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Sunil Hameed is a reporter with the weekly periodical The Fun Finance Times. Today, he is scheduled to interview a researcher who claims to have developed a successful technical trading strategy based on trading on the CEO’s birthday (sample was taken from the Fortune 500). After the interview, Hameed summarizes his notes (partial transcript as follows). The researcher:

• was defensive about the lack of economic theory consistent with his results.

• used the same database of data for all his tests and has not tested the trading rule on out-of-sample data.

• excluded stocks for which he could not determine the CEO’s birthday.

• used a sample cut-off date of the month before the latest market correction.

Select the choice that best completes the following: Hameed concludes that the research is flawed because the data and process are biased by:

A) data mining, time-period bias, and look-ahead bias.

B) data mining, sample selection bias, and time-period bias.

C) sample selection bias and time-period bias.

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Evidence that the researcher used data mining is that he was defensive about the lack of economic theory consistent with his results and that he used the same database of data for all his tests. One way to avoid data mining is to test the trading rule on out-of-sample data.  Sample selection bias occurs when some data is systematically excluded from the analysis, usually because it is not available. Here, the researcher excluded stocks for which he could not determine the CEO’s birthday. Time-period bias can result if the time period is too short or too long. Here, it is likely that the period was too short since the researcher used a cut-off date of the month before the latest market correction. Note: this could be an additional example of data mining.

We are not given enough information to determine if the researcher is guilty of look-ahead bias (which occurs when the analyst uses historical data that was not publicly available at the time being studied).

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An analyst has reviewed market data for returns from 1980–1990 extensively, searching for patterns in the returns. She has found that when the end of the month falls on a Saturday, there are usually positive returns on the following Thursday. She has engaged in:

A) data snooping.

B) data mining.

C) biased selection.

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Data mining refers to the extensive review of the same database searching for patterns.

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Which of the following is the best method to avoid data mining bias when testing a profitable trading strategy?

A) Increase the sample size to at least 30 observations per year.

B) Use a sample free of survivorship bias.

C) Test the strategy on a different data set than the one used to develop the rules.

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The best way to avoid data mining is to test a potentially profitable trading rule on a data set different than the one you used to develop the rule (out-of-sample data). A larger sample size won’t prevent data mining, and you can still data mine a database free of survivorship bias.