Albert Einstein’s famous definition for insanity — “doing the same thing over and over again and expecting different results” — is well adapted to the field of technical analysis and market timing. The continued application of good indicators to flawed data sets, while expecting different results, is as pointless in technical analysis as it is in physics.
Although there is an element of “art” in technical analysis and market timing commensurate with the skills and experience of the practitioner, the analytical ideal always should be to create objective results based on information derived from reliable data and good indicators.
With 20 Most Actives and New York Stock Exchange advance-decline (A-D) data inserted into comparative lines, we will show that the Most Actives series (MAAD) has reflected the “real” stock market more accurately, as expressed by big money, than the more widely used NYSE A-D series (NYAD) that employs inherently defective data. We will reveal how NYSE A-D data are statistically less reliable, despite modifications made in an attempt to eliminate deficiencies.
By applying this Most Actives methodology, market practitioners should find better opportunities in the stock market by identifying when and where informed money is focused, while using that information to realize greater profitability.
The A-D line has been a staple of stock market analysis since the 1930s (see “MAAD and NYAD,” below). The A-D line is created by subtracting declining issues from advancing issues and then by adding the net difference to a cumulative A-D line. When the majority of stocks is advancing, the line will rise. When the majority is declining, the line will fall. It is a popular indicator. Whether it is computed daily or weekly, A-D line data are reported by the major stock exchanges and then are published by the financial media.
One of the primary uses of the A-D line is as a divergence indicator. A negative divergence occurs when the market is approaching what turns out to be a major top and the A-D line consistently fails to confirm prices by moving higher also. If the market makes a series of lower lows and the A-D line refuses to make new lows also, A-D line action would indicate a positive divergence and a major market bottom.
Ideally, the A-D line should lead, or at least coincide with, key reversal points in the market. But theory and application have not always lived up to expectations. While the underlying premise is that analysis of A-D line trending is useful information, the problem with implementation has been that conventional A-D data are seriously flawed. Norm Fosback wrote in “Stock Market Logic” that the “A-D line is a theoretical nightmare.”
First, A-D data have been criticized because they include bond funds, preferred stocks, closed-end shares and other issues that are not pure equities. But if a scalpel is used to excise a particular issue, where should those cuts end? After all, the volume of all issues may better represent investor preferences. To expunge an issue and its volume is a lot like saying this vote or that vote in an election is not worth counting. At that point, data exclusion becomes increasingly problematic as new asset classes, such as exchange-traded funds, are added.
Second, exchange data, such as NYSE A-D data, are used to create an unweighted A-D line, like NYAD, which is then compared to a weighted price index like the S&P 500. On a particular trading day, IBM advances one point on 10 million shares, while a small-cap, low-volume stock, XYZ, declines one point on 500,000 shares. Using NYSE A-D data, the decline in XYZ cancels the advance in IBM.