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

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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