Akademik Veri Yönetim Sistemi
The 25th Annual Conference on Finance and Accounting, Praha, Çek Cumhuriyeti, 30 - 31 Mayıs 2024
This research investigates the intraday dynamics of BIST100 and focuses on the interaction between comprehensive volatility, liquidity and transitions. The study uses Markov-Switching Generalized Autoregressive Conditional Heteroscedasticity (MS GARCH) models to capture natural volatility switching utilizing a dataset comprising 6,691 hourly observations spanning the period from October 23, 2020, to October 23, 2023. Additionally, wavelet analysis is used to investigate the temporal evolution of both market liquidity and returns at multiple frequency scales. Using MS GARCH models allows for a nuanced understanding of how volatility situations break down throughout the day of trading and provides valuable insight into risk management and decision making. Additionally, the inclusion of wavelet analysis allows for the case of simultaneous accelerations between liquidity and transitions at different time scales. This multi-solution approach provides a comprehensive view of BIST100 dynamics, revealing potential patterns and relationships that may be obscured by traditional time series analyses.