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- Author: James Douglas Hamilton
- Title: Time Series Analysis
- Amazon Link: https://www.amazon.com/dp/0691042896/?tag=pfamazon01-20
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Time series analysis is a statistical method used to analyze and understand data that is collected over a period of time. It involves studying patterns and trends in the data to make predictions and identify relationships between variables.
Robert F. Engle is an American economist and statistician who won the Nobel Prize in Economics in 2003 for his work on time series analysis, specifically for developing the Autoregressive Conditional Heteroskedasticity (ARCH) model.
The Autoregressive Conditional Heteroskedasticity (ARCH) model is a statistical model used in time series analysis to describe the variability in a time series based on its own previous values. It is commonly used to model financial data and is the basis for many other models, such as the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model.
Time series analysis has a wide range of applications in various fields, including economics, finance, weather forecasting, and signal processing. Some specific examples include predicting stock market trends, forecasting sales data, and analyzing climate data to understand long-term patterns and changes.
The book "Time Series Analysis" by James D. Hamilton is a comprehensive guide to time series analysis, covering topics such as basic time series models, forecasting methods, and multivariate time series analysis. It is a widely used reference for students and researchers in the field of time series analysis.