抄録
Evolutionary processes are one of the most widely studied methods for market analysis. Genetic algorithm (GA) and genetic programming (GP) are considered to be two most used evolutionary processes to find solutions. Many were reported successful but some were not. Looking at those of GA or GP generated technical rules, they have some computational forms consisting of variables, constants, market data, operators, functions and so on. Most important ones are the functions (or indicators) such as moving averages. Those are essentially and often directly based on the indicators themselves. This suggests that developing good technical indicators is essential even with evolutionary processes. Most of the currently used market timing indicators were developed when fast computers were not conveniently available. There should be many undeveloped indicators which should be suitable with computers. In this paper, new indicators called numerical composite indicators are proposed and tested. And it is also shown that different ways to apply indicators make some significant differences.
