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In the modern financial market, traders constantly come across efficient techniques to make the best investment choices and maximize their profits while limiting their risk of loss. Backtesting is an effective tool that makes use of the historical data of the asset trading activity to provide complete results regarding the strategy that was used.
The main purpose of using a backtest is to provide traders with a clear view of the investment strategy results that worked effectively in the past and will possibly work the same in the future. Conversely, if a strategy performed poorly in the past it may have the same results in the future.
In this article, we will analyze how backtesting works as well as the criteria that should be adopted by traders to implement this mechanism in their portfolios. Moreover, we will list the benefits and risks the backtesting may hide and explain why it is an important tool for investors.
Every trader who wants to make correct investment decisions and achieve the highest profits from their trades should consider including backtesting in their portfolio. Any trading strategy that can be applied in the financial market can be backtested using historical data. Thus, a user can study and analyze those statistical backtesting results and know if the trading technique they have chosen will be profitable.
What is important in backtesting is to understand the behavior and performance of a strategy in different periods and markets. Thus, when a trader decides to backtest a trading strategy not only does he determine its accuracy without risking his capital but also adapts his investment choices in a risk-adjusted environment. Moreover, a significant characteristic of backtesting is that it can be done either using automated software or through a free demo trading account that helps investors try a trading strategy without wasting time and money.
Backtesting works as a mechanism that can help traders to avoid the risk of losing actual capital and boost their trading activities. If by using historical datum a strategy carries out good results then it may give good returns. Conversely, if it gives poor results it is more likely to perform badly in the future.
Backtesting is considered to be one of the most important mechanisms in the trading market. This is why it plays a crucial role in developing an effective trading strategy that traders can optimize without any risk and spot any theoretical or technical errors. Moreover, they can test any strategy without any trading costs and improve the viability of their trading.
Before applying any trading strategy to the live trading it’s possible to implement backtesting to find out if it is suitable to be used with real money and whether it may lead to high profits, or if the trader should give up on it since it may lead to a losing trade. Moreover, a trading portfolio embodies various strategies that have different characteristics, strengths, and weaknesses. Thus, by backtesting each trading strategy, users can know when it is more profitable to deploy each of them better and under which market conditions they may lead to a high cumulative return.
As mentioned before, backtesting a trading strategy by using past data can give traders information about its profitability, the dangers that may be hiding behind its use as well as the future result by adding this strategy to their portfolio. In the modern trading market users can utilize free demo accounts on trading platforms to backtest their strategies by using historical data, various indicators, and other market data to take accurate indications of this strategy. Moreover, backtest can provide a competitive advantage in the live market against other traders showing if the chosen strategy can be more effective in comparison with others.
Backtesting a trading strategy can show various information, such as which is the optimal risk per trade, and in which markets this strategy can be implemented more properly. Moreover, backtest is a mechanism that through a sterilized safe environment traders can use virtual funds to see real-time results of their chosen strategies and conclude if it is the one that suits their needs and goals.
Backtesting a trading strategy is an efficient tool that comes with many benefits. However, it has some drawbacks as well. Thus, any trader before using backtest should be well informed about the pros and cons so he will utilize this testing mechanism with the highest success. In the list below are mentioned the most important characteristics of backtesting.
Pros of Backtesting
Risks of Backtesting
A trader should always be aware of the risks that he will take when choosing a trading strategy and implementing it into his portfolio. Although backtesting uses virtual funds and the loss is not real, users need always to remember that the results from backtesting a trading strategy may not always coincide with those in the real market.
Backtest is an efficient procedure that helps traders to spot the weak points of their chosen strategy, test its adaptability, and adjust it to their needs without any risk involved. Of course, when a trader decides to backtest a strategy his main concern is to use impartial data to extract reliable and transparent conclusions.
However, unbiased data is not always easy to be found in the real financial market and most times the use of biased information may lead to distorting the model’s performance. There are several types of biases that may influence the reliability of the trading strategy that the user may apply. Some of those biases are listed and briefly explained below.
Before entering the market, traders have to decide which type of strategy or the combination of trading strategies they will use. There are no special conditions on which strategy should be backtested. However, some real-time market criteria should be taken into consideration before applying a trading strategy. A bearish or bullish market, the type of asset that is traded, the risks that may lurk, the potential profits, and many more, are some factors that influence the performance of the trading strategy.
The most important is to backtest any strategy before using it in the real-time market. Moreover, it is essential to test if the chosen strategy is compatible with the current trading models of the market and if it will perform the same and give profitable results.
After a trader has decided on the strategy that fits best to his portfolio and his plans, he needs to choose the type of asset on which the strategy should be backtested. The most reasonable is for the trader to choose the asset that is in his plans to invest on with real money. For example, if the asset that the trader is interested in is a currency pair, he needs to find and download data that are referred to this exact pair and run his model over it.
However, there is a possibility of not finding the eligible data to backtest a trading strategy. In this case, a trader can find and select an asset that is closer to his needs and has similar behavior to the ones in his portfolio. In that case, traders need to have in their minds that small adjustments are necessary to be done so the results from the backtest will be viable and legit.
Once a trader has backtested his strategy on his asset’s historical data, he needs to be only aware of factors such as the market’s volatility, the asset’s seasonality, as well as the demand and supply. Moreover, if traders choose to trade with more than one strategy and with a variety of assets (such as a set of stocks), they need to collect sufficient data and form a representative sample so they will backtest each strategy with the set of the asset.
After traders have decided on their strategy and the asset they will invest in, it’s time to backtest their trading strategy. One of the biases that one should be aware of is this that comes from optimization. The optimization bias, also popular as curve-fitting, appears when traders are simulating their strategies and they’re trying to make them bring more profitable results by adding additional specifications.
When traders try to correct the mistakes of their strategies with artificial parameters so they will get more satisfying results they are led to fake statistics about their strategy. Thus, when they put it to work in the real world the wrong insight about the expected results can lead to poor performance and high potential losses.
Another important bias that traders need to be aware of is the look-ahead bias which can cause a wrong apprehension about data that is not already known and the trader implements them in his backtesting either accidentally or on purpose. The look-ahead bias can be caused by various reasons such as data that are available after the model is being executed, a technical bug in the software that is used, etc. For traders to avoid such problematic situations, they need to check twice the data that they used to backtest their strategy before they go live.
Except for the biases that are most common to appear, more types can influence the trading strategy’s profitability. Some of those are the survivorship bias, the psychological tolerance bias, etc. The first may appear when a trader is using data that don’t represent effectively the assets that he will be trading with but only a range of that dataset. The latter is performed when the backtest happens for a short-term trading period but his real trading strategy is long-term.
A very important step after making your data bias-free is to properly choose your backtesting software. Of course, there are brokers and various platforms that use already developed backtest programs that offer security and higher assurance since they are already tested and have been certified that function properly. However, some traders may have advanced technical skills and can develop a backtesting mechanism by writing scripts in one of the programming languages. When developing something on your own don’t forget to implement some factors like possible commission costs, various trading costs, etc.
Once a trader has decided on the strategy he wants to embody in his portfolio and has oriented on the type of asset he wants to trade with, he needs to proceed with backtesting. This mechanism, as mentioned before, needs to gather some specific historical data, such as the asset’s price datum, the interest rate, etc. Thus, to proceed with the asset’s performance testing, traders should specify if they will be a long-term or short-term trading period.
Below are listed some of the most basic steps that a trader needs to follow to carry through with backtesting a trading strategy.
By accomplishing the last step of backtesting and having the percentage return as a result, traders will have a complete idea of how successful their strategy is or not. However, this may not always be the correct way to predict the future performance of a strategy and traders need also to proceed in forward testing it in the real-time market.
When a trader decides to backtest a trading strategy he can use various mechanisms. However, two main backtest tools are widely used among investors, the trading platforms and the coding libraries. Each of those useful tools has its characteristics and can be used by any trader for implementing different strategies.
The trading platforms are efficient instruments traders can use to backtest their trading strategies with different assets. It is the most widespread backtest mechanism and is used not only by new investors but also by the most experienced ones. Moreover, some trading platforms may include a build-in analysis, and taking advantage of the high data availability a trading platform can boost a trader’s strategy.
However, there is a variety of trading platforms that implement the benefit of the backtesting tool. Thus, depending on the trader’s investment portfolio as well as his technical knowledge and how user-friendly each platform is, he can choose the most suitable to his needs and capabilities.
For more experienced traders that also have the technical knowledge to develop their own backtest parameters, there is a variety of coding libraries, that they can use to write a backtest script. Thus, using Python, C++, C#, and other languages a trader can develop a backtesting script due to his trading logic. However, backtesting software is not a necessity. Sometimes, investors may use a simple technical analysis tool combined with an indicator and some historical data to create a chart and monitor simple statistics.
When analyzing the performance of a strategy, traders need to always have in mind that they need to analyze the returns of their trading strategy by comparing it with the risk that comes with it. For example, if a trading strategy has high returns but also hides high risk, it may deceive and push the trader to more risky options and higher losses. To avoid that, traders need to choose a strategy with satisfying returns and at the same time with reasonable risk exposure.
Moreover, traders need to include in their scenario analysis the level of volatility and always monitor its fluctuations. Traders need to adjust their trading orders according to their portfolio volatility and be aware of periods of high volatility due to a backtest. This can be translated in the real market as a sign of awareness that may provoke the trader’s stop-loss or take-profit orders.
Last but not least, a very crucial factor for traders to keep their investments safe is to define the level of dependence on their assets’ success. If there is a high correlation between them, a trader’s portfolio is considered to be exposed to any risks and vulnerable to market shocks.
Backtesting a trading strategy is an efficient tool that helps traders to have a more complete idea of the trading strategy they need to follow. Moreover, it offers the chance to understand if a trading strategy will be successful in the financial markets. Backtesting has become a necessity in the modern market, helping to avoid high losses and high-risk exposure. Most traders, before entering the market, backtest their strategies so they will optimize them in a safe environment and improve them. However, it’s crucial to be always aware of the pitfalls that this mechanism can hide so you will be able to adjust your investment decisions and trading strategies in the best way in the live financial market.
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Maxim Bohdan
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