Financial Innovation最新文献_第6页

Modeling the link between environmental, social, and governance disclosures and scores: the case of publicly traded companies in the Borsa Istanbul Sustainability Index 模拟环境、社会和治理信息披露与得分之间的联系：伊斯坦布尔证券交易所可持续发展指数中的上市公司案例

IF 8.4 1区经济学

Financial Innovation Pub Date : 2024-02-28 DOI: 10.1186/s40854-024-00619-1

Mustafa Tevfik Kartal, Serpil Kılıç Depren, Ugur Korkut Pata, Dilvin Taşkın, Tuba Şavlı

{"title":"Modeling the link between environmental, social, and governance disclosures and scores: the case of publicly traded companies in the Borsa Istanbul Sustainability Index","authors":"Mustafa Tevfik Kartal, Serpil Kılıç Depren, Ugur Korkut Pata, Dilvin Taşkın, Tuba Şavlı","doi":"10.1186/s40854-024-00619-1","DOIUrl":"https://doi.org/10.1186/s40854-024-00619-1","url":null,"abstract":"This study constructs a proposed model to investigate the link between environmental, social, and governance (ESG) disclosures and ESG scores for publicly traded companies in the Borsa Istanbul Sustainability (XUSRD) index. In this context, this study considers 66 companies, examining recently structured ESG disclosures for 2022 that were published for the first time as novel data and applying a multilayer perceptron (MLP) artificial neural network algorithm. The relevant results are fourfold. (1) The MLP algorithm has explanatory power (i.e., R2) of 79% in estimating companies’ ESG scores. (2) Common, environment, social, and governance pillars have respective weights of 21.04%, 44.87%, 30.34%, and 3.74% in total ESG scores. (3) The absolute and relative significance of each ESG reporting principle for companies’ ESG scores varies. (4) According to absolute and relative significance, the most effective ESG principle is the common principle, followed by social and environmental principles, whereas governance principles have less significance. Overall, the results demonstrate that applying a linear approach to complete deficient ESG disclosures is inefficient for increasing companies’ ESG scores; instead, companies should focus on the ESG principles that have the highest relative significance. The findings of this study contribute to the literature by defining the most significant ESG principles for stimulating the ESG scores of companies in the XUSRD index.","PeriodicalId":37175,"journal":{"name":"Financial Innovation","volume":"102 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140008518","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 volatility mechanism and intelligent fusion forecast of new energy stock prices 新能源股票价格的波动机制与智能融合预测

IF 8.4 1区经济学

Financial Innovation Pub Date : 2024-02-22 DOI: 10.1186/s40854-024-00621-7

Guo-Feng Fan, Ruo-Tong Zhang, Cen-Cen Cao, Li-Ling Peng, Yi-Hsuan Yeh, Wei-Chiang Hong

{"title":"The volatility mechanism and intelligent fusion forecast of new energy stock prices","authors":"Guo-Feng Fan, Ruo-Tong Zhang, Cen-Cen Cao, Li-Ling Peng, Yi-Hsuan Yeh, Wei-Chiang Hong","doi":"10.1186/s40854-024-00621-7","DOIUrl":"https://doi.org/10.1186/s40854-024-00621-7","url":null,"abstract":"The new energy industry is strongly supported by the state, and accurate forecasting of stock price can lead to better understanding of its development. However, factors such as cost and ease of use of new energy, as well as economic situation and policy environment, have led to continuous changes in its stock price and increased stock price volatility. By calculating the Lyapunov index and observing the Poincaré surface of the section, we find that the sample of the China Securities Index Green Power 50 Index has chaotic characteristics, and the data indicate strong volatility and uncertainty. This study proposes a new method of stock price index prediction, namely, EWT-S-ALOSVR. Empirical wavelet decomposition extracts features from multiple factors affecting stock prices to form multiple sub-columns with features, significantly reducing the complexity of the stock price series. Support vector regression is well suited for dealing with nonlinear stock price series, and the support vector machine model parameters are selected using random wandering and picking elites via Ant Lion Optimization, making stock price prediction more accurate.","PeriodicalId":37175,"journal":{"name":"Financial Innovation","volume":"22 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139927604","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

Drawdown-based risk indicators for high-frequency financial volumes 基于缩编的高频金融交易量风险指标

IF 8.4 1区经济学

Financial Innovation Pub Date : 2024-02-22 DOI: 10.1186/s40854-023-00593-0

Guglielmo D’Amico, Bice Di Basilio, Filippo Petroni

引用次数: 0

User acceptance of social network-backed cryptocurrency: a unified theory of acceptance and use of technology (UTAUT)-based analysis 用户对社交网络支持的加密货币的接受程度：基于技术接受和使用统一理论（UTAUT）的分析

IF 8.4 1区经济学

Financial Innovation Pub Date : 2024-02-21 DOI: 10.1186/s40854-023-00511-4

Márk Recskó, Márta Aranyossy

{"title":"User acceptance of social network-backed cryptocurrency: a unified theory of acceptance and use of technology (UTAUT)-based analysis","authors":"Márk Recskó, Márta Aranyossy","doi":"10.1186/s40854-023-00511-4","DOIUrl":"https://doi.org/10.1186/s40854-023-00511-4","url":null,"abstract":"Turbulent market conditions, well-publicized advantages, and potential individual, social, and environmental risks make blockchain-based cryptocurrencies a popular focus of the public and scientific communities. This paper contributes to the literature on the future of crypto markets by analyzing a promising cryptocurrency innovation from a customer-centric point of view; it explores the factors influencing user acceptance of a hypothetical social network-backed cryptocurrency in Central Europe. The research model adapts an internationally comparative framework and extends the well-established unified theory of acceptance and use of the technology model with the concept of perceived risk and trust. We explore user attitudes with a survey on a large Hungarian sample and analyze the database with consistent partial least square structural equation modeling methodology. The results show that users would be primarily influenced by the expected usefulness of the new technology assuming it is easy to use. Furthermore, our analysis also highlights that while social influence does not seem to sway user opinions, consumers are susceptible to technological risks, and trust is an important determinant of their openness toward innovations in financial services. We contribute to the cryptocurrency literature with a future-centric technological focus and provide new evidence from an under-researched geographic region. The results also have practical implications for business decision-makers and policymakers.","PeriodicalId":37175,"journal":{"name":"Financial Innovation","volume":"210 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139927586","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

Volatility spillovers among leading cryptocurrencies and US energy and technology companies 主要加密货币与美国能源和技术公司之间的波动溢出效应

IF 8.4 1区经济学

Financial Innovation Pub Date : 2024-02-20 DOI: 10.1186/s40854-024-00626-2

Amro Saleem Alamaren, Korhan K. Gokmenoglu, Nigar Taspinar

{"title":"Volatility spillovers among leading cryptocurrencies and US energy and technology companies","authors":"Amro Saleem Alamaren, Korhan K. Gokmenoglu, Nigar Taspinar","doi":"10.1186/s40854-024-00626-2","DOIUrl":"https://doi.org/10.1186/s40854-024-00626-2","url":null,"abstract":"This study investigates volatility spillovers and network connectedness among four cryptocurrencies (Bitcoin, Ethereum, Tether, and BNB coin), four energy companies (Exxon Mobil, Chevron, ConocoPhillips, and Nextera Energy), and four mega-technology companies (Apple, Microsoft, Alphabet, and Amazon) in the US. We analyze data for the period November 15, 2017–October 28, 2022 using methodologies in Diebold and Yilmaz (Int J Forecast 28(1):57–66, 2012) and Baruník and Křehlík (J Financ Economet 16(2):271–296 2018). Our analysis shows the COVID-19 pandemic amplified volatility spillovers, thereby intensifying the impact of financial contagion between markets. This finding indicates the impact of the pandemic on the US economy heightened risk transmission across markets. Moreover, we show that Bitcoin, Ethereum, Chevron, ConocoPhilips, Apple, and Microsoft are net volatility transmitters, while Tether, BNB, Exxon Mobil, Nextera Energy, Alphabet, and Amazon are net receivers Our results suggest that short-term volatility spillovers outweigh medium- and long-term spillovers, and that investors should be more concerned about short-term repercussions because they do not have enough time to act quickly to protect themselves from market risks when the US market is affected. Furthermore, in contrast to short-term dynamics, longer term patterns display superior hedging efficiency. The net-pairwise directional spillovers show that Alphabet and Amazon are the highest shock transmitters to other companies. The findings in this study have implications for both investors and policymakers.","PeriodicalId":37175,"journal":{"name":"Financial Innovation","volume":"278 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2024-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139927838","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

Detecting DeFi securities violations from token smart contract code 从代币智能合约代码中检测 DeFi 证券违规行为

IF 8.4 1区经济学

Financial Innovation Pub Date : 2024-02-20 DOI: 10.1186/s40854-023-00572-5

Arianna Trozze, Bennett Kleinberg, Toby Davies

{"title":"Detecting DeFi securities violations from token smart contract code","authors":"Arianna Trozze, Bennett Kleinberg, Toby Davies","doi":"10.1186/s40854-023-00572-5","DOIUrl":"https://doi.org/10.1186/s40854-023-00572-5","url":null,"abstract":"Decentralized Finance (DeFi) is a system of financial products and services built and delivered through smart contracts on various blockchains. In recent years, DeFi has gained popularity and market capitalization. However, it has also been connected to crime, particularly various types of securities violations. The lack of Know Your Customer requirements in DeFi poses challenges for governments trying to mitigate potential offenses. This study aims to determine whether this problem is suited to a machine learning approach, namely, whether we can identify DeFi projects potentially engaging in securities violations based on their tokens’ smart contract code. We adapted prior works on detecting specific types of securities violations across Ethereum by building classifiers based on features extracted from DeFi projects’ tokens’ smart contract code (specifically, opcode-based features). Our final model was a random forest model that achieved an 80% F-1 score against a baseline of 50%. Notably, we further explored the code-based features that are the most important to our model’s performance in more detail by analyzing tokens’ Solidity code and conducting cosine similarity analyses. We found that one element of the code that our opcode-based features can capture is the implementation of the SafeMath library, although this does not account for the entirety of our features. Another contribution of our study is a new dataset, comprising (a) a verified ground truth dataset for tokens involved in securities violations and (b) a set of legitimate tokens from a reputable DeFi aggregator. This paper further discusses the potential use of a model like ours by prosecutors in enforcement efforts and connects it to a wider legal context.","PeriodicalId":37175,"journal":{"name":"Financial Innovation","volume":"29 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2024-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139927762","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

Evaluating short- and long-term investment strategies: development and validation of the investment strategies scale (ISS) 评估短期和长期投资战略：制定和验证投资战略量表（ISS）

IF 8.4 1区经济学

Financial Innovation Pub Date : 2024-02-19 DOI: 10.1186/s40854-023-00573-4

Ibrahim Arpaci, Omer Aslan, Mustafa Kevser

{"title":"Evaluating short- and long-term investment strategies: development and validation of the investment strategies scale (ISS)","authors":"Ibrahim Arpaci, Omer Aslan, Mustafa Kevser","doi":"10.1186/s40854-023-00573-4","DOIUrl":"https://doi.org/10.1186/s40854-023-00573-4","url":null,"abstract":"In response to the growing importance of understanding individual investment strategies, the present study aimed to develop a new scale for measuring both the short- and long-term investment strategies of individuals. The study assessed the psychometric properties of the investment strategies scale (ISS) using data collected from 1428 individual investors. In the initial study, an exploratory factor analysis (EFA) was conducted to investigate the factor structure of the proposed scale (N = 700). The EFA results yielded a two-factor structure, and Cronbach’s alpha values for short- and long-term investment strategies were 0.90 and 0.88, respectively. A confirmatory factor analysis was performed to validate the factor structure of the scale in the second study (N = 728). The results demonstrated that the two-factor model fit the data well. In the third study, the correlation between Hofstede’s long-term orientation and the two dimensions of the scale was investigated. The results indicated that long-term investment strategies significantly predict long-term orientation, thus confirming the concurrent validity of the scale. These findings demonstrate that the proposed ISS is a reliable and valid instrument for measuring individuals’ short- and long-term investment strategies, contributing to a deeper understanding of investment decision-making processes. This study introduces a novel measurement tool—ISS—specifically designed to comprehensively assess both short- and long-term investment strategies among individual investors.","PeriodicalId":37175,"journal":{"name":"Financial Innovation","volume":"30 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139927603","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

Features of different asset types and extreme risk transmission during the COVID-19 crisis COVID-19 危机期间不同资产类型和极端风险传播的特点

IF 8.4 1区经济学

Financial Innovation Pub Date : 2024-02-17 DOI: 10.1186/s40854-023-00510-5

I-Chun Tsai

{"title":"Features of different asset types and extreme risk transmission during the COVID-19 crisis","authors":"I-Chun Tsai","doi":"10.1186/s40854-023-00510-5","DOIUrl":"https://doi.org/10.1186/s40854-023-00510-5","url":null,"abstract":"Unlike the current extensive literature, which discusses which assets can avoid the risks caused by the COVID-19 pandemic, this study examines whether the characteristics of different assets affect the extreme risk transmission of the COVID-19 crisis. This study explores the effects of COVID-19 pandemic–related risk factors (i.e., pandemic severity, pandemic regulations and policies, and vaccination-related variables) on the risk of extreme volatility in asset returns across eight assets. These eight assets belong to the following classes: virtual, financial, energy, commodities, and real assets. To consider the different possible aspects of the COVID-19 impact, this study adopts both empirical methods separately, considering variables related to the pandemic as exogenous shocks and endogenous factors. Using these methods, this study enabled a systematic analysis of the relationship between the features of different asset types and the effects of extreme risk transmission during the COVID-19 crisis. The results show that different types of asset markets are affected by different risk factors. Virtual and commodity assets do not exhibit extreme volatility induced by the COVID-19 pandemic. The energy market, including crude oil, is most affected by the negative impact of the severity of the pandemic, which is unfavorable for investment at the beginning of the pandemic. However, after vaccinations and pandemic regulations controlled the spread of infection, the recovery of the energy market made it more conducive to investment. In addition, this study explains the differences between the hedging characteristics of Bitcoin and gold. The findings of this study can help investors choose asset types systematically when faced with different shocks.","PeriodicalId":37175,"journal":{"name":"Financial Innovation","volume":"117 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2024-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139772375","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 simplified model for measuring longevity risk for life insurance products 衡量人寿保险产品长寿风险的简化模型

IF 8.4 1区经济学

Financial Innovation Pub Date : 2024-02-16 DOI: 10.1186/s40854-023-00515-0

David Atance, Eliseo Navarro

引用次数: 0

Pattern recognition of financial innovation life cycle for renewable energy investments with integer code series and multiple technology S-curves based on Q-ROF DEMATEL 基于 Q-ROF DEMATEL 的整数代码序列和多技术 S 曲线的可再生能源投资金融创新生命周期模式识别

IF 8.4 1区经济学

Financial Innovation Pub Date : 2024-02-08 DOI: 10.1186/s40854-024-00616-4

Gang Kou, Hasan Dinçer, Serhat Yüksel

{"title":"Pattern recognition of financial innovation life cycle for renewable energy investments with integer code series and multiple technology S-curves based on Q-ROF DEMATEL","authors":"Gang Kou, Hasan Dinçer, Serhat Yüksel","doi":"10.1186/s40854-024-00616-4","DOIUrl":"https://doi.org/10.1186/s40854-024-00616-4","url":null,"abstract":"The current study evaluates the financial innovation life cycle for renewable energy investments. A novel model is proposed that has two stages. First, the financial innovation life cycle is weighted by the two-generation technology S-curve (TTSC) for renewable energy investments. Second, the TTSC is ranked with integer patterns for renewable energy investments. For this purpose, the decision-making trial and evaluation laboratory (DEMATEL) is considered with q-rung orthopair fuzzy sets (q-ROFSs). A comparative examination is then performed using intuitionistic and Pythagorean fuzzy sets, and we find similar results for all fuzzy sets. Hence, the suggested model is reliable and coherent. Maturity phase 1 is the most significant phase of the financial innovation life cycle for these projects. Aging is the most important period for financial innovation in renewable energy investment projects—renewable energy companies should make strategic decisions after that point. In this situation, decisions should relate to either radical or incremental innovation. If companies do not make decisions during these phases, innovative financial products cannot be improved. As a result, renewable energy companies will not prefer financing products.","PeriodicalId":37175,"journal":{"name":"Financial Innovation","volume":"16 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139772241","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