> Alpha#90: ((rank((close - ts_max(close, 4.66719)))^Ts_Rank(correlation(IndNeutralize(adv40, IndClass.subindustry), low, 5.38375), 3.21856)) * -1)
I wonder how these magic numbers get picked (4.66719, 5.38375, etc) -- I guess there is some optimization solver which attempts to find the most profitable variables for a given alpha formulation, but isn't this approach also very vulnerable to overfit?
These alphas will likely be only profitable for a short time period as long as the market data distribution (i.e. strategies of other market participants) doesn't change. So you would need to continually optimize and update them.
The way I think about it is that you are essentially finding the right parameters to "exploit" the combination of algorithms of all other participants, where algorithm could also be a human looking at charts and following certain rules, with a lot of random noise from retail traders thrown in.
> (sign(delta(volume, 1)) * (-1 * delta(close, 1)))
That's crazy. Would be interesting to see WTF a "mega-alpha" actually does using these strategies.