Modeling Price of ethereum with machine learning

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Presentation transcript:

Modeling Price of ethereum with machine learning Scott Cilento

What is ethereum? Blockchain technology “Append only” Used for computing power of network Cryptocurrency called “Ether” Famous for boom and subsequent bust in 2017-18

Dataset July 2015 – October 2018 (1164 observations) Blockchain attributes: Transactions Hash rate growth Block size (cap on processing and storage)

Dataset (cont.)

Regression

Price Prediction Regression models relationships of data Allows for prediction given transactions, growth rate, and block size Want to predict the future price Strong autocorrelation from “buzz”?

Neural Network Powerful, popular way to compute predictions How does it work? In short: matrix multiplication Backpropagation, gradient descent Source: https://www.digitaltrends.com/cool-tech/what-is-an-artificial-neural-network/

Neural Net and Time series Neural net for sequential data: Long short-term memory network Inputs: Ct-1 = memory from previous cell Ht-1 = output of previous cell Xt = observation at t Outputs: Ct = memory Ht = output Source: https://colah.github.io/posts/2015-08-Understanding-LSTMs/

LSTM in action