1. Ninja Trader: Introduction to data mining in financial applications
Artem Gritsenko
CS 548 Showcase
Feb 7, 2014

2. Resources Ninja Trader: Homepage: http://www.ninjatrader.com
Download:
Tutorial:
Learning videos:
References on data mining in financial applications:

3. Motivation Why financial applications?
Real-world problem that can be solved with data mining and that is still subject to research.
FA use all variety of different KDD and data mining techniques:
data aggregation,
visualization,
feature selection,
prediction,etc.
Why Ninja Trader?
Free to download and use
Has a setting of simulated trading (to learn and play)

4. Nature of financial data
Financial dataset:
Usually consists of 5 attributes:
index value at open,
index value at close,
highest index value,
lowest index value,
trading volume (daily).
Data integration:
Mediation Approach: allows information to be retrieved directly from original databases (Yahoo finance, Google finance, etc.)

5. Dataset analysis Data exploration
Summary statistics - standard deviation, moving average, simple prediction based on linear regression
Visualization
...
Data Preprocessing
Data aggregation (day, month, year)
Feature construction (moving average)
Sampling - in Monte Carlo Simulation

6. Trading rules
Trading rules can be determined from data with a categorical outcome, e.g., buy or sell, rise or fall.
This leads to a classification task: at each time step data is classified into one of the categories:
Buy stock
Sell stock
If we consider rules in the form of conditional statements
IF CONDITION1 AND CONDITION2 THEN ACTION
the model can be fitted with a decision tree.
Langdel(2009)

7. Decision Tree Tree construction: Nodes: tests (X1 >= VALUE or
{(X2 = i)}, for i=1, 2,..)
Leaves:
decisions (sell, buy)
Ex. "When the 10-day moving average crosses above the 30-day moving average and both moving averages are increasing it is time to buy"

8. Other approaches Statistical Autoregressive models
Moving average models
Advantage: easy to interpret
Disadvantage: need parameters to be set properly
Neural networks:
Advantage: ability to model very complex data
Disadvantage: hard to interpret

9. Conclusion
Only main features and capabilities of the software discussed
There is an advanced and more powerful version of Ninja Trader exist (not free!)
You can add your own functionality(strategies, indicators, etc.) to Ninja Trader with NinjaScript (basically C#) htm