Timeseries Compute Documentation

Welcome to the Timeseries Compute project documentation! This project is a pet project for recreating a thesis in Python, focusing on time series modeling using ARIMA and GARCH models for financial data analysis, volatility forecasting, and market spillover effects.

Project Overview

Timeseries Compute provides tools for:

• Synthetic time series data generation with controlled properties

• Data preprocessing and transformation for time series analysis

• ARIMA modeling for conditional mean forecasting

• GARCH modeling for volatility forecasting

• Multivariate GARCH for correlation analysis

• Market spillover effects analysis

Project Links

• PyPI package: https://pypi.org/project/timeseries-compute/

• GitHub source code: https://github.com/garthmortensen/timeseries-compute

• ReadTheDocs: https://timeseries-compute.readthedocs.io/en/latest/

Contents

• Installation
• Examples
  • Univariate GARCH Example
  • Multivariate GARCH Example
• API Documentation
• Data Generator
  • PriceSeriesGenerator
• Data Processor
  • MissingDataHandler
  • MissingDataHandlerFactory
• Stats Model
  • ModelFactory
• Tests
• Modules
  • data_generator module
  • data_processor module
  • stats_model module
  • spillover_processor module
  • export_util module
  • Examples
  • tests package

Indices and Tables

• Index

• Module Index

• Search Page