Once a newbie found a trading strategy, once an experienced trader found a new trading technique or system, a test has to be done before launching it into the real trading account. The thing is that you would not send your troops to war before training. It's like a new weapon you just bought and you're not sure about its possibilities, you need to check them out. The same stuff is happening with trading strategies in the binary options market - before betting your own real money on it, you must check it out and provide several tests.
There several features for every separate trading system. It has to show profitability during a certain period of time, it has to be efficient enough just to avoid too many losses. At the same time, it has to fit your personal trading strategy, money management system and risk management rules. Moreover, there several different types of people from the psychological point of view. And every single type prefers a certain kind of trading strategy. So, all of the features above have to be taken into the count before pulling the trigger.
Another point of view is based on a simple assumption that markets always move in cycles, and history is aimed to repeat itself. In simple words, that means that if a trading system used to work in past, it would be efficient in the future as well. Therefore, before putting your own money on a table made of some wood, you need to test the strength of that wood. Every trading strategy has to be tested on historical data in order to get a result of its profitability, drawdown ratio, the number of losses coming in a row and the usability of the system in general. There are two ways of testing a strategy. First, traders can do that by visual inspection. Second, there is an automated approach.
It's worth noticing that both methods do not guarantee a 100% correct result. The main problem in the visual type of testing is that traders make mistakes from time to time like any other human. The automated approach of testing a strategy might mislead traders just because of several inaccuracies in the algorithm when uploading historic data. Nevertheless, the time spent for testing a strategy with both methods is an investment that could save you a hell lot of money in the future before placing bets on an algorithm that you don't even know how it works.
The visual testing suggests checking of trading signals based on historical quotes. In other words, you just scroll a chart on the left, shifting the period of time to the past and watch it closely in order to understand whether the chose strategy brings profitable trading signals or are they just fake. Then traders should also check such parameters as entry and exit points and levels in accordance with the trading algorithm, get those results in a notebook or a spreadsheet in order to analyse them after. Of course, it's recommended to test a strategy on a long period depending on the timeframe chosen. For example, an intraday algorithm based on the 5-minutes timeframe has to be tested for the last six months. The key advantage of this method is that traders will graphically and visually get used to the trading approach, developing a habit of discovering trading signals which is extremely important for profitable decisions. The experience and habit of right decisions is the key factor dividing trader on those who stay in the market making money and those who leave it with losses. At the same time, you can get a better understanding of market drivers and how the price action develops in different conditions, so that's also a useful experience.
The second type of testing trading strategies is an automated or mechanical one. As you could already guess, it's based on software that has to be installed as an additional plug-in to your trading terminal. The main idea is that traders can easily change settings and default parameters of that testing, as well as choose different trading algorithms. This kind of trading approach is also popular among traders who do not want to get involved in the too much time-consuming process of the market analysis. Another disadvantage of the automated software testing is that traders see the result only, without a basic understanding of what was happening during the trading process, why the algorithm made this or that particular mistake and what are the conditions when it does not work. You should remember one important thing. Strategies and trading systems work in a certain period of time when the market conditions and fundamental environment stays the same. Once it's changed - the algorithm stops working, creating troubles for traders who do not want to realise the key processes happening in the markets, hoping for a software to make money for them. Just try to think about a simple question: Why investment banks and institutional hedge funds continue paying millions of dollars to human employees if they have such great access to software and artificial intelligence? The answer is very simple. Software does not work in financial markets.
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