XLF and Lag

On the above chart pair . . Qs on the left, IWM on the right in 5 minute bars. At a quick glance 3 feet from your monitor, the charts are virtually identical. They both fade off R1 on the opening bar, bounce off the PP 30%, then plunge back through the PP to hit S1 at 14:45, show a little hairy bottom at 15:00 and then return to PP levels in the last half hour of the day. While the range volatility was more pronounced in the Qs, the pivot action was a mirror image.

Now let's look at a comparison of the same 5 minute charts today for the XLF on the left versus the IWM on the right. XLF comes out of the chute just below R3, slides through R2 down to R1 and then bounces back and forth between R2 and R1 for the rest of the day, closing just below R2 for the day. Clearly a strong day and a strong close.

Over the weekend I suggested that the LRs and the weekly pivot study argued for XLF to outperform the other components of my little ETF basket. That proved not to be the case yesterday, but was clearly the case today with XLF up 6.5%, while XLE was flat, IWM lost 2.8% and the Qs lost 4.3%. XLF's outperformance may have been driven by the adoption of the bank nationalization plan with the decline in other indices a function of the probable impact of that $250B drawdown on those sectors. Maybe . . . but I really have no way of knowing for sure.

What's interesting to me is not the underlying causes for XLFs gain, but the fact that it happened. For some time now I've been working on a timing project I call Lag, Sway and Slide and the relative action in XLF over the past few days has been perfect example of what I would term "lag". Traders who use RSI, %R and CCI based trading systems know well that profits can often be increased with reduced risk by entering the trade several bars after the actual trigger signal. Exactly why this lag works is not apparent, although I could conjure up a number of possible theories. I suspect there is no single simple explanation, but rather a variety of intervening market forces that can delay or slow down momentum in the markets. The trick is knowing when your trading signal is valid and on a short term pullback and when your trading signal is false, which can be costly. Daytraders often utilize fractal signals to both expose and manage lag. Traders who focus on 1 or 2 minute bars routinely toggle to 5 or 10 minute bars to confirm technical trigger signals. A multi-timeframe view of the markets helps avoid the chop inherent in 1 or 2 minute bars while at the same time lending confirmation to trade signals and providing logical stop loss levels. While the 1 or 2 minute bars may trigger a trade, it is often the lagged confirmation of the 5 or 10 minute bars that actually provides the higher profit, lower risk signal.

I'll explore lag, sway & slide concepts in future posts along with some practical applications.