Modeling the Stock Price Volatility
Using Asymmetry GARCH and Ann-Asymmetry GARCH Models
- 92 pages
- 4 hours of reading
The book explores the critical role of time series data modeling in a dynamic environment, emphasizing the integration of machine learning techniques within statistics. It highlights the use of Artificial Neural Networks, which can replicate human adaptability, in modeling both linear and non-linear time series data. A significant focus is placed on their application in economics, particularly in understanding and predicting Stock Price Volatility, showcasing the intersection of advanced statistical methods and financial analysis.
