Divergence Analysis

The year was 1985 and I considered myself adept at technical analysis. I continued to see the lag effect from technical analysis techniques, and wanted something better. I wanted to develop a systematic approach to market entries/exits. I had worked at using raw volume data on two previous occasions, but it was just too volatile to use. I had to develop some math to “calm” this data so it could be used in analysis. Working on my own (mostly in the small hours of the night) I began developing an algorithm that would incorporate raw volume data. My tools were a pencil, a calculator, and many ledger books (the kind accountants used to use). I would graph the results (yes, on graph paper!) and see how it looked relative to the price graph of the S&P. Only after I totally eliminated price from the input and the algorithm that I began to see on the graphs what I had been searching for. A leading indicator was emerging that would basically mirror price behavior—except at tops and bottoms. This is where it would diverge from price behavior, and these divergences marked the turning points by prices. The development of this, and several other indicators, using like techniques and methodologies took me from 1985 to 1987. In 1989 and started Divergence Analysis Inc. I learned a lot under fire working with heads of some top hedge funds of the day. In all these 27 years, not one decimal point has been changed from my original algorithms. Every indicator we have is derived from one of these two input streams. The synthetic volume data is what we developed around 2004, so we could use this same methodology (we call moneyflow) to other markets where raw volume data was unavailable. Now we could apply our systematic indicator approach to all markets such as bonds, currencies, individual stocks, options, futures, and commodities. We built all of our models to be “visually adaptive” for the trader to use, efficiently trading any asset in any time frame.