Litecoin Data Collection and saved data features

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I have already talked about the two scripts, one that pulls the financial data from Yahoo Finance hourly, then looks for the TA signals in that data. The other script searches one thousand tweets daily, forty-two tweets every hour for Litecoin, and uses hugging face to analyze sentiment. 

Let's talk about the data features we wanted to save and the tables we kept them in. 

Transactions:

We collect the following metrics open, high, low, close, adj close, volume, Morning Star, Hammer, Piercing Line, Engulf, and Three white nights as binary indicators.  

Morning Star: https://commodity.com/technical-analysis/morning-star/

Hammer: https://commodity.com/technical-analysis/hammer/

Piercing Line: https://commodity.com/technical-analysis/piercing-pattern/

Engulf: https://commodity.com/technical-analysis/bullish-engulfing/

Three White Knights / Soldiers: https://en.wikipedia.org/wiki/Three_white_soldiers

Sentiment: 

We collected hourly sentiment of the 42 tweets and recorded the positive, negative, and neutral numbers. 

Finally

I then combined them into a View base on the time stamp column on both of them. 

Everything was written as strings in the Database so we could manipulate it further along with an ETL process. 

We collected around 5115 hourly records before my Free API access was shut off on June 10th. 

Next, we will discuss the CNN and feature selection and cap it off with a Tensorflow predictions model based on separating the training and validation sets.  

 


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