Financial Innovation最新文献_第3页

Asymmetric connectedness between conventional and Islamic cryptocurrencies: Evidence from good and bad volatility spillovers 传统加密货币与伊斯兰加密货币之间的非对称关联性：好坏波动溢出效应的证据

IF 8.4 1区经济学

Financial Innovation Pub Date : 2024-06-03 DOI: 10.1186/s40854-024-00636-0

Elie Bouri, Mahdi Ghaemi Asl, Sahar Darehshiri, David Gabauer

引用次数: 0

Stock return prediction with multiple measures using neural network models 利用神经网络模型的多重衡量标准预测股票回报率

IF 8.4 1区经济学

Financial Innovation Pub Date : 2024-06-01 DOI: 10.1186/s40854-023-00608-w

Cong Wang

{"title":"Stock return prediction with multiple measures using neural network models","authors":"Cong Wang","doi":"10.1186/s40854-023-00608-w","DOIUrl":"https://doi.org/10.1186/s40854-023-00608-w","url":null,"abstract":"In the field of empirical asset pricing, the challenges of high dimensionality, non-linear relationships, and interaction effects have led to the increasing popularity of machine learning (ML) methods. This study investigates the performance of ML methods when predicting different measures of stock returns from various factor models and investigates the feature importance and interaction effects among firm-specific variables and macroeconomic factors in this context. Our findings reveal that neural network models exhibit consistent performance across different stock return measures when they rely solely on firm-specific characteristic variables. However, the inclusion of macroeconomic factors from the financial market, real economic activities, and investor sentiment leads to substantial improvements in the model performance. Notably, the degree of improvement varies with the specific measures of stock returns under consideration. Furthermore, our analysis indicates that, after the inclusion of macroeconomic factors, there is a dissimilarity in model performance, variable importance, and interaction effects among macroeconomic and firm-specific variables, particularly concerning abnormal returns derived from the Fama–French three- and five-factor models compared with excess returns. This divergence is primarily attributed to the extent to which these factor models remove the variance associated with the macroeconomic variables. These findings collectively offer valuable insights into the efficacy of neural network models for stock return predictions and contribute to a deeper understanding of the intricate relationship between factor models, stock returns, and macroeconomic conditions in the domain of empirical asset pricing.","PeriodicalId":37175,"journal":{"name":"Financial Innovation","volume":"64 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141195596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Asymmetric interactions among cutting-edge technologies and pioneering conventional and Islamic cryptocurrencies: fresh evidence from intra-day-based good and bad volatilities 尖端技术与先锋传统货币和伊斯兰加密货币之间的不对称互动：基于日内好坏波动率的新证据

IF 8.4 1区经济学

Financial Innovation Pub Date : 2024-05-29 DOI: 10.1186/s40854-024-00623-5

Mahdi Ghaemi Asl, David Roubaud

{"title":"Asymmetric interactions among cutting-edge technologies and pioneering conventional and Islamic cryptocurrencies: fresh evidence from intra-day-based good and bad volatilities","authors":"Mahdi Ghaemi Asl, David Roubaud","doi":"10.1186/s40854-024-00623-5","DOIUrl":"https://doi.org/10.1186/s40854-024-00623-5","url":null,"abstract":"This study examines the nexus between the good and bad volatilities of three technological revolutions—financial technology (FinTech), the Internet of Things, and artificial intelligence and technology—as well as the two main conventional and Islamic cryptocurrency platforms, Bitcoin and Stellar, via three approaches: quantile cross-spectral coherence, quantile-VAR connectedness, and quantile-based non-linear causality-in-mean and variance analysis. The results are as follows: (1) under normal market conditions, in long-run horizons there is a significant positive cross-spectral relationship between FinTech's positive volatilities and Stellar’s negative volatilities; (2) Stellar’s negative and positive volatilities exhibit the highest net spillovers at the lower and upper tails, respectively; and (3) the quantile-based causality results indicate that Bitcoin’s good (bad) volatilities can lead to bad (good) volatilities in all three smart technologies operating between normal and bull market conditions. Moreover, the Bitcoin industry’s negative volatilities have a bilateral cause-and-effect relationship with FinTech’s positive volatilities. By analyzing the second moment, we found that Bitcoin's negative volatilities are the only cause variable that generates FinTech's good volatility in a unidirectional manner. As for Stellar, only bad volatilities have the potential to signal good volatilities for cutting-edge technologies in some middle quantiles, whereas good volatilities have no significant effect. Hence, the trade-off between Bitcoin and cutting-edge technologies, especially FinTech-related advancements, appear more broadly and randomly compared with the Stellar-innovative technologies nexus. The findings provide valuable insights for FinTech companies, blockchain developers, crypto-asset regulators, portfolio managers, and high-tech investors. ","PeriodicalId":37175,"journal":{"name":"Financial Innovation","volume":"47 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2024-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141169505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Stock price index analysis of four OPEC members: a Bayesian approach 欧佩克四个成员国的股票价格指数分析：贝叶斯方法

IF 8.4 1区经济学

Financial Innovation Pub Date : 2024-05-29 DOI: 10.1186/s40854-024-00651-1

Saman Hatamerad, Hossain Asgharpur, Bahram Adrangi, Jafar Haghighat

引用次数: 0

The implications of the ecological footprint and renewable energy usage on the financial stability of South Asian countries 生态足迹和可再生能源的使用对南亚国家金融稳定的影响

IF 8.4 1区经济学

Financial Innovation Pub Date : 2024-05-10 DOI: 10.1186/s40854-024-00627-1

Muhammad Imran, Muhammad Kamran Khan, Shabbir Alam, Salman Wahab, Muhammad Tufail, Zhang Jijian

{"title":"The implications of the ecological footprint and renewable energy usage on the financial stability of South Asian countries","authors":"Muhammad Imran, Muhammad Kamran Khan, Shabbir Alam, Salman Wahab, Muhammad Tufail, Zhang Jijian","doi":"10.1186/s40854-024-00627-1","DOIUrl":"https://doi.org/10.1186/s40854-024-00627-1","url":null,"abstract":"This study explores the complex relationships involving ecological footprints, energy use, carbon emissions, governance efficiency, economic prosperity, and financial stability in South Asian nations spanning the period from 2000 to 2022. Employing various methodologies such as cross-sectional dependence tests, co-integration analysis, and first- and second-generation unit-root tests, we use a panel Autoregressive Distributed Lag model, feasible generalized least squares, and Panel Corrected Standard Errors to ensure the robustness of our findings. We find noteworthy positive correlations between several variables, including heightened ecological consciousness, effective governance structures, increased GDP per capita, and amplified CO2 emissions. These relationships suggest potential pathways to strengthen the financial stability of the entire region; they also highlight the latent potential of embracing ecologically sustainable practices to fortify economic resilience. Our results also underscore the pivotal role of appropriate governance structures and higher income levels in bolstering financial stability in South Asian countries. Interestingly, we also find negative coefficients associated with the use of renewable energy, suggesting that escalating the adoption of renewable energy could create financial instability. This finding stresses the importance of diversification in energy strategies, cautioning policymakers to carefully consider the financial ramifications of potentially costly imports of renewable energy sources while seeking to reduce carbon emissions, emphasizing the need to strike a balance between ambitious sustainability goals and the pursuit of sustained economic robustness in the region. In considering the implications of these findings, it is crucial to consider each country’s broader socioeconomic context. Our results offer valuable insights for policymakers in developing renewable energy strategies.","PeriodicalId":37175,"journal":{"name":"Financial Innovation","volume":"1 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140932773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Connectedness of cryptocurrency markets to crude oil and gold: an analysis of the effect of COVID-19 pandemic 加密货币市场与原油和黄金的关联性：COVID-19 大流行的影响分析

IF 8.4 1区经济学

Financial Innovation Pub Date : 2024-05-08 DOI: 10.1186/s40854-023-00596-x

Parisa Foroutan, Salim Lahmiri

{"title":"Connectedness of cryptocurrency markets to crude oil and gold: an analysis of the effect of COVID-19 pandemic","authors":"Parisa Foroutan, Salim Lahmiri","doi":"10.1186/s40854-023-00596-x","DOIUrl":"https://doi.org/10.1186/s40854-023-00596-x","url":null,"abstract":"The notion that investors shift to gold during economic market crises remains unverified for many cryptocurrency markets. This paper investigates the connectedness between the 10 most traded cryptocurrencies and gold as well as crude oil markets pre-COVID-19 and during COVID-19. Through the application of various statistical techniques, including cointegration tests, vector autoregressive models, vector error correction models, autoregressive distributed lag models, and Granger causality analyses, we explore the relationship between these markets and assess the safe-haven properties of gold and crude oil for cryptocurrencies. Our findings reveal that during the COVID-19 pandemic, gold is a strong safe-haven for Bitcoin, Litecoin, and Monero while demonstrating a weaker safe-haven potential for Bitcoin Cash, EOS, Chainlink, and Cardano. In contrast, gold only exhibits a strong safe-haven characteristic before the pandemic for Litecoin and Monero. Additionally, Brent crude oil emerges as a strong safe-haven for Bitcoin during COVID-19, while West Texas Intermediate and Brent crude oils demonstrate weaker safe-haven properties for Ether, Bitcoin Cash, EOS, and Monero. Furthermore, the Granger causality analysis indicates that before the COVID-19 pandemic, the causal relationship predominantly flowed from gold and crude oil toward the cryptocurrency markets; however, during the COVID-19 period, the direction of causality shifted, with cryptocurrencies exerting influence on the gold and crude oil markets. These findings provide subtle implications for policymakers, hedge fund managers, and individual or institutional cryptocurrency investors. Our results highlight the need to adapt risk exposure strategies during financial turmoil, such as the crisis precipitated by the COVID-19 pandemic.","PeriodicalId":37175,"journal":{"name":"Financial Innovation","volume":"157 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140932614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An evaluation of the adequacy of Lévy and extreme value tail risk estimates 评估莱维和极值尾部风险估计值的适当性

IF 8.4 1区经济学

Financial Innovation Pub Date : 2024-05-03 DOI: 10.1186/s40854-024-00614-6

Sharif Mozumder, M. Kabir Hassan, M. Humayun Kabir

{"title":"An evaluation of the adequacy of Lévy and extreme value tail risk estimates","authors":"Sharif Mozumder, M. Kabir Hassan, M. Humayun Kabir","doi":"10.1186/s40854-024-00614-6","DOIUrl":"https://doi.org/10.1186/s40854-024-00614-6","url":null,"abstract":"This study investigates the simplicity and adequacy of tail-based risk measures—value-at-risk (VaR) and expected shortfall (ES)—when applied to tail targeting of the extreme value (EV) model. We implement Lévy–VaR and ES risk measures as full density-based alternatives to the generalized Pareto VaR and the generalized Pareto ES of the tail-targeting EV model. Using data on futures contracts of S&P500, FTSE100, DAX, Hang Seng, and Nikkei 225 during the Global Financial Crisis of 2007–2008, we find that the simplicity of tail-based risk management with a tail-targeting EV model is more attractive. However, the performance of EV risk estimates is not necessarily superior to that of full density-based relatively complex Lévy risk estimates, which may not always give us more robust VaR and ES results, making the model inadequate from a practical perspective. There is randomness in the estimation performances under both approaches for different data ranges and coverage levels. Such mixed results imply that banks, financial institutions, and policymakers should find a way to compromise or trade-off between “simplicity” and user-defined “adequacy”.","PeriodicalId":37175,"journal":{"name":"Financial Innovation","volume":"140 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140830626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The use of high-frequency data in cryptocurrency research: a meta-review of literature with bibliometric analysis 加密货币研究中高频数据的使用：文献元综述与文献计量分析

IF 8.4 1区经济学

Financial Innovation Pub Date : 2024-05-01 DOI: 10.1186/s40854-023-00595-y

Muhammad Anas, Syed Jawad Hussain Shahzad, Larisa Yarovaya

{"title":"The use of high-frequency data in cryptocurrency research: a meta-review of literature with bibliometric analysis","authors":"Muhammad Anas, Syed Jawad Hussain Shahzad, Larisa Yarovaya","doi":"10.1186/s40854-023-00595-y","DOIUrl":"https://doi.org/10.1186/s40854-023-00595-y","url":null,"abstract":"As the crypto-asset ecosystem matures, the use of high-frequency data has become increasingly common in decentralized finance literature. Using bibliometric analysis, we characterize the existing cryptocurrency literature that employs high-frequency data. We highlighted the most influential authors, articles, and journals based on 189 articles from the Scopus database from 2015 to 2022. This approach enables us to identify emerging trends and research hotspots with the aid of co-citation and cartographic analyses. It shows knowledge expansion through authors’ collaboration in cryptocurrency research with co-authorship analysis. We identify four major streams of research: (i) return prediction and measurement of cryptocurrency volatility, (ii) (in)efficiency of cryptocurrencies, (iii) price dynamics and bubbles in cryptocurrencies, and (iv) the diversification, safe haven, and hedging properties of Bitcoin. We conclude that highly traded cryptocurrencies’ investment features and economic outcomes are analyzed predominantly on a tick-by-tick basis. This study also provides recommendations for future studies.","PeriodicalId":37175,"journal":{"name":"Financial Innovation","volume":"39 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140830595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Forecasting relative returns for S&P 500 stocks using machine learning 利用机器学习预测标准普尔 500 指数股票的相对回报率

IF 8.4 1区经济学

Financial Innovation Pub Date : 2024-04-20 DOI: 10.1186/s40854-024-00644-0

Htet Htet Htun, Michael Biehl, Nicolai Petkov

{"title":"Forecasting relative returns for S&P 500 stocks using machine learning","authors":"Htet Htet Htun, Michael Biehl, Nicolai Petkov","doi":"10.1186/s40854-024-00644-0","DOIUrl":"https://doi.org/10.1186/s40854-024-00644-0","url":null,"abstract":"Forecasting changes in stock prices is extremely challenging given that numerous factors cause these prices to fluctuate. The random walk hypothesis and efficient market hypothesis essentially state that it is not possible to systematically, reliably predict future stock prices or forecast changes in the stock market overall. Nonetheless, machine learning (ML) techniques that use historical data have been applied to make such predictions. Previous studies focused on a small number of stocks and claimed success with limited statistical confidence. In this study, we construct feature vectors composed of multiple previous relative returns and apply the random forest (RF), support vector machine (SVM), and long short-term memory (LSTM) ML methods as classifiers to predict whether a stock can return 2% more than its index in the following 10 days. We apply this approach to all S&P 500 companies for the period 2017–2022. We assess performance using accuracy, precision, and recall and compare our results with a random choice strategy. We observe that the LSTM classifier outperforms RF and SVM, and the data-driven ML methods outperform the random choice classifier (p = 8.46e−17 for accuracy of LSTM). Thus, we demonstrate that the probability that the random walk and efficient market hypotheses hold in the considered context is negligibly small.","PeriodicalId":37175,"journal":{"name":"Financial Innovation","volume":"53 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140627681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A firm-specific Malmquist productivity index model for stochastic data envelopment analysis: an application to commercial banks 用于随机数据包络分析的公司特定马尔奎斯特生产力指数模型：商业银行应用

IF 8.4 1区经济学

Financial Innovation Pub Date : 2024-04-18 DOI: 10.1186/s40854-023-00583-2

Alireza Amirteimoori, Tofigh Allahviranloo, Maryam Nematizadeh

{"title":"A firm-specific Malmquist productivity index model for stochastic data envelopment analysis: an application to commercial banks","authors":"Alireza Amirteimoori, Tofigh Allahviranloo, Maryam Nematizadeh","doi":"10.1186/s40854-023-00583-2","DOIUrl":"https://doi.org/10.1186/s40854-023-00583-2","url":null,"abstract":"In the data envelopment analysis (DEA) literature, productivity change captured by the Malmquist productivity index, especially in terms of a deterministic environment and stochastic variability in inputs and outputs, has been somewhat ignored. Therefore, this study developed a firm-specific, DEA-based Malmquist index model to examine the efficiency and productivity change of banks in a stochastic environment. First, in order to estimate bank-specific efficiency, we employed a two-stage double bootstrap DEA procedure. Specifically, in the first stage, the technical efficiency scores of banks were calculated by the classic DEA model, while in the second stage, the double bootstrap DEA model was applied to determine the effect of the contextual variables on bank efficiency. Second, we applied a two-stage procedure for measuring productivity change in which the first stage included the estimation of stochastic technical efficiency and the second stage included the regression of the estimated efficiency scores on a set of explanatory variables that influence relative performance. Finally, an empirical investigation of the Iranian banking sector, consisting of 120 bank-year observations of 15 banks from 2014 to 2021, was performed to measure their efficiency and productivity change. Based on the findings, the explanatory variables (i.e., the nonperforming loan ratio and the number of branches) indicated an inverse relationship with stochastic technical efficiency and productivity change. The implication of the findings is that, in order to improve the efficiency and productivity of banks, it is important to optimize these factors.","PeriodicalId":37175,"journal":{"name":"Financial Innovation","volume":"6 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140612467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0