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Luke Gotszling - Prediction Using Python
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NewCircle Training
September 19, 2013
Technology
1
1.9k
Luke Gotszling - Prediction Using Python
This is a quick introduction to prediction using Python.
NewCircle Training
September 19, 2013
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Transcript
Introduction to Prediction Luke Gotszling Co-founder & CEO at fina"y.io
luke@fina"y.io @lmgtwit September 11, 2013 | SFPython | San Francisco 1
Shark meets cable http://www.#.com/cms/s/0/4557b69c-c745-11de-bb6f-00144feab49a.html http://www.youtube.com/watch?v=1ex7uTQf4bQ 2
CPU graph 3
Linear regression y = α+βx 4
Linear regression Benefits: We" supported and straightforward calculation Built-in estimate
of the degree of fit: R2 (“coefficient of determination”) Problems: Doesn’t handle cycles Questions about parameters (e.g. amount of entries used for regression and steps of extrapolation) 5
EMA (exponential moving average / exponential smoothing / Holt-Winters) Image
citation: http://lorien.ncl.ac.uk/ming/filter/filewma.htm 6
EMA yt = αxt+(1-α)yt-1 y1=x0 7
EMA Benefits: More recent data weighed more heavily Seasonality can
be taken into account Problems: Relies on reversion to mean Divergence and multiple seasons in data Weighting options 8
Other approaches Higher dimensional polynomial fits (and exponential) Fourier transforms
Machine learning: neural networks... Bayesian RSI (relative strength index) and other methods used in technical analysis in finance 9
Data bit.ly/sfpython_prediction_slides bit.ly/sfpython_prediction_notebook 10
Thank you! luke@finally.io @lmgtwit 11