Trading Systems that Adapt
We specialize in trading systems, trading software and trading signals designed to adapt to changing market regimes. Our trading systems are designed to predict the short-term trends of stock market indexes and stock index futures.
A combination of 'in-house' and commercial software is utilized to build our stock index and futures trading systems.
Trading systems must be capable of adaptation to continue to be effective during different market regimes.
Mechanical trading systems for predicting trends with an average trade period ranging from 3 trading days all the way up to 2 years have been developed.
Integrating our trading software within the BioComp Dakota application framework enables walk-forward adaptation of model parameters. Our advanced trading software utilizes particle swarm adaptation, k-nearest neighbor, wavelet and adaptive SHM algorithms.
Trading strategies based on trading systems with static parameters tend to be brittle and usually fail quickly.
Trading strategies based on adaptive trading systems are more likely to succeed. This is akin to the 'adapt or 'die' axiom.
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James Slack-Smith tweets his view on the short, intermediate and long-term trends of the SP futures contract based on his favorite trading system signals.
NOTE: Hypothetical or simulated performance results have inherent limitations. Unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not actually been executed, the results may have under- or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown. Past performance of our trading systems, trading software and trading signals, whether actual or indicated by simulated historical tests of trading strategies, is not indicative of future results.
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