TradingSolutions Glossary

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Gain

The percentage that the equity has increased.

Gamma (Options Trading Usage)

The amount that the delta of an option will change for a one point move of the price of the underlying security.

Gamma Memory

A type of memory used in dynamic neural networks. Gamma memory is similar to an exponential moving average in that a percentage of each new value is combined with an opposing percentage of the previous value. Each additional memory tap does this with the value of the previous memory tap. This allows fewer memory values to be used to store more historical information, but may significantly water down the information in those values.

&  For help with neural network components, see the Advanced Topology Settings Dialog help.

&  For help with neural network topologies, see the Modify Field Dialog: Prediction Model page help.

Gaussian Mutation (Genetic Algorithms Usage)

A type of mutation used during genetic optimization. Gaussian mutation uses a bell-curve around the current value to determine a random new value. Under this bell-shaped area, values that are closer to the current value are more likely to be selected than values that are farther away.

&  For help with optimization, see Optimizing Signals and Predictions.

Gene (Genetic Algorithms Usage)

A single value or setting that is being optimized during genetic optimization. A collection of genes is called a chromosome.

&  For help with optimization, see Optimizing Signals and Predictions.

Generation (Genetic Algorithms Usage)

A set of chromosomes during genetic optimization. Each new generation is produced by modifying the previous generation in an attempt to highlight the characteristics that produced the best results.

&  For help with optimization, see Optimizing Signals and Predictions.

Genetic Algorithm

A method typically used for trying multiple solutions from a large set of potential solutions. A subset of the solutions are evaluated, then modified (evolved) in an attempt to find a best solution by highlighting the characteristics that produced the best results.

&  For an overview of how genetic algorithms work, see What are Genetic Algorithms?

Genetic Optimization

Using a genetic algorithm to find an optimal solution. See Genetic Algorithm above.

&  For help with optimization, see Optimizing Signals and Predictions.

Global Defaults

Settings that are used by the entire program unless another value is selected.

Group

In TradingSolutions, this term has multiple uses. Data can be placed in groups (also called subgroups) for organization and processing. Because of this, the portfolio as a whole is sometimes included when referring to possible groups of data. Function Definitions, Entry/Exit Systems, and TradingSolutions can also be placed in groups to make them easier to find.