Journal of Risk and Financial Management

Research

29 pages, 432 KiB

Open AccessArticle

Social Media for Investment Advice and Financial Satisfaction: Does Generation Matter?

by Olamide Olajide, Sabina Pandey and Ichchha Pandey

J. Risk Financial Manag. 2024, 17(9), 410; https://doi.org/10.3390/jrfm17090410 - 13 Sep 2024

Viewed by 1016

This study explores the relationship between social media usage for investment advice and financial satisfaction across different generations. Ten ordered logit models were estimated using Stata to explore this relationship. Ordered logit analyses using data from the 2021 National Financial Capability Study State-by-State [...] Read more.

This study explores the relationship between social media usage for investment advice and financial satisfaction across different generations. Ten ordered logit models were estimated using Stata to explore this relationship. Ordered logit analyses using data from the 2021 National Financial Capability Study State-by-State and Investor survey reveal that Generation X and millennials are less financially satisfied than baby boomers. While general social media use shows no statistically significant association, platform-specific analysis finds that Instagram and TikTok users report higher financial satisfaction, whereas YouTube users report lower satisfaction. Notably, millennials who use social media for investment advice are more financially satisfied than their peers. Detailed analyses reveal that Instagram, TikTok, and Twitter positively influence financial satisfaction across Gen Z, millennials, and Gen X, with more platform-specific associations observed for Facebook, LinkedIn, and Reddit among millennials and Gen X, respectively. These findings provide valuable insights for policymakers, financial professionals, and researchers, highlighting the need for targeted strategies to enhance financial well-being through social media. Full article

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

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20 pages, 1035 KiB

Open AccessArticle

Identifying Information Types in the Estimation of Informed Trading: An Improved Algorithm

by Oguz Ersan and Montasser Ghachem

J. Risk Financial Manag. 2024, 17(9), 409; https://doi.org/10.3390/jrfm17090409 - 12 Sep 2024

Viewed by 377

Abstract

The growing frequency of news arrivals, partly fueled by the proliferation of data sources, has made the assumptions of the classical probability of informed trading (PIN) model outdated. In particular, the model’s assumption of a single type of information event no longer reflects [...] Read more.

The growing frequency of news arrivals, partly fueled by the proliferation of data sources, has made the assumptions of the classical probability of informed trading (PIN) model outdated. In particular, the model’s assumption of a single type of information event no longer reflects the complexity of modern financial markets, making the accurate detection of information types (layers) crucial for estimating the probability of informed trading. We propose a layer detection algorithm to accurately find the number of distinct information types within a dataset. It identifies the number of information layers by clustering order imbalances and examining their homogeneity using properly constructed confidence intervals for the Skellam distribution. We show that our algorithm manages to find the number of information layers with very high accuracy both when uninformed buyer and seller intensities are equal and when they differ from each other (i.e., between 86% and 95% accuracy rates). We work with more than 500,000 simulations of quarterly datasets with various characteristics and make a large set of robustness checks. Full article

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

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18 pages, 1843 KiB

Open AccessArticle

Capturing Tail Risks in Cryptomarkets: A New Systemic Risk Approach

by Itai Barkai, Elroi Hadad, Tomer Shushi and Rami Yosef

J. Risk Financial Manag. 2024, 17(9), 397; https://doi.org/10.3390/jrfm17090397 - 5 Sep 2024

Viewed by 417

Abstract

Using daily returns of Bitcoin, Litecoin, Ripple and Stellar, we introduce a novel risk measure for quantitative-risk management in the cryptomarket that accounts for the significant co-movements between cryptocurrencies. We find that our model has a lower error margin when forecasting the extent [...] Read more.

Using daily returns of Bitcoin, Litecoin, Ripple and Stellar, we introduce a novel risk measure for quantitative-risk management in the cryptomarket that accounts for the significant co-movements between cryptocurrencies. We find that our model has a lower error margin when forecasting the extent of future losses than traditional risk measures, such as Value-at-Risk and Expected Shortfall. Most notably, we observe this in Litecoin’s results, where Expected Shortfall, on average, overestimates the potential fall in the price of Litecoin by 8.61% and underestimates it by 3.92% more than our model. This research shows that traditional risk measures, while not necessarily inappropriate, are imperfect and incomplete representations of risk when it comes to the cryptomarket. Our model provides a suitable alternative for risk managers, who prioritize lower error margins over failure rates, and highlights the value in exploring how risk measures that incorporate the unique characteristics of cryptocurrencies can be used to supplement and complement traditional risk measures. Full article

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

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17 pages, 229 KiB

Open AccessArticle

Perceptions of South African Accountants on Factors with a Role in the Adoption of Artificial Intelligence in Financial Reporting

by Tankiso Moloi and Hassan Obeid

J. Risk Financial Manag. 2024, 17(9), 389; https://doi.org/10.3390/jrfm17090389 - 2 Sep 2024

Viewed by 643

Abstract

Purpose—The objective of this study was to conduct a detailed South African study that sought to explore and analyse the views of South African accountants regarding the factors that affect the adoption of AI in financial reporting. In other words, this study [...] Read more.

Purpose—The objective of this study was to conduct a detailed South African study that sought to explore and analyse the views of South African accountants regarding the factors that affect the adoption of AI in financial reporting. In other words, this study aimed to understand what accountants in South Africa think about the use of AI in their field, especially concerning its integration into financial reporting practices. Three main theories underpinned the study, namely, the diffusion of innovation, technology, organisation, and environment framework, and the institutional theory. In essence, the study sought to determine the perception of South Africa’s accountants on these factors. Design/methodology/approach—This study adopted the quantitative research method and descriptive design. In this regard, positivism as a philosophy was preferred. An online survey was developed to collect information from the participants. Participants were recruited based on their affiliation with the four IFAC-recognised accounting bodies in South Africa: SAICA, SAIPA, CIMA, and ACCA. Findings—Th study found that, overall, South African accountants believe that organisational, technological, and environmental factors play a role in adopting artificial intelligence in financial reporting. Originality/value: This study contributes by enriching the understanding of South African accountants’ perceptions of the adoption of artificial intelligence in financial reporting through the lenses of the selected theories. Full article

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

23 pages, 326 KiB

Open AccessArticle

Regulations and Fintech: A Comparative Study of the Developed and Developing Countries

by Preethi Vijayagopal, Bhawana Jain and Shyam Ayinippully Viswanathan

J. Risk Financial Manag. 2024, 17(8), 324; https://doi.org/10.3390/jrfm17080324 - 26 Jul 2024

Viewed by 698

Abstract

Financial technology (Fintech) has influenced business by helping create better services for consumers and businesses. Fintech, however, brings new challenges for regulators, who struggle to keep pace with the constant evolution of technology and the resulting disruption. The progress of technology and regulations [...] Read more.

Financial technology (Fintech) has influenced business by helping create better services for consumers and businesses. Fintech, however, brings new challenges for regulators, who struggle to keep pace with the constant evolution of technology and the resulting disruption. The progress of technology and regulations in the Fintech industry has been uneven across developed and developing countries, resulting in numerous opportunities and challenges. Considerable progress has recently been made in the adoption of Fintech and the subsequent development and implementation of regulations in the US, the UK, and India. While the United States (US) and the United Kingdom (UK) are global leaders in Fintech innovation, India has shown fast-paced growth in adopting and utilizing Fintech services. This paper examines the growth and evolution of Fintech in the US, the UK, and India and also explores how the regulatory agencies across these countries have responded to the evolution of Fintech. This paper finds that economies should work towards improving digital infrastructure, financial inclusion, and financial literacy and enhance the collaboration among regulators, Fintech firms, and other stakeholders. Full article

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

16 pages, 663 KiB

Open AccessArticle

Bank Crisis Boosts Bitcoin Price

by Danilo Petti and Ivan Sergio

J. Risk Financial Manag. 2024, 17(4), 134; https://doi.org/10.3390/jrfm17040134 - 22 Mar 2024

Cited by 1 | Viewed by 2064

Abstract

Bitcoin (BTC) represents an emerging asset class, offering investors an alternative avenue for diversification across various units of exchange. The recent global banking crisis of 9 March 2023 has provided an opportunity to reflect on how Bitcoin’s perception as a speculative asset may [...] Read more.

Bitcoin (BTC) represents an emerging asset class, offering investors an alternative avenue for diversification across various units of exchange. The recent global banking crisis of 9 March 2023 has provided an opportunity to reflect on how Bitcoin’s perception as a speculative asset may be evolving. This paper analyzes the volatility behavior of BTC in comparison to gold and the traditional financial market using GARCH models. Additionally, we have developed and incorporated a bank index within our volatility analysis framework, aiming to isolate the impact of financial crises while minimizing idiosyncratic risk. The aim of this work is to understand Bitcoin’s perception among investors and, more importantly, to determine whether BTC can be considered a new asset class. Our findings show that in terms of volatility and price, BTC and gold have responded in very similar ways. Counterintuitively, the financial market seems not to have experienced high volatility and significant price swings in response to the March 9th crisis. This suggests a consumer tendency to seek refuge in both Bitcoin and gold. Full article

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

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20 pages, 1251 KiB

Open AccessArticle

FinTech and Financial Inclusion: Exploring the Mediating Role of Digital Financial Literacy and the Moderating Influence of Perceived Regulatory Support

by Muhammed Basid Amnas, Murugesan Selvam and Satyanarayana Parayitam

J. Risk Financial Manag. 2024, 17(3), 108; https://doi.org/10.3390/jrfm17030108 - 7 Mar 2024

Cited by 3 | Viewed by 7384

Abstract

Exploring the potential of financial technology (FinTech) to promote financial inclusion is the aim of this research. This study concentrated on understanding why people use FinTech and how it affects their access to financial services by taking into account the mediating role of [...] Read more.

Exploring the potential of financial technology (FinTech) to promote financial inclusion is the aim of this research. This study concentrated on understanding why people use FinTech and how it affects their access to financial services by taking into account the mediating role of digital financial literacy and the moderating effect of perceived regulatory support. This study used partial least squares structural equation modeling (PLS-SEM) for testing the research model by collecting data from 608 FinTech users in India. The results revealed the role of trust, service quality, and perceived security are essential in promoting the utilization of FinTech services. This study also demonstrated that FinTech positively impacts financial inclusion, making it easier for individuals to get into formal financial services. Furthermore, digital financial literacy emerged as an important mediator between FinTech use and financial inclusion. The research also confirmed that perceived regulatory support has a significant moderation influence on the relationship between FinTech and financial inclusion. This research would contribute to advancing theoretical frameworks and offer practical advice for policymakers and FinTech companies to make financial services more inclusive. Full article

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

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15 pages, 637 KiB

Open AccessArticle

The Causal Relationship between FinTech, Financial Inclusion, and Income Inequality in African Economies

by Abebe Gule Girma and Fariz Huseynov

J. Risk Financial Manag. 2024, 17(1), 2; https://doi.org/10.3390/jrfm17010002 - 19 Dec 2023

Cited by 1 | Viewed by 4256

Abstract

Income inequality is one of the biggest problems affecting developing economies. Market imperfections and information asymmetry lead to lack of access to the financial system, which will exacerbate income inequality. The growing adoption of FinTech (financial technology) has altered the structure of how [...] Read more.

Income inequality is one of the biggest problems affecting developing economies. Market imperfections and information asymmetry lead to lack of access to the financial system, which will exacerbate income inequality. The growing adoption of FinTech (financial technology) has altered the structure of how financial services are delivered and makes these services accessible to underserved groups. This study explores the causal relationship between FinTech development, financial inclusion, and income inequality in a panel study of 29 African countries. We apply pooled OLS regression and structural equation models to samples from the years 2011, 2014, and 2017. The findings indicate that FinTech has a positive and statistically significant effect on financial inclusion and income inequality in African countries. The study results also demonstrate that financial inclusion plays a pivotal mediation role in the negative effect of FinTech on income inequality in African economies. Further, financial inclusion (the ability to create a bank account and borrow money) negatively and significantly affects income inequality in African countries, whereas saving shows a positive and significant impact on income inequality. Overall, our study results suggest that to reduce income inequality and increase the effectiveness of FinTech investments, policymakers in African countries should design proper policies to enhance financial inclusion and offer more accessible and equitable financial services. Full article

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

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23 pages, 1420 KiB

Open AccessArticle

Understanding the Determinants of FinTech Adoption: Integrating UTAUT2 with Trust Theoretic Model

by Muhammed Basid Amnas, Murugesan Selvam, Mariappan Raja, Sakthivel Santhoshkumar and Satyanarayana Parayitam

J. Risk Financial Manag. 2023, 16(12), 505; https://doi.org/10.3390/jrfm16120505 - 6 Dec 2023

Cited by 3 | Viewed by 5455

Abstract

Financial technology (FinTech) is transforming the financial services industry by offering innovative, convenient solutions for businesses and individuals. This study examines the factors influencing FinTech adoption, with a special focus on trust. By integrating insights from both the unified theory of acceptance and [...] Read more.

Financial technology (FinTech) is transforming the financial services industry by offering innovative, convenient solutions for businesses and individuals. This study examines the factors influencing FinTech adoption, with a special focus on trust. By integrating insights from both the unified theory of acceptance and use of technology (UTAUT2), and the trust theoretic model (TTM), this research uncovers critical determinants of FinTech adoption. Utilizing survey responses obtained from 399 participants, this research employs the partial least squares structural equation modelling method. The findings reveal that performance expectancy, effort expectancy, social influence, habit, price value, and facilitating conditions significantly influence users’ intentions to use FinTech services. In addition, the study shows that trust plays a crucial role in FinTech use, as it influences both the intentions to use and the actual use of FinTech. Surprisingly, hedonic motivation was found not to affect users’ intentions, implying that people see FinTech as a practical, rather than enjoyable, endeavor. These insights provide valuable guidance for service providers and policymakers seeking to enhance FinTech adoption and utilization while ensuring the security and trustworthiness of these digital platforms. Full article

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

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22 pages, 11557 KiB

Open AccessArticle

A Hybrid Deep Learning Approach for Crude Oil Price Prediction

by Hind Aldabagh, Xianrong Zheng and Ravi Mukkamala

J. Risk Financial Manag. 2023, 16(12), 503; https://doi.org/10.3390/jrfm16120503 - 6 Dec 2023

Cited by 1 | Viewed by 2762

Abstract

Crude oil is one of the world’s most important commodities. Its price can affect the global economy, as well as the economies of importing and exporting countries. As a result, forecasting the price of crude oil is essential for investors. However, crude oil [...] Read more.

Crude oil is one of the world’s most important commodities. Its price can affect the global economy, as well as the economies of importing and exporting countries. As a result, forecasting the price of crude oil is essential for investors. However, crude oil price tends to fluctuate considerably during significant world events, such as the COVID-19 pandemic and geopolitical conflicts. In this paper, we propose a deep learning model for forecasting the crude oil price of one-step and multi-step ahead. The model extracts important features that impact crude oil prices and uses them to predict future prices. The prediction model combines convolutional neural networks (CNN) with long short-term memory networks (LSTM). We compared our one-step CNN–LSTM model with other LSTM models, the CNN model, support vector machine (SVM), and the autoregressive integrated moving average (ARIMA) model. Also, we compared our multi-step CNN–LSTM model with LSTM, CNN, and the time series encoder–decoder model. Extensive experiments were conducted using short-, medium-, and long-term price data of one, five, and ten years, respectively. In terms of accuracy, the proposed model outperformed existing models in both one-step and multi-step predictions. Full article

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

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24 pages, 569 KiB

Open AccessArticle

Derivative of Reduced Cumulative Distribution Function and Applications

by Kevin Maritato and Stan Uryasev

J. Risk Financial Manag. 2023, 16(10), 450; https://doi.org/10.3390/jrfm16100450 - 18 Oct 2023

Viewed by 1933

Abstract

The reduced cumulative distribution function (rCDF) is the maximal lower bound for the cumulative distribution function (CDF). It is equivalent to the inverse of the conditional value at risk (CVaR), or one minus the buffered probability of exceedance (bPOE). This paper introduces the [...] Read more.

The reduced cumulative distribution function (rCDF) is the maximal lower bound for the cumulative distribution function (CDF). It is equivalent to the inverse of the conditional value at risk (CVaR), or one minus the buffered probability of exceedance (bPOE). This paper introduces the reduced probability density function (rPDF), the derivative of rCDF. We first explore the relation between rCDF and other risk measures. Then we describe three means of calculating rPDF for a distribution, depending on what is known about the distribution. For functions with a closed-form formula for bPOE, we derive closed-form formulae for rPDF. Further, we describe formulae for rPDF based on a numerical bPOE when there is a closed-form formula for CVaR but no closed-form formula for bPOE. Finally, we give a method for numerically calculating rPDF for an empirical distribution, and compare the results with other methods for known distributions. We conducted a case study and used rPDF for sensitivity analysis and parameter estimation with a method similar to the maximum likelihood method. Full article

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

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32 pages, 469 KiB

Open AccessArticle

The Future of Insurance Intermediation in the Age of the Digital Platform Economy

by Lukas Stricker, Joël Wagner and Angela Zeier Röschmann

J. Risk Financial Manag. 2023, 16(9), 381; https://doi.org/10.3390/jrfm16090381 - 25 Aug 2023

Cited by 1 | Viewed by 3196

Abstract

Today most insurance is sold by over a million brokers and independent agents acting as intermediaries between the insurance companies and their customers. Digitalization and changing customer behavior have fostered the development of insurtech businesses, and, more recently, multi-sided platforms are emerging as [...] Read more.

Today most insurance is sold by over a million brokers and independent agents acting as intermediaries between the insurance companies and their customers. Digitalization and changing customer behavior have fostered the development of insurtech businesses, and, more recently, multi-sided platforms are emerging as new market forms for insurance intermediation. This paper aims to provide a better understanding of how the emergence of the platform economy, with a market dominated by multi-sided platforms, will potentially impact insurance intermediation in the future. Using inductive content analysis on the results of a systematic literature review of the body of research on insurance intermediation, we identify the key functional roles fulfilled by insurance intermediaries. Applying these roles to a literature review on multi-sided platforms allows us to compare how different market forms and players embody the functional roles of intermediaries. Our findings suggest that multi-sided platforms are better able to perform certain roles in terms of agility, scale and scope, and we discuss the future role of platforms in insurance intermediation. Full article

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

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