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Showing posts with the label k-means clustering

JPY-USD Support and Resistance Levels

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  The JPY has been uncharacteristically volatile. The chart above shows JPY-USD daily Close from Jan 2025. It has been plotted in different colors at different points in time after clustering by K-Means Clustering. The dashed lines are the Support and Resistance levels as calculated by proximity to cluster centers. Note that the width of dashed lines from each other varies. And note that the widest dashed lines lie between 156.13 and 150.13. We shall come back to this point later when we provide the instructions for trading  trading  But first, visualize JPY-USD  recent volatility in the  monthly chart from 2015  below; and see that it is now at the highest level of volatility, as can be seen by the number of peaks and troughs.  How to use the Support and Resistance levels in trades. See the instructions below the chart. The Green arrows means a Buy point and the Red arrows a Sell point.  For each trade, a stop-loss and take-profit level is set to...

Reducing Information Redundancy with Principal Components Analysis

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:-) Thank you to the University of Kansas, the Hexacoral project at http://www.kgs.ku.edu/Hexacoral/ for the use of the beautiful animated GIF which is a visualization of Principle Component Analysis . I copied it and I hope they don't mind. This animation shows how 12 clusters of data [the different colors] are reduced to 3 Principle Components. [the 3 orthogonal vectors (perpendicular to each other)] To see the animation, click on it to view it in a new window. In a world where so much information is available, we must learn to manage information overload. When we have several data feed on the same subject, chances are that much of the information overlaps i.e. is redundant. Overlap, meaning that mathematically speaking, if you could and did draw circles representing the true information content of the each data set, the circles would overlap. This is important when we are trying to use the data to model some aspect of the real world. For example, if we are trying to analyze a...