[Machine Learning for Trading] {ud501} Lesson 9: 01-08 Optimizers: Building a parameterized model |

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What is an optimizer?

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 Minimization example

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 How to defeat a minimizer

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 Convex problems

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 Building a parameterized model

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 Minimizer finds coefficients

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 What is portfolio optimization?

 

 

 

The difference optimization can make 

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Which criteria is easiest to solve for? 

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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

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 Ranges and constraints

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