Learning Algorithms for Trading

From Quantitative Analysis Software Courses

Revision as of 00:06, 4 March 2015 by 3xdkyr (talk | contribs) (→‎Artificial neural networks)

(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)

Jump to navigation Jump to search

Contents

1 Supervised machine learning
2 How ML fits into the computing at a hedge fund
3 Time series prediction as an ML problem
4 Learner APIs
5 Linear regression
6 KNN
7 Assessing a learning algorithm
8 Overfitting
9 Decision trees
10 Decision forests
11 Random trees & forests

Supervised machine learning

Regression
Classification
Parametric
Instance-based
Overview: LinReg, KNN, Decision Trees, ANN

How ML fits into the computing at a hedge fund

Long/short

Time series prediction as an ML problem

[note: need to create fake stock data that has embedded patterns]

Learner APIs

Linear regression

KNN

Assessing a learning algorithm

Now that we have two, (linreg & KNN), let's compare them
RMS error
Scatterplot predict vs actual
Corrcoef

Overfitting

Decision trees

Decision forests

Random trees & forests

Retrieved from "http://quantsoftware.gatech.edu/index.php?title=Learning_Algorithms_for_Trading&oldid=96"