Jan 242014

Technical Chart Analysis Of  Moving Average Fake-Outs




This is a daily chart of CMCSA (Comcast).

  1. It has been in a strong upwards trend for a long period.
  2. Price got into deeper pullbacks as accumulation took place.
  3. The steeper trend lines show that trend accelerated after the deep pullbacks.



This is a close-up chart of CMCSA. To highlight the moving average fake-out trading setup, we plotted three moving averages (14, 30, 50).

(Learn: Moving Average Fake-out Trading Strategy)

  1. All three moving averages are sloping up. This indicates a bullish market bias.
  2. Prices tried to pullback but could only move sideways, implying a lack of bearish conviction.
  3. The current bar tested the 14-period moving average and gave a bullish fake-out signal. A recent trend line is supporting the current bar as well.


CMCSA is definitely trending up. While the trend is accelerating, there is no sign of trend exhaustion (for e.g. extreme volume).

In this bullish context, the pullback to the 14-period moving average presents a decent fake-out setup. If price exceeds the high of the setup bar, it will trigger a bullish fake-out trade.

Jan 242014

The moving average fake-out trading setup was introduced by Mark Fisher. This trade setup is called the moving average fake-out as it uses moving averages to find false counter-trend moves. As Mark Fisher mentioned in his book, you may use the rules to establish a position or a trading bias.

Pivot point/Typical Price = (High+Low+Close)/3


  1. All three SMAs of pivot point sloping up (14-period, 30-period, 50-period)
  2. Pullback down to 14-period SMA without crossing below 30-period SMA
  3. Enter long when prices rise above the lowest prior high above the 14-period SMA


  1. All three SMAs of pivot point sloping down (14-period, 30-period, 50-period)
  2. Pullback up to 14-period SMA without crossing above 30-period SMA
  3. Enter short when prices fall below the highest prior low below 14-period SMA


Moving Average Fake-Out Winning Trade

Moving Average Fake-Out Winning Trade

This is a daily chart of AON Corporation listed on NYSE. All three moving averages were sloping up (color change from red to green). Prices continued to rise above the moving averages. This was followed by a sideways movement to the 14-period moving average, giving us the moving average fake-out setup. We placed a buy stop order above the high of the first bar that tested the 14-period moving average. The order was triggered the next day and led us into an extended bull trend.

The trade setup bar that tested the 14-period moving average had a long bottom tail. It is a sign of bullish support after the moving average fake-out. The next day was a bullish outside barwhich confirmed the support found at the moving average.


Moving Average Fake-Out Losing Trade

Moving Average Fake-Out Losing Trade

This is a daily chart of Korea Composite Stock Price Index (KOSPI) which tracks all the stocks listed on the Stock Market Division of the Korea Exchange. The three moving averages sloped up to confirm the bullish price action. Then, we saw a pullback down to the 14-period moving average. Prices tangled with it for two days before gapping up to trigger the buy order (at the blue horizontal line). The trade moved against us immediately. A few days later, a strong gap down forced us to exit with a loss.

This moving average fake-out setup was a reasonable one. The first bar that tested the 14-period moving average was a bullish reversal bar. It was followed by a bearish inside bar which was the second attempt to push prices down. These were bullish signs.

However, the climatic bullish action before the pullback might have been a concern. Climaxes tend to lead to either reversal or sluggish movement. Each of the three bars following our entry gapped up before closing down, which was extremely bearish. Hence, we had more than enough warning to get out before the large gap down (which changed the slope of the 14-period moving average down).


The moving average fake-out trading setup is a trend pullback trade setup. The use of multiple moving averages is usually redundant. Fortunately, this trade setup uses only three moving averages which is about the most my brain can process. In addition, the periods 14, 30 and 50 are all intermediate periods that are relatively meaningful.

A short period is just a proxy of price itself and only serves to confuse price action; a long period lags as a trend indicator and does nothing to filter ranging conditions. By focusing on the slope of these three intermediate period moving averages, Mark Fisher created a nice package of multiple moving averages. Look at the KOSPI chart above beyond the losing trade and you will see that this trading setup kept us out of ranging price conditions. Slope of moving averages hardly agree for any trade to take place.

A key feature of Mark Fisher’s moving average fake-out setup is the use of pivot points instead of closes for the moving averages. Using pivot points does not make much difference except for some smoothing. In fact, the closing price of each day holds important information as it is the price that all players contributed to by the end of each trading session. However, for intra-day charts, especially for non-time-based charts including tick and volume charts, that have their bar closes determined arbitrarily, using pivot points may make more sense.

The moving average fake-out trading setup is also a tool to determine a trend bias. Mark Fisher suggested this approach to augment other methods mentioned in his book,  ”The Logical Trader“.

Dec 092013

15 Ways To Trade Moving Averages

Reading a chart without moving averages is like baking a cake without butter or eggs.

Those simple lines above or below current price tell many tales, and their uses in market interpretation are unparalleled. Simply stated, they’re the most valuable indicators in technical analysis.

You can trade without moving averages, but you do so at your own risk. After all, these lines represent median levels where your competition will make important buying or selling decisions. So it makes sense to predict what they’re going to do before the fact, rather than afterward.

15 Ways To Manage Opportunity Through Moving Averages

1. The 20-day moving average commonly marks the short-term trend, the 50-day moving average the intermediate trend, and the 200-day moving average the long-term trend of the market.

2. These three settings represent natural boundaries for price pullbacks. Two forces empower those averages: First, they define levels where profit- and loss-taking should ebb following strong price movement. Second, their common recognition draws a crowd that perpetrates a self-fulfilling event whenever price approaches.

3. Moving averages generate false signals during range-bound markets because they’re trend-following indicators that measure upward or downward momentum. They lose their power in any environment that shows a slow rate of price change.

4. The characteristic of moving averages changes as they flatten and roll over. The turn of an average toward horizontal signifies a loss of momentum for that time frame. This increases the odds that price will cross the average with relative ease. When a set of averages flatline and draw close to one another, price often swivels back and forth across the axis in a noisy pattern.

5. Moving averages emit continuous signals because they’re plotted right on top of price. Their relative correlation with price development changes with each bar. They also exhibit active convergence-divergence relationships with all other forms of support and resistance.

6. Use exponential moving averages, or EMAs, for longer time frames but shift down to simple moving averages, or SMAs, for shorter ones. EMAs apply more weight to recent price change, while SMAs view each data point equally.

7. Short-term SMAs let traders spy on other market participants. The public uses simple moving average settings because they don’t understand EMAs. Good intraday signals rely more on how the competition thinks than the technicals of the moment.

8. Place five-, eight- and 13-bar SMAs on intraday charts to measure short-term trend strength. In strong moves, the averages will line up and point in the same direction. But they flip over one at a time at highs and lows, until price finally surges through in the other direction.

9. Price location in relation to the 200-day moving average determines long-term investor psychology. Bulls live above the 200-day moving average, while bears live below it. Sellers eat up rallies below this line in the sand, while buyers come to the rescue above it.

10. When the 50-day moving average pierces the 200-day moving average in either direction, it predicts a substantial shift in buying and selling behavior. The 50-day moving average rising above the 200-day moving average is called a Golden Cross, while the bearish piercing is called a Death Cross.

11. It’s harder for price to break above a declining moving average than a rising moving average. Conversely, it’s harder for price to drop through a rising moving average than a declining moving average.

12. Moving averages set to different time frames reveal trend velocity through their relationships with each other. Measure this with a classic Moving Average-Convergence-Divergence (MACD) indicator, or apply multiple averages to your charts and watch how they spread or contract over different time.

13. Place a 60-day volume moving average across green and red volume histograms in the lower chart pane to identify when specific sessions draw unexpected interest. The slope of the average also identifies hidden buying and selling pressure.

14. Don’t use long-term moving averages to make short-term predictions because they force important data to lag current events. A trend may already be mature and nearing its end by the time a specific moving average issues a buy or sell signal.

15. Support and resistance mechanics develop between moving averages as they flip and roll. Look for one average to bounce on the other average, rather than break through it immediately. After a crossover finally takes place, that level becomes support or resistance for future price movement.

by Alan Farley