  Previous work, mostly published, developed two-shell recursive trading
systems. An inner-shell of Canonical Momenta Indicators (CMI) is adaptively fit
to incoming market data. A parameterized trading-rule outer-shell uses the
global optimization code Adaptive Simulated Annealing (ASA) to fit the trading
system to historical data. A simple fitting algorithm, usually not requiring
ASA, is used for the inner-shell fit. An additional risk-management
middle-shell has been added to create a three-shell recursive
optimization/sampling/fitting algorithm. Portfolio-level distributions of
copula-transformed multivariate distributions (with constituent markets
possessing different marginal distributions in returns space) are generated by
Monte Carlo samplings. ASA is used to importance-sample weightings of these
markets.
  The core code, Trading in Risk Dimensions (TRD), processes Training and
Testing trading systems on historical data, and consistently interacts with
RealTime trading platforms at minute resolutions, but this scale can be
modified. This approach transforms constituent probability distributions into a
common space where it makes sense to develop correlations to further develop
probability distributions and risk/uncertainty analyses of the full portfolio.
ASA is used for importance-sampling these distributions and for optimizing
system parameters.
