Borsa Istanbul Review最新文献_第4页

The good, the better and the challenging: Insights into predicting high-growth firms using machine learning

IF 6.3 2区经济学

Borsa Istanbul Review Pub Date : 2024-12-01 DOI: 10.1016/j.bir.2024.12.001

Sermet Pekin, Aykut Şengül

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引用次数: 0

Stock price prediction using the Sand Cat Swarm Optimization and an improved deep Long Short Term Memory network

IF 6.3 2区经济学

Borsa Istanbul Review Pub Date : 2024-12-01 DOI: 10.1016/j.bir.2024.12.002

Burak Gülmez

引用次数: 0

More than just sentiment: Using social, cognitive, and behavioral information of social media to predict stock markets with artificial intelligence and big data

IF 6.3 2区经济学

Borsa Istanbul Review Pub Date : 2024-12-01 DOI: 10.1016/j.bir.2024.12.003

Yunus Emre Akdogan , Adem Anbar

{"title":"More than just sentiment: Using social, cognitive, and behavioral information of social media to predict stock markets with artificial intelligence and big data","authors":"Yunus Emre Akdogan , Adem Anbar","doi":"10.1016/j.bir.2024.12.003","DOIUrl":"10.1016/j.bir.2024.12.003","url":null,"abstract":"<div><div>Digital transformation offers unprecedented opportunities to access data on hard-to-measure social aspects. In this digital era, social media platforms have become critical data sources for the social sciences. This study moves beyond traditional finance assumptions of “perfect information,” “rational humans,” and “isolated individuals” by analyzing retail investor behavior using Twitter data. It adopts a human model characterized by incomplete information, bounded rationality, and the influence of social and emotional factors. Tweets shared between January 1, 2012, and February 28, 2020, were collected. A GRU-based context classifier achieved 98% accuracy in identifying tweets related to Borsa Istanbul (BIST). Sentiment classification using a BERT model achieved 91% accuracy for positive and negative classes. Relationships between Twitter-obtained features and BIST indices were analyzed using machine learning methods such as linear regression, Lasso regression, random forest, and XGBoost. The analysis revealed that 91% of the change in the opening value, 63% of the change in trading volume, and 67% in volatility of the BIST 100 index could be attributed to cognitive, behavioral, and social features gleaned from tweets.</div></div>","PeriodicalId":46690,"journal":{"name":"Borsa Istanbul Review","volume":"24 ","pages":"Pages 61-82"},"PeriodicalIF":6.3,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143347781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Beyond polarity: How ESG sentiment influences idiosyncratic volatility in the Turkish stock market

IF 6.3 2区经济学

Borsa Istanbul Review Pub Date : 2024-12-01 DOI: 10.1016/j.bir.2024.11.003

Alev Atak

{"title":"Beyond polarity: How ESG sentiment influences idiosyncratic volatility in the Turkish stock market","authors":"Alev Atak","doi":"10.1016/j.bir.2024.11.003","DOIUrl":"10.1016/j.bir.2024.11.003","url":null,"abstract":"<div><div>This study investigates the influence of Environmental, Social, and Governance (ESG) sentiment in corporate disclosures on idiosyncratic volatility (IVOL) in the Turkish stock market. Using FinBERT-ESG, a language model specifically designed for financial and ESG-related texts, we construct four novel indices: the Positive ESG Index (PESGIN), capturing positive ESG sentiment; the Negative ESG Index (NESGIN), representing adverse ESG sentiment; the Balanced Polarity Index (BPI), measuring the overall balance between positive and negative sentiment; and the Amplified Negative Polarity Index (ANPI), which emphasizes the intensity of negative sentiment. By employing a system-GMM approach, which effectively addresses endogeneity concerns common in finance, we find that PESGI is negatively associated with IVOL, suggesting that transparent and optimistic ESG communication reduces firm-specific risk. Conversely, ANPI positively correlates with IVOL, supporting the overreaction hypothesis and highlighting elevated investor sensitivity to adverse ESG disclosures. These findings underscore the complex interplay between ESG sentiment and investor behaviour, offering valuable insights for enhancing risk assessment and guiding investment strategies.</div></div>","PeriodicalId":46690,"journal":{"name":"Borsa Istanbul Review","volume":"24 ","pages":"Pages 10-21"},"PeriodicalIF":6.3,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143347782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Powering perception, echoing green voices: The interplay of Cryptocurrency's energy footprint and environmental discourse in steering the direction of the market

IF 6.3 2区经济学

Borsa Istanbul Review Pub Date : 2024-12-01 DOI: 10.1016/j.bir.2024.12.020

Iheb Ghazouani, Ines Ghazouani, Abdelwahed Omri

{"title":"Powering perception, echoing green voices: The interplay of Cryptocurrency's energy footprint and environmental discourse in steering the direction of the market","authors":"Iheb Ghazouani, Ines Ghazouani, Abdelwahed Omri","doi":"10.1016/j.bir.2024.12.020","DOIUrl":"10.1016/j.bir.2024.12.020","url":null,"abstract":"<div><div>This study examines the influence of cryptocurrency's environmental footprint on market behavior through an analysis of 66,582 Reddit posts about Bitcoin and 23,231 about Ethereum. Using a vector autoregression (VAR) model, it explores the relationship between social media discussions on environmental issues, electricity use, and cryptocurrencies' market dynamics. We find a negative correlation between environmental discussions and Bitcoin volatility. Moreover, real electricity use has a more pronounced impact than social media discussions on both Bitcoin and Ethereum volatility. This indicates that crypto market investors prioritize real-world indicators over information from social media discussions. The study also reveals a bidirectional relationship between Bitcoin volatility and environmental posts, highlighting the complex interplay between market behavior and public discourse on environmental matters in the cryptocurrency domain. These results suggest the need for policies that limit energy consumption due to mining, promote renewable energy, and enhance investor education on environmental impacts to support sustainable practices in the cryptocurrency market.</div></div>","PeriodicalId":46690,"journal":{"name":"Borsa Istanbul Review","volume":"24 ","pages":"Pages 91-101"},"PeriodicalIF":6.3,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143347785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Digital technology development and systemic financial risks: Evidence from 22 countries 数字技术发展与系统性金融风险：来自 22 个国家的证据

IF 6.3 2区经济学

Borsa Istanbul Review Pub Date : 2024-12-01 DOI: 10.1016/j.bir.2024.08.002

Xu Haoran, Miao Wenlong, Zhang Siyu

引用次数: 0

Gauging the dynamic interlinkage among robotics, artificial intelligence, and green crypto investment: A quantile VAR approach

IF 6.3 2区经济学

Borsa Istanbul Review Pub Date : 2024-12-01 DOI: 10.1016/j.bir.2024.11.006

Le Thanh Ha

{"title":"Gauging the dynamic interlinkage among robotics, artificial intelligence, and green crypto investment: A quantile VAR approach","authors":"Le Thanh Ha","doi":"10.1016/j.bir.2024.11.006","DOIUrl":"10.1016/j.bir.2024.11.006","url":null,"abstract":"<div><div>A large amount of new green crypto investment is required to achieve the United Nations’ sustainable development goals. The development and application of artificial intelligence (AI) are essential for attracting this investment because it has the potential to increase the adoption of environmental innovation and individual environmental awareness. In our research, we use a DCC-GARCH copula model to examine time-varying spillover effects and demonstrate interconnections between the development of AI and green cryptocurrencies from January 1, 2018, to September 8, 2023. Our results show that when we consider the full data sample, the variables studied all have only weak connections. These results clearly demonstrate temporal variance in systemic connection caused by the COVID-19 pandemic, the Russia-Ukraine war, and bank failures. Robotics & AI ETF (BOTZ) is a net recipient of shocks across quantiles throughout the study, according to the total net directional connectivity across quantiles. Pairwise directional connectivity in an evolving net indicates that BOTZ consistently appears to be dominated by green cryptocurrencies in both the short and long term. Understanding the primary sources of spillovers between AI and green cryptocurrencies can help policymakers design the most effective strategies for mitigating these vulnerabilities and reducing market risk.</div></div>","PeriodicalId":46690,"journal":{"name":"Borsa Istanbul Review","volume":"24 ","pages":"Pages 22-31"},"PeriodicalIF":6.3,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143347783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Classification of the optimal rebalancing frequency for pairs trading using machine learning techniques

IF 6.3 2区经济学

Borsa Istanbul Review Pub Date : 2024-12-01 DOI: 10.1016/j.bir.2024.12.004

Mahmut Bağcı, Pınar Kaya Soylu

引用次数: 0

Do firms increase ESG activities during periods of geopolitical risk? Evidence from Korean business groups 在地缘政治风险时期，企业是否会增加 ESG 活动？来自韩国企业集团的证据

IF 6.3 2区经济学

Borsa Istanbul Review Pub Date : 2024-11-01 DOI: 10.1016/j.bir.2024.11.002

Hongmin Chun , Boyoung Moon

引用次数: 0

Oil shocks and the transmission of higher-moment information in US industry: Evidence from an asymmetric puzzle 石油冲击与美国工业中高时刻信息的传播：来自不对称难题的证据