Good places to look for +EV:
1. The idea is hard to backtest
2. The data is hard to acquire
3. A known input can be transformed into something novel or hard to compute.
5. The idea is known, but has only been applied to one specific area or time horizon.
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After an absolute marathon of collaborative writing over the past few months, @SinclairEuan and I are pleased to announce the release of our new book: Retail Options Trading.
amazon.com/dp/B0DL7FCKKC
Please see follow-up posts for important release notes.
After a very long writing hiatus, I am pleased to announce the release of a new book, "Bayesian Sports Models in R".
355 pages. Fully colorized R & Stan code. Full R code download package.
Now if you'll excuse me, I've got some bets/trades to make 🫡
amazon.com/dp/B0D9H2YLWJ
A few suggested online courses for taking your sports modelling to the next level. [Available to take for free]
1. Excel: Wayne Winston "The Math Behind Moneyball"
2. Basic Statistics With R
3. Bayesian Statistics in R
1. Bayes
Adapt or get rekt.
2. Information Theory
Kelly is cool, but don't skip Shannon.
3. Game Theory
Markets = Nash equilibria under constant attack.
4. Tail Risk
Reality isn’t normal. Mandelbrot > Gauss.
Have a great weekend 🫡
In law school, we were taught to prepare case briefs/ exam answers using a structure called FIRAC. Facts, Issue, Ratio, Analysis, Conclusion. After spending some time this weekend going over some of @therobotjames trading threads, I sketched out a structure for trading edges.
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