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  • Medical Imaging
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  • Parametrizing Feet Scans
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  • ChatGPT - My perspective
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  • Linear Regression for Stocks
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  • Optimization of ETF Securities' Weights
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  • Machine Learning for Stocks Analysis pt2
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  • Machine Learning for Stocks Analysis
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  • Comparing Melodic Phrases
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  • The Mathematics Behind Musical Scales
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  • Chladni Plates for Music Visualization
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    Stocks price trend point-cloud for custom time intervals

    This post is the continuation of a previous post made about machine learning and stocks (here) . To understand the concepts that will be discussed, it is necessary to understand those discussed earlier. I want to continue with the idea of representing stock price trends (STPs) using points in a cartesian graph. Last time, the SPT I had discussed were studied over a fixed period. However, it would be interesting to study how those SPTs evolve for different time periods.

    Diagram representing how the periods are taken, original picture taken from google.

    To illustrate the use of Stock Price Trend (SPT) point-cloud, I have selected 8 stocks, 4 pharmaceutical ones and 4 related to oil companies. Depending on the time-interval selected I can guess which trends are closer to which other.

    2D visualization of the SPTs for customly selected intervals (Oil SPTs are in red and Pharmaceutical SPTs are in green)

    Multiple things can be inferred from the graph, first, pharmaceutical SPTs tend to be closer to each other than Oil SPTs; Their trends tend to be less diverse that those of Oil SPTs. Second, for a lot of time intervals, both types of SPTs seem to be at different sections of the canvas, indicating a clear distinction between the two types SPTs.