Project on forecasting ripple cryptocurrency prices using various autoregressive models.
Blockchain is a promising technology however, the attention is directed at cryptocurrencies prices. The purpose of the work is to learn about autoregressive models by building models with best predictive power. Personal motivation is as follows:
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Learn time series A popular class of models that have a wide range of applications from stock price prediction to speech recognition.
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Build intuition behind autoregressive model Understanding how a model determines its coefficients as well as the interpretation of the models output.
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Explore finance domain Explain why it is difficult to beat the market from a quantitative perspective
A detailed, step by step, process of the project could be found here
The repository contains tools to do the following:
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Collect a cryptocurrency price history and reddit thread titles from a subreddit
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Perform EDA and normality checks on the data
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Optimize parameters for the following models AR, ARMA, ARIMA, SARIMA, and SARIMAX
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Forecast daily percent change in the market
I would like to thank Adam Wearne, Robert Alvarez, and my fellow cohort members for their guidance and support.