Satria Amiputra Amimakmur, Muhammad Saifi, Cacik Rut Damayanti, Benny Hutahayan
This research investigates the connection between dividend policy, third-party funds, financial performance, and company value, with a focus on IT Innovation as a moderating factor. This research was conducted using a quantitative approach, utilizing Commercial Banks listed on the Indonesia Stock Exchange categorized as BUKU 4 Banks during the period of 2016–2022. This study employed Partial Least Squares (PLS) analysis with WarpPLS 6.0 software as the tool for data analysis. This research concludes that dividend policy does not significantly impact financial performance and company value, while third-party funds have a significant positive effect on both financial performance and company value. Although dividend policy does not directly affect company value, its impact may occur through the mediation of financial performance. Additionally, IT Innovation serves as a moderating factor that strengthens the positive relationship between third-party funds and financial performance towards company value. The novelty of this research lies in the development of a more comprehensive model or concept regarding dividend policy, third-party funds, financial performance as a mediating variable, and company value when considering IT Innovation as a moderating variable.
本研究调查了股利政策、第三方资金、财务业绩和公司价值之间的联系，重点关注作为调节因素的信息技术创新。本研究采用定量方法，利用 2016-2022 年期间在印尼证券交易所上市的商业银行（归类为 BUKU 4 银行）进行研究。本研究使用 WarpPLS 6.0 软件的偏最小二乘法（PLS）分析作为数据分析工具。本研究得出结论：股利政策对财务绩效和公司价值没有显著影响，而第三方基金对财务绩效和公司价值都有显著的积极影响。虽然股利政策不会直接影响公司价值，但其影响可能会通过财务业绩的中介作用而产生。此外，信息技术创新也是一个调节因素，它加强了第三方基金与财务业绩之间的正相关关系，进而影响公司价值。本研究的新颖之处在于，在将信息技术创新作为调节变量的情况下，就股利政策、第三方基金、作为中介变量的财务业绩和公司价值建立了一个更全面的模型或概念。
{"title":"Exploring the Nexus of Dividend Policy, Third-Party Funds, Financial Performance, and Company Value: The Role of IT Innovation as a Moderator","authors":"Satria Amiputra Amimakmur, Muhammad Saifi, Cacik Rut Damayanti, Benny Hutahayan","doi":"10.3390/jrfm17050210","DOIUrl":"https://doi.org/10.3390/jrfm17050210","url":null,"abstract":"This research investigates the connection between dividend policy, third-party funds, financial performance, and company value, with a focus on IT Innovation as a moderating factor. This research was conducted using a quantitative approach, utilizing Commercial Banks listed on the Indonesia Stock Exchange categorized as BUKU 4 Banks during the period of 2016–2022. This study employed Partial Least Squares (PLS) analysis with WarpPLS 6.0 software as the tool for data analysis. This research concludes that dividend policy does not significantly impact financial performance and company value, while third-party funds have a significant positive effect on both financial performance and company value. Although dividend policy does not directly affect company value, its impact may occur through the mediation of financial performance. Additionally, IT Innovation serves as a moderating factor that strengthens the positive relationship between third-party funds and financial performance towards company value. The novelty of this research lies in the development of a more comprehensive model or concept regarding dividend policy, third-party funds, financial performance as a mediating variable, and company value when considering IT Innovation as a moderating variable.","PeriodicalId":508146,"journal":{"name":"Journal of Risk and Financial Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140964247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper proposes a method for conducting quantitative inductive research on survey data when the variable of interest follows an ordinal distribution. A methodology based on novel and traditional penalising models is described. The main aim of this study is to pedagogically present the method utilising the new penalising methods in a new application. A case was employed to outline the methodology. The case aims to select explanatory variables correlated with the target debt level in Swedish listed companies. The survey respondents were matched with accounting information from the companies’ annual reports. However, missing data were present: to fully utilise penalising models, we employed classification and regression tree (CART)-based imputations by multiple imputations chained equations (MICEs) to address this problem. The imputed data were subjected to six penalising models: grouped multinomial lasso, ungrouped multinomial lasso, parallel element linked multinomial-ordinal (ELMO), semi-parallel ELMO, nonparallel ELMO, and cumulative generalised monotone incremental forward stagewise (GMIFS). While the older models yielded several explanatory variables for the hypothesis formation process, the new models (ELMO and GMIFS) identified only one quick asset ratio. Subsequent testing revealed that this variable was the only statistically significant variable that affected the target debt level.
{"title":"An Inductive Approach to Quantitative Methodology—Application of Novel Penalising Models in a Case Study of Target Debt Level in Swedish Listed Companies","authors":"Åsa Grek, Fredrik Hartwig, Mark Dougherty","doi":"10.3390/jrfm17050207","DOIUrl":"https://doi.org/10.3390/jrfm17050207","url":null,"abstract":"This paper proposes a method for conducting quantitative inductive research on survey data when the variable of interest follows an ordinal distribution. A methodology based on novel and traditional penalising models is described. The main aim of this study is to pedagogically present the method utilising the new penalising methods in a new application. A case was employed to outline the methodology. The case aims to select explanatory variables correlated with the target debt level in Swedish listed companies. The survey respondents were matched with accounting information from the companies’ annual reports. However, missing data were present: to fully utilise penalising models, we employed classification and regression tree (CART)-based imputations by multiple imputations chained equations (MICEs) to address this problem. The imputed data were subjected to six penalising models: grouped multinomial lasso, ungrouped multinomial lasso, parallel element linked multinomial-ordinal (ELMO), semi-parallel ELMO, nonparallel ELMO, and cumulative generalised monotone incremental forward stagewise (GMIFS). While the older models yielded several explanatory variables for the hypothesis formation process, the new models (ELMO and GMIFS) identified only one quick asset ratio. Subsequent testing revealed that this variable was the only statistically significant variable that affected the target debt level.","PeriodicalId":508146,"journal":{"name":"Journal of Risk and Financial Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140974519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this study, we examine whether and how banks employ dividend payout policies in response to the risk of stock price crashes. Using a sample of U.S. banks, we find that banks increase their dividend payouts when faced with a higher risk of stock price crashes. In addition, we find that well-capitalized banks tend to pay more dividends when the risk of a stock price crash is elevated. This aligns with the regulatory pressure theory that banks distribute dividends when they have sufficient capital that meets or exceeds the regulatory standards. This is also in line with the signaling theory that dividend payments reflect a bank’s confidence in its financial health. Furthermore, we find that financially opaque banks tend to make more dividend payments when they are at a higher risk of stock price crashes. This supports the agency cost theory, suggesting that dividends counterbalance the need to monitor bank managers in less transparent reporting environments.
{"title":"The Impact of Stock Price Crash Risk on Bank Dividend Payouts","authors":"Justin Yiqiang Jin, Yi Liu","doi":"10.3390/jrfm17050209","DOIUrl":"https://doi.org/10.3390/jrfm17050209","url":null,"abstract":"In this study, we examine whether and how banks employ dividend payout policies in response to the risk of stock price crashes. Using a sample of U.S. banks, we find that banks increase their dividend payouts when faced with a higher risk of stock price crashes. In addition, we find that well-capitalized banks tend to pay more dividends when the risk of a stock price crash is elevated. This aligns with the regulatory pressure theory that banks distribute dividends when they have sufficient capital that meets or exceeds the regulatory standards. This is also in line with the signaling theory that dividend payments reflect a bank’s confidence in its financial health. Furthermore, we find that financially opaque banks tend to make more dividend payments when they are at a higher risk of stock price crashes. This supports the agency cost theory, suggesting that dividends counterbalance the need to monitor bank managers in less transparent reporting environments.","PeriodicalId":508146,"journal":{"name":"Journal of Risk and Financial Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140975420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Taiwan is an island where the city and nature combine to become the most beautiful open-air museum in the world, known as Formosa. With climate change and industrial development as the main changes in consumption behavior, the integration of ecology, the environment, and agriculture into food culture is gradually becoming valued in Taiwan. This study explores the quality of the rural outdoor dining experience in Taiwan; therefore, questionnaires were distributed to outdoor dining attendees from the north, central, south, and east, and we obtained 396 valid questionnaires. The rural outdoor dining satisfaction experience can be improved using the innovative New Importance–Performance Analysis (NIPA) model, which is based on the original IPA methodology but modified by the performance of the risk management judge. Additionally, we applied the zone of tolerance (ZOT) to evaluate the quality of priority and the importance–performance analysis (IPA) to make innovation decisions. The model also encourages decision-makers to consider environmental factors and customer feedback. It has not only been used to measure customer satisfaction, assess customer behavior, identify customer needs, and determine areas where quality needs to be improved, but it can also be used to measure the success of business decisions and identify potential areas for improvement. The results show that rural outdoor dining experiences in Taiwan have led to the development of a low carbon economy and a new business model for operators in order to follow the result of NIPA and develop service marketing strategies.
台湾是一个城市与自然相结合的岛屿，被称为世界上最美丽的露天博物馆--福尔摩沙。随着气候变化和工业发展成为消费行为的主要变化，将生态、环境和农业融入饮食文化在台湾逐渐受到重视。本研究探讨台湾乡村户外用餐体验的质量，因此向北部、中部、南部和东部的户外用餐者发放问卷，获得 396 份有效问卷。创新的新重要性-绩效分析（NIPA）模型是在原有的 IPA 方法基础上，根据风险管理法官的绩效对其进行修改，从而改善农村户外用餐的满意度体验。此外，我们还应用了容忍区（ZOT）来评估优先级的质量，并应用重要性-绩效分析（IPA）来做出创新决策。该模型还鼓励决策者考虑环境因素和客户反馈。该模型不仅可用于衡量客户满意度、评估客户行为、确定客户需求以及确定需要提高质量的领域，还可用于衡量商业决策的成功与否，并确定潜在的改进领域。研究结果表明，台湾的乡村户外餐饮体验带动了低碳经济的发展，也为经营者提供了新的商业模式，以便遵循 NIPA 的结果，制定服务营销战略。
{"title":"Application of the New Importance–Performance Analysis Method to Explore the Strategies of Rural Outdoor Dining Experiences in Taiwan","authors":"Shang-Pin Li","doi":"10.3390/jrfm17050208","DOIUrl":"https://doi.org/10.3390/jrfm17050208","url":null,"abstract":"Taiwan is an island where the city and nature combine to become the most beautiful open-air museum in the world, known as Formosa. With climate change and industrial development as the main changes in consumption behavior, the integration of ecology, the environment, and agriculture into food culture is gradually becoming valued in Taiwan. This study explores the quality of the rural outdoor dining experience in Taiwan; therefore, questionnaires were distributed to outdoor dining attendees from the north, central, south, and east, and we obtained 396 valid questionnaires. The rural outdoor dining satisfaction experience can be improved using the innovative New Importance–Performance Analysis (NIPA) model, which is based on the original IPA methodology but modified by the performance of the risk management judge. Additionally, we applied the zone of tolerance (ZOT) to evaluate the quality of priority and the importance–performance analysis (IPA) to make innovation decisions. The model also encourages decision-makers to consider environmental factors and customer feedback. It has not only been used to measure customer satisfaction, assess customer behavior, identify customer needs, and determine areas where quality needs to be improved, but it can also be used to measure the success of business decisions and identify potential areas for improvement. The results show that rural outdoor dining experiences in Taiwan have led to the development of a low carbon economy and a new business model for operators in order to follow the result of NIPA and develop service marketing strategies.","PeriodicalId":508146,"journal":{"name":"Journal of Risk and Financial Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140976950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Enkeleda Lulaj, M. Tase, Conceição Gomes, Lucília Cardoso
The problem addressed in this study is the profound impact of the COVID-19 pandemic on the tourism economies of Kosovo (KOS) and Albania (AL), which led to economic–financial stagnation and price increases. The aim was to analyze the financial frontier challenges facing the tourism industry during COVID-19 and beyond and propose effective strategies for shaping a sustainable future for countries within Europe with great potential for tourism development in the current decade. The survey was conducted in 102 locations, including cities, municipalities, regions, villages, and neighborhoods in both countries over the years 2020–2023, while data analysis was performed using a cluster analysis (K-means and hierarchical) and the multidimensional scaling method (Alscal). The results highlighted (a) the severe impact of COVID-19 on both the population and businesses in the tourism sector, which will persist beyond the pandemic, (b) the indispensable role of government intervention in alleviating the financial crisis, (c) the need for innovative approaches and accurate financial management by both the country and businesses to attract tourists, and (d) the importance of control and management for financial sustainability. This paper is of significant importance to tourism destinations as it provides insights into the severe impact of COVID-19 on both the population and businesses in the tourism economies. By highlighting the indispensable role of government intervention, the need for innovative approaches and accurate financial management, and the importance of control and management for financial sustainability, the study offers valuable guidance for tourism destinations in navigating the current crisis and attracting tourists. Furthermore, the paper emphasizes the need for future studies to explore opportunities for long-term financial resilience and growth, contributing to the development of sustainable tourism destinations.
{"title":"Navigating Financial Frontiers in the Tourism Economies of Kosovo and Albania during and beyond COVID-19","authors":"Enkeleda Lulaj, M. Tase, Conceição Gomes, Lucília Cardoso","doi":"10.3390/jrfm17040142","DOIUrl":"https://doi.org/10.3390/jrfm17040142","url":null,"abstract":"The problem addressed in this study is the profound impact of the COVID-19 pandemic on the tourism economies of Kosovo (KOS) and Albania (AL), which led to economic–financial stagnation and price increases. The aim was to analyze the financial frontier challenges facing the tourism industry during COVID-19 and beyond and propose effective strategies for shaping a sustainable future for countries within Europe with great potential for tourism development in the current decade. The survey was conducted in 102 locations, including cities, municipalities, regions, villages, and neighborhoods in both countries over the years 2020–2023, while data analysis was performed using a cluster analysis (K-means and hierarchical) and the multidimensional scaling method (Alscal). The results highlighted (a) the severe impact of COVID-19 on both the population and businesses in the tourism sector, which will persist beyond the pandemic, (b) the indispensable role of government intervention in alleviating the financial crisis, (c) the need for innovative approaches and accurate financial management by both the country and businesses to attract tourists, and (d) the importance of control and management for financial sustainability. This paper is of significant importance to tourism destinations as it provides insights into the severe impact of COVID-19 on both the population and businesses in the tourism economies. By highlighting the indispensable role of government intervention, the need for innovative approaches and accurate financial management, and the importance of control and management for financial sustainability, the study offers valuable guidance for tourism destinations in navigating the current crisis and attracting tourists. Furthermore, the paper emphasizes the need for future studies to explore opportunities for long-term financial resilience and growth, contributing to the development of sustainable tourism destinations.","PeriodicalId":508146,"journal":{"name":"Journal of Risk and Financial Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140358105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sreenivasulu Puli, Nagaraju Thota, A. C. V. Subrahmanyam
The historical prevalence of banking crises and their profound impact on global economies underscores the imperative for policy makers to refine their crisis forecasting frameworks. Against this backdrop, the present study endeavors to predict potential banking crises in India by leveraging a spectrum of artificial intelligence and machine learning techniques (AI-ML). These techniques encompass logistic regression, random forest, naïve Bayes, gradient boosting, support vector machine, neural networks, K-nearest neighbors, and decision trees. Initially, a banking fragility index was constructed utilizing monthly banking data spanning 2002 to 2023, demarcating the periods of crisis and stability. Subsequently, an extensive array of early warning indicators (EWIs) encompassing asset prices, macroeconomic factors, external influences, and credit-related variables were employed to forecast crisis periods. Our findings reveal that AI-ML models exhibit reasonable accuracy in predicting banking crises. Moreover, advanced model performance metrics highlight neural networks and random forest models as particularly effective in crisis prediction, surpassing other methodologies. Notably, among the EWIs, variables related to credit, interest rates, and liquidity emerge as possessing relatively higher information value in discerning fragilities within the Indian banking system. Importantly, the methodological framework presented herein can be extrapolated for banking crisis prediction in other economies.
{"title":"Assessing Machine Learning Techniques for Predicting Banking Crises in India","authors":"Sreenivasulu Puli, Nagaraju Thota, A. C. V. Subrahmanyam","doi":"10.3390/jrfm17040141","DOIUrl":"https://doi.org/10.3390/jrfm17040141","url":null,"abstract":"The historical prevalence of banking crises and their profound impact on global economies underscores the imperative for policy makers to refine their crisis forecasting frameworks. Against this backdrop, the present study endeavors to predict potential banking crises in India by leveraging a spectrum of artificial intelligence and machine learning techniques (AI-ML). These techniques encompass logistic regression, random forest, naïve Bayes, gradient boosting, support vector machine, neural networks, K-nearest neighbors, and decision trees. Initially, a banking fragility index was constructed utilizing monthly banking data spanning 2002 to 2023, demarcating the periods of crisis and stability. Subsequently, an extensive array of early warning indicators (EWIs) encompassing asset prices, macroeconomic factors, external influences, and credit-related variables were employed to forecast crisis periods. Our findings reveal that AI-ML models exhibit reasonable accuracy in predicting banking crises. Moreover, advanced model performance metrics highlight neural networks and random forest models as particularly effective in crisis prediction, surpassing other methodologies. Notably, among the EWIs, variables related to credit, interest rates, and liquidity emerge as possessing relatively higher information value in discerning fragilities within the Indian banking system. Importantly, the methodological framework presented herein can be extrapolated for banking crisis prediction in other economies.","PeriodicalId":508146,"journal":{"name":"Journal of Risk and Financial Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140363247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, the use of artificial neural networks (ANNs) is proposed to approximate the option price sensitivities of Johannesburg Stock Exchange (JSE) Top 40 European call options in a classical and a modern multi-curve framework. The ANNs were trained on artificially generated option price data given the illiquid nature of the South African market, and the out-of-sample performance of the optimized ANNs was evaluated using an implied volatility surface constructed from published volatility skews. The results from this paper show that ANNs trained on artificially generated input data are able to accurately approximate the explicit solutions to the respective option price sensitivities of both a classical and a modern multi-curve framework in a real-world out-of-sample application to the South African market.
{"title":"Approximating Option Greeks in a Classical and Multi-Curve Framework Using Artificial Neural Networks","authors":"Ryno du Plooy, Pierre J. Venter","doi":"10.3390/jrfm17040140","DOIUrl":"https://doi.org/10.3390/jrfm17040140","url":null,"abstract":"In this paper, the use of artificial neural networks (ANNs) is proposed to approximate the option price sensitivities of Johannesburg Stock Exchange (JSE) Top 40 European call options in a classical and a modern multi-curve framework. The ANNs were trained on artificially generated option price data given the illiquid nature of the South African market, and the out-of-sample performance of the optimized ANNs was evaluated using an implied volatility surface constructed from published volatility skews. The results from this paper show that ANNs trained on artificially generated input data are able to accurately approximate the explicit solutions to the respective option price sensitivities of both a classical and a modern multi-curve framework in a real-world out-of-sample application to the South African market.","PeriodicalId":508146,"journal":{"name":"Journal of Risk and Financial Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140365290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The accounting principles prevalent in Hollywood are seemingly crafted to mislead creators and investors. Film studios and streaming platforms have been found to use complex strategies to annually divert millions in net profits. Many contracts include audit clauses, but the cost of auditing a billion-dollar system is prohibitive for most creatives with “net profit” deals. However, a resourceful minority have recovered billions in profits and damages. We suggest using Bitcoin’s transparent, immutable ledger to eliminate fraudulent accounting and build trust among profit-seeking filmmakers willing to trade maximum income for maximum profit per share. This trust can be spread globally utilizing the Bitcoin network as a transparent and immutable triple-entry accounting system. Our research shows that distributing this decentralized trust is achievable by configuring an ecosystem of existing Bitcoin wallets, applications, and recorded contracts to create a universal source of truth for all parties assisting in the creation of valuable content in the form of movies. This network can form the foundation on which to build a legal blockchain infrastructure that can eventually facilitate the sale of tokenized securities, discretely disseminate recorded financial data, and transparently distribute revenue to a collective of filmmakers indefinitely.
{"title":"Ostrom’s Razor: Using Bitcoin to Cut Fraud in Hollywood Accounting","authors":"Ted Rivera, Dave Foderick","doi":"10.3390/jrfm17040139","DOIUrl":"https://doi.org/10.3390/jrfm17040139","url":null,"abstract":"The accounting principles prevalent in Hollywood are seemingly crafted to mislead creators and investors. Film studios and streaming platforms have been found to use complex strategies to annually divert millions in net profits. Many contracts include audit clauses, but the cost of auditing a billion-dollar system is prohibitive for most creatives with “net profit” deals. However, a resourceful minority have recovered billions in profits and damages. We suggest using Bitcoin’s transparent, immutable ledger to eliminate fraudulent accounting and build trust among profit-seeking filmmakers willing to trade maximum income for maximum profit per share. This trust can be spread globally utilizing the Bitcoin network as a transparent and immutable triple-entry accounting system. Our research shows that distributing this decentralized trust is achievable by configuring an ecosystem of existing Bitcoin wallets, applications, and recorded contracts to create a universal source of truth for all parties assisting in the creation of valuable content in the form of movies. This network can form the foundation on which to build a legal blockchain infrastructure that can eventually facilitate the sale of tokenized securities, discretely disseminate recorded financial data, and transparently distribute revenue to a collective of filmmakers indefinitely.","PeriodicalId":508146,"journal":{"name":"Journal of Risk and Financial Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140365907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yuan Hu, W. B. Lindquist, S. Rachev, Frank J. Fabozzi
We develop a binary tree pricing model with underlying asset price dynamics following Itô–McKean skew Brownian motion. Our work was motivated by the Corns–Satchell, continuous-time, option pricing model. However, the Corns–Satchell market model is incomplete, while our discrete-time market model is defined in the natural world, extended to the risk-neutral world under the no-arbitrage condition where derivatives are priced under uniquely determined risk-neutral probabilities, and is complete. The skewness introduced in the natural world is preserved in the risk-neutral world. Furthermore, we show that the model preserves skewness under the continuous-time limit. We provide empirical applications of our model to the valuation of European put and call options on exchange-traded funds tracking the S&P Global 1200 index.
{"title":"Option Pricing Using a Skew Random Walk Binary Tree","authors":"Yuan Hu, W. B. Lindquist, S. Rachev, Frank J. Fabozzi","doi":"10.3390/jrfm17040138","DOIUrl":"https://doi.org/10.3390/jrfm17040138","url":null,"abstract":"We develop a binary tree pricing model with underlying asset price dynamics following Itô–McKean skew Brownian motion. Our work was motivated by the Corns–Satchell, continuous-time, option pricing model. However, the Corns–Satchell market model is incomplete, while our discrete-time market model is defined in the natural world, extended to the risk-neutral world under the no-arbitrage condition where derivatives are priced under uniquely determined risk-neutral probabilities, and is complete. The skewness introduced in the natural world is preserved in the risk-neutral world. Furthermore, we show that the model preserves skewness under the continuous-time limit. We provide empirical applications of our model to the valuation of European put and call options on exchange-traded funds tracking the S&P Global 1200 index.","PeriodicalId":508146,"journal":{"name":"Journal of Risk and Financial Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140377542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
{"title":"Knowledge Sharing and Cumulative Innovation in Business Networks","authors":"Gilles Saint-Paul","doi":"10.3390/jrfm17040137","DOIUrl":"https://doi.org/10.3390/jrfm17040137","url":null,"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 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.","PeriodicalId":508146,"journal":{"name":"Journal of Risk and Financial Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140380383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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