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Use Decision Trees in Machine Learning to Predict Stock Movements

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 Nitin Thapar, Content Marketing Manager at QuantInsti

 Friday, October 6, 2017

Learn how you can predict stock movements (that’s either up or down) with the help of ‘Decision Trees’ one of the most commonly used ML algorithms. http://ow.ly/VCK630fGjtP


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6 comments on article "Use Decision Trees in Machine Learning to Predict Stock Movements"

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 Peter Button, Product Management bei Nectar Financial AG

 Monday, October 9, 2017



Good post. Decision trees are powerful indeed. I pretty much built this on my webpage to demonstrate applications of machine learning for traders. You can play around with different indicators and see real results on abaca.ai


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 private private,

 Tuesday, October 10, 2017



Really interesting post. Thank you


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 private private,

 Tuesday, October 10, 2017



Interesting in particular because it shows some key weaknesses of the approach


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 Vitaly Khudyakov, Proprietary trader and developer of trading robots/trading algorithms (MQL4, Metatrader 4)

 Wednesday, October 25, 2017



Peter Button, unfortunetly your link (abaca.ai) don't work. Msg me correct link, please


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 Oscar Cartaya, Private Investor

 Sunday, November 5, 2017



Your example has 16 days worth of data and you talk about splitting the dataset into a training dataset and a test dataset. That is like 8 days worth of data for each dataset. Are you kidding me? A 16 day dataset which includes both the training and test datasets is what you are going to use in your example to predict future stock movements? How far into the future and for how long do you pretend that anything coming out of this tiny dataset will be of use for the stated purpose? Let's get real here.


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 Nitin Thapar, Content Marketing Manager at QuantInsti

 Monday, November 6, 2017



Hi Oscar Cartaya, We have taken data from 2010-01-01. The code snippet for the same is already shown in the blog. The excel table only illustrates the data used and the technical indicators added for prediction.

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