Decision Table Based Analysis of Trading Models

This paper presents a decision table based-methodology to analyze trading models. There are many trading systems available but mostly do not work. Ninety percent of traders lose money including those using professionally developed systems. The same system that works for one trader may not work for the other. Where is the problem? The problem is in execution. The success of a system depends upon the person using it. The market movement is very complex and it is driven by many factors. It is not possible to fully automate a system. Human interaction is necessary and that is where the problem comes. Trading is a game of fear and greed. Every trader is different because people manage the emotions of fear and greed differently. The best way to succeed in trading is to use a system developed especially for the user. This paper shows how to develop such a system. The paper starts with an overview of a trading system and then develops use case models based on the user requirements. It introduces three technical indicators. The information about the system is stored in decision tables which help to program and execute the trading logic. The model tells when to buy and when to sell. It discusses trade management as well as risk management. It is dynamic and it can be adapted to individual needs and risk levels. It can be implemented using MS Excel and Visual Basic