Using what you have learnt from Submissions 1 and 2, implement a trading strategy using machine learning. We recommend that students focus on classification – for example: trying to forecast if a stock will move up and down, above some threshold such as the 90-day standard deviation.

Using what you have learnt from Submissions 1 and 2, implement a trading strategy using

machine learning. We recommend that students focus on classification – for example: trying to

forecast if a stock will move up and down, above some threshold such as the 90-day standard

deviation.

1 Decide on an algorithm or group of algorithms (for example, ensemble techniques).

2 Fit the model.

3 Show that it works out of sample, and use appropriate cross-validation techniques.

4 Provide the following performance metrics:

(a) ROC curves,

(b) Confusion Matrix,

(c) Precision, Recall, F1-Score, Accuracy, and AUC.

5 Analysis of metrics and report.

Create a fund factsheet for your new investment strategy. Have a look at examples of popular

funds found online and create a fact sheet with all the bells and whistles. It must at a minimum

include (Pyfolio can be used):

1 Maximum Drawdown

2 Annualized Returns

3 Sharpe Ratio

4 Plot the Equity Curve