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Working to migrate to the algorithm framework in my coding. Right now, the majority of my strategies are binary. For example, if the 9day sma crosses down over the 50day sma, then go short and vice versa.
From what I gather, Alpha will generate a price/volatility directional insight if the previous criteria is met. However, I do not understand the advantage (if any) of a returned insight over manually executing once the logic is met. Will the alpha insight not always execute even though the logic is met?
Lucas
Hi James.
Hope that I understand your question right.
The QC framework tries to split up the development of algorithm into 5 parts. Universe selection, alpha creation, portfolio construction mode (just PCM for short), execution and risk. This way, we have a lot of seperation of concern. We can thrown in a new universe selection model, without having to re-do every part of the algorithm.
You can find more about the QC framework here:
Or check out the github where I think a lot of good examples can be found:
To answer your question, the alpha part Only sends signals or insight objects. These objects is sent to the PCM, where we can set the objects to be equal-weighted, we can also do a mean-variance portfolio or something totally different. After this, a portfolio target is send to the execution part, which sends out the market or limit order. So, to summarize a bit, the alpha does not place the orders, but only makes the prediction. The execution part is where we will send out the orders and so on.
I have found that going through the github examples have provided me with some insight.
Hope I cleared it up a bit
Lucas
James Hawkins
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