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Bumped by Community user
Bumped by Community user
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edit approved Mar 5, 2023 at 4:48
tripleee
edit approved Mar 5, 2023 at 4:48
tripleee
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I have basic knowledge in time series prediction and supervised/unsupervised machine learning algorithms  (clustering,classification classification,decision decision tree,etc etc.) I am now given a task to predict a bunch of stock priceprices. Each stock has its previous trading price (a period of 18 months) as well as some other features: coupon, asset rating, industry,etc etc. I only nowknow how to use time series analysis or supervised machine learning separately, I have no idea of how to combine these two together.Is Is there any particular algorithm that I can use as a predictive model? What are steps to combine both dynamic and static information? Any help will be appreciated!

I have basic knowledge in time series prediction and supervised/unsupervised machine learning algorithms(clustering,classification,decision tree,etc.) I am now given a task to predict a bunch of stock price. Each stock has its previous trading price (a period of 18 months) as well as some other features: coupon, asset rating, industry,etc. I only now how to use time series analysis or supervised machine learning separately, I have no idea of how to combine these two together.Is there any particular algorithm that I can use as a predictive model? What are steps to combine both dynamic and static information? Any help will be appreciated!

I have basic knowledge in time series prediction and supervised/unsupervised machine learning algorithms  (clustering, classification, decision tree, etc.) I am now given a task to predict a bunch of stock prices. Each stock has its previous trading price (a period of 18 months) as well as some other features: coupon, asset rating, industry, etc. I only know how to use time series analysis or supervised machine learning separately, I have no idea of how to combine these two together. Is there any particular algorithm that I can use as a predictive model? What are steps to combine both dynamic and static information? Any help will be appreciated!

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Alex
Alex
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Combine machine learning feature selection with time series

I have basic knowledge in time series prediction and supervised/unsupervised machine learning algorithms(clustering,classification,decision tree,etc.) I am now given a task to predict a bunch of stock price. Each stock has its previous trading price (a period of 18 months) as well as some other features: coupon, asset rating, industry,etc. I only now how to use time series analysis or supervised machine learning separately, I have no idea of how to combine these two together.Is there any particular algorithm that I can use as a predictive model? What are steps to combine both dynamic and static information? Any help will be appreciated!