From the February 01, 2008 issue of Futures Magazine • Subscribe!

Pinpointing entries across time frames

When trading highly leveraged auction markets, it’s critical to stay on top of changes in the market environment with a strategic management approach that continuously reviews and enhances all aspects of a trading program. As you develop this process, you’ll be able to assess, mitigate and reduce your risk on a trade-by-trade basis.

Strategic Management describes this practice. It is a methodical feedback process that takes current market information and system performance and uses it to adapt a viable trading strategy. Formulation is the creation of the strategy. Implementing is the process the trader must undergo to accomplish the trading mission. Eighty percent of traders fail in the execution stage due to a failure to link the mission and strategy implementation.

One missing piece is often a well-constructed argument that exemplifies legitimate market situations. Traders are best suited by identifying and implementing leading indicators that seek to increase the probability of making a winning trade prior to entry, while conforming to the natural flow of the market and trading in the same direction of the larger trend.

The process for identifying leading indicators begins by pinpointing the essence of the underlying instrument itself. According to, essence is the “intrinsic or indispensable properties that serve to characterize or identify something, the most important ingredient; the crucial element.” The essence of the market is composed of money flow, volume, open interest, price, support/resistance and volatility. Now, all we need to do is determine how to measure that essence, and we should find ourselves with a high probability of entering a winning position.


The Herrick Payoff Index (HPI), developed by John Herrick, displays the money flowing into and out of the market through the fluctuation of volume, price changes and open interest. Money is considered to be flowing into the underlying instrument when HPI is above a zero line, creating a bullish indication. Money is considered to be flowing out of the underlying instrument when HPI is below the zero line, establishing a bearish sentiment.

Divergence between price and the HPI line is a key development. If HPI is decreasing and prices are increasing, analysis suggests the uptrend will reverse. If HPI is increasing and prices are decreasing, analysis suggests the downtrend should reverse.

The fluctuation of prices can be statistically assessed through the use of regression analysis, and standard deviation.

Regression analysis sounds complicated, but in our application, it is quite simple. Linear regression, sometimes called simple regression, can use time as the independent variable, or predictor variable, to forecast price as the dependent variable, or predicted variable. Linear regression is much more valid and less lagging than moving averages.

Standard deviation is a measure of the dispersion of a set of data from its mean. The more spread apart the data is, the higher the deviation. The volatility of the underlying instrument characterizes standard deviation. The first deviation away from the mean is accountable for approximately 68% of the data. The second deviation away from the mean represents relatively 95% of the data. Three standard deviations from the mean contain roughly 99% of the fluctuations from the mean.

In practice, a 55-period linear regression curve (LRC) with three standard deviation bands both above and below the curve should provide a leading indication of future price direction. It also can identify support/resistance. The greater the standard deviation of prices is away from the 55-period LRC, the higher the probability the underlying instrument will revert back to the mean. This tendency is known as mean reversion.

The forecast oscillator is derived from linear regression; it was popularized by Tushar Chande. The oscillating line is plotted by computing the percent difference between the forecast price and the actual price, hence “forecast oscillator.” The forecast price is determined with an x-period linear regression. When the forecast price is greater than the actual price, the oscillator will be above zero. When the forecast price is less than the actual price, the oscillator will be below zero. By plotting an x-period moving average of the oscillator, Chande created a trigger line that determines trend — or, more important, changes in trend. If the forecast oscillator crosses below the signal line, expect lower prices. If the forecast oscillator crosses above the signal line, expect higher prices.

The Commodity Channel Index (CCI) is another indicator. It measures overbought/oversold levels. The CCI was created by Donald Lambert and measures the distance between the current price and the statistical mean. The statistical mean is derived by the standard deviation and serves to standardize the indicator’s output. The CCI indicator is unlimited in regard to the distance between the current price of the market and the statistical mean; however, key extreme levels are considered overbought and oversold distances, suggesting price reversals when the CCI is above or below these extremes. The most popular settings for extreme levels are plus/minus 100 and 200.

Support and resistance levels can be derived from multiple technical measurements (examples include Fibonacci fans, past highs and lows, standard deviation bands and pivot analysis formulas). Two that work well include the for-mentioned standard deviation bands based off the 55-period LRC and significant past highs and lows.

Significant highs and lows can be identified by using the standard pivot high and pivot low tools (commonly available in trading software). Some modification might be necessary. For example, in Tradestation, modify the defaulted left and right strengths from three to five and select a different color for both the pivot highs and pivot lows. Finally, add thickness to the dots so they are more easily identified. Using these inputs, a significant high is a high price that does not have a higher high five bars to the left or five bars to the right, and a significant low is a low price that does not have a lower low for five bars to the left or right.

Finally, the foundational trend is derived from the long-term perspective. The longer the time frame the more accurate the assessment, no matter what preferred time or tick-value length on which the trader will actually trade. You must start with the long term and finish with the short term; this process follows a critical path and you must complete the first step before you can move to the next.

This multiple time frame analysis increases the chance of success by keeping a strategy aligned with the foundational trend. Analysis should seek confluence along all time frames within the strategy. The greater the confluence the higher the probability of a profitable position with the least amount of risk will result.


This scalping technique uses three time frames, a 987-tick chart, a 233-tick chart, and a 55-tick chart. The HPI, forecast oscillator, CCI, and a 55-period LRC with three standard deviation bands are implemented on each time frame. This analysis will use the indicators shown in the chart “From top to bottom.”

The first step along the critical path is to identify the foundational trend on the 987-tick chart. The idea is to trade in the market direction depicted by the indicator set on this chart. If HPI is increasing in value, money is flowing into the contract and we will look for decreasing prices; this divergence will suggest the prices should reverse. If this is the case, the forecast oscillator must be below -0.1 and crossing or above the signal line. The CCI indicator must be below the oversold extreme value, which is set to -100, and it must be increasing in value.

Next, we’ll look to the 55-period LRC and its standard deviation bands. We’ll look for the next standard deviation below the market that could provide support — again the more standard deviations the market moves away from the LRC, the higher the probability that a reversal will occur. In this example, the market is approaching the second standard deviation below the 55-period LRC on the 987-tick chart, which is sitting just below the price of 765.This process will be performed upon each time frame. The goal is to ultimately find support at a particular price upon all time frames.

In this example, we’re looking for a bullish condition, as indicated by the foundational trend established on the 987-tick chart. That’s what we find as our analysis drills down on the 233-tick chart. The 55-period LRC is sitting just below 765 and establishes further strength of a possible reversal. As we continue down to the 55-tick chart, we see additional confluence of bullish signals on the indicators, maintaining conformity on all three time frames. The next step is to identify key support at or near 765.

The second standard deviation to the downside of the 55-period LRC is sitting at 764.90, one tick below the established multiple time frame support price. With this strategy, it’s good practice to always seek to enter the market at the price displayed by the second or third standard deviation of the 55-period LRC on the 55-tick chart. Which band to use, the upper or the lower, is determined by two protocols, the first is whether the trader is buying or selling, and the second is confluence between the other identified key support resistance levels on the 987- and 233-tick charts.

If buying, use the second or third deviation below the 55-period LRC. If selling, the second or third deviation band above the 55-period LRC is key. In this example, the trader would place a buy on a limit order at 764.90, looking to trade in the direction indicated by the multiple time frame analysis, and entering at a key established support price on each time frame.


Once filled, the trader should implement a scaling-out strategy that attempts to make the market pay for the trade. The determination of the scale is derived from the trader’s predetermined stop loss or the amount of risk set prior to entry.

For example, based on this scalping strategy, the predetermined stop loss may be eight ticks, which is $80 per contract on the E-mini Russell. The trader will need to trade in odd number lots (that is, three, five, seven, etc.) and place the first scale at five ticks.

Say the trader enters the market buying five contracts on a limit at 764.90. Once the market achieves the scale of six ticks, the trader will liquidate three contracts, making a profit of $180. The trader will have two remaining contacts in the market, which should be protected with a trailing stop.

The money pulled out of the market when scaling out should balance the amount of money at risk on the remaining contracts. In this example, the trader would have two riders with eight-tick stop losses, which would amount to 16 ticks, or $160 dollars. This example’s scale pays for the amount of risk associated with the two remaining contracts plus the trader’s commissions.

Once the trader’s established scale is achieved, it would be quite difficult to lose money on the trade. The trader may want to move the stop to his entry price on the riders once the scale is achieved. This will allow the trader to maintain the $180 minus the per contract commissions, as well as trail a stop, which provides the scalper with the ability take part in

a trend.

Matthew D. Reynolds is president of Derivative Concepts Inc. Reach him via or

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