Before starting to trade, it is important to test your trading strategy on historical data. Traders call this procedure of picking historical data and see if the strategy was profitable backtesting. In order for this step to be successful, and not produce false results, historic data needs to be accurate. Although backtesting is an important step in developing a trading strategy, it is not the only step. Traders must forward test their trading strategy on a demo account after successful results on a backtest. In this article, we will talk about historic data and backtest. We will also discuss tick history and tick quality.
What is historic data?
In order to evaluate the trading strategy, traders have to test it on historical data. Historic data is price data for a certain period of time. High-quality historic data is key to evaluating how well a trading strategy would perform in a historical environment. Most trading platform programs have a backtesting feature inbuilt. If you are using the MetaTrader platform for backtesting this mt4 historical data should help to get quality test results. There are many websites that offer historic data for various assets for free. MetaTrader 4 and 5 have their own historical price data that can be downloaded automatically or manually when testing expert advisors or EAs. These little inbuilt features make it easier for traders to test their EAs without the need to search online for relevant data. But sometimes, it is better to download more accurate historical prices for better test quality. In this situation, paid sources could be useful. For beginners, free data is more suitable for playing with backtesting and finding out more about its basics. But finding good-quality historical data may become a challenge, especially when testing for longer historical periods of more than 10 years. In this case, try to find reliable sources with long-time experience. But it’s not only about historic data, but how accurate tick data is as well.
Quality of tick history
A tick is the smallest movement that prices make on live markets. Most often, it is 0.1 pip or 0.00001 points of change in currency pairs’ price change. But depending on the markets, tick size could be different. For Forex, tick data is important for backtesting for short periods of time, when the strategy is trading on a daily timeframe, tick data is of less importance, and vice versa for scalping strategies. It all depends on the trading strategy and timeframe in which it operates. This little detail can increase backtesting speeds in the MetaTrader strategy tester. Tick data has to be as close to real data as possible to make testing more realistic.
We will take examples from MetaTrader as it is a very popular and widely-used trading platform. Accurate tick data is important for scalper EAs but loses significance when long-term strategies are tested.
For long-term EAs, it is more relevant to use open prices only or any other option for maximum speed. Tick data also affects the simulation quality, with accurate data the quality of backtesting improves.
Importance of backtesting
Backtesting is a keystone for successful trading and must be conducted to develop a profitable trading strategy. After designing the outline of the strategy, traders then test it on historic data to see if it would be profitable if traded on historical data. This gives good groundwork for further improving the strategy. Also, it is very important to backtest a strategy, past success is no guarantee of future success and a forward test should follow. Forward testing is the opposite of backtesting, and it means testing the strategy on a demo account to simulate live trading.
There is one important challenge during backtest as well, it’s called overfitting and happens when all settings are adjusted to just a specific historic period. This can lead to providing great results for specific time periods, but the strategy will not produce similar results during live testing, giving the trader a false feeling of success.
To sum up our findings, accurate historical data is crucial for backtesting. Backtesting can evaluate a trading strategy’s pros and cons and give an overall overview of its performance on historic data. Tick data sometimes can be a determining factor for simulation quality when testing scalper EAs. For relatively long-term trading strategies, other options like open prices only could be more beneficial. Overfitting could happen if parameters were adjusted extensively on the specific time period, to avoid this try to test the strategy on a different period as well.