Our tutorial and manual cover all of TSSB's capabilities. Here is just a sample that gives a sense of what it can do.
Develop and test predictive-model based trading systems for individual instruments as well as multiple markets and provide unbiased out-of-sample performance and in many instance p-values that are robust to data mining bias. All development is machine-learning based.
Develop and test market neutral (long/short) that trade portfolios of instruments.
Develop and test signal filters for any existing trading system.
Develop complex trading system architectures completely integrated with walk-forward or cross-validation testing
Committees (aka ensembles)
Oracles (intelligent committees with conditional differential weighting of components via gate variable)
Regime Specific Trading Systems via Event-Triggering
Develop optimal portfolios of trading systems based on individual models, committees, oracles based on the unbiased out-of-sample performance of each candidate and then walk-forward the portfolio to get its unbiased out-of-sample performance.
Create Signal Filters to eliminate just a few of the worst trades. Most signal filters retain just a few of the best trades. TSSB can do this as well but also permits the development of filters that retain most trades except the very worst.