Benford’s laws tests on S&P500 daily closing values and the corresponding daily log-returns both point to huge non-conformity

The so-called Benford's laws are of frequent use in order to observe anomalies and regularities data sets, particular, election results financial statements. Yet, basic market indices have not been much studied, if studied at all, within such a perspective. This paper presents features the distributions S\&P500 daily closing values corresponding log returns over long time interval, [03/01/1950 - 22/08/2014], amounting 16265 points. We address frequencies first, second, first two significant digits counts explore conformance these five different (equal size) levels disaggregation. for either positive or negative cases. S&P500 showing huge lack non-conformity, whatever Some "first digits" even missing. causes this non-conformity discussed, pointing danger taking granted databases, whence drawing "definite conclusions". agreements with better returns. Such disparity finds an explanation set itself: inherent trend index. To further validate this, simulated calibrating simulations observed averages tested against laws. One that only but also standard deviation relevant parameters concluding about conformity