So you doubt that there is such a thing as “cool visuals” for Data Science? Well the guys doubted it too, especially Tom, but ended up calling more than a a few of the slides “cool” and others "neat" and “interesting”. Michael Rechenthin, Ph.D., the head of our research team joins the guys to explain that only “…when we do something with data, when we visualize it, does it become something useful. It becomes knowledge.” We think when you watch this you’ll be saying “cool” a few times too and you’ll realize why Data Science is the hottest field.
The first cool visualization tool was a whisker plot of VIX levels for the year over the years. It looks sort of like a candle chart but with more information and of course Dr Data tells us how to easily read it. The next cool visual was the application of a heat map (color coding) to an ordinary table of the P/L results of a short Strangle. It’s much easier to see the impact of Theta (time decay) in this visual. A distribution plot of the 10 year note, S&P 500, Gold and Crude came next. The color coding made it easy to see how the four compared to each other and how we should expect them to move.
Take a distribution plot and add a tweak and you get distribution plots. We’re sure you’ve never seen the seasonality of the S&P 500 explained this way or so easily. At first glance the shapes are random but after a simple explanation from Mike you can see so much more. Another chart is a combo of a scatter chart and a bubble chart. It plots the Implied Volatility (IV) of Dow stocks by IV Rank (IVR) and combines it with market cap data. A scatter chart with bar chart characteristics helps us understand the capitalization of stocks in the different indices. The final slide of a color coded table of the correlation of 3 month returns of the S&P 500, Dow, Nasdaq, Russell, Bonds, Gold, Silver and Crude is so intuitive it doesn’t even require an explanation.
Watch this segment of Skinny on Options Data Science with Tom Sosnoff, Tony Battista and Dr. Data, aka Michael Rechenthin, Ph.D., to see some of the “cool visuals” and you’ll be surprised how much you’ll enjoy seeing the transformation of raw data into useful knowledge that is easily understood.
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