 A quantitative trading system determines buy or sell decisions to minimize risks or to enhance your portfolio based on pure mathematics and statistics. Some trading systems are even designed to the extent of eliminating human intervention. These kind of quantitative trading systems are used with algorithmic trading. Unlike a qualitative trading system, which bases its decision on human insight and analysis, a quantitative trading system relies on software with predetermined values and parameters to make its trading decisions. As opposed to active trading, the software itself will track trends and follow price and volume movements of different securities or assets to uncover opportunities that’s deemed by the software as precedent to successful and profitable trades. What are the Advantages of a Quantitative Trading System? There are reasons why large hedge funds and mutual funds use quantitative trading systems to make trading decisions. Here are some of the distinct advantages such system has over qualitative trading system: ● It eliminates raging emotions in a trade. Emotion has always been and will always be the biggest deterrent of a successful trading career for aspiring traders. And even the best trader is still plagued by emotions during a crucial trade because traders, before anything else, are still humans. Even if you have the best trading strategy, if emotions intervenes at the most crucial point of a trade, all the best laid plans can go awry. Quantitative trading systems eliminate such risks. It makes its trading decisions based on mathematically tested ideal condition. Thus, no emotions are involved in the executions of trades. ● A quantitative system of trading can track details that humans may not be able to identify right away. Such minute details can go both ways: it can prove to be an opportunity waiting to be mined or it can be risks to your positions. In either case, it’s best to identify these information the moment it presents itself and act upon such information appropriately. It’s an edge that quantitative trading systems have over qualitative trading systems. ● A good quantitative system is tested and validated. It does not merely rely on conventional trading wisdom. No bias or subjective analysis is ever introduced in the validity of the system. Therefore, you rest your trading confidence (as far as it is possible to have that) on quantifiable and tested values. Methodology of Devising a Quantitative Trading System Quantitative trading models and systems are built following a scientific process. Here are the basic steps and methodologies in devising such a system for profitable trading. Design Everything starts off with a set of hypotheses and conditions that are believed to be precedent to a profitable trade. The hypotheses must include both models as well as data in its outline. Models refer to rules that identify a pattern which will signal an ideal condition for a profitable trade to be executed. It includes parameters for entries and exits of positions; trade size and the assessment of risk. There are many conditions that may trigger an exit of position. For example, exits may be based on or a combination of holding period, profit target, trailing stop and maximum stop loss. On the other hand, data refers to the price and volume movement of a certain stock or asset. This, as well as the model makes up the initial design of the system. This initial step of formulating a quantitative trading system is the step with the most human intervention since everything initially starts with hypotheses. Whether it works or not remains to be seen in the succeeding steps. Testing An excellent trading system is something that undergoes a battery of tests. A designer can use trading software that offers historical data for this purpose. All components of the system – the rules of entry and exit points as well as trade size - should be thoroughly tested. For example, you want to test the stop loss since it’s one of the components of the exit conditions. You need to first define all the rules of the system such as entry conditions, data series and exit rules. Through a series of tests, you need to make all components constant and vary only the stop loss level. You would want to start with a stop loss level such that none of the trades will be triggered to exit by the stop loss. You can then adjust the level such that all the trades are triggered to exit by the stop loss. The developer has to record the performance of each trade at different stop loss levels. Testing provides the trading system designer the opportunity to tweak and develop every component of the system. Proper and thorough back-testing eliminates human biases in the face of numerical evidence. Validation In testing, the rules and parameters are modified to develop the most robust system. In quantitative trading systems validation, the developer needs to check if the system will detect different patterns and show consistently favorable results on different market conditions. To do this, the developer has to subject the system on different data that has not been used during testing or out-of-sample data. This way, profit is not overestimated nor risks underestimated.
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