[Machine Learning for Trading] {ud501} Lesson 9: 01-08 Optimizers: Building a parameterized model | Lesson 10: 01-09 Optimizers: How to optimize a portfolio

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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转载自www.cnblogs.com/ecoflex/p/10972798.html