The Different View of Weather Anomalies on BIST100
Küçük Resim Yok
Tarih
2024
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer Nature
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
The main purpose of this paper is to determine the effects of different weather conditions on human behavior and decision-making processes in the financial markets. Weather and BIST100 data starting from January 1988 to December 2017 in Turkey are considered. The study covers the longest time period used so far for Turkey. Firstly, apparent temperature values are calculated by using the NWS heat index and wind chill, and the effect of apparent temperature values on returns and trading volume is also investigated. In addition, Kawamura's discomfort index was calculated and the differences in closing prices and trading volume at different comfort levels were also examined. The results show both positive and negative correlations among apparent temperature and trading volume and returns. In the last part of the study, time series analyses are carried out, and financial returns and trade volumes in BIST100 are comparatively analyzed by using seven different time series analysis methods. Our findings indicate that the most successful method is the ANN (Artificial Neural Network) method, which is an artificial intelligence method. In addition, analysis performed with VAR and VECM presented findings indicating the existence of relationships between weather and BIST100. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
Açıklama
Anahtar Kelimeler
ANN, Behavioral finance, Heat index, Kawamura’s discomfort index, Weather anomalies, Wind chill index
Kaynak
Accounting, Finance, Sustainability, Governance and Fraud
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
Part F2403
