Editorial Board Members’ Collection Series: Journal of Risk and Financial Management

A special issue of Journal of Risk and Financial Management (ISSN 1911-8074).

Deadline for manuscript submissions: 1 September 2024 | Viewed by 15117

Special Issue Editor

Special Issue Information

Dear Colleagues,

We are pleased to announce this Special Issue titled ‘Editorial Board Members' Collection Series: Journal of Risk and Financial Management’. It will be a collection of papers from researchers invited exclusively by the Editorial Board Members. The aim is to provide an avenue for networking and communication between JRFM and scholars in the field of financial and economic risk and management. All papers will be published with fully open access after a through peer-review process.

Areas of interest for the collection

  • Banking
  • Financial markets
  • International finance
  • Financial economics
  • Mathematical methods in economics and finance
  • Risk management and analysis
  • Financial technology and innovation
  • Corporate finance
  • Entrepreneurial finance
  • Financial accounting and reporting
  • Sustainable and environmental finance
  • Energy economics and finance
  • Tourism: economics, finance, and management

Prof. Dr. Thanasis Stengos
Guest Editor

Manuscript Submission Information

The Journal of Risk and Financial Management is an international peer-reviewed open access semimonthly journal published by MDPI.

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published in the journal (as soon as accepted) and will be listed together on the Special Issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and a short abstract (about 100 words) can be sent to the Editorial Office for announcement on the website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page; please visit this site before submitting a manuscript.

Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and written articulately in English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (13 papers)

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Research

25 pages, 441 KiB  
Article
Testing and Ranking of Asset Pricing Models Using the GRS Statistic
by Mark J. Kamstra and Ruoyao Shi
J. Risk Financial Manag. 2024, 17(4), 168; https://doi.org/10.3390/jrfm17040168 - 19 Apr 2024
Viewed by 374
Abstract
We clear up an ambiguity in the statement of the GRS statistic by providing the correct formula of the GRS statistic and the first proof of its F-distribution in the general multiple-factor case. Casual generalization of the Sharpe-ratio-based interpretation of the single-factor GRS [...] Read more.
We clear up an ambiguity in the statement of the GRS statistic by providing the correct formula of the GRS statistic and the first proof of its F-distribution in the general multiple-factor case. Casual generalization of the Sharpe-ratio-based interpretation of the single-factor GRS statistic to the multiple-portfolio case makes experts in asset pricing studies susceptible to an incorrect formula. We illustrate the consequences of using the incorrect formulas that the ambiguity in GRS leads to—over-rejecting and misranking asset pricing models. In addition, we suggest a new approach to ranking models using the GRS statistic p-value. Full article
17 pages, 336 KiB  
Article
Knowledge Sharing and Cumulative Innovation in Business Networks
by Gilles Saint-Paul
J. Risk Financial Manag. 2024, 17(4), 137; https://doi.org/10.3390/jrfm17040137 - 26 Mar 2024
Viewed by 551
Abstract
How can we explain the success of cooperative networks of firms which share innovations, such as Silicon Valley or the Open Source community? This paper shows that if innovations are cumulative, making an invention publicly available to a network of firms may be [...] Read more.
How can we explain the success of cooperative networks of firms which share innovations, such as Silicon Valley or the Open Source community? This paper shows that if innovations are cumulative, making an invention publicly available to a network of firms may be valuable if the firm expects to benefit from future improvements made by other firms. A cooperative equilibrium where all innovations are made public is shown to exist under certain conditions. Furthermore, such an equilibrium does not rest on punishment strategies being followed after a deviation: it is optimal not to deviate regardless of another firm’s actions following a deviation. A cooperative equilibrium is more likely to arise the greater the number of firms in the network. When R&D effort is endogenous, cooperative equilibria are associated with strategic complementarities between firms’ research effort, which may lead to multiple equilibria. Full article
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17 pages, 786 KiB  
Article
Segmenting Bitcoin Transactions for Price Movement Prediction
by Yuxin Zhang, Rajiv Garg, Linda L. Golden, Patrick L. Brockett and Ajit Sharma
J. Risk Financial Manag. 2024, 17(3), 128; https://doi.org/10.3390/jrfm17030128 - 21 Mar 2024
Viewed by 997
Abstract
Cryptocurrencies like Bitcoin have received substantial attention from financial exchanges. Unfortunately, arbitrage-based financial market price prediction models are ineffective for cryptocurrencies. In this paper, we utilize standard machine learning models and publicly available transaction data in blocks to predict the direction of Bitcoin [...] Read more.
Cryptocurrencies like Bitcoin have received substantial attention from financial exchanges. Unfortunately, arbitrage-based financial market price prediction models are ineffective for cryptocurrencies. In this paper, we utilize standard machine learning models and publicly available transaction data in blocks to predict the direction of Bitcoin price movement. We illustrate our methodology using data we merged from the Bitcoin blockchain and various online sources. This gave us the Bitcoin transaction history (block IDs, block timestamps, transaction IDs, senders’ addresses, receivers’ addresses, transaction amounts), as well as the market exchange price, for the period from 13 September 2011 to 5 May 2017. We show that segmenting publicly available transactions based on investor typology helps achieve higher prediction accuracy compared to the existing Bitcoin price movement prediction models in the literature. This transaction segmentation highlights the role of investor types in impacting financial markets. Managerially, the segmentation of financial transactions helps us understand the role of financial and cryptocurrency market participants in asset price movements. These findings provide further implications for risk management, financial regulation, and investment strategies in this new era of digital currencies. Full article
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14 pages, 891 KiB  
Article
Analyzing Portfolio Optimization in Cryptocurrency Markets: A Comparative Study of Short-Term Investment Strategies Using Hourly Data Approach
by Sonal Sahu, José Hugo Ochoa Vázquez, Alejandro Fonseca Ramírez and Jong-Min Kim
J. Risk Financial Manag. 2024, 17(3), 125; https://doi.org/10.3390/jrfm17030125 - 20 Mar 2024
Viewed by 1017
Abstract
This paper investigates portfolio optimization methodologies and short-term investment strategies in the context of the cryptocurrency market, focusing on ten major cryptocurrencies from June 2020 to March 2024. Using hourly data, we apply the Kurtosis Minimization methodology, along with other optimization strategies, to [...] Read more.
This paper investigates portfolio optimization methodologies and short-term investment strategies in the context of the cryptocurrency market, focusing on ten major cryptocurrencies from June 2020 to March 2024. Using hourly data, we apply the Kurtosis Minimization methodology, along with other optimization strategies, to construct and assess portfolios across various rebalancing frequencies. Our empirical analysis reveals significant volatility, skewness, and kurtosis in cryptocurrencies, highlighting the need for sophisticated portfolio management techniques. We discover that the Kurtosis Minimization methodology consistently outperforms other optimization strategies, especially in shorter-term investment horizons, delivering optimal returns to investors. Additionally, our findings emphasize the importance of dynamic portfolio management, stressing the necessity of regular rebalancing in the volatile cryptocurrency market. Overall, this study offers valuable insights into optimizing cryptocurrency portfolios, providing practical guidance for investors and portfolio managers navigating this rapidly evolving market landscape. Full article
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14 pages, 1179 KiB  
Article
On the Realized Risk of Foreign Exchange Rates: A Fractal Perspective
by Masoumeh Fathi, Klaus Grobys and James W. Kolari
J. Risk Financial Manag. 2024, 17(2), 79; https://doi.org/10.3390/jrfm17020079 - 18 Feb 2024
Viewed by 1129
Abstract
While well-established literature argues that realized variances are close to a lognormal distribution, this study follows Benoit Mandelbrot by taking a fractal perspective. Using power laws to model realized foreign exchange rate variances, our findings indicate that power laws offer an alternative to [...] Read more.
While well-established literature argues that realized variances are close to a lognormal distribution, this study follows Benoit Mandelbrot by taking a fractal perspective. Using power laws to model realized foreign exchange rate variances, our findings indicate that power laws offer an alternative to the lognormal in terms of goodness-of-fit tests. Further, our analysis shows that estimated power law exponents for seven out of nine realized FX variances are α^<3, which indicates that the variance of realized variance is statistically undefined. We conclude that the foreign exchange rate market is far riskier than earlier believed. By implication, documented research in an enormous body of literature that draws conclusions from variance analyses stands on shaky grounds. Full article
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22 pages, 1437 KiB  
Article
Volatility and Herding Bias on ESG Leaders’ Portfolios Performance
by Nektarios Gavrilakis and Christos Floros
J. Risk Financial Manag. 2024, 17(2), 77; https://doi.org/10.3390/jrfm17020077 - 16 Feb 2024
Viewed by 1412
Abstract
We here analyze the factor loadings given by the CAPM, the Fama–French three (FF3), and the five-factor model (FF5), and test the performance and the validity of adding two more factors (volatility and dispersion of returns) to the FF5 factor model of European [...] Read more.
We here analyze the factor loadings given by the CAPM, the Fama–French three (FF3), and the five-factor model (FF5), and test the performance and the validity of adding two more factors (volatility and dispersion of returns) to the FF5 factor model of European index-based ESG leaders’ portfolios. Our ESG leaders’ portfolios generated significant negative alphas during 2012–2022, corroborating the literature’s negative argument. The negative abnormal returns of ESG leaders’ portfolios are homogeneous across the three ESG pillars. We conclude that European ESG leaders’ portfolios are biased toward large cap and value stocks with robust operating profitability and against aggressive investments. As robustness tests, we examine Global ESG leaders’ index-based portfolios, producing the same results but with reduced importance in some loading factors like profitability and investment strategy. Furthermore, we deduced that European and Global ESG leaders’ portfolios tilt towards volatility and herding bias. Full article
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17 pages, 1676 KiB  
Article
Option Pricing with the Logistic Return Distribution
by Haim Levy and Moshe Levy
J. Risk Financial Manag. 2024, 17(2), 67; https://doi.org/10.3390/jrfm17020067 - 10 Feb 2024
Viewed by 1002
Abstract
The Black–Scholes model and many of its extensions imply a log-normal distribution of stock total returns over any finite holding period. However, for a holding period of up to one year, empirical stock return distributions (both conditional and unconditional) are not log-normal, but [...] Read more.
The Black–Scholes model and many of its extensions imply a log-normal distribution of stock total returns over any finite holding period. However, for a holding period of up to one year, empirical stock return distributions (both conditional and unconditional) are not log-normal, but rather much closer to the logistic distribution. This paper derives analytic option pricing formulas for an underlying asset with a logistic return distribution. These formulas are simple and elegant and employ exactly the same parameters as B&S. The logistic option pricing formula fits empirical option prices much better than B&S, providing explanatory power comparable to much more complex models with a larger number of parameters. Full article
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18 pages, 677 KiB  
Article
The Impact of ESG Rating on Hedging Downside Risks: Evidence from a Weight-Tilted Hang Seng Index
by Joseph K. W. Fung, F. Y. Eric Lam and Yiuman Tse
J. Risk Financial Manag. 2024, 17(2), 57; https://doi.org/10.3390/jrfm17020057 - 31 Jan 2024
Viewed by 1213
Abstract
The study examines the return performance and resilience to market volatility of the recently introduced environment, social/sustainable, and governance (ESG) weight-tilted Hang Seng index compared to its parent, the Hang Seng index. The ESG-infused index has a higher mean return and lower return [...] Read more.
The study examines the return performance and resilience to market volatility of the recently introduced environment, social/sustainable, and governance (ESG) weight-tilted Hang Seng index compared to its parent, the Hang Seng index. The ESG-infused index has a higher mean return and lower return volatility than the parent index, although the differences are statistically and economically insignificant, a result consistent with the high correlation between the two index returns. Most importantly, the ESG weight-tilted index is more resilient to volatility spikes than the parent index and, therefore, has lower downside risks. The overall results show that stocks with high ESG ratings are less susceptible to trading pressures triggered by volatility-induced turnovers. The paper contributes to the literature by providing significant incremental information on the emerging market for ESG-related equity products in Hong Kong. Full article
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48 pages, 585 KiB  
Article
A Survey of Literature on the Interlinkage between Petroleum Prices and Equity Markets
by Miramir Bagirov and Cesario Mateus
J. Risk Financial Manag. 2024, 17(1), 40; https://doi.org/10.3390/jrfm17010040 - 22 Jan 2024
Viewed by 1378
Abstract
The multifaceted interrelationship between petroleum prices and equity markets has been a subject of immense interest. The current paper offers an extensive review of a plethora of empirical studies in this strand of literature. By scrutinising over 190 papers published from 1983 to [...] Read more.
The multifaceted interrelationship between petroleum prices and equity markets has been a subject of immense interest. The current paper offers an extensive review of a plethora of empirical studies in this strand of literature. By scrutinising over 190 papers published from 1983 to 2023, our survey reveals various research themes and points to diverse findings that are sector- and country-specific and contingent on employed methodologies, data frequencies, and time horizons. More precisely, petroleum price changes and shocks exert direct or indirect effects dictated by the level of petroleum dependency across sectors and the country’s position as a net petroleum exporter or importer. The interlinkages tend to display a time-varying nature and sensitivity to major market events. In addition, volatility is not solely spilled from petroleum to equity markets; it is also observed to transmit in the reverse direction. The importance of incorporating asymmetries is documented. Lastly, the summarised findings can serve as the basis for further research and reveal valuable insights to market participants. Full article
19 pages, 5686 KiB  
Article
The Financial Market of Indices of Socioeconomic Well-Being
by Thilini V. Mahanama, Abootaleb Shirvani, Svetlozar Rachev and Frank J. Fabozzi
J. Risk Financial Manag. 2024, 17(1), 35; https://doi.org/10.3390/jrfm17010035 - 16 Jan 2024
Viewed by 1274
Abstract
This study discusses how financial economic theory and its quantitative tools can be applied to create socioeconomic indices and develop a financial market for the so-called “socioeconomic well-being indices”. In this study, we quantify socioeconomic well-being by assigning a dollar value to the [...] Read more.
This study discusses how financial economic theory and its quantitative tools can be applied to create socioeconomic indices and develop a financial market for the so-called “socioeconomic well-being indices”. In this study, we quantify socioeconomic well-being by assigning a dollar value to the well-being factors of selected countries; this is analogous to how the Dow 30 encapsulates the financial health of the US market. While environmental, social, and governance (ESG) financial markets address socioeconomic issues, our focus is broader, encompassing national citizens’ well-being. The dollar-denominated socioeconomic indices for each country can be viewed as financial assets that can serve as risky assets for constructing a global index, which, in turn, serves as a “market of well-being socioeconomic index”. This novel global index of well-being, paralleling the Dow Jones Industrial Average (DJIA), provides a comprehensive representation of the world’s socioeconomic status. Through advanced financial econometrics and dynamic asset pricing methodologies, we evaluate the potential for significant downturns in both the socioeconomic well-being indices of individual countries and the aggregate global index. This innovative approach allows us to engineer financial instruments akin to portfolio insurance, such as index puts, designed to hedge against these downturn risks. Our findings propose a financial market model for well-being indices, encouraging the financial industry to adopt and trade these indices as mechanisms to manage and hedge against downturn risks in well-being. Full article
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12 pages, 282 KiB  
Article
Can Investment Views Explain Why People Insure Their Cell Phones But Not Their Homes?—A New Perspective on the Catastrophe Insurance Puzzle
by Annette Hofmann and Peter Zweifel
J. Risk Financial Manag. 2024, 17(1), 30; https://doi.org/10.3390/jrfm17010030 - 12 Jan 2024
Viewed by 1236
Abstract
The consistently missing demand for catastrophe insurance and for coverage of other low-probability–high-consequence risks is often referred to as the catastrophe insurance puzzle. People show reluctance to insure low-probability–high-consequence events, even with some disastrous consequences, yet insure against small high-probability–low-consequence events. There has [...] Read more.
The consistently missing demand for catastrophe insurance and for coverage of other low-probability–high-consequence risks is often referred to as the catastrophe insurance puzzle. People show reluctance to insure low-probability–high-consequence events, even with some disastrous consequences, yet insure against small high-probability–low-consequence events. There has been no convincing explanation of this puzzle to this date. This article points out that the underlying rationale may be that individuals interpret insurance contracts with low payout probability as an investment with negative expected net present value. While premium payments start with the conclusion of the contract, usually there is only one loss payment in the near or far future. Using a simple annuity model with fixed annual premiums and expected indemnity payouts, it is found that even an individual characterized by the degree of risk aversion found in the literature is unlikely to purchase insurance with these characteristics. To alleviate this unfavorable insurance purchase syndrome, combining a low-probability with a high-probability loss insurance contract may be a way to incentivize individuals to purchase catastrophe risk coverage. Full article
24 pages, 2106 KiB  
Article
Monte Carlo Sensitivities Using the Absolute Measure-Valued Derivative Method
by Mark Joshi, Oh Kang Kwon and Stephen Satchell
J. Risk Financial Manag. 2023, 16(12), 509; https://doi.org/10.3390/jrfm16120509 - 08 Dec 2023
Viewed by 1123
Abstract
Measure-valued differentiation (MVD) is a relatively new method for computing Monte Carlo sensitivities, relying on a decomposition of the derivative of transition densities of the underlying process into a linear combination of probability measures. In computing the sensitivities, additional paths are generated for [...] Read more.
Measure-valued differentiation (MVD) is a relatively new method for computing Monte Carlo sensitivities, relying on a decomposition of the derivative of transition densities of the underlying process into a linear combination of probability measures. In computing the sensitivities, additional paths are generated for each constituent distribution and the payoffs from these paths are combined to produce sample estimates. The method generally produces sensitivity estimates with lower variance than the finite difference and likelihood ratio methods, and can be applied to discontinuous payoffs in contrast to the pathwise differentiation method. However, these benefits come at the expense of an additional computational burden. In this paper, we propose an alternative approach, called the absolute measure-valued differentiation (AMVD) method, which expresses the derivative of the transition density at each simulation step as a single density rather than a linear combination. It is computationally more efficient than the MVD method and can result in sensitivity estimates with lower variance. Analytic and numerical examples are provided to compare the variance in the sensitivity estimates of the AMVD method against alternative methods. Full article
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23 pages, 742 KiB  
Article
The Effect of Short-Sale Restrictions on Corporate Managers
by Baixiao Liu, John J. McConnell and Andrew Schrowang
J. Risk Financial Manag. 2023, 16(11), 486; https://doi.org/10.3390/jrfm16110486 - 17 Nov 2023
Viewed by 1385
Abstract
This paper studies the effect of short selling on corporate managers from 2002 through 2010. We examine how the exemption of short-sale uptick tests due to the Regulation SHO pilot program affects managers’ decisions to abandon value-reducing acquisition attempts. We find that when [...] Read more.
This paper studies the effect of short selling on corporate managers from 2002 through 2010. We examine how the exemption of short-sale uptick tests due to the Regulation SHO pilot program affects managers’ decisions to abandon value-reducing acquisition attempts. We find that when deciding whether to abandon value-reducing acquisition attempts during the program, managers of pilot firms, whose stocks are less subject to short-selling impediments, are more sensitive to stock price changes than managers of nonpilot firms. We find no difference in managers’ sensitivity prior to nor post SHO. These results indicate that, despite their dislike of short sellers, managers believe that the level of informativeness from capital markets is superior when short sellers are less impeded. Full article
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