{"title":"Analysis on the Next Generation of Artificial Intelligence Development Plan and Digital Financial Inclusion: Evidence from China","authors":"Aili Zhang, Xinyu Sun","doi":"10.47260/jafb/1261","DOIUrl":"https://doi.org/10.47260/jafb/1261","url":null,"abstract":"Abstract\u0000\u0000In 2017, the State Council of China released the Next Generation Artificial Intelligence Development Plan in order to seize the opportunity to develop artificial intelligence. Based on a panel dataset from 31 regions in China from 2014-2019, this study utilizes a difference-in-difference model to examine the impact of the release of the Next Generation of Artificial Intelligence Development Plan on the development of digital financial inclusion, and then utilizes a spatial difference-in-difference model to examine the spatial spillover effect of the release of the plan. In this study, results demonstrate that the release of the Next Generation of Artificial Intelligence Development Plan had a significant impact on the promotion of the development of digital financial inclusion, as indicated predominantly by the depth of its use and digitalization. Additionally, the spatial difference-in-difference analysis shows that the impact of this plan has a significant spatial spillover effect, which promotes the development of digital financial inclusion in the region, as well as increases the level of digital financial inclusion in the surrounding areas. The development of digital financial inclusion has been accompanied by a spatial agglomeration.\u0000\u0000JEL classification numbers: O25, O33, R58.\u0000Keywords: Artificial Intelligence, Digital Financial Inclusion, Difference-in-Difference Model, Spatial Difference-in-Difference Model, Spatial Spillover Effect.","PeriodicalId":330012,"journal":{"name":"Journal of Applied Finance & Banking","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134473872","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}
{"title":"International Fund Allocation under Economic Policy Uncertainty Shock","authors":"Jing-Yi Hou, Daoguo Wang","doi":"10.47260/jafb/1255","DOIUrl":"https://doi.org/10.47260/jafb/1255","url":null,"abstract":"Abstract\u0000\u0000This paper focuses on the impact of economic policy uncertainty on international asset allocation and international capital flows. Our results show that economic policy uncertainty shocks have a negative impact on the international asset allocation, which can be explained from the real economic activity channel and the expectation channel. We also explore a full fledge of country level heterogeneities about the economic policy uncertainty shocks on international asset allocation. Specifically, good institutional quality, transparent information, good information access to the international financial market and bilateral informational link help to alleviate the negative effect that economic policy uncertainty shock does to asset allocation. And a healthy public and external sector also help to alleviate the negative effect. While the importance of government in the economy amplifies the negative effect of economic policy uncertainty shocks to asset allocation.\u0000\u0000JEL classification numbers: E44, G11, G15.\u0000Keywords: Economic policy uncertainty, Global fund allocation, Institutional quality, Global imbalance.","PeriodicalId":330012,"journal":{"name":"Journal of Applied Finance & Banking","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115275182","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}
{"title":"The Effects of Ownership Structure on Bank Efficiency for Taiwan: Is there a Non-Linear Relationship?","authors":"C. Liao, Xinyan Li","doi":"10.47260/jafb/1254","DOIUrl":"https://doi.org/10.47260/jafb/1254","url":null,"abstract":"Abstract\u0000\u0000To investigate the impact of ownership structure and concentration on bank efficiency in the case of Taiwan, we consider the non-linear relationship between ownership and efficiency, using the panel threshold model technique to test whether a non-linear relationship is significant. Empirical findings indicate that ownership structure is significantly impacted by bank efficiency; the results show that managerial ownership negatively relates to efficiency and ownership concentration, and state-ownership has no regard for bank efficiency. The results show that the threshold effect is significant, implying a significant non-linear relationship between board ownership and efficiency. This supports the form of non-linear relation as found in previous literature.\u0000\u0000JEL Classification: G21, G34.\u0000Keywords: Ownership structure, Concentration, Panel threshold model.","PeriodicalId":330012,"journal":{"name":"Journal of Applied Finance & Banking","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121350216","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}
{"title":"Pricing Rent-to-Own Options with a Barrier Level: Taking Housing Contracts as an Example","authors":"Yi-Long Hsiao, C. Ting","doi":"10.47260/jafb/1253","DOIUrl":"https://doi.org/10.47260/jafb/1253","url":null,"abstract":"Abstract\u0000\u0000How to effectually price a rent-to-own option embedded a barrier level? This question is an important issue in financial market. For the purpose, we use the boundary integral method of PDE to derive a closed-form approximate solution of the rent-to-own option embedded a barrier level, where the tenant has the right to buy a specified rental house during the duration of contract. This study finds several characteristics through a sequence of numerical analyses and provides an available method for pricing rent-to-own options taking housing contracts with a barrier level as an example. This paper is original research in pricing a rent-to-own option using a boundary integral method and provides a reference to financial market about the valuation of a rent-to-own option embedded a barrier level well.\u0000\u0000JEL classification numbers: C02, G13.\u0000Keywords: Rent-to-own option, Boundary integral method, Green’s function.","PeriodicalId":330012,"journal":{"name":"Journal of Applied Finance & Banking","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122474874","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}
{"title":"Predicting Bitcoin Prices via Machine Learning and Time Series Models","authors":"","doi":"10.47260/jafb/1252","DOIUrl":"https://doi.org/10.47260/jafb/1252","url":null,"abstract":"Abstract\u0000\u0000In this study, we predict Bitcoin price trends using the back propagation neural network (BPNN), autoregressive integrated moving average (ARIMA), and generalized autoregressive conditional heteroscedasticity (GARCH) models. Based on principal component analysis (PCA), we extract two new input components for BPNN from Bitcoin’s three-day closing prices, MA5, MA20, daily trading volume, Ether price, and Ripple price. The training set covers the period between September 1, 2015 and March 31, 2020, and the forecasting set covers the period between April 1, 2020 and June 30, 2020. Empirical results reveal (1) the predictive ability of BPNN over that of the ARIMA models; (2) BPNN with two hidden layers is able to predict price trends more precisely than that with only one hidden layer; (3) in terms of time series models, the ARIMA-GARCH family of models demonstrates better predictive performance than ARIMA models; and (4) among the ARIMAGARCH family of models, the ARIMA-EGARCH model is proven to produce the best predictive results on price, and the ARIMA-GARCH model predicts more accurately than the ARIMA-GJR-GARCH model. Specifically, our findings provide a reference on Bitcoin for market participants.\u0000\u0000JEL classification numbers: C32, C45, C53, G17.\u0000Keywords: Bitcoin, Back propagation neural network, Autoregressive integrated moving average, Generalized autoregressive conditional heteroscedasticity, Principal component analysis.","PeriodicalId":330012,"journal":{"name":"Journal of Applied Finance & Banking","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133764618","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}
{"title":"Corporate Governance and Financial Crisis - A Empirical Study of Taiwanese Listed Companies","authors":"Cheng-An Shen, Hsiu-Fang Wang, H. Chiang","doi":"10.47260/jafb/1251","DOIUrl":"https://doi.org/10.47260/jafb/1251","url":null,"abstract":"Abstract\u0000\u0000This study mainly examines the association between corporate governance and\u0000financial crises of firms cross-listed in Taiwan. Using Logistic regression analysis,\u0000it takes Taiwan listed companies and the firms cross-listed in Taiwan from 2009 to\u00002019 as the research objects, to discuss corporate governance and corporate\u0000financial crisis and predict the possibility of the company’s future financial crisis.\u0000The empirical results reveal that the corporate governance mechanism of the firms\u0000cross-listed in Taiwan had no significant correlation between the change of financial\u0000controller and the future financial crisis of accounting firm and the possibility, while\u0000the number of internal audit changes, the shareholding ratio of major shareholders,\u0000and the size of the company were positively correlated with the possibility of future\u0000financial crisis. The results of this audit confirm that the corporate governance\u0000mechanism of the first listed company has an important influence on the\u0000management and the operating performance of the company. It may also serve as a\u0000basis for external investors and the government to judge the financial soundness of\u0000the first listed company.\u0000\u0000JEL classification numbers: G32.\u0000Keywords: Corporate governance, Financial crisis, Majority shareholding.","PeriodicalId":330012,"journal":{"name":"Journal of Applied Finance & Banking","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116974911","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}
{"title":"Application of the Real-Time Tourism Data in Nowcasting the Service Consumption in Taiwan","authors":"C. Ting, Yi-Long Hsiao, Rui Su","doi":"10.47260/jafb/1244","DOIUrl":"https://doi.org/10.47260/jafb/1244","url":null,"abstract":"Abstract In this paper, we examined the relationship between tourism and service consumption in Taiwan. The service consumption in Taiwan is nowcasted with the real-time tourism data in Google Trends database. We used the high-frequency internet-searching tourism data to predict the low-frequency service consumption data, for the real-time data with rich information could enhance prediction accuracy. Applying the Principal Components Analysis (PCA), we used the internet-searching tourism keywords in Google Trends database to construct the diffusion indices. Following the classification of the tourism keywords in Matsumoto et al. (2013), we classified those keywords into five groups and twenty-nine classifications. We focused on the reciprocal reactions between those diffusion indices with service consumption to conclude which component has higher influence on service consumption in Taiwan. Our empirical results indicated that the keywords in “Recreational areas, and Travel-related” group have significant effects on service consumption in Taiwan via nowcasting. Among the components of those diffusion indices, “Farm, Travel insurance, and Visitor center” are important variables with higher weights in common. JEL classification numbers: C60, C80, E01, E2, E60. Keywords: Nowcasting, the Principal Components Analysis (PCA), Service Consumption, Tourism.","PeriodicalId":330012,"journal":{"name":"Journal of Applied Finance & Banking","volume":"94 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120885313","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}
{"title":"Corporate Social Responsibility and Value of Cash Holdings in Taiwan: The Role of Family Firms","authors":"Min-lee Chan, Cho-Min Lin, Huan You","doi":"10.47260/jafb/1243","DOIUrl":"https://doi.org/10.47260/jafb/1243","url":null,"abstract":"Abstract\u0000\u0000This paper is to shed light on the relationship between corporate social responsibility (CSR) and cash value at family businesses using 3630 firm-year observations representing 395 listed Taiwanese companies. The results indicate that CSR has a significantly positive impact on cash value at family businesses, but no apparent relationship is supported at non-family businesses. Regarding the CSR activities, environmental protection, corporate commitment and corporate governance are consistently and significantly confirm the positive effects on corporate cash value at the family business, but social participation does not confirm this finding. The above results imply that conflict resolution view/or socio-emotional wealth view is evidenced at the relationship between family firm’s CSR and cash value. To the best of our knowledge, our results are firstly documented on the relationship between cash value and CSR of family business and thus make major contributions to related literature of family business.\u0000\u0000JEL classification numbers: G32, G34, M14.\u0000Keywords: Family Business, Corporate Social Responsibility, Cash Value.","PeriodicalId":330012,"journal":{"name":"Journal of Applied Finance & Banking","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134294622","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}
{"title":"How Does International Crude Price Affect China’s Carbon Emission?","authors":"Qiaoling Chen","doi":"10.47260/jafb/1242","DOIUrl":"https://doi.org/10.47260/jafb/1242","url":null,"abstract":"Abstract\u0000\u0000This study extends the standard STIRPAT model by introducing an energy price factor and uses the extended STIRPAT model to examine the effect of international crude oil prices on China’s carbon emission, This paper applies Ridge regression to conduct empirical analysis. The study finds that changes in international crude prices have a significantly positive impact on China’s carbon emission. A 1 percent increase in international crude oil price leads to a 0.12 percent increase in China’s carbon emission This finding remains unchanged even after a set of control variables are included in the analysis and survives all the rigidity tests.\u0000\u0000Keywords: Crude price, China, Carbon emission.","PeriodicalId":330012,"journal":{"name":"Journal of Applied Finance & Banking","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116798047","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}
{"title":"Mutual Causal Effects Between Bank Stability and Profitability in SSA Banking System","authors":"Changjun Zheng, Sinamenye Jean-Petit","doi":"10.47260/jafb/1241","DOIUrl":"https://doi.org/10.47260/jafb/1241","url":null,"abstract":"Abstract\u0000\u0000This paper intends to assess the interaction between stability factors and profitability\u0000proxies with macroeconomic factors as controllable variables. The analysis used\u0000bank risk metrics (LLRs, Credit Growth, and NPLs) and bank performance proxies\u0000(NIM, ROE, and ROA) with a dataset from 40 countries with 350 active commercial\u0000banks. The study uses Autoregressive Distributed Lags estimation with Dynamic\u0000Fixed Effect method (ARDL-DFE) to assess both short and long-run interaction\u0000effects. The analysis finds that both are interesting for a better sustainable banking\u0000system: the results evidenced a causal interdependence effect between bank\u0000profitability ratios and bank stability proxies. Furthermore, three causality tests and\u0000cointegration analyses were significant enough, which allowed us to conclude that\u0000caring for bank risk is caring for bank performance. This study recommends\u0000regulators (central banks and the Basel Committee) to enforce the bank profitability\u0000to mitigate related bank risks. The study also suggests (especially Basel Committee)\u0000a regulator tool called Bank Performance/Profit Requirement Ratio (BPRR).\u0000\u0000JEL classification numbers: P430, G4, E510.\u0000Keywords: Bank, Risk, Performance, Stability, Profitability, Interdependence,\u0000DFE, SSA, Africa.","PeriodicalId":330012,"journal":{"name":"Journal of Applied Finance & Banking","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115039069","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}