The document describes an automatic system for selecting the best trading strategies from a dataset of 5600 samples with 1881 features. Previous attempts used subjective human criteria or simple linear methods. The new system formalizes the problem as finding the top N samples that best approximate expert selections, while adapting to new data. It uses a neural network with feature selection, data preprocessing, supervised learning and backpropagation to train on 700 samples. Testing on 300 samples found the system agreed with experts on most selections and identified a few the experts missed.

1. AUTOMATIC SELECTION
OF TRADING
STRATEGIES
Nilitis LLC, Minsk
18-09-2012
Teut Sofia

2. The Problem
5600
1881
Strategy Name Priority
9000518100 1
…. ….
900051825 10

3. Main difficulties
• “Best strategy” definition
• Subjective selection criteria
• Varying data
Previous attempts
Linear weighted
Linear function
filtering
Experts steps
reproducing

4. Problem formalization
Data: 5600 samples of 1881 features
Find: N “best” samples
Requirements for solution:
• Best approximation of experts selection
• Adaptation to new data
Adaptive System?
Sample Rate
Regression
problem

5. Feature Selection
• Independent features using by experts
• No chance to use picture for rating
• Features with information about curve form
Result
65 features were selected (from more than 1500)

6. Preprocessing
First iteration:
1. Filtering
2. Missed values recovering
3. Value normalization
Second iteration:
1. Principal component analysis
2. De-correlation methods

7. Solving
Architecture
• Neuron Net: Feed-forward type, Hyperbolic tangent sigmoid transfer function
• First layer: 15 neurons
• Second layer: 1 neuron
Teaching
• Supervised learning with “Sample-Rate”
• Back-propagation learning method
• Training set: 700 samples

8. Testing
Testing set 300 samples:
• 216 similar to training data
• 84 different
Result
Selected by the System and Selected by the System and
Experts: maybe by Experts:
• 11 from 16 • 3 from 16
• and 3 from 5 • and 1 from 5
Selected by the System and never by
Experts:
• 2 from 16
• and 1 from 5

9. Thank You!