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Occasional comments on technical analysis investing, evolutionary computation, genetic programming and the Genetic System Search for Technical Analysis program.

Often a set of investment rules will generate conflicting signals. For instance, it might call for an Enter Long trade on the same bar as an Enter Short trade. What is to be done in those cases? The governing directives are often called the Order of Execution. The Genetic System Search for Technical Analysis program, Equis MetaStock and others use the following rules to resolve any signal conflicts.

If you use the MetaStock Enhanced System Tester (EST) in the development of your trading system, it is important to verify the results. Some configurations, for instance, may result in simulated trades that you would never execute. The EST may both buy and sell a stock at the same time. That results in two additional brokerage fees with no possibility of profit.

It's important to construct a set of investment rules that generate signals in which you are confident. Imagine that you're using a system in live trading and the last five trades have been losers. Your trading capital is depleted and your confidence shaken. Are you going to make the next trade without question?

Consider the case of a huge drawdown during an open trade. Your profit has turned into a loss. Will you stay with the current rules or jump ship? Can you hold on for a vague promise of a profitable outcome in a few days or weeks? That's unlikely.

Tempus Fugit

The investment market moves continuously. Opportunities for profit appear regularly. If you're spending time developing a trading system, you are missing these prospects. What is your development time costing you?

Take Advantage of the Available Tools

Modern techniques such as the algorithms employed in Genetic System Search for Technical Analysis shorten the path to active trading. Take advantage of the tools available. You don't even have to use the fastest machine with four monitors arrayed in front of you. Leverage the power of the computer.

Exhaustive Search Method

In the construction of technical analysis trading systems one might use a brute-force or exhaustive search for the optimized set of rules. You select a list of indicators and, for each indicator, the range of possible values.

As an example, one indicator would be the simple moving average. There are versions of that average for the open, high, low, close and volume values at each trading bar. Each of those versions must be tested with a range of periods. One might build tests for each period from 5 to 300 bars.

All indicators must be tested with each of the possible variables. That's everything from the 5-bar, simple moving average of the open to the 300-bar simple moving average of the volume. Now multiply that by the number of bars in your stock's data file.

So far you have built the tests for just one indicator. The number of test combinations quickly explodes.

The genetic programming engine inside the Genetic System Search for Technical Analysis program uses several operations to arrive at a set of technical analysis trading rules.

Some charting programs use a value for margin rates that may differ from your broker's specification. For instance, your broker may require a 50% margin to enter a short position. In the Genetic System Search for Technical Analysis program Brokerage Configuration window and in older versions of Equis MetaStock, use the same value. In the Equis MetaStock Enhanced System Tester, you would enter 150%. See the full explanation of this discrepancy in the Equis MetaStock Knowledge Base.

Many investors study the movement of and the statistical properties of market prices and volumes and base their decisions upon such technical analysis.

A Typical Technical Analysis Investment System

  • Enter a long order when the closing price of the stock is greater than the 30-day simple moving average of the closing price.
  • Close a long order when the closing price of the stock falls below the 10-day weighted moving average of the low price.

The construction of an successful investment system is often time-consuming and must be performed periodically as market conditions change. Furthermore, a system which works well for one stock may not be profitable for another stock.

Because of the number of possible indicator terms multiplied by the number of variations of each indicator, a genetic programming search may be efficiently employed to quickly find investment systems.

Subcategories

The use of technical indicators

Comments on the operation of the GSSTA Program

On the development of security investment rules

A form of evolutionary computation