matlab的GARCH工具箱-经管之家官网！

免费学术公开课,扫码加入

一共260页 PDF文档 超清晰

包括 introduction, garch overview,simulation,estimation,forcasting,regression components in conditional mean models and so on

有问题的话可以随时提问

1
What is the GARCH Toolbox? . . . .. . . . . . . . . 1-2
GARCH Overview . . . . . . . . . . . .. . . . . . . . . . . . 1-3
What is GARCH? . . . . . . . . . . . . . . . . . . . . . . . 1-3
Why Use GARCH? . . . . . . . . . . . . . . . . . . . . . . 1-3
GARCH Limitations . . . . . . . . . . . . . . . . . . . . 1-4
Software Requirements and Compatibility . . . . . . . . . . . . . . 1-5
Expected Background . . . . . . . . . . . . . . . . . . . . 1-6
Technical Conventions . . . . . . .. . . . . . . . . . . . . . 1-7
Data Sets . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . 1-11
DEM2GBP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-11
NASDAQ . . . . . . . . . . . .. . . . . . . . . . . . . . . 1-12
NYSE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
GARCH Overview
Modeling of Financial Time Series . . . . . . . . . . . . . . . . 2-2
Characteristics of Financial Time Series . . . . . . . . . . . . . . . . . . 2-2
Correlation and Forecasting of Financial Time Series . . . . . . . 2-4
Serial Dependence in Innovations . . . . . . . . . . . . . . . . . . . . . . . 2-4
Conditional Mean and Variance Models . . . . . . . . . . . . . . . . . 2-6
Conditional Mean Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-6
Conditional Variance Models . . . . . . . . . . . . . . . . 2-6
Comments on the Models . . . . . . . . . . . .. . . . . . . . . 2-9
The Default Model . . . . . . . . . . . . . . . . . . 2-12
Primary Toolbox Functions . . . . . .. . . . . 2-13
Analysis and Estimation Example Using the
Default Model . . . . . . . . . . . . . . . . . . . . . . . 2-15
Preestimation Analysis . . . . . . . . .. . . . . 2-15
Parameter Estimation . . . . . . . . . . . . . . . . . 2-23
Postestimation Analysis . . . . . . . . . . . . . . 2-26
3
GARCH Specification Structure
Introduction . . . . . . . . . . . . . . . . . . . . . . . 3-2
Equation Variables and Parameter Names . . . . . . . . . . . . . . 3-4
Conditional Mean Model . . . . . . . . . . . . . . . . . . 3-4
Conditional Variance Models . . . . . . . . . . . . . 3-4
Examples of Specification Structures . . . . . . . . . . . . . 3-5
Reading and Writing Specification Structures . . . . . . . . . . . 3-8
Creating and Modifying a Specification Structure . . . . . . . . . . . 3-8
Retrieving Specification Structure Values . . . . . . . . . . . . . . . . 3-11
4
Simulation
Simulating Sample Paths . . . . . . . . . . . . 4-2
Introduction . . . . . . . . . . . . . . . . . . . . . . . 4-2
Simulating a Single Path . . . . . . . . . . . . 4-3
Simulating Multiple Paths . . . . . . . . . . . 4-4
Presample Data . . . . . . . . . . . . . . . . . . . 4-6
Automatically Generated Presample Data . . . . . . . . . . . . . . . . . 4-6
User-Specified Presample Data . . . . . . 4-10
5
Estimation
Maximum Likelihood Estimation . . . . . . . 5-2
Initial Parameter Estimates . . . . .. . . . . 5-4
User-Specified Initial Estimates . . . . . . . 5-4
Automatically Generated Initial Estimates . .. . . . 5-5
Parameter Bounds . . . . . . . . . . . . . . . . . . . 5-9
Presample Observations . . . . . . . . . 5-11
User-Specified Presample Observations . . . . . . . . . . 5-11
Automatically Generated Presample Observations . . . . .. . . 5-11
Termination Criteria and Optimization Results . . . . . . . . . 5-13
MaxIter and MaxFunEvals . . . . . . . . . . . . . 5-13
TolCon, TolFun, and TolX . . . . . . . . . . . . . . 5-14
Convergence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-14
Optimization Results . . . . . . . . . . . .. . . . . . 5-15
Constraint Violation Tolerance . . . . . . . . . . . . . . . . . . . . . . . . . 5-16
Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-19
Specifying Presample Data . . . . . . . . . .. . . . . 5-19
Presample Data and Transient Effects . . . . . . . . . 5-23
Alternative Technique for Estimating ARMA(R,M)
Parameters . . . . . . . . . . . . . . . . . . . . . 5-27
Active Lower Bound Constraint . . . . . . .. . . . . 5-28
Determining Convergence Status . . . . . .. . . . . . 5-316
Minimum Mean Square Error Forecasting . . . . . .. . . . 6-2
Conditional Standard Deviations of Future Innovations . . . . . 6-2
Conditional Mean Forecasts of the Return Series . . . . . . . . . . . 6-3
MMSE Volatility Forecasts of Returns . . . . . . . . . . . . . . . . . . . . 6-3
RMSE Associated with Conditional Mean Forecasts . . . . . . . . . 6-4
Presample Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-5
Asymptotic Behavior for Long-Range Forecast Horizons . 6-6
Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-8
Computing a Forecast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-8
Volatility Forecasts over Multiple Periods . . . . . . . . . . . . . . . . 6-11
Computing a Forecast with Multiple Realizations . . . . . . . . . 6-13
7
Regression Components in Conditional
Mean Models
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-2
Incorporating a Regression Model in an Estimation . . . . . . 7-3
Fitting a Model to a Simulated Return Series . . . . . . . . . . . . . . 7-3
Fitting a Regression Model to the Same Return Series . . . . . . . 7-5
Simulation and Inference Using a Regression
Component . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-8
Forecasting Using a Regression Component . . . . . . . . . . . . . 7-9
Forecasted Explanatory Data . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-9
Generating Forecasted Explanatory Data . . . . . . . . . . . . . . . . 7-10
Ordinary Least Squares Regression . . . . . . . . . . . . . . . . . . . 7-11
Regression in a Monte Carlo Framework . . . . . . . . . . . . . . . 7-13
8
Likelihood Ratio Tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-2
Akaike and Bayesian Information Criteria . . . . . . . . . . . . . . 8-5
Equality Constraints and Parameter Significance . . . . . . . . 8-7
The Specification Structure Fix Fields . . . . . . . . . . . . . . . . . . . . 8-7
The GARCH(2,1) Model as an Example . . . . . . . . . . . . . . . . . . . 8-8
Equality Constraints and Initial Parameter Estimates . . . 8-11
Complete Model Specification . . . . . . . . . . . . . . . . . . . . . . . . . . 8-11
Empty Fix Fields . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-12
Limiting Use of Equality Constraints . . . . . . . . . . . . . . . . . . . . 8-13
Simplicity and Parsimony . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-14
9
Advanced Example
Estimating the Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-2
Forecasting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-4
Monte Carlo Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-6
Comparing Forecasts with Simulation Results . . . . . . . . . . . 9-8
10
Function Reference
Functions — Categorical List . . . . . . . . . . . . . . . . . . . . . . . . . 10-2
GARCH Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-2
GARCH Innovations Inference . . . . . . . . . . . . . . . . . . . . . . . . . 10-2
Statistics and Tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-2
GARCH Specification Structure Interface Functions . . . . . . . 10-3
Helpers and Utilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-3
Graphics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-3
Functions — Alphabetical List . . . . . . . . . . . . . . . . . . . . . . . . 10-4

「经管之家」APP：经管人学习、答疑、交友，就上经管之家！
免流量费下载资料----在经管之家app可以下载论坛上的所有资源，并且不额外收取下载高峰期的论坛币。
涵盖所有经管领域的优秀内容----覆盖经济、管理、金融投资、计量统计、数据分析、国贸、财会等专业的学习宝库，各类资料应有尽有。
来自五湖四海的经管达人----已经有上千万的经管人来到这里，你可以找到任何学科方向、有共同话题的朋友。
经管之家（原人大经济论坛），跨越高校的围墙，带你走进经管知识的新世界。
扫描下方二维码下载并注册APP