Zephyer314 hello, interesting read. It is interesting to me that the lowest cumulative level for the tuned model is approximately equal to the lowest cumulative level for the simple model with no tuning. In fact if we had been only looking at the results up until Dec. 12 or so we would have concluded that the simpler model works better and barely beats the house and that maybe the performance of the simple and tuned models are converging.<p>However, they now seem to be diverging with a clear advantage to the tuned model. If you had been actually using this to bet you might have given up on the tuned model around Dec. 7th when draw down was at its worst.<p>What will really be interesting is whether the performance over the rest of the season continues to diverge in the current direction or if the performance tends float up and down around the break even line.<p>Is one of the parameters a progress through the season index? Anyway thanks for sharing the example.
Hello, I'm the author of this post and co-founder of SigOpt (YC W15). Let me know if you have any questions about the post or what we do at SigOpt.<p>All of the code used in this post can be found at <a href="https://github.com/sigopt/sigopt-examples" rel="nofollow">https://github.com/sigopt/sigopt-examples</a>