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univariatetimeseriesforecast's Introduction

Univariate Time Series Forecast

This study was developed with Filipe Roberto Ramos (https://ciencia.iscte-iul.pt/authors/filipe-roberto-de-jesus-ramos/cv) for his phD thesis entitled "Data Science in the Modeling and Forecasting of Financial Timeseries: from Classic methodologies to Deep Learning". Submitted in 2021 to Instituto Universitário de Lisboa - ISCTE Business School, Lisboa, Portugal.

  1. Notebooks
  2. Citation

Notebooks

ExploratoryDataAnalysis

  • Imports and Defines
  • Data Inspection
  • Data Visualization
  • Data Analysis
  • Hypothesis Test

ARIMA and SARIMA

  • Imports and Defines
    • Imports
    • Define Functions
    • Define Univariate Time-Series
  • Stationarity of the Time-Series
    • Data transformation and its graphical representation
    • Normality tests
    • Jarques-Bera
    • Kolmogorov-Smirnov
    • Unit Root and Stationarity Tests
    • The Augmented Dickey-Fuller test
    • Kwiatkowski-Phillips-Schmidt-Shin
    • Correlation plots
  • (S)ARIMA Selection
    • Pre-processing
    • Model training
    • Model Comparison based on Information Criteria
    • Selected Models Information Criteria Comparison
    • Selected Models Cross-Validation
  • Model Validation
    • Model Residual Analysis
    • Normality tests
    • Kurtosis and Kurtosis Test
    • Skew and Skewness Test
    • Jarque-Bera and Kolmogorov-Smirnov tests
    • Engle's Test for Autoregressive Conditional Heteroscedasticity (ARCH)
    • Test for No Autocorrelation
    • Brock–Dechert–Scheinkman test
    • Breusch-Godfrey test [NOT IN SARIMA]
    • Box-Pierce and Ljung-Box tests
    • QQplot
    • Auto-correlation and Partial Auto-correlation functions
  • Model Prediction
    • Model Prediction Overview

ExponenTialSmoothing

  • Imports and Defines
    • Imports
    • Define Functions
    • Define Univariate Time-Series
  • Data Visualization
  • Model Training
    • Single Exponential Smoothing
    • TS (N, N) - Simple Exponential Smoothing
    • Double Exponential Smoothing
    • TS (A, N) - Holt’s linear method
    • TS (Ad, N) - Additive damped trend method
    • Triple Exponential Smoothing
    • TS (N, A) method
    • TS (A, A) - Additive Holt-Winters method
    • TS (Ad, A) method
    • TS (N, M) method
    • TS (A, M) Multiplicative Holt-Winters’ method
    • TS (Ad, M) Holt-Winters’ damped method
  • Model Selection
  • Model Validation
    • Normality Test
    • Kurtosis and Kurtosis Test
    • Skew and Skewness Test
    • Jarque-Bera test
    • Kolmogorov-Smirnov test
    • Engle's Test for Autoregressive Conditional Heteroscedasticity (ARCH)
    • Test for No Autocorrelation
    • Brock–Dechert–Scheinkman test
    • Box-Pierce and Ljung-Box tests
    • QQplot
    • Plot Auto-correlation and Partial Auto-correlation functions
  • Model Prediction
    • Model Prediction Overview

DeepNeuralNetwork

And DNN_OurApproach

  • Imports and Defines
    • Imports
    • Define Functions
    • Define Univariate Time-Series
  • Training Deep Neural Network
    • Data Pre-Processing
    • Visualization of Data Pre-Processed
    • Model Selection (tune hyper-parameters)
    • Cross-Validation
    • Compute Cross-Validation Errors
    • Cross-Validation Performance
    • Cross-Validation Plot
  • Model forecasting
    • Perform statistics on predictions
    • Statistics cleaning
    • Plot Prediction
    • Plot Forecast in-sample vs out-sample

Citation

APA

Ramos, F. (2021). Data Science na Modelação e Previsão de Séries Económico-financeiras: das Metodologias Clássicas ao Deep Learning. (PhD Thesis submitted, Instituto Universitário de Lisboa - ISCTE Business School, Lisboa, Portugal).

@phdthesis{FRRamos2021,
      AUTHOR = {Filipe R. Ramos},
      TITLE = {Data Science na Modelação e Previsão de Séries Económico-financeiras: das Metodologias Clássicas ao Deep Learning},
      PUBLISHER = {PhD Thesis submitted, Instituto Universitário de Lisboa - ISCTE Business School, Lisboa, Portugal},
      YEAR =  {2021}
}

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