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Alpha and Beta in Finance

In this short video, Max Margenot gives an overview of alpha and beta in finance. Max gives an intuitive description of market beta and the calculation of alpha and how they interact with finance and in algorithms on Quantopian.

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4 responses

Excellent, thanks Phoebe and Max!

I find these very helpful and informative as well. Keep'em coming! :)

Since Alpha is unknown, it is found by using Beta to strip away returns attributed to the market and can be based on a lot of things such as common factor risk, quantopian model risk, etc. Does this imply also that because we can quantify and isolate different market returns via Beta, we are also isolating the risk associated with those returns as well?

@Viridian Hawk @Blue Seahawk Can one of you explain how the &= operator is used in the algorithm code? Are you using it to do a set calculation to make m a big screen?

In &=, the & can be thought of as 'and'. Adding to the mask.. m &= something ... says to further restrict the mask progressively as pipeline is processed.
So the mask (m here) collection of stocks becomes progressively smaller and smaller for each operation on them.
I have the impression that route is important to avoid allowing operations to be accidentally chewing on larger sets than intended, which can then make for nans in the inputs to factors or gaps in zscore, rank, percentile_between, top, etc. So I always use mask=m with those, even if it isn't strictly necessary at the moment, because in future edits it could play a role.
Also then, any m &= something ... line one is using can be commented out in a comparison test to see what effect that has.