Pivot Price Target Based Historical Investigations

As blog readers know, I post each morning before the market open a series of proprietary price targets for the S&P 500 Index (SPY). These Twitter posts summarize the prior day's Pivot level (an approximation of the day's average trading price), as well as three upside targets (R1, R2, R3) and three downside targets (S1, S2, S3). The targets have been empirically derived to adjust for recent market volatility so that, back to 2000, approximately 75% of all trading days will hit either R1 or S1; 50% will hit either R2 or S2; 33% will hit either R3 or S3.

Days--and periods of days--where we don't hit any of these targets are range bound days. These tend to cluster, given serial correlations of volatility. Thus we'll have periods of time in which we hit one or more targets and periods of time in which we'll stay closer to daily pivot levels. Much of the skill of trading, across any time frame, is identifying when we're in a directional market environment (and thus likely to hit the price targets) or a range environment (and thus likely to oscillate around pivot levels and/or volume-weighted moving averages).

Once we define the pivot and price target levels for a particular day, we can ask some rather sophisticated questions. For instance, if we hit R3 or S3 in yesterday's trade, what are the odds of hitting the R1 or S1 level today? If we do not hit either R1 or S1 in today's trade, what are the odds that we'll have a directional move (i.e., one that hits one or more price targets) tomorrow?

Notice that, the segmentation of market moves into R1/R2/R3 and S1/S2/S3, each adjusted for that market's level of volatility, provides us with an objective measure of a day's directionality. We can then ask whether stronger up or down days (those that hit R2/S2 or beyond) are more likely to lead to reversal than days that only hit R1/S1.

Such investigations are likely to uncover trading patterns that provide a possible edge to traders. For example, did you know that the market two days from now (e.g., Monday's market) has a 43% chance of touching today's (Thursday's) pivot level? If we factor relative volume into the mix, those odds rise substantially. Knowing that we have high odds of a range market over a swing trading period could be quite valuable to both day traders and those holding overnight.

To get even more ambitious, imagine that we calculate similar pivot and price targets for various sector ETFs and stock indexes. We can then ask such questions as, "What happens when the S&P 500 Index touches R1/S1 today, but financial stocks (XLF) do not hit their R1/S1?" If a sector hits its R1 early in the trading day, what are the odds that the S&P 500 Index will follow and hit its R1 target? Do certain sectors tend to lead the S&P 500 in hitting their targets?

All of these investigations offer potential decision support for traders, and Twitter is an ideal mechanism for blasting the results of these investigations to traders in real time. More to come--
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