Market Breadth Primer: Broad Based Market Breadth vs. Custom Market Breadth
Broad Based Market Breadth are general statistics collected across a large group of tradable instruments with no specific focus. Custom Market Breadth refers to statistics collected on a specialized basket of tradable instruments with either conventional or special statistic measures. There are subtle differences between the two approaches. I will explain what the basic differences are in this article.
Do not confuse custom market breadth with market breadth indicators. Many people label their indicators derived from broad based market breadth data as custom market breadth which is a very confusing practice. The better sound bite achieved from meshing those words together misleads everyone into thinking that there is something customized in the statistics itself which is not true. These indicators derived from broad based market breadth data can be called market breadth indicators to avoid confusion.
Broad Based Market Breadth Characteristics
Most of the time, broad based market breadth are collected on a large basket of instruments. For example, the NYSE Advance Issues is the number of stocks traded at NYSE that closes above the previous close on a particular trading day. Since the stocks trade at New York Stock Exchange are completely diversified into different industries and other aspects, the market breadth data collected on these stocks is a general statistics. If the data collected has any predictive value, it will be generic across the whole spectrum of stocks traded at NYSE.
The main advantage of broad based market breadth data is that they are readily available most of the time. In United States, the major exchanges broadcast their own market breadth data in real-time so that market participants can track the information easily. This tradition, however, does not extend to other major stock exchanges in Europe or Asia. Investors interested in US equities are indeed lucky in this aspect.
Due to the consistent changes in the listing of stocks in the major stock exchanges, the broad based market breadth data collected are statistically inconsistent. The reading you get from a week ago on NYSE advance issues may include some stocks that no longer list at NYSE. By the same token, some new issues added to the exchange are affecting the advance issues reading. Since the components contributing to the statistic measures are not the same set of underlying components all the time, it leads to potential change in behaviour of the statistics collected.
Broad based market breadth are also known to be very volatile from one reading to the next due to the uncontrolled sample space issue. Most of the time, we can expect the most active stocks in an exchange on a particular trading day would be trading actively the very next day. For the lightly traded stocks, however, this is not the case. An illiquid stock may trade on a particular day and contribute to the market breadth reading on that day. However, there is no guarantee that it will show up the next trading day again. To complicate the issue further, remember statistics like advance issues is measured from a reference, the last traded price. For an illiquid issue, the last traded price could have happen several days ago hence providing a reading that is not really a reflection of the day to day changes.
In retrospect broad based market breadth data was functional because the stock markets were not as big and as diversified many years ago. The investment communities were not as sophisticated. Hence overall market health could be identified with some rudimentary market breadth data. They are now less useful and more error-prone.
Custom Market Breadth Characteristics
Custom market breadth data provides a focused measure of the pre-defined basket of symbols. It is by definition automatically overcome the weaknesses of the broad based market breadth.
One of the unique features of custom market breadth is the exact number of symbols that you are collecting statistics is known beforehand. There is no guess work nor surprise additional data. This feature removes the need of an opposite statistic measure most of the time. For example, if you are collecting advance issues reading on the S&P500 index components, you do not really need to collect the decline issues reading. The two statistics are complementary events to each other hence one of them is redundant. This property makes it easy to construct percentage based reading for comparison purpose across multiple baskets of symbols.
For certain specific types of statistics, like volume based readings, we still have to collect the data for complementary events because the extra information cannot be derived from just one of the complementary statistics. Using the same example mentioned above, advance issue volume and decline issue volume have the added information from the volume data which cannot be derived from just one of them.
Well Known Custom Market Breadth
Many people would assume that we do not have access to custom market breadth unless we construct that ourselves. Well, there are several widely used custom market breadths that are broadcasted by the exchanges.
First there is the Volatility Index, also known as VIX, which measures the implied volatility of the options traded near the current price of S&P 500. Since the measure is done on the S&P 500 options, it is indirectly bounded as a measure on just that 500 components’ combined behaviour. Thus VIX has many useful properties for the analysis of S&P 500 price movements.
The other well known custom market breadth is the Dow Jones Industrial Average Tick Index, also known as TIKI to many traders. The NYSE Tick Index is a broad based market breadth data while TIKI just monitor the 30 components of Dow. Some high-end data sources provide TIKI update in real-time right after every trade happened with any one of the components, making TIKI the fastest proxy for a fast moving market. For the other data sources, you are still likely to get TIKI real-time update faster than the NYSE Tick Index on a time polling basis.
Non-Standard Market Breadth Measures
When people talks about market breadth, they often think of the advance / decline issues, the total volume traded, put / call ratios, etc. These are the standard measures which were invented mostly back in the 1980s. They are quite simple in nature because the computation power at the time was very limited and the understanding of price discovery was also very limited. Most of these tools were invented mainly for end of day analysis only. They are not that useful in general for intraday market analysis.
Let’s consider one of the modern funds common stock buying / selling behaviour. As oppose to using just stock traders to go out in the market and making large size trades, which often result in very bad fills and directly impact the profitability of the funds, the large institutions have switched to use volume weighted average price (VWAP) algorithms during most trading days to automate the process of stock accumulation and distribution. The results is better average cost and reduced visibility of their intentions within the markets.
Such activity can be reverse engineered by measuring the accumulated up ticks and down ticks of the market with VWAP applied as a filter on the raw data. The result is a cleaned up picture like x-ray on the human body, where we can identify clearly if certain stock is being accumulated or distributed in large scale. Until these funds figure out new ways to hide their acts, it is quite easy to use non-standard custom market breadth to find out the collective intentions of the participants.
Custom market breadth is a heavily under develop area in financial market analysis. This makes it very efficient and powerful as a predictive tool. Firms I work with have been doing their own research in this area for a long time. None of them ever want to publish anything regarding custom market breadth analysis. Yet they are using these custom market breadth models they built everyday. It is a loud and clear statement how useful and powerful custom market breadth can be.