Title Details: | |
Classic and Contemporary Time Series Models Volume A' |
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Other Titles: |
Applications to Greek Financial Data |
Authors: |
Anagnostou, Angeliki |
Subject: | LAW AND SOCIAL SCIENCES > ECONOMIC SCIENCES > MATHEMATICAL AND QUANTITATIVE METHODS LAW AND SOCIAL SCIENCES > ECONOMIC SCIENCES > MATHEMATICAL AND QUANTITATIVE METHODS > ECONOMETRIC AND STATISTICAL METHODS AND METHODOLOGY: GENERAL LAW AND SOCIAL SCIENCES > ECONOMIC SCIENCES > MATHEMATICAL AND QUANTITATIVE METHODS > ECONOMETRIC MODELING |
Keywords: |
Time series models
Applications in econometrics Greek economy Econometric models Time series econometric models and applications to financial data Time series analysis |
Description: | |
Abstract: |
In recent decades, several classes of non-linear time series models have appeared in the literature; namely, bilinear time series models, threshold AR models, exponential AR models, random coefficient AR models, Smooth Transition Regression Model, (STAR models), exponential moving average models, Neural Networks model, Genetic Algorithm Models, and other related models. (A detailed analysis of these models will be provided in the following chapters.) Each of these models was developed to identify and capture behaviors that are not detected by linear models. The potential of this book is to model and predict economic data using different nonlinear and chaotic processes. Therefore, in this book, we will examine various nonlinear time series model models, as well as their properties, and attempt to fit them to data and produce forecasts. We will also review a number of nonlinearity tests developed by various authors. The purpose of this paper is to present the Classical & Contemporary Time Series Models, which are used in the forecasting of economic and financial variables.
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Linguistic Editors: |
Kalogera, Maria |
Graphic Editors: |
Kalogera, Andriani |
Type: |
Undergraduate textbook |
Creation Date: | 28-01-2024 |
Item Details: | |
ISBN |
978-618-228-086-7 |
License: |
Attribution - NonCommercial - ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
DOI | http://dx.doi.org/10.57713/kallipos-319 |
Handle | http://hdl.handle.net/11419/10456 |
Bibliographic Reference: | Anagnostou, A. (2024). Classic and Contemporary Time Series Models Volume A' [Undergraduate textbook]. Kallipos, Open Academic Editions. https://dx.doi.org/10.57713/kallipos-319 |
Language: |
Greek |
Consists of: |
1. Regression Analysis - Overview 2. Violation of the Classic Assumptions of Linear Regression 3. Introduction to Time Series Analysis 4. Linear Models of Stochastic Processes 5. Historical Overview of Modeling and Forecasting Financial Time Series 6. Non-Linear Models of the Conditional Variance 7. Non-Linear Models of the Conditional Mean 8. Tests for Non-Linearities 9. Artificial Neural Networks 10. Forecasting with Non-Linear Time Series Models 11. Chaos and Forecasting of Time Series Data 12. Multivariable Models of Time Series Data 13. Analysis and Modelling of Panel Data 14. Guidelines for the Conduct and Writing of a Scientific Paper 15. EViews Program Software Instructions |
Number of pages |
478 |
Publication Origin: |
Kallipos, Open Academic Editions |
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