of portfolio capability as an enabler of organizational flow.

Future Robust Product Portfolio Development: Modelling Innovation Potentials in Product Portfolios

The advancement of product portfolios is a challenging task for companies. The growing number of variants and a significant increase in interactions between mechatronic products create unprecedented complexities. Currently, there is no holistic approach to cope with this increased complexity and to enable the future robust advancement of the product portfolio.Therefore, a descriptive model for the advancement of product portfolios is required to map elements of the product portfolio in the early phase of product development. This work aims to build upon an initial descriptive model to support the modelling of innovation potential in the advancement of the product portfolio. This research is based on the Design Research Methodology to develop a descriptive support approach. Challenges and potential improvements were collected while synthesizing the initial descriptive model and an observational study with 29 individual product developers. Based on the descriptive study, product profiles were worked out to describe the higher product portfolio levels solution-openly. As an extension of this feature, common characteristics of different products in the product portfolio can be modeled in a summarized manner. The extended descriptive model was initially validated in an expert workshop with eleven participants.

Ownership of ESG characteristics

A portfolio can be viewed as the collection of the businesses, policies and practices of constituent companies. We measure investors’ Ownership of this collection. Ownership metrics aggregate an assortment of company specific Environmental, Social and Governance (ESG) characteristics to the portfolio level, and they can inform investment and engagement decisions. Relative to a benchmark, investor Ownership is active and satisfies a zero-sum property, which underscores the distinction between Ownership and impact. Ownership of ESG characteristics may be interpreted as ascribing ethical responsibility, but that conclusion and any decisions that result from it belong to the investor.

ESG criteria and the credit risk of corporate bond portfolios

Demand for sustainable fixed-income investment solutions is surging but there is hardly research on the impact of sustainability on the risk characteristics of fixed-income portfolios. This study examines the impact of sustainability on the credit risk exposure of corporate bond portfolios between 2013 and 2020 by analyzing the returns of sustainable and non-sustainable portfolios using two different asset pricing models and environmental, social, and governance (ESG) ratings from different providers. Controlling for a set of portfolio characteristics, our results show that sustainable portfolios are significantly less exposed to credit risk than their non-sustainable peer portfolios. This finding implies that considering ESG criteria in portfolio management is a suitable means to systematically manage credit risk. Being the first study to investigate the relationship between sustainability and credit risk on a portfolio level, this study contributes to the understanding of the effects of ESG criteria in portfolio management and provides academics and investment professionals with valuable insights.