MC3-Project-2

Draft

"Draft" will be removed when the assignment is final.

Overview

In this project you will transform your regression learner into a stock trading strategy. Overall, you should follow these steps:

• Train a regression learner (KNN or LinReg, or other of your choice with or without bagging) on data from 2008 to 2009.
  • For your X values: Identify and implement at least 3 technical features that you believe may be predictive of future return. You should implement them so they output values typically ranging from -1.0 to 1.0. This will help avoid the situation where one feature overwhelms the results.
  • For your Y values:

Template and Data

You will use data in the ML4T/Data directory. In particular files named ML4T-XXX.csv, where XXX are digits.

Part 1: Build TrainY

Use ML4T-399.csv

Your code should predict 5 day change in price. You need to build a new Y that reflects the 5 day change and aligns with the current date.

Create a plot that shows current price and overlays the 5 day change, and overlays one on the other. The result should appear to be just a shifted version of the price.

Part 3: Develop Technical Indicators

Select and implement at least 3 technical indicators that you will use to predict prices.

Part 4: Train and Show Results

Train your system on 2008-2009. Create a chart that shows your predicted 5 day return versus actual.

Part 5: Create a Trading Strategy

Use your forecaster to generate a trading strategy. Create a chart that shows entry and exit points.

Generate trades, show backtest. Show results for in sample (2008-2009) and out of sample 2010-2011

Apply this now to real data, IBM, over the same period.