A Pull-Back Technique for Swing Trading

One familiar recommendation for swing trade entries is to buy the pullback's. But, what is the best method for determining at what point a pullback makes a good entry?

The Ideal Pull-back Criteria

Some of the desirable characteristics of a pull back entry technique are:

1. Works for a diverse group of trading entities: stocks, futures, Forex.
2. Includes symbol selection filters that maximize risk-adjusted gain.
3. Self-adjusting for price and volatility.
4. Allows an easy calculation of risk and reward.

Popular Pull-Back Methods

There are several methods of identifying suitable pullbacks, but most have one or more disadvantages.

Table 1. Pull-back methods and potential disadvantages of each

Only the last item, deviation from linear regression center line expressed in standard error units, appears not to have any significant weaknesses. Let's take a coser look at this method and see why it is favored.

The chart below shows a linear regression line drawn thru the most recent 2 month period of a daily chart of GLBL (Global Industries). This company was identified in a scan for companies that had a high Sharpe ratio over the most recent 2 month period. Sharpe ratio is the annualized average growth rate divided by the standard deviation of the grow rate. The ideal Sharpe ratio stock (one that will have a high Sharpe ratio value), will be growing at a relatively high rate, and have a very little variation in this growth rate.

High Sharpe ratio stocks will, using the chart below as an example, have a linear regression channel with a relatively steep slope (high percentage rate of change) and a relatively narrow width if the width is measured in standard error units. Standard error, by definition, is the average amount the price deviates from a linear regression center line drawn thru the price trend for the time frame under question. A low average deviation from the linear regression line means the channel will be narrow.

Fig 1. Linear Regression Channel Standard Error Deviation Method of Swing Trading

The above chart stock represents a typical stock selected for swing trading. In the subgraph, the running 40 bar Sharpe Ratio indicator reflects the risk adjusted (volatiliy adjusted) rate of gain of the stock. The FxDeviation indicator reveals where the current price is in terms of standard error units from the linear regression line. At the right most bar, the current closing price is 2.01 standard error units above the center line. Looking at the Linear Regression Channel in the main chart, the closing price of the last bar is 2 lines above the center line. Displaying the FxDeviation indicator in the subgraph provides a convenient way to cross-check the Linear Regression Channel (_LRChan) to ensure both are set up correctly. The Avg$Traded indicator, expresses the liquidty of the stock in terms of dollars traded each day (price x total daily volume). Expressing liquidity in these dollars traded, instead of shares, makes it easier to determine if the desired trade size can be accomodated since the desired trade size is usually expressed in dollars.

Important Characteristics of Standard Error Linear Regression Channels

When a stocks is in a well-behaved trend, the price action typically moves between minus 2-3 and plus 2-3 standard error units from the linear regression center line. This is true regardless of the price and regardless of the volatility. This is because standard error calculation automatically adjusts for volatiliy and price and adjusts the width of the linear regression channel accordingly. Thus, this pullback measure has a self-normalizing property that makes it especially attractive to traders, since a single technique will work for a symbol of any price and volatility.

Swing trading entry and exits goals are approximately -2 standard error units and +2 standard error units, regardless of the entity traded. Not only does this method provide you with a rational entry point, it also provides for a rational profit target! For this method to work reliably, the time period over which the stock trend is analyzed must be long enough to show at least 2 or more decent amplitude "wiggles" so that the standard error measurement has some validity. If the time frame is too short, you will not have a "history" of what is "typical" for this stocks volatility as it continues its trend. The symbol should also be in a well behaved trend, ensured by requiring a high Sharpe Ratio filter in the selection process.

There is a second important observation regarding price action within the linear regression channel. When the price deviates by more than 3 standard error units from the center line, the trend is usually breaking down. The parallel line 3 standard errors below the center line can be considered quite similar to a classical trend line drawn just below the lows of a trending stock. One rule for traders that then follows is: Do not take trades in the direction of the trend when the price has pulled back to almost 3 or more standard error units from the center line.

Recommended Entry Rules

In stocks prescreened for adequate liquidity and risk-adjusted growth rate (Sharpe ratio), these observations may be summarized for long trades as follows:

1. Enter when the price has pulled back to approximately -1.75 to -2.50 standard error units from the linear regression center line.
2. Do NOT make long entries when the price has pulled back to -3.0 or more standard error units.
3. Consider taking profit when the stock climbs to approximately +1.75 to +2.50 standard error units.
4. Since deviations greater than -3.0 usually indicate a break in current trend, place an initial stop loss at -3.0 to -3.5. If price moves in your favor, using trailing stops to lock in profits as the price moves in the desired direction.

Examples of Successful Swing Trades

DVR Entry at -2.75 standard error units.

DVR Price hesitated and then rose for profitable exit at +2 standard error units.

GLBL Successful swing trade. Entry at -2 standard error units , exit at 2.5 standard error units.

EKX (Silver) entry at -3.0 Std Error deviation. This is a high risk trade asentry rule #2 was violated.

EXK (Silver) one week later. Did not place stop, violated entry rule #4 to always place a stop loss.

EXK (Silver) Continued sideways and then rose. Bad trading technique, but lucky outcome.

I showed this EXK trade as an example of two common trading mistakes, entering on larger than typical pull-backs and not placing a stop loss. Most trades like this one above do not work out favorably and will consistently generate losses. The results of these losses were what has lead to the formulation of "recommended entry rules" referred to previously.

HEK Chased price on first entry. Did not wait for good pull back, therefore set initial stop loss set just below entry price.

HEK Second trade successful.

HEK Third swing trade attempted at next pull back to -2.0 Std Err units.

IDCC Trailing ATR (solid red) and Std Err (dotted red) stops can be used to trail price after entry and lock in profits.

IDCC rose a bit further after profit target, and then pulled back sharply.

ROIAK entry at -2.25 SE deviation units.

ROIAK ATR (red solid) and SE (red dotted) Trailing Stops lock in profit as price rises.

VG Adding to original position as price does not drop below deviation -2 trend line.

VG Upslope weakened after entry

VG continues upwards and regression lines slope upwards, but price never reaches target. Trailing stop is hit.

Examples of Failed Trades

CPST Entry at -3.5 Standard Error units, violating rule #2. Stopped out at -4.5 standard error units.

CPST Price turned upwards after swing trade stopped out.

ACHN Stop Placement at -4 standard error units, violating rule #2.

ACHN Stopped out and continued to decline. Rule #2: Do not enter below -3 deviation band.

EMKR Entry far below -3, and therefore a risky trade as price has broken upward trend.

EMKR Price moved sideways and held, so added to position.

EMKR Price continues sideways. Stopped out for lack of progress by trailing stop.
Deviations < -3.0 usually signify trend is over.

Market Indexes fell on bad economic news. High risk trade because trend already broken.

ES Price remains sideways and manually closed trade for lack of progress.

HW High risk entry below -3 deviation band.

HW Stopped out at -4 standard error units deviation. Price continued to decline.

ACHN Entry at -4 standard error units violates entry rule #2, and usually signifies the trend has been broken.

Swing Trading Method Summary

1. Screen for Adequate Liquidity

My minimum liquidity criteria is the intended position may not exceed 2% of daily dollars traded per day. This is a fairly aggressive position relative to liquidity. More conservative traders may prefer limiting position size to 0.5% to 1% of daily dollars traded. In general position size greater than 0.1% of the daily dollars traded per day may require scaling in and out to enter and exit over a several minute period to avoid moving the price significantly. With low liquidity stocks, it is also useful to hide the size of your limit orders using the "Show Only" size option of the Order Bar and to make trades at the beginning or end of the trading day, when volumes are typically 3-5X higher than mid-day.

Stocks may be prescreened for adequate liquidity using the scanner. Liqudity is measured in dollars traded per day rather than shares because it is easier to relate this unit of measure to the position size (in dollars) the trader is prepared to make in each stock in the portfolio.

The scanner setup is shown below:

Fig. 2. The entire universe of stocks and ETF's are selected (approximately 8000 symbols)

Fig. 3. Custom function Liquidity impliements the lquidity criteria

Input parameters for function Liquidity are set to ensure the 10 day average dollars traded and the 50 day average dollars trader both are above 0.5 million dollars. A second criteria is to ensure the price of the stock is above $0.50. My preference is to look for low priced stocks in the $1 to $15 range. I will rarely consider a stock below $1, even if the liquidity is adequate. Low priced stocks tend to move up at a greater rate of growth and also show more resistance to downward movements when the market indexes are pulling back. Out of the entire universe of stocks (8000) approximately half (4000) pass the liquidity screen.

2. Determine Best Risk Adjusted Return Candidates.

A 2 month (40 daily bars) or 4 month (80 daily bars) Sharpe Ratio value is calculated for all stocks determined to have adequate liquidity by the preliminary liquidity scan above. The best 100 Sharpe ratio stocks are then examined to confirm consistent, well-behaved gain, an absence of news generated price gaps and relative current price to prior significant resistance and support levels.

Results of the previous Liquidity Scan are used as the symbol universe

Scan formatting: Scan criteria tab settings

For example, stocks that have just advanced past a recent significant resistance level, are more desirable than stocks that are just below such as level because of the likelihood of a pull back at the resistance level. The deviation from the linear regression center line is being monitored by indicator FxDeviation.