[Machine Learning for Trading] {ud501} Lesson 9: 01-08 Optimizers: Building a parameterized model |
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What is an optimizer?
Minimization example
How to defeat a minimizer
Convex problems
Building a parameterized model
Minimizer finds coefficients
What is portfolio optimization?
The difference optimization can make
Which criteria is easiest to solve for?
Cumulative return is the most trivial measure to use - simply investing all your money in the stock with maximum return (and none in others) would be your optimal portfolio, in this case.
Hence, it is the easiest to solve for. But probably not the best for risk mitigation.
Framing the problem
Ranges and constraints
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