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Look-Ahead Bias

A type of bias that occurs when a study or simulation relies on data or information that is not yet available or known during the study

What is Look-ahead Bias?

Look-ahead bias is a type of bias that occurs when a study or simulation relies on data or information that is not yet available or known during the study or simulation. It generally leads to inaccurate results from a study or simulation. The incorporation of fundamental data that wasn’t available at the time of study delivers biased results that are close to the desired outcome but not to the real outcomes.

 

Look-Ahead Bias

 

In finance, look-ahead bias is commonly encountered in trading strategies and various financial models. If an analyst commits a look-ahead bias in a trading strategy, testing the strategy will likely to return the unreasonably positive results. However, the real application of the strategy is likely to deliver dramatically different results from those obtained during the testing process.

One of the issues with look-ahead bias is that it is reasonably complicated to indicate during backtesting. Backtesting is a process of applying a model or a simulation to historical data to assess the accuracy of a model or a simulation.

In some cases, backtesting cannot signal that the model is biased. However, if during backtesting, the model returns the exceptional result, it can be a red flag that there is something wrong with the model. Many finance professionals involved in the development of trading strategies carefully review the strategies that indicate the returns above 10%.

The best solution to avoid the look-ahead bias is a thorough assessment of the developed models and strategies.

 

Example of Look-ahead Bias

Let’s consider that you work as a quantitative analyst at a hedge fund. You’re working on the development of a new trading strategy for equities. Your model assesses the relationship between the release of quarterly earnings reports and the stock price.

The main assumption behind your model is that the stock price reacts to earnings reports. However, during the backtesting of the model, you assume that the company’s earnings reports are released on the same date when the fiscal quarter closes.

The situation is a classic example of look-ahead bias, particularly when the quarterly earnings reports become available only one month after the end of the quarter. Therefore, your backtesting incorporates the information that’s not been available during testing time. Thus, the results of the backtesting are likely to be inaccurate.

 

Additional Resources

CFI offers the Financial Modeling & Valuation Analyst (FMVA)™ certification program for those looking to take their careers to the next level. To keep learning and advancing your career, the following resources will be helpful:

  • Anchoring Bias
  • Belief Perseverance
  • Confirmation Bias
  • Hypothesis Testing

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