Tag: Moving Average Crossover

Bull / Bear Dichotomy Indicator v 1.0 (BBD)

The purpose of a trading or investing model is to move probability in your favour.  One can be considered worthwhile if it can consistently produce risk adjusted returns in excess of the broad market over any period greater than 2 years.  A mechanical trading model can be considered worthwhile if in addition to this it can:

  1. Remove emotion from decisions.
  2. Do the hard work so you have the time freedom to enjoy your profits.

Regardless of the time domain of your preferred trading style, being able to clearly slice the market into high probability bullish and bearish periods is of great advantage.  So far during the Technical Indicator Fight for Supremacy we have identified three very effective and different ways of doing this:

Below I will cover a quick summary of the previous research or you can jump straight to the latest findings.

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The True Golden Cross

EMA Crossover 13/48 EOD Long

Using a simple 13 / 48 Day EMA crossover; 62% of the time the 13 Day EMA was above the 48 Day EMA.  During this time the average trade duration was 93 days and there was an annual return of 10.17% vs 6.32% for the global average during our test period.  During the balance of time there was an annual return of -3.48% (see full tests and research).

Conclusion:

EMA(13) > EMA(48) = Bullish
EMA(13) < EMA(48) = Bearish

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Relative Strength Index

126 Day RSI EOW, Long

Using a 126 Day RSI (with an EMA instead of Wilder’s Smoothing, it would be 63.5 instead of 126 on a standard RSI) and End OF Week (EOW) signals; 63% of the time the RSI was above 50.  During this period the average trade duration was 97 days and there was an annual return of 8.73% vs 6.32% for the global average during our test period.  During the balance of time there was an annual return of -2.77% (see full tests and research).

Conclusion:

RSI(126) > 50 = Bullish
RSI(126) < 50 =Bearish

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Stochastic Oscillator

252 Day Stochastic Oscillator EOD, Long

Using a 252 Day Stochastic Oscillator (SO); 66% of the time the SO was above 50.  During this period the average trade duration was 104 days and there was an annual return of 8.43% vs 6.32% for the global average during our test period.  During the balance of time there was an annual return of -2.05% (see full tests and research).

Conclusion:

SO(252) > 50 = Bullish
SO(252) < 50 = Bearish

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The Bull and Bear Dichotomy v 1.0 (BBD)

The EMA crossover shows us that there is value in measuring shorter term momentum vs longer term momentum.  The RSI shows us that there is value in a measure of declines vs advances.  While the Stochastic Oscillator shows us that there is value in being long a market when it is in the top half of its range.  The trade profile for each indicator is desirable but their signals are often in conflict.

Don Beasley of Trademark Capital has been an inspiration of mine for many years and has been kind enough on several occasions to share his insight and experience.  He likes to combine the RSI and Stochastic Oscillator by taking an average of the two.  This is straight forward because both move between the same 0-100 range.

Including the EMA crossover is not as straight forward however; it is not limited to a scale at all.  But because the percentage distance between the EMA(13) and EMA(48) should be normally distributed we decided to force it into a 0-100 range by using the cumulative distribution of a bell curve.  It has a SD of 2.17% when EMA(13) > EMA(48) and SD of 2.35% when EMA(13) < EMA(48):

Bull / Bear Dichotomy v1 Example

Above you can see the readings from each indicator during a randomly selected 2.5 year period on the Australian All Ordinaries Index.  The thick red line is an equally weighted average of the RSI, SO and MA Cross, smoothed with a EMA(10).  This we are calling the Bull / Bear Dichotomy or BBD Indicator v1.  By combining all three indicators, a greater level of stability and robustness is achieved.  See below the full trade profile:

Bull / Bear Dichotomy (BBD) v1 Trade Profile

In looking at the trade profile the signal stability is clear with an average trade duration of 170 days, an average profit of 21.81% and a probability of profit sitting at 48%!  The other statistics are not dissimilar to the component indicators.  The only thing missing from the BBD is a measure of volume.  We plan to include this in v2 and this will hopefully improve the stability further.

It is highly likely that that we are reaching the upper limits of what is possible, as far as returns, from a long term indicator applied to a blind selection of broad market indices.  To improve on these results it will be necessary to do one or a combination of the following:

  • Have a selection process for the assets to be traded.
  • Apply a secondary trading system specifically designed to perform during the bullish or bearish environments identified by the BBD.

How do think these results could be improved?  What other long term measures would be worth researching for inclusion in v2 of The Bull / Bear Dichotomy Indicator?

Please note: These returns are the result of evenly allocating funds between 16 different global test markets.  If only one market was on a buy signal then only 1/16th of the capital was exposed to the market.  Some markets performed better than others and lifted the returns.  All were profitable and the strategy outperformed on an absolute basis on 15/16 of the test markets.  A further explanation of the methodology can be found here.

Golden Cross – Which is the best?

The Golden Cross typically referrers to the crossing of the 50 and 200 Day Simple Moving Averages. When the shorter term average moves above the longer term average this is seen by many as the beginning of a sustained bullish period and vise versa. It is not wise however to risk your money in the market on the assumption that such a theory is true.

One has to ask, which is better, a SMA Golden Cross or an EMA Golden Cross? Are the settings of 50 & 200 really the best? What is the profile of the trades that this strategy generates as far as duration, probability of profit, draw downs etc.  In order to answer these questions we applied some brute mathematical force and tested 1750 different combinations through 300 years of data across 16 different global markets~. We have done the hard work and you get the benefits for free… aren’t you lucky.

Michael Stokes over at MarketSci has also written a great series on Trading The Golden Cross.

 

Download A FREE Spreadsheet With Data, Charts

And Results For all 1750 Moving Average Crossovers Tested

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Golden Cross, Moving Average Crossover – Test Results:

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Golden Cross Conclusion

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Our Testing Strategy Explained

There are endless combinations of moving averages that we could test in search of the best. To cast our testing range wide but intelligently we have used progressions of a ratio; slow/fast MA:

Fast Moving Averages (FC) = 5, 10, 15, 20, 25, 30, 35, 40, 45, 50
Slow Moving Averages (SC) = 1.2 * FC, 1.4 * FC, 1.6 * FC, …….. 5.6 * FC, 5.8 * FC, 6 * FC

So each of the ten FC settings were tested against twenty five SC settings based on a multiple of the FC. e.g The traditional Golden Cross with a SC of 50 and a FC of 200 has a multiple of 4 (because 50 * 4 = 200). The tests against a FC of 50 had a multiple as low as 1.2… (50 * 1.2 = 60) and as high as 6… (50 * 6 = 300).

Hopefully by using this tactic we can identify the multiples or ratios that deserve more targeted testing.

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Simple vs Exponential Moving Average Crossover

In our original MA test; Moving Averages – Simple vs. Exponential we revealed that the Exponential Moving Average (EMA) was superior to the Simple Moving Average (SMA). If the same proves to be true with the ‘Golden Moving Average Crossover’ then this will further validate the EMA as being of higher-caliber than the SMA.

Simple vs Exponential MA Crossover Returns


The chart above fades between the results from the EMA and the SMA crossover tests. As you can see the EMA outperforms the SMA by well over a percentage point on average. This unequivocally confirms that the EMA is superior to the SMA. Further more it should be noted that every single EMA combination tested (and most SMAs) outperformed the buy and hold annualized return of 6.32%^ during the test period (before allowing for transaction costs and slippage). But “technical analysis doesn’t work” they say.

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Below are the all the individual Annualized returns from the EMA chart above:

EMA Crossover, EOD Long, Annualized Return During Exposure

The best returns came from an fast EMA of 10 days with a slow EMA of 50 (ratio of 5 because 10 * 5 = 50). Based on these results we will run more refined tests on fast moving averages in the range of 8 – 17 and slow moving averages 20 – 56.

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Daily vs Weekly Moving Average Golden Cross

What about Weekly data you ask? We didn’t test with Weekly data but we did test using End Of Week (EOW) signals on Daily data (previous tests on the EMA revealed that the two produce almost identical results). When we used EOW signals the returns dropped by 0.5% on average while the trade duration increased by just 10 days and the probability of profit increased by only 2%. In other words; you are better to use daily data and EOD signals on a Moving Average Crossover Strategy.

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Golden Cross – Refined Test Sets

After getting a better idea of the ‘sweet’ spot from our first round of testing, we refined our range and instead of continuing with ratios of fast and slow EMA crossovers, we progressed in a liner fashion. So what is the “True Golden Cross” that proved the best returns during our tests?

EMA Crossover, EOD Long, Annualized Return

There is a zone of dark green on the grid above but the very best from our tests, the True Golden Cross has a slow EMA of 48.5 and a fast EMA of 13. Reality is very different from the 50/200 SMA Golden Cross that someone made up once upon a time and that is why we must test everything.

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The True Golden Cross

EMA Crossover, 13 / 48.5 EOD, Long

The profile of the trades produced by the true Golden Cross have many very desirable features; a significant average trade duration (94 days), a high probability of profit (45%) and solid returns across the board (even on the difficult, bear savaged Nikkei 225).  While it does not produce returns any where near as good as the best FRAMA, it certainly out performs the traditional Golden Cross of 50 / 200.  Plus with the long trade duration, it may be more desirable than the slower FRAMA for use as a long term indicator as one part of a complete trading system:

252 Day FRAMA, EOW 40, 250 Long

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Golden Cross Conclusion

Moving average crossovers have proven themselves to be a powerful and effective form of technical analysis, however the so called “Golden Cross” of the 50 and 200 day SMA is far from the best.  Our testing revealed that the EMA produces better results than the SMA and the best settings are that of a 13 / 48.5 EMA Crossover.  The long duration of the trades produced, ability to sidestep bear markets and the high probability of profit make it worth testing as a major component in a complete trading system.

The moving average crossover is a component of the popular Moving Average Convergence Divergence (MACD), see the completed test results here.

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More in this series:

We have conducted and continue to conduct extensive tests on a variety of technical indicators. See how they perform and which reveal themselves as the best in the Technical Indicator Fight for Supremacy.

 

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  • ~ An entry signal to go long for each crossover tested was generated when the faster moving average of each pair closed above the slower moving average (the opposite closed the position or triggered a signal to go short. No interest was earned while in cash and no allowance has been made for transaction costs or slippage. Trades were tested using End Of Day (EOD) and End Of Week (EOW) signals for Daily data. Eg. Daily data with an EOW signal means that only the signals at the end of each week were taken.
  • ^ This was the average annualized return of the 16 markets during the testing period. The data used for these tests is included in the results spreadsheet and more details about our methodology can be found here.