Note: A version of this article appeared on the Trading Markets site on 10/6/06.
Suppose you see the S&P 500 Index (ES) futures rise a full point in a short period of time on solid volume. Seeing the market rally, you jump aboard, only to have the entire move retrace.
In a nutshell, that move you saw on the screen wasn't real.
Yes, the index rose on buying, but what you didn't see on the screen was that the very same buyers of the index were selling the S&P 500 Index ETF (SPY). Once the futures moved a full point higher, exceeding fair value, they then sold the futures against a basket of stocks in the index to bring the futures and cash back into line. The moves were real, in the sense that they genuinely cost traders money. They're not real, in the sense that buying or selling did not reveal bullish or bearish tendencies on the parts of large market participants.
According to H. L. Camp, about 45% of all NYSE volume is now attributable to program trading. What that means is that the buying or selling you see on the screen may or may not reflect genuine demand or supply in the marketplace.
Most readers are familiar with the NYSE TICK, a measure of how many New York stocks are trading on upticks (at their offer price) vs. downticks (at their bid price). Let's say that, instead of measuring the number of NYSE stocks trading at their offer prices vs. those trading at their bids, we simply focus on the Dow 30 Industrial stocks and investigate how many of them are trading bid vs. offer. The resulting statistic is called TIKI and, it too, can be viewed as a sentiment measure. When Dow buyers are aggressive, they will be willing to transact at the stocks' offer prices, and you'll see TIKI values skyrocket above +20. When Dow sellers are aggressive, they're willing to bail out at the stocks' bid prices and TIKI will plunge below -20.
Because the Dow stocks are quite liquid and trade frequently, the TIKI moves much faster than the NYSE TICK. Its values are also distributed very differently from the TICK; TICK and TIKI correlate significantly (around .60), but hardly perfectly. The majority of variance in TIKI cannot be explained by the general buy/sell sentiment captured by TICK. Something else, apart from general market buying or selling impacts TIKI values.
The reason for this is that TIKI is highly sensitive to program trading. Whenever a program is executed that calls for the simultaneous buying or selling of a basket of stocks (arbing stocks against index futures would be a common example), TIKI values will shoot very high or very low. The Dow stocks, being liquid, are frequent components of such stock baskets. When the Dow stocks move in unison, it is often because programs are being set off.
One way we know this is by looking at the distribution of TIKI values on a 10 second basis. The odds of a very high number of Dow stocks upticking or downticking at exactly the same time should be quite small if we assume that there is an even probability of the next tick being an uptick or downtick in each issue. What we see, however, is many more extreme values than would be predicted by chance. These bulges at the extreme are the result of systematic buying and selling by institutions, often as part of arb (non-directional) trade.
If you get that idea, then it will make sense to you that absolute TIKI values are not especially helpful in gauging the sentiment of the market. TIKI can soar or plunge, simply because institutions are buying or selling stocks at the same time that they sell or buy index futures. It is the correlation between TIKI and price that is crucial. When TIKI hits extremes and price is moving in a correlated fashion, we know this is part of directional trade--not arb.
So let us take a moving correlation between TIKI and price change in the S&P 500 Index (SPY). I have cumulated each day's TIKI values, adjusted them for a zero mean, and correlated TIKI and daily price change over a moving 10-day window going back to 2004 (N = 682 trading days).
The average 10-day correlation between daily TIKI and daily price change in SPY over this period has been .63. When we have a strong TIKI/price correlation (above .80; N = 108), the next ten days in SPY average a gain of .73% (73 up, 35 down). That is significantly stronger than the average 10-day price change in SPY of .26% (397 up, 285 down).
When the TIKI/price correlation is relatively low (below .50; N =133), the next ten days in SPY average a loss of -.41% (57 up, 76 down). That is significantly weaker than the average 10-day performance.
What this suggests is that, when TIKI is well correlated with price, the market tends to outperform. When TIKI is poorly correlated with price, the market tends to underperform. This pattern, I have found, is also present at intraday time frames. A reasonable explanation for the findings is that low correlation periods represent occasions of high program/arb trading, whereas high correlation periods represent periods of high directional trade.
We last saw very high TIKI/price change correlations on September 21 and 22, when the values were about .88. The recent price strength in the equity markets have followed from that. We are now at relatively average levels of correlation (.60). Much of May and June--a period of correction--featured very low correlations.
The moral of the story is that markets today are different than they were a decade or two ago. You can't necessarily trust what is on your screen or what your price-based indicators are telling you. Who is in the markets ultimately impacts what markets do.
Brett N. Steenbarger, Ph.D.