A Look at Our Market Breadth Report In Detail

The concept for our Market Breadth Report was inspired by the work of Gerald Appel. Gerald Appel is a highly respected market technician, the inventor of the widely used MACD (Moving Average Convergence Divergence) indicator and author of numerous trading and investing books. In his book "Technical Analysis: Power Tools for Active Investors" he applies the concept of averaging daily market breadth readings for the overall market. In one of his trading methods he employs a 10-day exponential moving average of daily breadth. When that average reaches a certain level it is considered a market buy signal, when the average then falls below a certain level it is considered a sell (get flat) signal. His results were back tested from December 1970 to May 2004 and they are quite impressive.

Our service provides this 10-day exponential moving average of daily market breadth used by Gerald Appel for all 273 market sectors, as well as a 4 day simple moving average and a 20, 30 and 50 day exponential moving average! To be clear, this is not the breadth for a 4-day period, i.e. the number of stocks that advanced and declined over the 4 day period but rather the average of the daily breadth for the past 4 days. This is how all of our averages are computed. We measure the daily market breadth in our report as (A-D)/Total which means we subtract the number of stocks that declined for the day from the number of stocks that advanced and then divide that number by the total number of stocks traded in the sector that day.

Ready to try our Market Breadth Report yet?

So for example, lets say the HOLDRS Oil Services Trust Exchange Traded Fund OIH currently has 15 stocks in its holdings and 10 advanced today and 5 declined. The daily breadth would be 33.33% which is (10-5)/15 or 5/15. Lets say, the next day all 15 advanced, the daily breadth would then be 100%. Then on the 3rd day let’s say only 2 advanced and the other 13 declined, the market breadth would be (2-13)/15 or –73.33%. Then on the 4th day let’s say all 15 stocks declined, the breadth would be –100%. So, on the 4th day, the 4 day average of breadth would be the average of 33.33%, 100%, -73.33% and –100% which equals –10%.

We use exponential weighting for the longer averages because we are more interested in the recent data than the older data. Gerald Appel comments: “In their effect, exponential averages are fairly similar to front-weighted moving averages, which are adjusted by weighting so that more recent data assumes more significance in the average than past data. Front-weighting is employed by technicians who believe that recent events carry more significance than older events and want to reflect this in the type of statistical tracking that they employ.” This is exactly the premise we are working with in our Market Breadth Report.

There is often times a debate amongst market technicians as to which averages are best to use, simple or exponential moving averages. I think one correct answer to this question is whichever averages are most used and watched. It is somewhat common knowledge that many major financial institutions follow simple moving averages, such as the 50 day and 200 day simple moving averages.

But it is important to distinguish here between price averages and breadth averages. In the case of price averages it does make sense, in our opinion, to be very aware of the 50 day and 200 day simple moving average since it is so highly watched. But in general, it is not a common practice, as of yet, to monitor averages of breadth. So, our concern then becomes entirely focused on what is the most useful and recent information about each market sector, hence we use exponential moving averages.

Hopefully this is a more in depth explanation of our Market Breadth Report. We hope you will try it out for yourself and see what a great tool it is!

Although subscriptions are currently full for both our Daily Market Breadth Reports, the Bronze and Silver we are still offering our Weekly Report to the public for FREE!

See our Blog for more details.