在做资本市场实证的时候如果样本的选取只保留当前在市场上的证券，那么那些被淘汰掉的证券就没有算进样本，导致证券的收益率高于市场的实际情况。如果实证的期限较长，退市的公司较多，生存者偏差就会比较严重

Survivorship bias is the logical error of concentrating on the people or things that "survived" some process and ignoring those that didn't. This can lead to false conclusions in several different ways. The survivors may literally be people, as in a medical study, or could be companies or research subjects or applicants for a job, or anything that must make it past some selection process to be considered further.

Survivorship bias can lead to overly optimistic beliefs because failures are ignored, such as when companies that no longer exist are excluded from analyses of financial performance. It can also lead to the false belief that the successes in a group have some special property, rather than being just lucky. For example, if the three of the five students with the best college grades went to the same high school, that can lead one to believe that the high school must offer an excellent education. This could be true, but the question cannot be answered without looking at the grades of all the other students from that high school, not just the ones who "survived" the top-five selection process.

In finance, Survial bias is the tendency for failed companies to be excluded from performance studies because they no longer exist. It often causes the results of studies to skew higher because only companies which were successful enough to survive until the end of the period are included.

For example, a mutual fund company's selection of funds today will include only those that are successful now. Many losing funds are closed and merged into other funds to hide poor performance. In theory, 90% of extant funds could truthfully claim to have performance in the first quartile of their peers if the peer group includes funds that have closed.

In 1996 Elton, Gruber, & Blake showed that survivorship bias is larger in the small-fund sector than in large mutual funds (presumably because small funds have a high probability of folding).They estimate the size of the bias across the U.S. mutual fund industry as 0.9% per annum, where the bias is defined and measured as:

"Bias is defined as average α for surviving funds minus average α for all funds"
(Where α is the risk-adjusted return over the S&P 500. This is the standard measure of mutual fund out-performance).

感谢各位啊！解释的很详细，多谢啦！

如何解决这个问题呢？有什么计量方法吗？