Journal of Risk and Financial Management

19 pages, 977 KiB

Open AccessArticle

Reinforcement Learning Pair Trading: A Dynamic Scaling Approach

by Hongshen Yang and Avinash Malik

J. Risk Financial Manag. 2024, 17(12), 555; https://doi.org/10.3390/jrfm17120555 - 11 Dec 2024

Cryptocurrency is a cryptography-based digital asset with extremely volatile prices. Around USD 70 billion worth of cryptocurrency is traded daily on exchanges. Trading cryptocurrency is difficult due to the inherent volatility of the crypto market. This study investigates whether Reinforcement Learning (RL) can [...] Read more.

Cryptocurrency is a cryptography-based digital asset with extremely volatile prices. Around USD 70 billion worth of cryptocurrency is traded daily on exchanges. Trading cryptocurrency is difficult due to the inherent volatility of the crypto market. This study investigates whether Reinforcement Learning (RL) can enhance decision-making in cryptocurrency algorithmic trading compared to traditional methods. In order to address this question, we combined reinforcement learning with a statistical arbitrage trading technique, pair trading, which exploits the price difference between statistically correlated assets. We constructed RL environments and trained RL agents to determine when and how to trade pairs of cryptocurrencies. We developed new reward shaping and observation/action spaces for reinforcement learning. We performed experiments with the developed reinforcement learner on pairs of BTC-GBP and BTC-EUR data separated by 1 min intervals (n = 263,520). The traditional non-RL pair trading technique achieved an annualized profit of 8.33%, while the proposed RL-based pair trading technique achieved annualized profits from 9.94% to 31.53%, depending upon the RL learner. Our results show that RL can significantly outperform manual and traditional pair trading techniques when applied to volatile markets such as cryptocurrencies. Full article

(This article belongs to the Special Issue Financial Technologies (Fintech) in Finance and Economics)

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19 pages, 2836 KiB

Open AccessArticle

The Application of Machine Learning Techniques to Predict Stock Market Crises in Africa

by Muhammad Naeem, Hothefa Shaker Jassim and David Korsah

J. Risk Financial Manag. 2024, 17(12), 554; https://doi.org/10.3390/jrfm17120554 - 10 Dec 2024

Abstract

This study sought to ascertain a machine learning algorithm capable of predicting crises in the African stock market with the highest accuracy. Seven different machine-learning algorithms were employed on historical stock prices of the eight stock markets, three main sentiment indicators, and the [...] Read more.

This study sought to ascertain a machine learning algorithm capable of predicting crises in the African stock market with the highest accuracy. Seven different machine-learning algorithms were employed on historical stock prices of the eight stock markets, three main sentiment indicators, and the exchange rate of the respective countries’ currencies against the US dollar, each spanning from 1 May 2007 to 1 April 2023. It was revealed that extreme gradient boosting (XGBoost) emerged as the most effective way of predicting crises. Historical stock prices and exchange rates were found to be the most important features, exerting strong influences on stock market crises. Regarding the sentiment front, investors’ perceptions of possible volatility on the S&P 500 (Chicago Board Options Exchange (CBOE) VIX) and the Daily News Sentiment Index were identified as influential predictors. The study advances an understanding of market sentiment and emphasizes the importance of employing advanced computational techniques for risk management and market stability. Full article

(This article belongs to the Special Issue Investment Management in the Age of AI)

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23 pages, 867 KiB

Open AccessArticle

Bachelier’s Market Model for ESG Asset Pricing

by Svetlozar Rachev, Nancy Asare Nyarko, Blessing Omotade and Peter Yegon

J. Risk Financial Manag. 2024, 17(12), 553; https://doi.org/10.3390/jrfm17120553 - 10 Dec 2024

Abstract

Environmental, Social, and Governance (ESG) finance is a cornerstone of modern finance and investment, as it changes the classical return-risk view of investment by incorporating an additional dimension to investment performance: the ESG score of the investment. We define the ESG price process [...] Read more.

Environmental, Social, and Governance (ESG) finance is a cornerstone of modern finance and investment, as it changes the classical return-risk view of investment by incorporating an additional dimension to investment performance: the ESG score of the investment. We define the ESG price process and include it in an extension of Bachelier’s market model in both discrete and continuous time, enabling option pricing valuation. Full article

(This article belongs to the Section Economics and Finance)

29 pages, 1079 KiB

Open AccessArticle

Large Drawdowns and Long-Term Asset Management

by Eric Jondeau and Alexandre Pauli

J. Risk Financial Manag. 2024, 17(12), 552; https://doi.org/10.3390/jrfm17120552 - 10 Dec 2024

Abstract

Long-term investors are often hesitant to invest in assets or strategies prone to significant drawdowns, primarily due to the challenge of predicting these drawdowns. This study presents a multivariate Markov-switching model for small- and large-cap returns in the U.S. equity markets, demonstrating that [...] Read more.

Long-term investors are often hesitant to invest in assets or strategies prone to significant drawdowns, primarily due to the challenge of predicting these drawdowns. This study presents a multivariate Markov-switching model for small- and large-cap returns in the U.S. equity markets, demonstrating that three distinct regimes are necessary to capture the negative trends in expected returns during financial crises. Our findings indicate that this framework enhances the prediction of conditional drawdowns compared to standard alternative models of financial returns. Furthermore, out-of-sample analysis shows that investment strategies based on these predictions outperform those relying on models with one or two regimes. Full article

(This article belongs to the Special Issue Featured Papers in Mathematics and Finance)

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33 pages, 3351 KiB

Open AccessArticle

Risk-Averse, Integrated Contract, and Open Market Procurement with Quantity Adjustment Costs

by Santosh Mahapatra, Santosh Kar and Shlomo Levental

J. Risk Financial Manag. 2024, 17(12), 551; https://doi.org/10.3390/jrfm17120551 - 9 Dec 2024

Abstract

This paper examines the issue cost-effective procurement of a commodity product when its spot (open) market prices are stochastic, contract prices are previously determined, and there are costs associated with adjusting (i.e., switching) the procurement quantities from an alternative. Spot (open) market and [...] Read more.

This paper examines the issue cost-effective procurement of a commodity product when its spot (open) market prices are stochastic, contract prices are previously determined, and there are costs associated with adjusting (i.e., switching) the procurement quantities from an alternative. Spot (open) market and contract as sole modes of procurement could present risks of high magnitude and uncertainty of expenses for the buyer. To address these risks, a risk-averse buyer may consider simultaneous use of both alternatives with adjustment of the purchase quantities from both the alternatives over time. Scenarios when the switching costs depend on the relative prices of the two alternatives are considered. The problem being analytically intractable, a mixed method decision model combining analytical and computational techniques to analyze the problem is proposed. The model helps identify expected optimal contract and spot market procurement quantities with respect to unknown spot prices and known contract prices over the planned procurement horizon when procurement quantity adjustment costs are influenced by the spends. The analysis reveals that it is cost-effective to continue purchasing with an existing pattern of procurement from the two alternatives until the contract to spot market price ratio reaches a threshold level and then to change the proportion of quantity purchased from the two alternatives. Using numerical analysis, we illustrate the theoretical and managerial significance of this stickiness to continue with an existing pattern until an adjustment. Full article

(This article belongs to the Collection Business Performance)

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31 pages, 1616 KiB

Open AccessArticle

Conceptualizing an Institutional Framework to Mitigate Crypto-Assets’ Operational Risk

by Deepankar Roy, Ashutosh Dubey and Daitri Tiwary

J. Risk Financial Manag. 2024, 17(12), 550; https://doi.org/10.3390/jrfm17120550 - 9 Dec 2024

Abstract

Extent ecosystems of crypto financial assets (crypto-assets) lack parity and coherence across the globe. This asymmetry is further heightened with a knowledge gap in operational risk management, wherein the global landscape of crypto-assets is characterized by unprecedented external risks and internal vulnerabilities. In [...] Read more.

Extent ecosystems of crypto financial assets (crypto-assets) lack parity and coherence across the globe. This asymmetry is further heightened with a knowledge gap in operational risk management, wherein the global landscape of crypto-assets is characterized by unprecedented external risks and internal vulnerabilities. In this study, we present a critical examination and comprehensive analysis of current crypto-asset operational guidelines across geographies. We benchmark these guidelines to the Basel Committee for Banking Supervision (BCBS) risk classification framework for crypto-assets, identifying gaps in the operations across organizations. We, hence, conceptualize a novel institutional framework which may help in understanding and mitigating the gaps in operational risks’ regulation of crypto-assets. Our proposed Crypto-asset Operational Risk Management (CORM) framework determines how operational risk associated with crypto-assets of financial institutions can be mitigated to respond to the increasing demand for crypto-assets, cross border payments, electronic money, and cryptocurrencies, across countries. Applicable to firms irrespective of their size and scale of operations, CORM aligns with global regulatory initiatives, facilitating compliance and fostering trust among stakeholders. Strengthening our argument of CORM’s applicability, we present its efficacy in the form of alternate hypothetical outcomes in two distinct real-life cases wherein crypto-asset exchanges succumbed to either external risks, such as hacking, or internal vulnerabilities. It paves the way for future regulatory response with a structured approach to addressing the unique operational risks associated with crypto-assets. The framework advocates for collaborative efforts among industry stakeholders, ensuring its adaptability to the rapidly evolving crypto landscape. It further contributes to the establishment of a more resilient and regulated financial ecosystem, inclusive of crypto-assets. By implementing CORM, institutions can navigate the complexities of crypto-assets while safeguarding their interests and promoting sustainable growth in the digital asset market. Full article

(This article belongs to the Special Issue The Future of Money: Central Bank Digital Currencies, Cryptocurrencies and Stablecoins)

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20 pages, 699 KiB

Open AccessArticle

Evaluating Financial Inclusion in Peru: A Cluster Analysis Using Self-Organizing Maps

by Alvaro Talavera, Rocío Maehara, Luis Benites, Benjamin Arriaga and Alejandro Aybar-Flores

J. Risk Financial Manag. 2024, 17(12), 549; https://doi.org/10.3390/jrfm17120549 - 4 Dec 2024

Abstract

This study evaluates financial inclusion in Peru through self-organizing maps. Financial inclusion is a multidimensional issue of great importance on the global agenda and continues to concern various actors internationally. In this context, the objective is to assess the financial inclusion situation in [...] Read more.

This study evaluates financial inclusion in Peru through self-organizing maps. Financial inclusion is a multidimensional issue of great importance on the global agenda and continues to concern various actors internationally. In this context, the objective is to assess the financial inclusion situation in the country and determine how self-organizing maps can complement standard models for this purpose. The empirical aim is to demonstrate how this technique can help identify priority areas and vulnerable groups, thus facilitating decision-making and policy design to improve the access to and use of financial services among Peruvian consumers by finding clearly defined profiles that allow the identification of potential problems within each category. This makes it possible to create customized strategies for each group, such as addressing the financial inclusion barriers faced by rural residents, compounded by low income and educational levels. Full article

(This article belongs to the Special Issue Applied Statistics and Big Data Analysis in Finance: Exploring Emerging Trends and Opportunities)

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22 pages, 1429 KiB

Open AccessArticle

Determinants of Sustainable Entrepreneurship in Morocco: The Role of Entrepreneurial Orientation, Financial Literacy, and Inclusion

by Ikram Zouitini, Hamza El Hafdaoui, Hajar Chetioui, Pierre-Martin Tardif and Mohamed Makhtari

J. Risk Financial Manag. 2024, 17(12), 548; https://doi.org/10.3390/jrfm17120548 - 30 Nov 2024

Abstract

This paper investigates the relationship between sustainable entrepreneurship and financial inclusion, financial literacy, and entrepreneurial orientation. As sustainable entrepreneurship gains academic and practical interest, understanding factors that enable entrepreneurs to operate sustainably is fundamental. The manuscript uses an electronic questionnaire distributed to key [...] Read more.

This paper investigates the relationship between sustainable entrepreneurship and financial inclusion, financial literacy, and entrepreneurial orientation. As sustainable entrepreneurship gains academic and practical interest, understanding factors that enable entrepreneurs to operate sustainably is fundamental. The manuscript uses an electronic questionnaire distributed to key economic stakeholders and performs partial least squares structural equation modeling on data from 169 respondents. The results show that entrepreneurial orientation has a positive and significant impact on sustainable entrepreneurship, with a beta coefficient of 0.878 and a probability value of less than 0.01. Financial literacy significantly influences sustainable entrepreneurship, with a beta coefficient of 0.389 and a probability value of less than 0.001, and it partially mediates its relationship with financial inclusion, showing a beta coefficient of 0.3 and a probability value of 0.013. Financial literacy and financial inclusion are positively correlated, with a beta coefficient of 0.771 and a probability value of less than 0.05. However, the impact of financial inclusion on sustainable entrepreneurship is negative and insignificant, with a beta coefficient of −0.392, and there is no evidence that entrepreneurial orientation moderates the link between financial literacy and sustainable entrepreneurship. The findings provide valuable insights for Moroccan policymakers to promote entrepreneurship, suggesting that financial literacy plays a crucial role in enhancing sustainable business practices. The study emphasizes the need for Morocco to adapt to current programs and create a supportive financial environment for entrepreneurs. Due to a lack of comprehensive datasets, the study’s conclusions are limited and might not accurately reflect the entire landscape. Full article

(This article belongs to the Special Issue The New Horizons of Global Financial Literacy)

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27 pages, 458 KiB

Open AccessArticle

Inflation _targeting with an Optimal Nonlinear Monetary Rule—The Case Study of Colombia

by Martha Misas, Edgar Villa and Andres Giraldo

J. Risk Financial Manag. 2024, 17(12), 547; https://doi.org/10.3390/jrfm17120547 - 30 Nov 2024

Abstract

This article examines whether Banco de la República (Banrep), Colombia’s central bank, has operated under a dual-regime policy framework—one for recessionary periods and another for periods of economic overheating—since adopting inflation _targeting (IT) from Q4 2000 to Q4 2019. We modify the canonical [...] Read more.

This article examines whether Banco de la República (Banrep), Colombia’s central bank, has operated under a dual-regime policy framework—one for recessionary periods and another for periods of economic overheating—since adopting inflation _targeting (IT) from Q4 2000 to Q4 2019. We modify the canonical New Keynesian inflation model to accommodate an optimal nonlinear monetary rule aligned with a two-regime policy framework. Using a LSTAR model estimated over the study period, with the output gap lagged by three periods as the transition variable, we identify two distinct monetary regimes. Our findings reveal that the smooth transitions between regimes were driven by shifts in Banrep’s preferences related to its loss function, alongside adjustments in the parameters of the aggregate demand and supply curves within the Colombian economy. Notably, we observe that a modified Taylor principle is not met in either identified monetary regime. This suggests that, in this context, IT has been a successful policy framework even without requiring the policy interest rate to respond aggressively to inflation gaps, as the Taylor principle would otherwise dictate. Full article

(This article belongs to the Special Issue Open Economy Macroeconomics)

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19 pages, 1931 KiB

Open AccessArticle

Researching the Impact of Corporate Social Responsibility on Economic Growth and Inequality: Methodological Aspects

by Mihail Chipriyanov, Galina Chipriyanova, Radosveta Krasteva-Hristova, Atanas Atanasov and Kiril Luchkov

J. Risk Financial Manag. 2024, 17(12), 546; https://doi.org/10.3390/jrfm17120546 - 30 Nov 2024

Abstract

The study focuses on analyzing the impact of corporate social responsibility (CSR) on economic growth and reducing inequality, highlighting the importance of CSR in achieving sustainable development and social justice. The main aim is to analyze how different CSR initiatives contribute to economic [...] Read more.

The study focuses on analyzing the impact of corporate social responsibility (CSR) on economic growth and reducing inequality, highlighting the importance of CSR in achieving sustainable development and social justice. The main aim is to analyze how different CSR initiatives contribute to economic development, social prosperity, and the reduction in inequality by reviewing the methods used to assess their impact. The research methodology includes a detailed literature review, bibliometric analysis and scientific mapping, surveys of various business organizations, and a gap analysis regarding the identification of gaps between the current state of CSR activities and the expected outcomes. The research shows that companies perceive CSR as a key tool for improving corporate image, responding to stakeholder expectations, and investing in social justice. Despite positive intentions, challenges include the lack of clearly defined methodologies for measuring the impact on economic inequality, as well as difficulties in assessing the long-term effects of CSR initiatives. Key conclusions highlight the need for more structured approaches to assessing the social and economic effects of CSR, recommending that companies improve their transparency and accountability and implement clear indicators of success to achieve sustainable economic and social outcomes. Full article

(This article belongs to the Special Issue Research on Economic Growth and Inequality)

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21 pages, 3180 KiB

Open AccessArticle

Trends in the Literature About the Adoption of Digital Banking in Emerging Economies: A Bibliometric Analysis

by Julio César Acosta-Prado, Joan Sebastián Rojas Rincón, Andrés Mauricio Mejía Martínez and Andrés Ricardo Riveros Tarazona

J. Risk Financial Manag. 2024, 17(12), 545; https://doi.org/10.3390/jrfm17120545 - 29 Nov 2024

Abstract

This study examines the trends in the literature about adopting digital banking in emerging economies. It is based on the concepts of digital transformation and technological adoption, which significantly impact the development of the banking industry. A quantitative approach was used through a [...] Read more.

This study examines the trends in the literature about adopting digital banking in emerging economies. It is based on the concepts of digital transformation and technological adoption, which significantly impact the development of the banking industry. A quantitative approach was used through a bibliometric analysis using data from Scopus to achieve the objective. The search equation allowed 118 publications to be extracted and analyzed. The results show that digital banking in emerging countries is a growing field of research that has driven the introduction of new information technologies. The perceived usefulness of digital banking is a key factor in promoting its adoption in the market. Attributes such as security and trust were identified as affecting the level of user satisfaction. Most studies are based on technological adoption, where perceived risk, usefulness, and ease of use are key to understanding the intention to use these technologies. Some countries’ concerns about financial inclusion, cyber security, and trust in financial technology are evident. While digital banking has the potential to increase the coverage of financial services, there are concerns about cybersecurity risks and user data protection. Full article

(This article belongs to the Special Issue Financial Technology (Fintech) and Sustainable Financing, 3rd Edition)

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20 pages, 288 KiB

Open AccessArticle

The Relationship Between Sociodemographic Attributes and Financial Well-Being of Low-Income Urban Families Amid the COVID-19 Pandemic: A Case Study of Malaysia

by Abdullah Sallehhuddin Abdullah Salim, Norzarina Md Yatim and Al Mansor Abu Said

J. Risk Financial Manag. 2024, 17(12), 544; https://doi.org/10.3390/jrfm17120544 - 29 Nov 2024

Abstract

The COVID-19 pandemic and the Movement Control Order (MCO) have had a negative impact on the financial well-being of low-income families in urban areas. This study involved respondents living in the public housing project (PPR) residential areas in Kuala Lumpur—the capital of Malaysia. [...] Read more.

The COVID-19 pandemic and the Movement Control Order (MCO) have had a negative impact on the financial well-being of low-income families in urban areas. This study involved respondents living in the public housing project (PPR) residential areas in Kuala Lumpur—the capital of Malaysia. The key finding is that the financial well-being of low-income urban families was negatively impacted due to the COVID-19 pandemic and the MCO implementation. Furthermore, the impact on the financial well-being of low-income urban families is significantly different in terms of types of families, type and sector of employment, type of home ownership, household monthly income, and education level. Reforms to the financial assistance system and the community empowerment of low-income urban families are necessary to increase the community’s preparedness and resilience in the face of new shocks in the future. Full article

(This article belongs to the Special Issue Featured Papers in Finance and Society Wellbeing—in Honor of Professors Joe Gani and Chris Heyde)

28 pages, 803 KiB

Open AccessArticle

Impact of International Oil Price Shocks and Inflation on Bank Efficiency and Financial Stability: Evidence from Saudi Arabian Banking Sector

by Fathi Mohamed Bouzidi, Aida Arbi Nefzi and Mohammed Al Yousif

J. Risk Financial Manag. 2024, 17(12), 543; https://doi.org/10.3390/jrfm17120543 - 29 Nov 2024

Abstract

This study examines the short-run and long-run equilibrium relationship between the banking sector’s efficiency and stability and its endogenous and exogenous determinants, such as inflation and international oil price shocks in Saudi Arabia from 2004 to 2022. This study differentiates between the direct [...] Read more.

This study examines the short-run and long-run equilibrium relationship between the banking sector’s efficiency and stability and its endogenous and exogenous determinants, such as inflation and international oil price shocks in Saudi Arabia from 2004 to 2022. This study differentiates between the direct and indirect effects of international oil price changes on bank efficiency and stability and investigates how these changes can affect the banking sector through inflation. The first stage uses a panel Autoregressive Distributive Lag (ARDL). The empirical result confirms a long/short-run relationship between oil price shocks and the stability and efficiency of banks. In the long run, the relationship is statistically significant and positive, and it is negative in the short run. On the other hand, this study finds that oil price shocks directly affect the stability and efficiency of banks. In the second stage, this study uses a nonlinear ARD (NARD) to examine the short- and long-run asymmetric impacts of oil price shocks on the stability and efficiency of banks by decomposing the oil price index into positive and negative changes. The findings confirm an asymmetric relationship between oil prices and the stability and efficiency of banks in Saudi Arabia. In addition, a positive change in oil price can affect the stability and efficiency of banks more than a negative one. Overall, the findings highlight the need for policymakers in Saudi Arabia to be vigilant in addressing potential risks arising from oil price fluctuations and to adopt appropriate policy measures to maintain stability and efficiency in the banking sector. Full article

(This article belongs to the Section Economics and Finance)

24 pages, 4901 KiB

Open AccessArticle

Compliance Behavior in Environmental Tax Policy

by Suci Lestari Hakam, Agus Rahayu, Lili Adi Wibowo, Lazuardi Imani Hakam, Muhamad Adhi Nugroho and Siti Sarah Fuadi

J. Risk Financial Manag. 2024, 17(12), 542; https://doi.org/10.3390/jrfm17120542 - 29 Nov 2024

Abstract

This study examines compliance behavior in the context of environmental tax policies, highlighting the essential role that these policies play in achieving the objectives of the Sustainable Development Goals (SDGs). Environmental taxes are crucial instruments for reducing environmental damage and increasing energy efficiency. [...] Read more.

This study examines compliance behavior in the context of environmental tax policies, highlighting the essential role that these policies play in achieving the objectives of the Sustainable Development Goals (SDGs). Environmental taxes are crucial instruments for reducing environmental damage and increasing energy efficiency. Nevertheless, taxpayer compliance, which is impacted by several variables, including social acceptability, regulatory quality, and perceptions of fairness, is a key component of these policies’ efficacy. In contrast to earlier research, which frequently concentrated on certain kinds of tax or discrete policy mechanisms, this study takes a broad approach, looking at a range of environmental taxation instruments. Emerging trends, significant factors influencing compliance behavior, and noteworthy contributions from eminent authors and organizations are all identified via bibliometric and scientometric analyses. To create fair and effective environmental tax policies, interdisciplinary approaches and international collaboration are required. Along with presenting policies to improve environmental regulation compliance, this study offers insightful advice for businesses that can help them innovate toward sustainability and adjust to shifting policy. It also provides a solid theoretical base for future researchers by highlighting important areas that require more investigation, especially when it comes to the wider effects of environmental taxes on various industries. Full article

(This article belongs to the Special Issue Sustainable Tax and Accounting Reporting in Building a New Tax Culture)

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21 pages, 2096 KiB

Open AccessArticle

The Determinants and Growth Effects of Foreign Direct Investment: A Comparative Study

by Sheng-Ping Yang

J. Risk Financial Manag. 2024, 17(12), 541; https://doi.org/10.3390/jrfm17120541 - 29 Nov 2024

Abstract

This study examines the factors determining inward foreign direct investment (FDI) and its effects on productivity, ultimately contributing to economic growth. Using a two-step generalized method of moments (GMM) approach, we analyzed a panel of 84 countries, comprising 34 OECD and 50 non-OECD [...] Read more.

This study examines the factors determining inward foreign direct investment (FDI) and its effects on productivity, ultimately contributing to economic growth. Using a two-step generalized method of moments (GMM) approach, we analyzed a panel of 84 countries, comprising 34 OECD and 50 non-OECD countries, from 2010 to 2019. The findings suggest that FDI positively impacts productivity and benefits both OECD and non-OECD countries. Economic freedom plays a significant role in attracting FDI, particularly in OECD countries, and contributes to economic growth in non-OECD countries. However, economic freedom alone does not guarantee strong economic growth in OECD countries but significantly enhances growth in non-OECD countries. The results also highlight that only economies with robust economic infrastructure and development levels benefit more from FDI. It appears that FDI by itself has no direct effect on output growth. Instead, the impact of FDI is contingent on the level of economic freedom in the host countries. This paper presents a key finding on how policy decisions influence the effects of foreign capital investment on productivity and income. It indicates that countries promoting economic freedom can more effectively leverage productivity gains from FDI. Full article

(This article belongs to the Special Issue Globalization and Economic Integration)

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15 pages, 270 KiB

Open AccessArticle

The Impact of CEO Characteristics on Investment Efficiency in Jordan: The Moderating Role of Political Connections

by Loona Shaheen, Zakarya Alatyat, Qasem Aldabbas, Ruba Nimer Abu Shihab and Murad Abuaddous

J. Risk Financial Manag. 2024, 17(12), 540; https://doi.org/10.3390/jrfm17120540 - 29 Nov 2024

Abstract

This study investigates the impact of CEO characteristics—specifically CEO age, founder status, and family membership—on investment efficiency in Jordanian non-financial companies, with a focus on the moderating role of political connections. Drawing on the existing literature, we identify conflicting views regarding how these [...] Read more.

This study investigates the impact of CEO characteristics—specifically CEO age, founder status, and family membership—on investment efficiency in Jordanian non-financial companies, with a focus on the moderating role of political connections. Drawing on the existing literature, we identify conflicting views regarding how these characteristics influence investment decisions. Some studies suggest that younger CEOs may adopt more aggressive investment strategies, while older CEOs tend to be conservative, leading to balanced resource allocation. Similarly, CEOs with founder status and family membership are thought to have an emotional attachment to the company, theoretically resulting in cautious investment behavior. However, empirical evidence remains mixed. By using data from 62 non-financial firms listed on the Amman Stock Exchange (ASE) from 2019 to 2023, this study employs regression analysis to explore these relationships. The findings reveal that CEO age contributes to investment efficiency by mitigating both over- and under-investment. Contrary to expectations, CEO founder status shows no significant effect on investment efficiency. Additionally, family-member CEOs exhibit a tendency toward under-investment, driven by a desire to preserve family wealth. Political connections further complicate these dynamics, encouraging riskier investment strategies while diluting the positive effects of CEO characteristics. These results provide new insights into the intricate interplay between CEO traits and political networks, contributing to the discourse on corporate governance in emerging markets. The study concludes with practical implications for policymakers and company boards, emphasizing the need for balanced leadership selection strategies to optimize investment efficiency. Full article

(This article belongs to the Special Issue Featured Papers in Corporate Finance and Governance)

13 pages, 269 KiB

Open AccessArticle

Leveraging Corporate Assets and Talent to Attract Investors in Japan: A Country with an Innovation System Centered on Large Companies

by Ryo Okuyama

J. Risk Financial Manag. 2024, 17(12), 539; https://doi.org/10.3390/jrfm17120539 - 28 Nov 2024

Abstract

Drug discovery and development require significant costs and time, making investment acquisition crucial. However, there are few biopharmaceutical startups with high valuations in Japan. Unlike other countries, entrepreneurship in Japan is relatively inactive, and startups have a minimal presence in the drug-discovery field. [...] Read more.

Drug discovery and development require significant costs and time, making investment acquisition crucial. However, there are few biopharmaceutical startups with high valuations in Japan. Unlike other countries, entrepreneurship in Japan is relatively inactive, and startups have a minimal presence in the drug-discovery field. Instead, in Japan’s innovation system, research and development (R&D) has been led by large incumbent companies, which are believed to have a wealth of promising assets and talent. This study tested the hypothesis that biopharmaceutical startups leveraging these assets and talent might be more attractive to investors by regression analysis using a dataset of Japanese unlisted biopharmaceutical startups. The results demonstrated that Japanese biopharmaceutical startups showed significantly higher valuations and total funding amounts if they were corporate spin-offs (CSOs). Additionally, they achieved significantly higher valuations and total funding amounts if their R&D lead persons had corporate backgrounds. These findings suggest that in Japan’s innovation system, which is centered on large companies, CSOs and startups leveraging R&D talent with corporate experience may be more appealing to investors. Full article

(This article belongs to the Section Business and Entrepreneurship)

29 pages, 1411 KiB

Open AccessArticle

Optimizing Energy Storage Profits: A New Metric for Evaluating Price Forecasting Models

by Simone Sbaraglia, Alessandro Fiori Maccioni and Stefano Zedda

J. Risk Financial Manag. 2024, 17(12), 538; https://doi.org/10.3390/jrfm17120538 - 26 Nov 2024

Abstract

Storage profit maximization is based on buying energy at the lowest prices and selling it at the highest prices. The best strategy must thus be based on both accurately predicting the price peak hours and on rightly choosing when to buy and when [...] Read more.

Storage profit maximization is based on buying energy at the lowest prices and selling it at the highest prices. The best strategy must thus be based on both accurately predicting the price peak hours and on rightly choosing when to buy and when to sell the stored energy. In this aim, price prediction is crucial, but choosing the prediction model by means of the usual metrics, as the lowest mean squared error, is not an effective solution as the mean squared error computation equally weights the prediction error of all prices, while the focus must be on the higher and lower prices. In this paper, we propose a new metric focused on the correct forecasting of high and low prices so as to allow for a more effective choice among price forecasting models. Results show that the new metric outperforms the standard metrics, allowing for a more accurate estimation of the possible profit for storage (or other trading) activities. Full article

(This article belongs to the Special Issue Forecasting, Predictive Analytics and Econometrics in Business Research)

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21 pages, 2778 KiB

Open AccessArticle

Fin-ALICE: Artificial Linguistic Intelligence Causal Econometrics

by Shawn McCarthy and Gita Alaghband

J. Risk Financial Manag. 2024, 17(12), 537; https://doi.org/10.3390/jrfm17120537 - 26 Nov 2024

Abstract

This study introduces Fin-ALICE (Artificial Linguistic Intelligence Causal Econometrics), a framework designed to forecast financial time series by integrating multiple analytical approaches including co-occurrence networks, supply chain analysis, and emotional sentiment analysis to provide a comprehensive understanding of market dynamics. In our co-occurrence [...] Read more.

This study introduces Fin-ALICE (Artificial Linguistic Intelligence Causal Econometrics), a framework designed to forecast financial time series by integrating multiple analytical approaches including co-occurrence networks, supply chain analysis, and emotional sentiment analysis to provide a comprehensive understanding of market dynamics. In our co-occurrence analysis, we focus on companies that share the same emotion on the same day, using a much shorter horizon than our previous study of one month. This approach allows us to uncover short-term, emotion-driven correlations that traditional models might overlook. By analyzing these co-occurrence networks, Fin-ALICE identifies hidden connections between companies, sectors, and events. Supply chain analysis within Fin-ALICE will evaluate significant events in commodity-producing countries that impact their ability to supply key resources. This analysis captures the ripple effects of disruptions across industries and regions, offering a more nuanced prediction of market movements. Emotional sentiment analysis, powered by the Fin-Emotion library developed in our prior research, quantifies the emotional undertones in financial news through metrics like “emotion magnitude” and “emotion interaction”. These insights, when integrated with Temporal Convolutional Networks (TCNs), significantly enhance the accuracy of financial forecasts by capturing the emotional drivers of market sentiment. Key contributions of Fin-ALICE include its ability to perform month-by-month company correlation analysis, capturing short-term market fluctuations and seasonal patterns. We compare the performance of TCNs against advanced models such as LLMs and LSTMs, demonstrating that the Fin-ALICE model outperforms these models, particularly in sectors where emotional sentiment and supply chain dynamics are critical. Fin-ALICE provides decision-makers with predictive insights and a deeper understanding of the underlying emotional and supply chain factors that drive market behaviors. Full article

(This article belongs to the Section Financial Technology and Innovation)

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Journal of Risk and Financial Management

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