As of 11/20/2024   Indus: 43,408 +139.53 +0.3%     Trans: 17,002 -26.31 -0.2%     Utils: 1,055 +1.25 +0.1%     Nasdaq: 18,966 -21.33 -0.1%     S&P 500: 5,917 +0.13 +0.0%	YTD  +15.2%    +6.9%    +19.7%    +26.3%    +24.1%	Targets    Overview: 11/12/2024     46,000 or 43,000 by 12/01/2024   18,000 or 16,600 by 12/01/2024   1,075 or 1,000 by 12/01/2024   20,000 or 18,400 by 12/01/2024   6,100 or 5,800 by 12/01/2024
Chart Pattern Indicator: on 11/18/24

As of 11/20/2024   Indus: 43,408 +139.53 +0.3%     Trans: 17,002 -26.31 -0.2%     Utils: 1,055 +1.25 +0.1%     Nasdaq: 18,966 -21.33 -0.1%     S&P 500: 5,917 +0.13 +0.0%	YTD  +15.2%    +6.9%    +19.7%    +26.3%    +24.1%
Targets    Overview: 11/12/2024     46,000 or 43,000 by 12/01/2024   18,000 or 16,600 by 12/01/2024   1,075 or 1,000 by 12/01/2024   20,000 or 18,400 by 12/01/2024   6,100 or 5,800 by 12/01/2024
Chart Pattern Indicator: on 11/18/24

Bulkowski's Moving Average Study

By combining a simple moving average with chart patterns as a buy signal, you can increase profits and reduce risk.

Moving Average Study: Summary

Use a simple moving average to remove chart patterns more likely to fail and trade those more likely to succeed.

First, assume that tomorrow the chart pattern will breakout in the direction you want to trade (either upward or downward). Second, look at today's closing price. The following table shows you where the 9-day or 50-day moving average in relation to the closing price should be to maximize gains and minimize risk.

In all cases, the reward increases even as the risk of a failure decreases, but the differences are slight when compared to the benchmark move.

Moving Average Study: Methodology

I measured the move from 36 different chart pattern types (such as double tops and head-and-shoulder bottoms) using the closing price the day before the breakout to the ultimate high or low. The ultimate high is the highest peak before price drops by at least 20% or closes below the bottom of the chart pattern. The ultimate low is the lowest valley before price rises by at least 20% or climbs above the top of the chart pattern. In other words, these are perfect trades, and one should not expect to achieve similar results but they suffice for comparison purposes.

I used 21,696 sample trades covering the period from April 1989 to January 2009. This covers two bear markets, as exemplified by the S&P 500 dropping at least 20% during March 24, 2000 to October 10, 2002 and another period from October 11, 2007 to the end of the study (January 2009). Dates outside of those ranges are classified as a bull market.

For each trade, I logged the value of several simple moving averages (9, 20, 50 and 200 day) and compared it to the closing price the day before the breakout. For failures, I counted the number of times price after the breakout failed to move at least 5% and 15% before reaching the ultimate high or low.

I also compared the trend of the moving average, either up or down, and compared it to the post breakout move and failure rate.

Moving Average Study: Results

The following table shows failure rates based on price failing to move more than 15% away from the breakout price. I chose to display this instead of the 5% failure rate because the sample counts are higher and the results are more consistent. If price moves by at least 15% after a breakout, there is a good chance that a trader can capture at least some of that profit.

The above table highlights in red when the moving average exceeds the benchmark rise or decline and has a lower failure rate. For example, using the third row down, the move of all stocks following a downward breakout from a chart pattern in a bull market was 21.5%, and 41% of those failed to see price drop at least 15%. If price is above the 9 day simple moving average the day before the breakout, the average drop increases to 22.9% and the failure rate drops to 40.1%. Both are improvements, but not dramatic ones.

Substituting the trend (either rising or falling) of the moving average for the position either above or below the closing price prior to the breakout, I found that the results are similar. The only difference is the failure rate rises in a bull market after a downward breakout when the 9 day simple moving average is rising (the failure rate becomes 42.8%, up from 40.1% and the benchmark 41%. The cell is highlighted in green). The performance results using the moving average trend are similar to the numbers listed in the above table.

The following table shows the per trade average profit or loss assuming an investment of $10,000 per trade less $10 for commissions ($10 for buying and $10 for sales) with the number of shares traded rounded down to the nearest 100. That means stocks priced over $100 (such as google) would not be traded. Again, each trade is a perfect one, buying at the close the day before the breakout and holding until the highest high or lowest low before a trend change. Do not expect to duplicate these amounts, but they highlight which technique works best.

Values in parentheses are negative, and those highlighted in red are the best performing (highest profit or loss) per row.

Notice how the best results cluster in the 9 day moving average column. This reinforces the results shown in the prior table. The highest profit is when the closing price is below the 9 day moving average the day before an upward breakout in a bull market. The 1,210 trades made an average of $4,651.

For downward breakouts, the largest loss came when the closing price was below the 200 day simple moving average in a bear market. The 1,792 trades lost an average of $2,185.

Notice that the above table shows the best results when using a 200 day SMA and the prior table does not. The prior table is the more accurate of the two because the table showing dollar amounts does not include high priced stocks (prices over $100).

Moving Average Study: Risk

A word about risk. Risk is normally a function of draw down, which is the maximum decline from a peak to a trough. Since the method I used determines the highest high or lowest low before a 20% trend change, the draw down would be 20% or higher, by definition.

Instead, I chose to measure risk by counting the number of trades that failed to move more than 15% from the closing price the day before the breakout. The risk ranges between a low of 25.1% (bear market, price below the 9 day SMA, and a downward breakout) to a high of 44.9% (bull market, price above the 50 day SMA and a downward breakout). In other words, between a quarter to half of all chart patterns will fail to show moves of at least 15%.

Moving Average Study: Trading Tactics

Based on the above results, I come to the following conclusions.

Compare the 9 or 50 day moving average with the closing price the day before a breakout then using the following table.

For example, if this is a bull market and you expect an upward breakout from a chart pattern the next day, then the closing price should be below the 9 day simple moving average. If this is a bear market and you expect a downward breakout, then the close should be below the 50 day SMA. If your situation does not agree with the combination shown in the table, then look elsewhere for a more promising trading setup.

I ran my actual trades against the 9 day SMA for upward breakouts and found that my win/loss ratio improved by 16% and profits soared by 340% using this method. Not all of those trades used chart patterns and I compared the moving average to the closing price the day before I bought instead of a chart pattern breakout.

Moving Average Study: Example

The adjacent figure shows an example of a descending triangle on the daily scale. The red line is a 50 day simple moving average chosen because the market is bearish and descending triangles breakout downward 64% of the time.

Looking at the inset which zooms in on the breakout, price closes below the bottom of the descending triangle at point A. The day before the breakout, at B, the closing price is below the 50 day simple moving average. This combination identifies a lower risk, higher probability trade. You would short the stock by placing an order a penny or two below the bottom of the triangle.

-- Thomas Bulkowski

See Also

• Price stages. Does Stan Weinstein's four stages work? Yes!
• 12 Month moving average. Use a moving average to time the market.
• Oscillator myths. Explains the trouble with oscillators.
• Swing rule. A reliable way to predict price targets.
• Trendline mirrors. Use trendlines to predict price movements.
• Market direction. 7 tips to determining.

You have a drinking problem if you fall off the floor.