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Dimensionality reduction for prediction: Application to Bitcoin and Ethereum

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  • Hugo Inzirillo
  • Benjamin Mat

Abstract

The objective of this paper is to assess the performances of dimensionality reduction techniques to establish a link between cryptocurrencies. We have focused our analysis on the two most traded cryptocurrencies: Bitcoin and Ethereum. To perform our analysis, we took log returns and added some covariates to build our data set. We first introduced the pearson correlation coefficient in order to have a preliminary assessment of the link between Bitcoin and Ethereum. We then reduced the dimension of our data set using canonical correlation analysis and principal component analysis. After performing an analysis of the links between Bitcoin and Ethereum with both statistical techniques, we measured their performance on forecasting Ethereum returns with Bitcoin s features.

Suggested Citation

  • Hugo Inzirillo & Benjamin Mat, 2021. "Dimensionality reduction for prediction: Application to Bitcoin and Ethereum," Papers 2112.15036, arXiv.org, revised Feb 2022.
    • Handle: RePEc:arx:papers:2112.15036
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    References listed on IDEAS

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    1. Sifat, Imtiaz Mohammad & Mohamad, Azhar & Mohamed Shariff, Mohammad Syazwan Bin, 2019. "Lead-Lag relationship between Bitcoin and Ethereum: Evidence from hourly and daily data," Research in International Business and Finance, Elsevier, vol. 50(C), pages 306-321.
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