Portfolio Management Research Articles

Applications of derivatives for portfolio risk management

Applications of derivatives for portfolio risk management

Dynamic portfolio optimization with the MARCOS approach under uncertainty

This paper introduces a dynamic portfolio selection approach that integrates the robustness of interval type-2 fuzzy sets (IT2FSs) with the flexibility of the MARCOS (Measurement of Alternatives and Ranking according to COmpromise Solution) method, offering a novel framework for asset evaluation amidst uncertainty. The IT2FSs enhance the adaptability of asset criteria representation, while the innovative application of MARCOS within the IT2FS environment refines the asset selection process. The weighted semi-absolute deviation metric is embraced to capture portfolio risk characteristic, which ingeniously harnesses the utility function values derived from the IT2F-MARCOS framework to delineate the anticipated return profile. On this basis, a dynamic bi-objective portfolio allocation model with realistic constraints and dynamic risk preference is formulated to rebalance portfolio periodically. Empirical evidence demonstrates the robustness and effectiveness of this approach compared to benchmark indexes, different allocation strategies, and the TOPSIS-based selection method, offering significant advancements in portfolio optimization for investors navigating uncertain markets. This study endeavors to contribute to the field of portfolio management, providing a thoughtful approach that enhances both theoretical understanding and practical application.

Mesoscopic structure of the stock market and portfolio optimization

AbstractThe idiosyncratic and systemic components of market structure have been shown to be responsible for the departure of the optimal mean-variance allocation from the heuristic ‘equally weighted’ portfolio. In this paper, we exploit clustering techniques derived from Random Matrix Theory to study a third, intermediate (mesoscopic) market structure that turns out to be the most stable over time and provides important practical insights from a portfolio management perspective. First, we illustrate the benefits, in terms of predicted and realized risk profiles, of constructing portfolios by filtering out both random and systemic co-movements from the correlation matrix. Second, we redefine the portfolio optimization problem in terms of stock clusters that emerge after filtering. Finally, we propose a new wealth allocation scheme that attaches equal importance to stocks belonging to the same community and show that it further increases the reliability of the constructed portfolios. Results are robust across different time spans, cross sectional dimensions and set of constraints defining the optimization problem.

Quantitative Portfolio Management: Review and Outlook

This survey aims to provide insightful and objective perspectives on the research history of quantitative portfolio management strategies with suggestions for the future of research. The relevant literature can be clustered into four broad themes: portfolio optimization, risk-parity, style integration, and machine learning. Portfolio optimization attempts to find the optimal trade-off of future returns per unit of risk. Risk-parity attempts to match the exposure of various asset classes such that no single asset class dominates portfolio risk. Style integration combines risk factors on a security level such that rebalancing differences cancel out. Finally, machine learning utilizes large arrays of tunable parameters to predict future asset behavior and solve non-convex optimization problems. We conclude that machine learning will likely be the focus of future research.

Re-examining China and the u.s.’s respective green bond markets in extreme conditions: Evidence from quantile connectedness

This study explores the role of green bonds in mitigating risks during extreme conditions, considering China and the US’ robust green bond markets and global risk events. It analyzes the interconnectedness of green bonds with other sectors like conventional bonds, equities, crude oil, and monetary policy. Using the quantile connectedness approach, it reveals how stabilized green bond markets in both countries act as hedges during extreme situations. By examining time-varying spillover effects, it identifies commonalities and differences in linkages between green bond markets and other sectors. These findings endorse green bonds’ integration into finance and hold implications for enhancing portfolio management and risk models.

Innovation portfolio management for the public non-profit research and development sector: What can we learn from the private sector?

ABSTRACT Innovation Portfolio Management refers to the systems, processes and mechanisms to intentionally manage innovation investments and decisions within an organization against its mission or strategy. This approach to managing and optimizing innovation and scaling investments is rarely used by public non-profit R&D organizations. This study draws lessons from innovation portfolio management in private sector organizations. Private sector invests in innovation portfolio management to: (i) enhance transparent and evidence-based decision-making, (ii) strengthen organizational agility and mission-orientedness, (iii) facilitate monitoring, risk management and prioritization and (iv) improve overall organizational performance and learning. These innovation portfolio management benefits are equally relevant for the public non-profit R&D sector, where innovation performance and outcomes are for societal impact. Public non-profit R&D can and should manage their innovation portfolios more intentionally, and can learn from private sector successes and challenges. Embracing the opportunities, whilst managing the challenges and risks requires investment in methods, mechanisms and mindsets for effective innovation portfolio management.

Applications of CDS to bond portfolio management

Applications of CDS to bond portfolio management

Loan delinquency in private sector banks in Kerala

The Indian Banking Sector faces significant difficulties in recovering debt. The banker must understand the underlying causes of loan delinquency to address the problem efficiently. A delinquent loan becomes a NPL (Non Performing Loan) when the borrower failed to repay the loan for a period of 90 days or more. Delinquency is the sign of increased credit risk, warnings of willful default, poor asset quality management and operational inefficiency. It may help to predict the loan loss provision for the sub standard, doubtful and loss assets. This article explores the various causes of loan delinquencies of private-sector banks operating in Kerala. The analysis revealed that the retails and SMEs registered high level of loan delinquency. A significant difference was found between the old and new generation private sector banks for the Poor loan portfolio management, inadequate collateral, inadequate monitoring and follow-up. From the mean score it is evident that the NPA management in new generation private sector banks is appreciable when compared to old generation private sector banks.

Iterative Deep Learning Approach to Active Portfolio Management with Sentiment Factors

Iterative Deep Learning Approach to Active Portfolio Management with Sentiment Factors

Applications of FX derivatives to portfolio management

Applications of FX derivatives to portfolio management

Dividend omissions and dividend cuts behaviour: a dynamic random-effect probit panel regression analysis

PurposeThe study aims to examine the dividend omissions and dividend cuts behaviour of manufacturing and non-financial services firms to identify the determinants of dividend omissions and dividend cuts.Design/methodology/approachThe study analyses the financial data of 3,546 firms from 2011 to 2020 (35,460 firm-year observations) using a dynamic random-effect probit panel regression model.FindingsThe results suggest that profitability, growth opportunity, leverage, liquidity, risk, extraordinary income, shareholding pattern and buyback are major determinants of dividend omissions. Similarly, dividend cut in the previous year, profitability, operating cash flow, risk and extraordinary income are major factors leading to dividend cuts.Research limitations/implicationsFirms which omit the dividend are less likely to start paying dividend in subsequent years, whereas firms which cut the dividend may increase dividend in later years. Also, profitability decreases for a significant number of firms post dividend omission and cut. This indicates that dividend omission is a more prominent signal than a dividend cut for the financial health of a firm.Practical implicationsThe determinants identified in the study enable analysts and portfolio managers to decide the propensity of dividend omission and cut even before actual announcements and can alleviate the significant loss in the portfolio. Also, managers and the board of directors would be able to monitor the firm’s financial performance to avoid the situation leading to dividend omissions and cuts.Social implicationsThe study strongly recommends that firms should voluntarily pay dividends to shareholders to encourage the healthy participation of retail shareholders in the equity market and create a long-term win–win situation for all stakeholders in society. If a large number of firms continue not to pay the dividend, the study appeals to the regulators to intervene to protect shareholders' interests for the greater good of society.Originality/valueTo the best of author’s knowledge, this is the first study to empirically identify the determinants of dividend omission and cut in the unique setting like India where dividend taxation had undergone a significant change.

Analyzing the energy markets and financial markets linkage: A bibliometric analysis and future research agenda

AbstractThis study has been conducted using 200 articles from 1984 to 2023, by undertaking a meta‐literature review on the subject of energy markets and financial markets linkage (EFML). Our study consists of content analysis of 200 articles along with other analyses such as (i) co‐citation analysis, (ii) co‐authorship analysis, and (iii) cartographic analysis. We have identified five research streams: (1) Oil, stock, commodities markets, crypto currency, real estate, exchange rate linkage; (2) Oil and stock market linkage; (3) Energy as a portfolio diversification tool; (4) Dynamic linkage between the oil‐commodity market and stock market; and (5) Oil and other market linkages with respect to the COVID‐19 pandemic, the subsequent financial crisis, and other events. We have performed a comprehensive review of the EFML literature and provided the influential aspects of top journals and authors, the characteristics of the most studied topics, past and current key research streams in the EFML literature. We have also suggested 63 future research questions. Looking at the widespread interest of finance scholarship in the area of energy market linkages, the assessment of energy market linkages, and possible portfolio diversification opportunities and benefits, is of great importance and interest to researchers, policy holders, and portfolio managers.

Pure contagion vs. financial interconnection in the subprime crisis context: Short- and long-term dynamics

This paper examines the difference between pure contagion and financial interconnection by studying the U.S. and some American and Asian markets in the subprime crisis context. These markets are affected by the mortgage crisis, with data available from January 1, 2003 to December 30, 2011. The paper first identifies the turmoil period via the wavelet technique and adopts cointegration and Granger causality approaches by estimating vector autoregressive (VAR) and vector error correction models (VECM) models. Based on daily returns from stock market indices in five American countries (Mexico, Brazil, Canada, Argentina, and the U.S.) and eight Asian ones (Hong Kong, Japan, India, Indonesia, Malaysia, Singapore, Korea, and China), the results show eight cases of pure contagion and 10 cases of financial interconnection. In addition, there were high co-movements in the short term and low co-movements in the long term for financial interconnection cases. These findings have several implications for investors looking to diversify their portfolios internationally and for portfolio managers to expect and limit market risk. The results provide additional guidance to regulators and policymakers.

Addressing the Issue of Supply Chain Disruptions Through Sustainable Managerial Accounting and Strategic Investment: An Economic Resilience Booster

This study addresses the increasing emphasis on sustainability in business, driven by concerns over climate change, resource depletion, and supply chain disruptions, particularly highlighted by the COVID-19 pandemic. The pandemic underscored the vulnerability of supply chains, prompting a shift towards integrating sustainable practices. This research proposes a novel model that integrates Eco-Financial Integration Portfolios (EFIPs) and Sustainable Management Accounting (SMA) to embed sustainability metrics into investment portfolios. Building on Erhun et al. (2021), who advocate for "triple-A supply chains" that are adaptable, agile, and aligned, this model aims to enhance organizational competitiveness. The research also draws on Govindan et al. (2020), who established a link between sustainability and improved organizational performance. The study employs a meta-analysis approach to demonstrate how integrating SMA and EFIPs into supply chains can optimize cost management and environmental performance, providing a competitive edge. The findings suggest that this approach can strengthen the economy by fostering resilient and sustainable supply chains, addressing key global challenges.

Cross-border ESG rating dynamics: An in-depth connectedness analysis of portfolio returns and volatilities in the USA and Canada

This study uses a time-varying parameter vector autoregression (TVP-VAR) model to examine the dynamic relationship between rating changes and portfolio returns in the US and Canada across the environmental (E), social (S), governance (G) and total ESG assessment pillars. The analysis includes both return and volatility spillovers and covers the period from March 2009 to October 2022. The study reveals a fluctuating pattern of connectedness, influenced by global financial events, such as the 2008 financial crisis. In particular, the US shows higher levels of connectedness. Rating changes, particularly in the ESG dimension, show stronger spillovers than returns, highlighting their importance in portfolio construction. The study further explores net connectedness profiles, identifying ESG rating changes as net transmitters. The results suggest that investors should prioritize rating changes over returns, highlighting the importance of considering ESG factors in portfolio management, especially the social criterion, to mitigate investment risks. The research contributes to the understanding of ESG dynamics in international equity markets and provides valuable insights for investors and market regulators.

Comparative Analysis of Portfolio Management Models: Markowitz, CAPM, and Multi-Factor Models

This paper presents a comparative analysis of three foundational portfolio management models: the Markowitz Efficient Frontier, the Capital Asset Pricing Model (CAPM), and Multi-Factor Models. It aims to explore their theoretical foundations, empirical applicability, and practical usage to assess their strengths and limitations in financial portfolio management. The Markowitz model is appreciated for its detailed risk-return optimization framework but criticized for its reliance on historical data and computational demands. The CAPM simplifies risk assessment through market beta, yet its assumptions of market efficiency and a risk-free rate are viewed as impractical under current market conditions. Multi-Factor Models address some limitations of the CAPM by incorporating various risk factors, offering enhanced explanatory power but also adding complexity in factor selection.The study concludes that while no single model is universally superior, the choice of model should depend on the specific needs of the portfolio manager, including risk-return objectives and market environment. The paper suggests a blended or adaptive approach to model selection, highlighting the need for flexibility in response to evolving market dynamics and advances in computational finance.

Preface: 3rd International Conference on Financial Technology and Market Management (FTMM 2024)

The 2024 3rd International Conference on Financial Technology and Market Management (FTMM 2024) have been conducted during July 27-28, 2024, in San Francisco, USA. This conference aims to bring together leading academic scientists, researchers, and scholars to exchange and share their experiences and research results on all aspects of economics, business, and marketing management. It also provides a premier interdisciplinary platform for researchers, practitioners, and educators to present and discuss the most recent innovations, trends, and concerns as well as practical challenges encountered and solutions adopted in the fields of economics, business, and marketing management. More than 180 participants from China, Japan, Malaysia, France, and some other countries attended FTMM 2024. About 36 presentations including 6 plenary talks were presented. The presentations are grouped into 9 areas of particular interest: (1): Economic and monetary crisis, (2): Taxes and regulation, (3): Emerging markets issues, (4): Corporate finance and governance, (5): Asset pricing, investment, and portfolio management, (6): Financial markets, (7): Risk management and quantitative finance, (8) Econometric modeling and empirical issues, (9): Mathematical Finance. With best regards, Conference Organizing Chair San Francisco, USA

Research on the Development of Investment Portfolio Theory

This paper provides a comprehensive analysis of portfolio theory evolution and its practical applications, tracing its development since Harry Markowitz introduced Modern Portfolio Theory (MPT) in 1952. The urgency to enhance capital market efficiency, optimize asset portfolios, and effectively measure and manage risks has intensified due to the rapid transmission of risk across global financial markets. This study reviews historical advancements and recent achievements in portfolio theory and practice. Furthermore, it constructs a theoretical research framework to guide the future development of quantitative investment strategies, focusing on active portfolio management. This framework also delineates several prospective research avenues. The advent of artificial intelligence and big data has transformed portfolio theory into a multidisciplinary nexus involving mathematical statistics, machine learning, and behavioral finance. This integration is crucial for refining asset portfolio optimization and understanding the dynamics of risk spillover and its determinants. The findings and theoretical advancements discussed herein are vitally important for fostering the sustainable development of capital markets and ensuring economic and financial stability. This study not only revisits foundational theories but also sets the stage for pioneering future research in financial analysis and portfolio management.

Enterprise risk management implementation challenges in medical laboratories in Harare, Zimbabwe.

Medical laboratories play crucial roles in healthcare, and effective enterprise risk management (ERM) is necessary to ensure business continuity, patient safety, and quality of care. In medical laboratories, ERM is important for enhancing patient safety, regulatory compliance and accreditation, quality management, business continuity, and cyber security. By following ERM principles and approaches, the medical laboratories can proactively manage their risks, improve patient safety, and maintain a high level of quality and reliability of outcomes. However, implementing ERM in medical laboratories faces unique challenges. This study explored the specific challenges and offers practical solutions for overcoming them to ensure successful ERM implementation in Harare, Zimbabwe. A cross-sectional survey was done through 41 self-administered questionnaires and interviews with medical laboratory staff from the six main medical laboratories in Harare. Data were analyzed using the Statistical Package for Social Sciences version 22. Quantitative data were analyzed using descriptive statistics such as frequencies and percentages. Qualitative data were analyzed using mean scores of Likert scale responses. The main challenges identified in the study included increased workload, staffing, organizational structures, timeliness of information, inadequate information technology support, and insufficient financial support in ERM. These can be addressed by portfolio management of risks, leveraging on cutting edge technology, restructuring to ensure swift responses to issues and redistributing staff workload, and training personnel to avoid burnouts and ensure maximum efficiency. Implementing ERM in medical laboratories requires understanding and addressing these challenges. By following the ERM principles and approaches the medical laboratories can proactively manage their risks, improve patient safety and maintain a high level of quality and reliability of outcomes ERM is still a new approach in the sector and needs further research.

Impact of ESG Risk on Portfolio Optimization and Returns: An Analysis Using the Markowitz Model

This paper explores the integration of Environmental, Social, and Governance (ESG) factors into portfolio optimization using the Markowitz Model, focusing on two groups of ten stocks each from the Technology, Media, and Telecom (TMT) sectors. These stocks are categorized into low and high ESG risk groups according to established ESG rating agencies. Employing historical data, the study computes key financial metrics such as annualized returns, standard deviation, and Sharpe ratios to conduct various portfolio optimizations including the minimal risk frontier, efficient frontier, and inefficient frontier, while also applying five specific operational constraints reflective of real-world investment limits. The analysis distinctly highlights the superior performance of the low ESG risk group, which demonstrated higher returns and better risk-adjusted return profiles, as evidenced by elevated Sharpe ratios. These findings suggest that ESG integration not only aligns with broader societal goals but also enhances financial performance, especially under diverse regulatory and strategic constraints. This research enriches the discourse on sustainable investing by providing empirical evidence on how ESG factors influence traditional portfolio management strategies, potentially guiding future investor decisions and promoting a shift towards more sustainable investment practices.