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CryptoPricePredictor

About

Project Proposal

Overall Objective: Predict future prices of various cryptocurrency

  • Implement two machine learning algorithms
  • Find datasets containing detailed history of various coins to train our algorithm
  • Compare performance of different algorithms

Justification: Being able to accurately predict prices of cryptocurrency could enable someone to make smarter investments.

Algorithms of Choice

Time Series Analysis - Regression

  • Support Vector Machine (SVM)

    • Widely applied and well surveyed
    • Non-linear and non-stationary process
  • Generalized Additive Model (GAM)

    • Application: Facebook's Prophet, a forecasting tool
    • Decomposition: Trend + Cyclical + Seasonal + Irregular

Datasets

Kaggle Datasets

  • Bitcoin's data at 1-minute inverals from Jan 2012 - Jan 2018

    • Attributes
      • Timestamp
      • Price (Open/High/Low/Close)
      • Volume in BTC & USD (Value of amount transacted in 24 hours)
  • Several top coin's data at daily intervals over several years

    • Attributes
      • Timestamp
      • Price (Open/High/Low/Close)
      • Market Cap (Coin Price * Circulating Supply)

Authors

  • Benjamin Carpenter
  • Jacob Pauly
  • Shuning Jin
  • Tristan Larsin

About

We are attempting to create a cryptocurrency price predictor using machine learning

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  • Jupyter Notebook 78.7%
  • PostScript 15.6%
  • TeX 4.1%
  • R 1.2%
  • Other 0.4%