What Is Backtesting? A Definitive Guide (Plus Pros and Cons)

Updated 8 February 2023

Trading stocks often requires significant research and a lot of information on historical trends, prices and company data. Using certain methods, traders can test the viability of certain trades before posting them, potentially reducing the chances of placing a bad trade and increasing their Return on Investment (ROI). Understanding how to conduct backtests can help investors learn how to use historical data and other information to test trades before committing funds to those trades. In this article, we define backtesting, explain how it works, examine some pros and cons and compare it to forward performance testing for context.

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What is backtesting?

Backtesting is a method traders can use to determine how viable certain trades are before they commit to those trades. This can be especially valuable for potentially high-risk trades, as it allows the investor to determine the chances of a positive or negative outcome using historical data. The rationale behind this method is that any strategies or trades with historical success might work in the current time, and likewise, any strategies or trades with poor historical performance may perform the same.

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How does backtesting work?

To use this method, traders collect historical data on trading strategies or specific trades. They often collect data from various points in time to reflect different market conditions for a more accurate simulation. Some backtesting collects data on various stocks to test an overall trade strategy, and can even include bankrupt companies for greater context. If investors only collect data from companies that are currently operational, the results might be an exaggerated positive outcome. Once investors collect crucial data, they begin analysing the data for trends and historical information.

Traders may look at trading costs, the steps in each trading strategy, historical performance for different companies and the overall health of the stock during specific periods of time. This can give the trader a more complete idea of how well the strategy might work on a current trading prospect. For example, if the trader notices that trading tech stocks only in the final hours of the trading day seems to produce higher yields, they might adopt this strategy for themselves. Investors typically use advanced computer software to simulate trades and predict potential trading outcomes.

Pros and cons of backtesting

While backtesting is a common method of strategic planning for investors, it can offer both pros and cons, including:


Here are some of the pros of using backtesting:

Predicting potential Return on Investment (ROI)

One of the most significant advantages of using this method is that it can help investors predict the ROI of specific trades. Some investors only place trades when they're nearly certain the trade produces a certain return. For example, some investors might not place any trades unless they believe the trade can return at least 10% of the initial investment. Using backtests allow investors to more accurately determine whether a trade might produce a significant ROI and can even predict a percentage of return. Many investors depend on backtests to create their entire trading strategy and minimise losses.

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Reducing risk

Risk is an important factor when placing trades and can influence an investor's strategy and individual trading decisions. Determining the risk each investment represents with backtesting can help investors create a more accurate portrayal of those risks, which can help them avoid potentially bad trades. For example, an investor might identify through backtesting that buying penny stocks typically produces a negative return and might avoid those kinds of stocks altogether to minimise their overall trading risk.

Providing significant insight

Backtests allow traders to collect information and helpful insights into certain market conditions, trading strategies and other important data. This data can be crucial to creating more effective strategy and may not be available outside of backtesting. Backtesting software allows for realistic simulations of market conditions and trade information to also help new investors learn how to read charts, markets and determine trade performance. Veteran investors can also use this method to refine their strategies and even analyse their own historic trades.


Despite the advantages of backtesting, it does have a few setbacks. Here are some cons of using backtesting:

Potentially exaggerated or inaccurate results

The information investors collect using this method is primarily historic data, which may be incomplete or produce exaggerated or inaccurate results. For example, if an investor performs a backtest on a trading strategy that worked before recent regulatory changes in the market, the backtest might provide inaccurate results, since it can't account for the new regulations and how they might affect the market. Investors typically reduce this issue by not depending entirely on backtests for their strategy and using the information as more of a suggestion than a standard guideline.

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Possible over-confidence

With historic data suggesting the viability of certain trades, some investors might experience over-confidence. This occurs when an investor becomes too confident that a specific trade or strategy can produce their desired return and places the trade based on those emotions. Over-confidence can have negative results, but investors typically reduce those feelings by minimising the number of trades they make based on emotions. They use the data from backtests as a reference and understand it doesn't offer a guarantee of a positive outcome.

Possible discrepancies in data

Backtesting can sometimes create data discrepancies, where the investor analyses data that offers a skewed or incomplete view of trades or historic trends. It's important that investors consider each factor that might affect backtest results, including historic market conditions, regulations, the status of the company or its stock prices and the software they're using. By studying the historical market conditions and history of specific companies, investors using the backtest method can ensure that any information they collect has the proper context to provide a more accurate summary.

Backtesting vs. forward performance testing

Backtesting and forward performance testing are both evaluation systems traders use to test trading or strategy viability. The two systems have several differences, including:

Live markets

Backtesting and forward performance testing, or 'paper trading', differ in how they utilise different markets. Paper trading uses a computer algorithm to allow investors to place artificial trades in live markets to determine certain outcomes. The outcome depends on the system's specific logic protocols and the behaviour of the market. This allows investors to see how their trades have different effects in a live market without committing capital. Backtests also allow investors to work backwards, testing strategies and trades using historic data instead of live market data.

System logic

Each paper trading system has its own logic and algorithms that allow traders to simulate trades within that trading platform. For example, a stock brokerage company might create its own paper trading system for investors that follows specific logic for the company's trading practices. Backtesting occurs without these restrictions, subject only to the logic of whichever backtesting software the investor uses to simulate trades and strategies. These systems differ across different platforms and may produce different results with the same test.


Evaluating backtesting results and paper trading results requires different techniques. To understand backtesting results, investors typically need more information, such as market conditions at the time, regulations, company health and historic pricing data. Paper trading allows investors to place trades during a live trading day, allowing them to watch the trades perform on the market during regular hours. This changes how investors evaluate the results, as live results can be more accurate and effective and require less extensive research.

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Backtesing vs. scenario analysis

Scenario analysis is another technique for evaluating the viability of certain trades and strategies, but can differ from backtesting. Backtests use historic data, whereas scenario analysis depends on hypothetical data to simulate potential outcomes of trades and strategies. For example, a scenario analysis might reveal that if an investor commits $20,000 to a certain stock at the end of Q4, it could create a potential return of 20% by the end of Q1. Investors also use scenario analysis to examine the effects of more specific events or scenarios, such as a general market shift or change in market regulations.

Since scenario analysis depends almost entirely on hypothetical data, it can create inaccurate results. Some traders use scenario analysis as part of their main trading strategy to avoid potentially disastrous trades, while others use this method in combination with backtesting to determine the efficacy of new strategies. Combining hypothetical and historic data can produce more accurate and valuable results.

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