The present invention comprises a method using cellular automata to process existing trading data from traders to generate unprecedented output that improves a wide range of future financial trading decisions and alerts for both individual traders and institutions. However, the method and system of the present invention is not a predictive system based on input of market data and it is not algorithmic. Rather, the method and system instead uses cellular automata logic to mimic human trading behavior. Based on the observations of human trading behavior decisions, the present invention generates an output of buy and sells decisions or simply an alert signal. This use of cellular automata as a basis for evaluating trading behavior provides a different basis for generating trading decisions and alerts and forms a new class of financial alerts over the prior art. The method of using cellular automata logic to process financial trading signals is therefore a paradigm shift in the logic behind trading decisions and alerts. It creates a new kind of technical analysis that features cellular automata interacting with human traders and data.
A first for the game, the replicator demonstrates how astounding complexity can arise from simple beginnings and processes – an echo of life’s origins, perhaps. It might help us understand how life on Earth began, or even inspire strategies to build tiny computers.
The Game of Life is the best-known example of a cellular automaton, in which patterns form and evolve on a grid according to a few simple rules. You play the game by choosing an initial pattern of “live” cells, and then watch as the configuration changes over many generations as the rules are applied over and over again (see “Take two simple rules”).
The rules of the game were laid down by mathematician John Conway in 1970, but cellular automata first took off in the 1940s when the late mathematician John von Neumann suggested using them to demonstrate self-replication in nature. This lent philosophical undertones to Life, which ended up attracting a cult following.
Life enthusiasts have since catalogued an entire zoo of interesting patterns, such as “spaceships” that travel across the grid, or “guns”, which constantly spawn other patterns. But a pattern that spawned an identical copy of itself proved elusive.
Above: Edna, the longest living soup currently known.
The Online Life-Like CA Soup Search is a collaborative online project designed to find interesting patterns in Life-like cellular automata by watching the evolution of random initial configurations (known as soups). In particular, random soups are evolved until they stabilize, and all the resulting stable patterns are uploaded to the server and catalogued. If the initial soup lived for an exceptionally long time then it is also uploaded to the server.