Portfolio Risk Research Articles

Assessing the infringement risk of patent portfolios using network analysis and IF-TOPSIS: A case of standard-essential patent portfolios in the ICT industry

With the intensification of technological innovation competition and the surge in the number of patents in modern society, companies' technology activities such as technology R&D, technology licensing and technology transfer now regularly involve large patent portfolios, as well as a rising risk of patent infringement. However, the existing patent infringement risk assessment methods are only designed for individual patents, which is not enough to meet the companies' practical need for assessing and managing the infringement risk of large patent portfolios. Therefore, this study proposes a combined approach using network analysis and intuitionistic fuzzy technique for order preference by similarity to ideal solution (IF-TOPSIS), which can assess and rank the infringement risk of a company's patent portfolio relative to each of its competitors' patent portfolios, thereby providing a scientific base for the company's management decisions on patent portfolios. In this approach, one-mode weighted patent proximity networks are constructed to extract topology information of patent portfolios, and the IF-TOPSIS method is combined to obtain and rank the risk results under a proper fuzzy framework. The case study uses patent portfolios containing a total of 6736 standard-essential patents (SEPs) in the information and communications technology (ICT) industry as test data, and verifies the practicality and validity of this intelligent approach. Managerial implications for technology managers and patent attorneys are elaborated.

Risk exposure in ESG-driven portfolios: A wavelet study within the tail-concerned insurance sector

This paper employs wavelet analysis methodology to examine the pairwise time-frequency connectedness and lead-lag relationships between ESG rating changes and insurance equity portfolios' risk exposure. Focusing on the influence of ESG rating changes rather than absolute levels, it contributes to existing research, shedding light on the nuanced dynamics within the insurance sector. The findings underscore the importance of incorporating ESG considerations into portfolio risk assessments for policymakers and portfolio managers alike. Notably, the study reveals the impact of ESG upgrades on portfolio risk exposure, suggesting potential higher returns but also higher total volatility. Moreover, disaggregate risk (total, downside and upside) analysis uncovers insights into environmental, social, and governance factors, emphasizing the relevance of navigating beyond the total volatility and the overall ESG ratings. These insights inform adaptive risk management strategies aligned with evolving ESG standards, contributing to sustainable and risk-conscious economic and investment decisions within the insurance sector.

Hedging global currency risk: A dynamic machine learning approach

We propose a dynamic method to hedge foreign exchange risk of international equity portfolios. The method is based on the currency return forecasts derived from a set of alternative machine learning models, built on the main factor components of the currency return time series. To illustrate our method, we take the perspective of a US portfolio manager investing in a global equity portfolio of developing and developed economies. The analysis of several model performance indicators, back-tested on data from 27 October 2008 to 30 December 2022, allows to conclude that accurate predictions of global currency factor returns, such as those obtained with non linear machine learning models, can improve currency risk hedging of global equity portfolios.

Managing ESG ratings disagreement in sustainable portfolio selection

In sustainable portfolio selection, investors have a twofold objective: they want to achieve the best compromise between portfolio risk and return, but they also want to take into account the sustainability of their investment, assessed through some Environmental, Social, and Governance (ESG) evaluation criteria. The inclusion of sustainable goals in the portfolio selection process may have an impact on the portfolio financial performance. ESG scores provided by the rating agencies are generally considered good proxies for the sustainability performance of an investment, as well as appropriate measures for Socially Responsible Investments (SRI). In this framework, the lack of alignment between ratings provided by different agencies is a crucial issue that inevitably undermines the robustness and reliability of these evaluation measures. In fact, the ESG rating disagreement may produce conflicting information, implying difficulty for the investors in the ESG evaluation of their portfolios. This may cause underestimation or overestimation of the market opportunities for a sustainable investment.In this paper, we deal with a multi-criteria portfolio selection problem, taking into account risk, return, and ESG criteria. For the ESG evaluation of the securities, we consider more than one agency and propose a new approach to overcome the problem related to the disagreement between the ESG ratings given by different agencies. For our three-criteria portfolio selection problem, we present an optimization model which adopts the so-called k−sum operator to formulate a concise ESG evaluation measure. The natural formulation of the model, in which the portfolio risk is measured by the variance of its returns, leads to a nonlinear program, but we show that it can be reformulated as an equivalent convex quadratic model. We also show that the model can be generalized to include any convex portfolio risk measures. An extensive empirical analysis of the out-of-sample performance of this model is provided on real-world financial data sets. From a theoretical viewpoint, our work extends the use of k−sum methodology to quadratic programming.

How do market volatility and risk aversion sentiment inter-influence over time? Evidence from Chinese SSE 50 ETF options

We propose to implement the TVP-VAR-SV model and the spillover index approach to investigate the dynamics of mutual influences between market volatility and risk aversion sentiment (represented by variance risk premium), from aspects of realized variance (RV) and implied variance (IV). We innovatively study the evolution of volatility information transmission mechanisms by analyzing time-varying impulse response and dynamic connectedness in the Chinese market. Upon inspecting shock effects from investor sentiment to RV and IV, we discover that investor sentiment can cause sudden shocks on realized volatility but produce expansive shocks on expected volatility. As we compare spillover effects in call and put options, we find that (i) sentiments in put option contain more volatility information and can affect market volatility, while sentiments in call option primarily perceive volatility spillovers from market volatility, and (ii) investor sentiments in call (put) option become to present more volatility information in a bullish (bearish) market. Our study provides valuable insights on behavioral finance theory and portfolio risk management.

The Complementary Nature of Financial Risk Aversion and Financial Risk Tolerance

Financial risk aversion and financial risk tolerance are sometimes considered to be ‘opposite sides of the same coin’, with the implication being that risk aversion (a term describing the unwillingness of an investor to take risks based on a probability assessment) and risk tolerance (an investor’s willingness to engage in a behavior based on their subjective evaluation of the uncertainty of the outcomes) are inversely-related substitutes. The purpose of this paper is to present an alternative way of viewing these constructs. We show that risk aversion and risk tolerance act as complementary factors in models designed to describe the degree of risk observed in household investment portfolios. A series of multivariate tests were used to determine that financial risk aversion is inversely related to portfolio risk, whereas financial risk tolerance is positively associated with portfolio risk. When used in the same model, the amount of explained variance in portfolio risk was increased compared to models where one, but not the other, measure was used. Overall, financial risk tolerance exhibited the largest model effect, although financial risk aversion was also important across the models analyzed in this study.

Portfolio diversification opportunities in traditional energy and alternative/renewable energy ETF segments

"This study evaluates the diversification benefits of investing in traditional and alternative/renewable energy Exchange Traded Funds (ETFs) using the VAR-ADCC-GARCH model to analyze yields, correlations, and volatilities. The results demonstrate that alternative/renewable energy ETFs not only offer higher average returns but also significantly reduce portfolio risk compared to traditional energy ETFs. The research underscores the distinct investment dynamics between the two ETF segments, highlighting the advantages of incorporating renewable energy assets into diversified portfolios. These findings support the inclusion of environmentally-conscious investment strategies that effectively balance risk and return, emphasizing their importance for investors aiming to optimize their portfolios in line with sustainable practices. Keywords: portfolio diversification, ETFs, traditional energy, renewable energy, VAR-ADCC-GARCH Model JEL classification: G11, C58, A100, A110"

Old age care fund helps to manage their funds In easy way

Abstract: A Old Age Care Funds is a sort of investment vehicle in which the combined capital of several participants is used to purchase a diverse range of bonds, equities, and other securities. Funds, which are professionally managed, give people the chance to invest in a variety of assets without having to handle them themselves. The value of the Fund shares that investors purchase varies according to how well the underlying assets perform. Funds are well-liked by both rookie and seasoned investors because they offer diversity, liquidity, and expert management. Diverse mutual fund categories, such as stock, bond, money market, and hybrid funds, are available to suit varying investment goals and risk tolerances. Investors can select funds according to their risk tolerance, time horizon, and financial objectives. Securities regulators supervise mutual funds to maintain transparency and safeguard the interests of investors. They are now an essential instrument for people to develop a diversified investment portfolio and engage in the financial markets. Old Age Care Fund portfolio analysis is an important component of investment management that includes a variety of approaches for evaluating the performance, risk, and composition of investment portfolios. The efficient market hypothesis (EMH) states that markets are efficient and reflect all available information, making it difficult for fund managers to regularly outperform the market, according to Malkiel and Fame (1970). Jensen (1968) proposed the Capital Asset Pricing Model (CAPM), which emphasizes risk-adjusted returns and the identification of alpha, which indicates a fund manager’s capacity to create excess returns above the market. IndexTerms – Python, Powet-BI, Data Analysis.

Multilayer networks for measuring interconnectedness among global stock markets through the lens of trading volume-price relationship

Using daily data spanning from 5 January 2004 to 22 November 2022, we quantify the spillover effects between 42 global stock markets. Specifically, combining causal structure learning and Elastic-Net-VAR methods, we innovatively construct multilayer causal networks based on volume-price relationship. Then, we analyze the network characteristics of multilayer spillover networks from system and market levels. Our findings indicate that there is heterogeneity in risk spillovers of price and volume networks, highlighting how trading volume spillover network play an important role in the risk contagion. Furthermore, multilayer interconnected networks confirm the risk spillovers between volume and price, and it exhibits significant differences compared to single-layer network. In addition, at system-level, each network layer shows unique network structures and dynamic evolution characteristics. At market-level, global stock markets play different roles in emitting or receiving shocks through various transmission channels. Our study emphasizes the importance of intra- and inter-layer risk propagation in multilayer networks based on volume and price, and has significant implications for developing investment strategies and global portfolio risk management.

Implementing the Variance-Covariance Method for Assessing Market Transaction Risks in Raw Material Sector Stocks

The capital market plays a crucial role in supporting a country's economic growth. Besides being a funding source, the capital market also serves as an investment avenue for investors, particularly through stocks. Every investor must be willing to bear risks in line with their targeted returns. Risk is defined as the uncertainty of future outcomes due to market condition changes, and VaR (Value at Risk) is used to determine the tolerated loss at a certain confidence level. This study discusses the application of the Value at Risk (VaR) method using the Variance-Covariance approach to mitigate market risks in the portfolio of raw material sector stocks. The study focuses on two raw material sector stocks in Indonesia, assuming a normal distribution of asset price changes. The measurement results indicate that with an investment of Rp. 100,000,000.00, a 95% confidence level, and a 1-day period, the VaR of the portfolio of these five stocks is Rp. 2,769,750.00. This research provides critical insights to assist investors in understanding and managing portfolio risks, making VaR a key indicator to measure potential future risks and laying the foundation for decision-making in risk management.

Price discovery share: An order invariant measure of price discovery

To address the order-dependence issue in Hasbrouck’s (1995) Information Share (IS) measure, which assesses a market’s contribution to price discovery, we propose a new metric called the Price Discovery Share (PDS). The PDS is straightforward to compute, easy to interpret, order invariant, and unique. Our measure is inspired by a commonly used method in portfolio risk management that decomposes portfolio volatility into specific contributions from each asset. Through analytical methods and simulations, we demonstrate that the PDS measure offers significant advantages over both the original IS measure and the Modified Information Share (MIS) measure proposed by Lien and Shrestha (2009).

Safe haven properties of industrial stocks against ESG in the United States: Portfolio implication for sustainable investments

This study explores the safe haven role of industry sectors classified by the Global Industry Classification Standards (GICS) for global Environmental, Social, and Governance (ESG) stocks in the United States. Our study applies the novel cross-quantilogram and quantile time-frequency connectedness approach for daily time series data from November 2019 to October 2023. Our findings confirm that industry sectors, mainly financials, industrial, communication, information technology, energy, consumer staples, and consumer discretionary, are the safe haven avenues at down, normal, and up market conditions; however, these safe haven avenues vanish for the long-term investment horizon. We also explore the risk spillover patterns for the total time domain and the decomposed spillover level for the short- and long-term spillovers. Our connectedness finding shows that the net transmitters and net receiver patterns are similar for the extreme markets but dramatically change for the normal markets. Finally, based on the portfolio rebalancing strategy, the returns of our portfolio, comprised of industry sectors and the ESG index, outperform the overall market. Moreover, our portfolio yields lower negative returns and a higher Sharpe ratio when compared with the overall market returns. These findings confirm the benefits of diversification by reducing downside portfolio risk. This study is primarily relevant for socially responsible portfolio and risk management investors.

An empirical investigation of return spillover and volatility dynamics of Indian sectoral indices

ABSTRACT This research delves into the interconnectedness and volatility dynamics within sectoral indices amid the COVID-19 pandemic, to determine the most appropriate model for elucidating these dynamics. It addresses the burgeoning interest among investors in comprehending sectoral dynamics within India’s stock markets. Leveraging five years of daily closing price data (April 2017 to December 2021) sourced from the National Stock Exchange’s official website for 16 sectoral indices and the Nifty50 index, the study employs the Diebold-Yilmaz Spillover 2012 framework alongside four GARCH models (E-GARCH, T-GARCH, FIE-GARCH, and FE-GARCH). Empirical analysis underscores that the mid-small financial sector is the riskiest sector among others, advocating for the inclusion of the pharmaceutical sector to mitigate portfolio risks. Furthermore, the research underscores the persistence of volatility across sectors and identifies the TGARCH model as the appropriate model to capture the volatility for most sectoral indices.

Measuring ESG risks in multi-asset portfolios: Decomposing VaRESG into CVaRESG

This study investigates the contribution of different asset classes to investment portfolio risk by integrating environmental, social, and governance (ESG) factors into traditional financial risk measures. We propose a new methodology for decomposing VaRESG by measuring the Component VaRESG (CVaRESG) of a multi-asset financial portfolio. A pilot empirical application's results provide evidence of the reliability of CVaRESG to define the maximum contribution of the risk accepted for securities or parts of the financial portfolio. This study contributes to the debate on how ESG factors can have quantifiable long-term financial impacts and clarifies the risk contribution of each security included in a financial portfolio.

The rise of passive investing: a systematic literature review applying PRISMA framework

Purpose Passive investing has established itself as the dominant force in the world of professionally managed assets, surpassing the concept of index funds. Its meteoric rise is fueled by investors’ preference for its dual benefits of strong diversification and low cost. A comprehensive study of the economic model, addressed areas and market structure has not yet been conducted, despite the existence of numerous studies on more specific topics. To address this gap, this paper examines 943 articles on passive investing published between 1998 and 2022 in SCOPUS and Web of Science.Design/methodology/approach The study utilizes the most pertinent tools for conducting a systematic review by the PRISMA framework. This article is the result of SLR and extensive bibliometric analysis. Contextualized systematic literature review is used to screen and select bibliographic data, which is then subjected to a variety of bibliometric analyses. The study provides a bibliometric overview of works on passive investment research that are indexed in Scopus and Web of Science. Bibliometrix, VoS Viewer and Cite Space are the tools used to conduct content and network analysis, to ascertain the present state of research, as well as its focus and direction.Findings Our exhaustive analysis yields important findings. One, the previous decade has witnessed a substantial increase in the number of publications and citations; in particular, the inter-disciplinary and international scope of related research has expanded; Second, the top three clusters on “active versus passive funds,” “price discovery and market structures” and “exchange-traded funds (ETFs) as an alternative” account for more than fifty percent of the domain’s knowledge; Third, “Leveraged ETFs (LETFs)” and “environmental, social and governance (ESG)” are the two emerging themes in the passive investing research. Fourth, despite its many benefits, passive investing is not suitable for everyone. To get the most out of what passive investing has to offer, investors, intermediaries and regulators must all exercise sufficient caution. Our study makes a substantial contribution to the field by conducting a comprehensive bibliometric analysis of the existing literature, highlighting key findings and implications, as well as future research directions.Research limitations/implications While the study contributes significantly to the field of knowledge, it has several limitations that must be considered when interpreting its findings and implications. With our emphasis on academic journals, the study analyzed only peer-reviewed journal articles, excluding conference papers, reports and technical articles. While we are confident that our approach resulted in a comprehensive and representative database, our reliance on Elsevier Scopus and Web of Science may have resulted in us overlooking relevant work accessible only through other databases. Additionally, specific bibliometric properties may not be time-stable, and certain common distribution patterns of the passive investing literature may still be developing.Practical implications With this study, it has been possible to observe and chart the high growth trajectory of passive investing research globally, especially post-US subprime crisis. Despite the widespread adoption of passive investing as an investment strategy, it is not a one-size-fits-all proposition. Market conditions change constantly, and it frequently requires an informed eye to determine when and how much to shift away from active investments and toward passive ones. Currency ETFs enable investors to implement a carry trade strategy in their portfolios; however, as a word of caution, currency stability and liquidity can play a significant role in international ETFs. Similarly, LETFs may be better suited for dynamic strategies and offer less value to a long-term investor. Lastly, the importance of investor education cannot be underestimated in the name of the highly diversified portfolio when using passive alternatives, for which necessary efforts are required by regulators and investors alike.Social implications The inexorable trend to passive investing creates numerous issues for fund management, including fee and revenue pressure, which forces traditional managers to seek new revenue streams, such as illiquid and private assets, which also implies increased portfolio risk. Additionally, the increased transparency and efficiency associated with the ETF market indicates that managers must rethink the entire value chain, beginning with technology and the way investments interact. Passive investments have triggered changes in market structure that are still not fully understood or factored in. Active management and a range of valuation opinions on whether a price is “too low” or “too high” provide much-needed depth to a market as it attempts to strike a delicate balance between demand and supply forces, ensuring liquidity at all price points.Originality/value I hereby certify that I am the sole author of this paper and that no part of this manuscript has been published or submitted for publication.

Employment of the DCC-GARCH Copula Model to explore a link between robotics and artificial intelligence and green crypto investments.

The pursuit of the Sustainable Development Goals (SDGs) requires considerable new green crypto investments. To attract the flow of this investment, it is necessary to develop and apply robotic artificial intelligence (AI) as it has the potential to encourage the adoption of environmental innovation and increase individuals' environmental awareness. Our research employs the DCC-GARCH Copula Model to examine time-varying spillovers and prove interlinkages between the development of AI and green cryptocurrencies in the period from January 1, 2018, to September 8, 2023. Comparing the optimum hedge ratios with the optimal portfolio weights, we demonstrate that the optimal hedge strategy for BOTZ is the most successful one. However, the success of hedging depends on the portfolio's risk profile. Based on our analysis of the cumulative profit profile of different approaches, we continue to believe that the best portfolio weighting strategy is the one that produces positive returns in the middle of 2020 and the first part of 2022 and 2023. This demonstrates that the most profitable diversification approach is not always the most successful one. Our results have important policy implications for investors and governments.

Financing constraints, major business performance, and return on financial assets

This study systematically examines the relationship between financing constraints and the return on corporate financial assets based on data from Chinese listed companies from 2012 to 2022. It found a positive correlation between the risk and return of financial asset portfolios; higher risk leads to higher return. Firms with fewer financing constraints have better returns on financial assets. A decrease in return on a firm's operating assets often coincides with an increase in return on financial assets.

A Moorland dam: remedial grouting works

Dam T was constructed around 1880 as a water supply to Greater Manchester and is a category A impounding reservoir, comprising an earth embankment with a central puddle clay core and storage capacity of approximately 934 000 m3. It is one of the earliest dams constructed by Bateman and lies in a cascade of three reservoirs. As part of United Utilities portfolio risk assessment an Internal Erosion Toolbox, flood and slope stability studies were undertaken. These identified the reservoir's primary failure mechanism as internal erosion through the embankment, presenting an unacceptable risk. To confirm the conclusions and target a potential solution a Willowstick survey suggested a compromised central core. This paper summarises the grouting works undertaken to remediate the potential core defect in a constrained and environmentally sensitive site. It highlights the benefits of collaborative working, supported by specialist contractors, the qualified civil engineer and catchment teams, the use of innovative techniques and lessons learnt from previous projects as well as the challenges presented by the proximity of the public and nesting birds. A total of 322 980 litres of grout was carefully injected with the works completed two months ahead of programme and significantly below predicted costs.

An uncertain bi-objective mean-entropy model for portfolio selection with realistic factors

In the imprecise investment environment, there are many indeterminate factors impacting security returns. This paper introduces a portfolio optimization problem where cross-entropy is utilized to control portfolio risk within the framework of uncertainty theory and presents an uncertain bi-objective mean-entropy portfolio selection model. To be more realistic, some realistic factors such as minimum transaction lots, dividend factors and tax factors are also considered. By introducing a risk preference coefficient, the bi-objective model is converted into a single-objective model and some equivalents are discussed. Additionally, a hybrid intelligent algorithm integrating a genetic algorithm with uncertain estimation is designed to solve the proposed model. Finally, a case study is executed to confirm the practicability of the model and the performance of the algorithm, and an empirical analysis based on the proposed model and the uncertain mean–variance model is developed to illustrate the advantage of the uncertain mean-entropy model in practical investment.

Risk price decomposition and the output gap

AbstractWe employ a time‐varying price of risk model that allows us to track the change in prices of risk. We find that the output gap generates the time‐varying prices of market and momentum risks, but the exposures to the output gap have the opposite signs. In contrast, we do not observe that the output gap is linked to time variations in the prices of value and investment risks. We uncover that the output gaps impact the prices of market risk for European and Japanese portfolios, while there are weak relationships between the prices of momentum risk and output gaps.