Quantitative Trading, a blog owned by Ernest Chan has a pessimist post about data mining. To be brief, the author writes that data mining is often useless for financial purposes, and gives an example with stock picking. To his mind, the reasons are the lack of historical data and the noise. To the denoising methods that exist, he responds that the overfitting problem persists. He certainly is true when writing that mining small quantity of data having a lot of relationships is not easy. Although I think it is not easy, I do believe there are solutions such as cross-validation, dimensionality reduction, etc. to obtain good results. Since I have no experience in the financial field, I ask your opinion about that question. So feel free to give your mind by posting a comment.