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BTC and Gold Price Relationship Analysis in R

This project aims to explore and analyze the relationship between Bitcoin (BTC) and gold prices using advanced time series tools in R. By leveraging techniques such as Engle-Granger causality tests and cointegration tests, we seek to uncover potential long-term relationships and dependencies between these two assets.

Project Overview

  • Perform data collection and preprocessing: Obtain historical price data for BTC and gold from reliable sources, clean the data, and ensure consistency.
  • Conduct exploratory data analysis: Visualize the price trends and statistical characteristics of BTC and gold to gain insights into their behavior.
  • Perform Engle-Granger causality test: Determine if there is a causal relationship between BTC and gold prices, exploring whether one asset's price movements predict or influence the other.
  • Conduct cointegration analysis: Investigate the presence of a long-term relationship between BTC and gold, examining whether their prices move together over time.
  • Implement other relevant time series analyses: Utilize additional advanced techniques such as ARIMA modeling, Granger causality tests, or Vector Autoregression (VAR) models, as appropriate.
  • Interpret and present findings: Analyze the results obtained from the analyses and provide meaningful insights into the relationship between BTC and gold prices.

How to Use the Project

  1. Install the necessary packages specified in the project's dependencies section.
  2. Execute the R scripts to fetch historical BTC and gold price data and preprocess the data.
  3. Run the analysis scripts, which include Engle-Granger causality tests, cointegration tests, and other relevant time series analyses.
  4. Interpret the results and visualize the findings using appropriate plots or graphs.
  5. Modify and customize the analysis as desired, experimenting with different models or techniques.
  6. Document your observations, insights, and conclusions based on the analysis.
  7. Feel free to contribute improvements, bug fixes, or additional analysis methods to enhance the project.

Dependencies

  • R version 3.x or higher
  • Required R packages: tidyverse, stats, ggplot2, urca, vars, and any additional packages specified in the project's scripts.

License

This project is licensed under the MIT License.

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