https://github.com/avinash793/time-series-analysis-examples

Detailed implementation of various time series analysis models and concepts on real datasets.
https://github.com/avinash793/time-series-analysis-examples

acf ar-model arima-model arma-model dickey-fuller-test forecasting-models garch-models hidden-markov-models model-diagnostics model-selection-and-evaluation pacf q-q-plot random-walk residuals time-series-analysis time-series-decomposition time-series-forecasting var-model volatility-modeling white-noise

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Detailed implementation of various time series analysis models and concepts on real datasets.

• Host: GitHub
• URL: https://github.com/avinash793/time-series-analysis-examples
• Owner: Avinash793
• Created: 2024-01-15T18:25:20.000Z (11 months ago)
• Default Branch: master
• Last Pushed: 2024-01-15T20:47:45.000Z (11 months ago)
• Last Synced: 2024-01-29T14:19:20.519Z (11 months ago)
• Topics: acf, ar-model, arima-model, arma-model, dickey-fuller-test, forecasting-models, garch-models, hidden-markov-models, model-diagnostics, model-selection-and-evaluation, pacf, q-q-plot, random-walk, residuals, time-series-analysis, time-series-decomposition, time-series-forecasting, var-model, volatility-modeling, white-noise
• Language: Jupyter Notebook
• Homepage:
• Size: 3.15 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Time Series Analysis Examples

Detailed implementation of various time series analysis models and concepts on real datasets. 

### Time Series Models Covered

* White Noise Model

* Random Walk

* AR Model

* ARIMA Model

* Vector Autoregressive Regression (VAR) Model

* Volatility Modelling using ARCH & GARCH Models

* Markov Switching Dynamics Regression (MSDR) Model

### Time Series Concepts Covered

You will find implementation of below concepts which can be used for your reference:

* Log Returns 

* White Noise Model

* White Noise Tests - Autocorrelation plot and Ljung Box Test 

* Random Walk

* Time Series Decomposition

* AR(p) Model

* MA(q) Model

* ARMA(p,q) Model

* ARIMA(p,q,d) Model

* Augumented Dickey Fuller Test - Check for Stationarity / Non-Stationarity

* Differencing Method

* Autocorrelation Function (ACF)

* Partial Autocorrelation Function (PACF)

* Model Selection Criterion - AIC, BIC, HQC

* Model Diagnostics

* Residual Diagnostics

* Normal Q-Q plot

* Forecasting return

* Multi-Variate Time Series Analysis

* VAR(p) Model

* Impulse Response Functions

* Volatility Modelling

* ARCH(p) model

* GARCH(p,q) model

* Jarque Bera Test

* Forecasting volatility - One step ahead and N step ahead

* Hidden Markov Models (HMM)

* Markov Switching Dynamic Regression (MSDR) Model