Answers.Body: <p>I will tell you this. What you are trying to do is a bad idea almost universally if you feed only stock time series data into a model what you will get out is something resembling a moving average. The reason for this is that the stock market is a complex adaptive system and any strategy used will become less effective the more its used and because every single person who studies machine learning has thought of this i.e. it's a canonical idea it basically will not work at all. (low loss and low percentage error are misleading if you really want an accurate measure of performance check what percentage of the time its right about the direction of movement)</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2024-11-06T20:09:53.690Z
Answers.LastActivityDate: 2024-11-06T20:09:53.690Z
Answers.UserDisplayName: Leonhard Piff
Body: <p>I am looking for more advanced models for my stock market software can anyone either point me in the right direction for the latest research on LSTM or others or any experts collab/provide models for me in this specific area? Models must be convertible to onnx format currently.</p>
  
Tags: <long-short-term-memory><software-evaluation><software-development>
Title: Stock Market LSTM predictions request models
UserDisplayName: Philip Bray
ThreadText: # Stock Market LSTM predictions request models
  
  (Asked by: username_0 on 2024-11-04)
  
  I am looking for more advanced models for my stock market software can anyone either point me in the right direction for the latest research on LSTM or others or any experts collab/provide models for me in this specific area? Models must be convertible to onnx format currently.
  
  **Tags:** long-short-term-memory, software-evaluation, software-development
  
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  ## 1 answers
  
  ### Answer by username_1 on 2024-11-06. Score: 0
  
  I will tell you this. What you are trying to do is a bad idea almost universally if you feed only stock time series data into a model what you will get out is something resembling a moving average. The reason for this is that the stock market is a complex adaptive system and any strategy used will become less effective the more its used and because every single person who studies machine learning has thought of this i.e. it's a canonical idea it basically will not work at all. (low loss and low percentage error are misleading if you really want an accurate measure of performance check what percentage of the time its right about the direction of movement)
  
  
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