Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
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
Last synced: about 14 hours ago
JSON representation
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 (10 months ago)
- Default Branch: master
- Last Pushed: 2024-01-15T20:47:45.000Z (10 months ago)
- Last Synced: 2024-01-29T14:19:20.519Z (9 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
Awesome Lists containing this project
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