{"title":"Autoregressive distributed lag estimation of bank financing and Nigerian manufacturing sector capacity utilization","authors":"K. A. Saka, Y. I. Bolanle","doi":"10.3934/qfe.2023004","DOIUrl":"https://doi.org/10.3934/qfe.2023004","url":null,"abstract":"This study examined the short-term and long-term relationship between credit financing by commercial banks and capacity utilization of the manufacturing sector in Nigeria. The study employed both classical Multiple Linear Regression (OLS-MLR) and the autoregressive distributed lag model (ARDL) to analyze data representing the period 1981–2020 relating to sectoral credit finance,labor employment,and capacity utilization from the Central Bank of Nigeria Statistical Bulletin (2020) and World Bank Development Indicators (2021). Further,the two estimation procedures were performed within a classical endogenous Cobb-Douglas production function framework that takes technical change into consideration. The bounds test indicated no long-term relationship between bank financing and average capacity utilization of the manufacturing sector in Nigeria. However,the ARDL results revealed that bank financing exerts a positive but insignificant short-term impact on the average capacity utilization of the manufacturing sector in Nigeria. Consequently,the researchers affirm that credit financing by commercial banks in Nigeria has no significant impact on the capacity utilization of the country's manufacturing sector,in neither the short run nor the long run.","PeriodicalId":45226,"journal":{"name":"Quantitative Finance and Economics","volume":"1 1","pages":""},"PeriodicalIF":5.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70231231","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":"Investor sentiment and the interdependence structure of GIIPS stock market returns: A multiscale approach","authors":"S. Agyei, A. Bossman","doi":"10.3934/qfe.2023005","DOIUrl":"https://doi.org/10.3934/qfe.2023005","url":null,"abstract":"The GIIPS economies are noted to suffer the most consequences of systemic crises. Regardless of their bad performance in crisis periods, their role(s) in asset allocation and portfolio management cannot go unnoticed. For effective portfolio management across divergent timescales, cross-market interdependencies cannot be side-lined. This study examines the conditional and unconditional co-movements of stock market returns of GIIPS economies incorporating investor fear in their time-frequency connectedness. As a result, the bi-, partial, and multiple wavelet approaches are employed. Our findings explicate that the high interdependencies between the stock market returns of GIIPS across all time scales are partly driven by investor fear, implying that extreme investor sentiment could influence stock market prices in GIIPS. The lagging role of Spanish stock market returns manifests at zero lags at high (lower) and medium frequencies (scales). At lower frequencies (higher scales), particularly quarterly-to-biannual and biannual-to-annual, Spanish and Irish stock markets, respectively, lag all other markets. Although portfolio diversification and safe haven benefits are minimal with GIIPS stocks, their volatilities could be hedged against by investing in the US VIX. Intriguing inferences for international portfolio and risk management are offered by our findings.","PeriodicalId":45226,"journal":{"name":"Quantitative Finance and Economics","volume":"1 1","pages":""},"PeriodicalIF":5.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70231287","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":"Determinants and evolution of financial inclusion in Latin America: A demand side analysis","authors":"S. Orazi, L. Martinez, H. Vigier","doi":"10.3934/qfe.2023010","DOIUrl":"https://doi.org/10.3934/qfe.2023010","url":null,"abstract":"The benefits of financial inclusion could be particularly important in Latin America, where the levels of ownership and use of different instruments lag behind those of developed countries. An improvement in the ownership and use of formal financial instruments could result in a reduction in informality, the promotion of formal savings and productive credit, and, therefore, an inclusive economic growth. The objective of this paper is to analyze the financial inclusion of a group of Latin American countries in order to detect the most used financial instruments and the main socioeconomic determinants that explain their ownership or use. At the same time, the evolution of the main variables was also studied for the years 2011, 2014, 2017 and 2021. Micro-data from the Global Findex database was examined (except for 2021, in which only macro-data are available). Statistical models and multivariate econometrics are applied to understand the individual socioeconomic characteristics of people who are still very unlikely to own and use formal financial instruments. Finally, the main reasons for not having an account were analyzed in order to delve into the main restrictions on which the financial market must focus to achieve greater financial inclusion.","PeriodicalId":45226,"journal":{"name":"Quantitative Finance and Economics","volume":"1 1","pages":""},"PeriodicalIF":5.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70231418","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":"Machine learning-based quantitative trading strategies across different time intervals in the American market","authors":"Yimeng Wang, Keyue Yan","doi":"10.3934/qfe.2023028","DOIUrl":"https://doi.org/10.3934/qfe.2023028","url":null,"abstract":"<abstract><p>Stocks are the most common financial investment products and attract many investors around the world. However, stock price volatility is usually uncontrollable and unpredictable for the individual investor. This research aims to apply different machine learning models to capture the stock price trends from the perspective of individual investors. We consider six traditional machine learning models for prediction: decision tree, support vector machine, bootstrap aggregating, random forest, adaptive boosting, and categorical boosting. Moreover, we propose a framework that uses regression models to obtain predicted values of different moving average changes and converts them into classification problems to generate final predictive results. With this method, we achieve the best average accuracy of 0.9031 from the 20-day change of moving average based on the support vector machine model. Furthermore, we conduct simulation trading experiments to evaluate the performance of this predictive framework and obtain the highest average annualized rate of return of 29.57%.</p></abstract>","PeriodicalId":45226,"journal":{"name":"Quantitative Finance and Economics","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135660636","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":"A naive justification of hyperbolic discounting from mental algebraic operations and functional analysis","authors":"Salvador Cruz Rambaud, Jorge Hernandez-Perez","doi":"10.3934/qfe.2023023","DOIUrl":"https://doi.org/10.3934/qfe.2023023","url":null,"abstract":"<abstract><sec><title>Background</title><p>Intertemporal decision-making, which involves making choices between outcomes at different time points, is a fundamental aspect of human behavior. Understanding the underlying mental processes is vital for comprehending the complexities of human decision-making and choice behavior.</p> </sec> <sec><title>Objective</title><p>The main objective of this study is to investigate the interplay of mental processes, specifically cognitive evaluation, subjective valuation, and comparison, in the context of intertemporal decision-making, with a specific focus on understanding the discounting process.</p> </sec> <sec><title>Methodology</title><p>Development of a mathematical representation of the discounting process that incorporates the mental processes associated with intertemporal decision-making.</p> </sec> <sec><title>Result</title><p>Our findings indicate that hyperbolic discounting aligns well with the cognitive processes underlying intertemporal decision-making. Subsequent research will employ qualitative questionnaires to establish the discount function relevant to specific groups, thereby enhancing our comprehension of the discounting process within intertemporal decision-making.</p> </sec></abstract>","PeriodicalId":45226,"journal":{"name":"Quantitative Finance and Economics","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135784056","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}
Fabrizio Di Sciorio, Raffaele Mattera, Juan Evangelista Trinidad Segovia
{"title":"Measuring conditional correlation between financial markets' inefficiency","authors":"Fabrizio Di Sciorio, Raffaele Mattera, Juan Evangelista Trinidad Segovia","doi":"10.3934/qfe.2023025","DOIUrl":"https://doi.org/10.3934/qfe.2023025","url":null,"abstract":"<abstract><p>Assuming that stock prices follow a multi-fractional Brownian motion, we estimated a time-varying Hurst exponent ($ h_t $). The Hurst value can be considered a relative volatility measure and has been recently used to estimate market inefficiency. Therefore, the Hurst exponent offers a level of comparison between theoretical and empirical market efficiency. Starting from this point of view, we adopted a multivariate conditional heteroskedastic approach for modeling inefficiency dynamics in various financial markets during the 2007 financial crisis, the COVID-19 pandemic and the Russo-Ukranian war. To empirically validate the analysis, we compared different stock markets in terms of conditional and unconditional correlations of dynamic inefficiency and investigated the predicted power of inefficiency measures through the Granger causality test.</p></abstract>","PeriodicalId":45226,"journal":{"name":"Quantitative Finance and Economics","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135799357","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 spillover effect of international monetary policy on China's financial market","authors":"Cunyi Yang, Li Chen, Bin Mo","doi":"10.3934/qfe.2023026","DOIUrl":"https://doi.org/10.3934/qfe.2023026","url":null,"abstract":"<abstract> <p>This study analyzes the impact of global financial integration and monetary policies from the United States, European Union and Japan on China's financial markets post-pandemic. Using TVP-FAVAR (Time-Varying Parameter Factor Augmented Vector Autoregression) and TVP-VAR-DY (Time-Varying Parameter Vector Autoregression DY) models, a Chinese financial market stress index was developed, showing that developed nations' monetary policies influence China's financial stress. The impact varies based on the economy's size and policy effectiveness. The spillovers occur mainly through accelerated short-term capital flows and foreign exchange reserve fluctuations. These effects have evolved over two decades, particularly noticeable during economic crises and the COVID-19 pandemic, highlighting the need for emerging economies, like China, to protect against international financial spillovers.</p> </abstract>","PeriodicalId":45226,"journal":{"name":"Quantitative Finance and Economics","volume":"854 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136257116","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 different modes of foreign bank entry in the Turkish banking sector during the 2007–2009 Global financial crisis","authors":"N. Polovina, K. Peasnell","doi":"10.3934/qfe.2023002","DOIUrl":"https://doi.org/10.3934/qfe.2023002","url":null,"abstract":"This paper provides insights on how foreign bank entry modes (acquisition vs. greenfield investment) in an emerging market (Turkey) influenced bank strategies during the 2007–2009 global financial crisis. Using a comprehensive dataset comprising twenty-nine accounting variables from Turkish banks' financial statements during 2005–2010, we find important differences between foreign-acquired banks and foreign bank branches in lending and sourcing funds. We find that foreign bank branches continued to support international trade by issuing import loans during 2007–2009 global financial crisis, whereas foreign-acquired banks focused on issuing consumer and credit card loans. In terms of bank sourcing funds, we find that foreign-acquired banks were able to continue to use foreign currency deposits of Turkish residents and local interbank funding including participation (Islamic) banks. Foreign bank branches, on the other hand, relied on sourcing funds from international interbank funding and foreign currency deposits of residents abroad, which led to the necessity for them to change their strategies because of funding shortage in international markets. Our results show that the presence of foreign banks in Turkish banking sector enabled the continuity of bank lending activities in host market during the turmoil of 2007–2009 global financial crisis. Our findings on foreign bank entry mode provide new evidence and have important implications for both policy makers and practitioners in emerging markets.","PeriodicalId":45226,"journal":{"name":"Quantitative Finance and Economics","volume":"1 1","pages":""},"PeriodicalIF":5.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70230832","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":"Cost and performance of carbon risk in socially responsible mutual funds","authors":"J. C. Matallín‐Sáez, A. Soler‐Domínguez","doi":"10.3934/qfe.2023003","DOIUrl":"https://doi.org/10.3934/qfe.2023003","url":null,"abstract":"Investors and other financial actors are attracted by the role of socially responsible (SR) mutual funds in the transition to a low-carbon economy. In response to the demand for more information, Morningstar reported the level of carbon risk of funds by using the following indicators: Carbon Risk, Carbon Management, Carbon Operations risk and Carbon Exposure. Dealing with a sample of 3370 equity SR mutual funds worldwide from 2017 to 2021, this study analyzes the relationships between these indicators and the expense ratio and performance of the funds. In general, the results point to funds with lower carbon scores that have lower fees and perform better than those with higher scores. Considering the effects of the COVID-19 crisis, this evidence holds true for most of the sample period analyzed. With a spatial analysis, although the evidence generally holds, regional differences are found. Thus, funds that invest in the USA and Canada are on average cheaper and show lower carbon scores, while funds that are oriented to other areas, such as emerging markets, are more expensive and show higher scores. In summary, there is good news for the utility function of the investor and the planet: Green investing is cheaper and better.","PeriodicalId":45226,"journal":{"name":"Quantitative Finance and Economics","volume":"1 1","pages":""},"PeriodicalIF":5.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70230885","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":"Investing in virtue and frowning at vice? Lessons from the global economic and financial crisis","authors":"Lucía Morales, Daniel Rajmil","doi":"10.3934/qfe.2023001","DOIUrl":"https://doi.org/10.3934/qfe.2023001","url":null,"abstract":"Socially responsible mutual funds (SRMF) and the \"antisocially conscious\", Vitium Global Fund Barrier Fund (formerly known as the Vice Fund, the term used in this paper) returns, volatility patterns, and causal effects are examined in this study within the context of the lessons learned from the 2008 Global Economic and Financial Crisis (GEFC). In times of a new and unprecedented crisis due to the COVID-19 pandemic, a look back to our recent past reveals that volatility patterns on daily stock returns presented some level of predictability on prices for both types of funds. The research findings are significant as funds' potential predictability could help market players when designing their investment strategies. More specifically, an increase in volatility persistence is found after the GEFC, together with an increase in the Vice Fund's resilience to market shocks. Although all funds, without substantial differences, take time to absorb the shocks. A noteworthy outcome relates to SRMF that was able to achieve higher returns and exhibited lower volatility levels during the crisis period. Whereas the Vice Fund revealed long-run sustainable performance offering fund managers and investors investment opportunities that are endorsed by the fund performance over the period. Furthermore, unidirectional causality was found running from the Vice Fund to the SRMF, exhibiting a clear dominance during the GEFC period. The research findings contribute to the debate on the future of socially responsible investment, indicating that SRMF appears to be driven by \"antisocially conscious\" funds signaling limited rewards for investors inclined to invest in funds that are considered socially responsible.","PeriodicalId":45226,"journal":{"name":"Quantitative Finance and Economics","volume":"1 1","pages":""},"PeriodicalIF":5.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70231132","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}