Predict Stock Prices Using Technical Indicators and Machine Learning in Python

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  • Опубликовано: 12 янв 2025

Комментарии • 8

  • @shailendrakaushik9281
    @shailendrakaushik9281 2 месяца назад +3

    Excellent work! Keep it up

  • @samsquamsh78
    @samsquamsh78 18 дней назад +1

    thanks, I really like your videos! have tried out some of this myself with ollama - but so far I have not struck gold! Hopefully I will get better, thanks for your content, really appreciate how you walk through the code, your rationale and the relevance to underlying/what it does so to say.

    • @DeepCharts
      @DeepCharts  18 дней назад

      Thanks -- glad you found value from the videos!

  • @GodX36999
    @GodX36999 10 дней назад +1

    Top of top 👍👍👍

  • @lucasmrancez
    @lucasmrancez 2 месяца назад +1

    Thanks for sharing! but you may be incorrectly looking for direct corrections between indicator and stock closing prices. As I understand, indicator usually work as a guidance, sometimes even a visual guidance, to help find trends, or more importantly, trend changes. I would be interested if you could finding the correlation between indicators and the highest high or the lowest low of a trend, or to the derived closing price, for example.

    • @DeepCharts
      @DeepCharts  2 месяца назад +1

      Thanks for the comment. While indicators are often used for trend detection, this analysis tests their predictive value for next-day closing prices to evaluate their utility in forecasting. Moving averages are commonly used as direct predictors in ML time series models, but other indicators are less frequently examined this way, which is why we’re testing them here. The shared GitHub code in the video description can be modified to test alternative hypotheses, including different predictive time horizons and relationships to highest highs or lowest lows.

  • @istaruscanada6572
    @istaruscanada6572 Месяц назад +1

    Do you offer one-on-one training?

    • @DeepCharts
      @DeepCharts  Месяц назад

      Send me an email (info at deepcharts.xyz) about what you're looking for.