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The eMESA trading system has been exclusively available to add onto eSignal for more than a year, and users have been finding the results are terrific! These results are attributable to the fact that the trading rules the system uses are founded on basic principles. Consequently, the trading results are not only consistent month after month, but, also, the system is robust across a wide variety of instruments.
eMESA was initially designed to trade the S&P E-Mini futures contract, but real-time performance shows that it turns in profits on other futures indices and even Exchange Traded Funds (ETFs).
Here’s how it works: eMESA senses when the prices reach an extreme deviation from the mean and, therefore, have a high probability of reversion to the mean. That is, it anticipates turning points in advance of their occurrence. It does this by comparing the amplitude swing of a short-term cycle to the amplitude swing of a longer-term cycle plus a fraction of the recent price volatility.
The trading results are shown in Figure 1 as equity growth, where the equity gain for trading one contract without compounding over the last three years includes an allowance of $20 per roundturn for slippage and commission.
Figure 1. Three-Year Hypothetical eMESA Equity
Growth Has Been Consistent
This equity growth means that the annualized return on a $10,000 account is 63.6%. That is certainly a better return than from a CD at your local bank. The specific statistics are:
Net Profit |
$19,067 |
# Trades |
58 |
% Profitable |
58.6% |
Profit Factor |
2.03 |
Maximum Drawdown |
-$6,070 |
When we define the reward-to-risk ratio as the annualized net profit divided by the maximum peak-to-valley drawdown, eMESA has a reward-to-risk ratio of 1.05. That is, you stand to earn more money every year than you put at risk. This is an outstanding ratio for futures trading.
The performance statistics of any trading system can be compared to the statistics used in gaming. For example, profit factor (the ratio of gross winnings to gross losses) is analogous to the payoff in gaming. That is, if you bet and lose, you lose a dollar. If you bet and win, you win by the profit factor amount.
“Percentage winners” speaks for itself. So, if you have nearly 60% winners, and you win twice as much as you lose (statistically) on every bet, you break the bank in Vegas very quickly.
On the other hand, basing the statistics on only 58 trades stretches the premise of statistical sampling to the limit. To get a better handle on expected results from a trading system, I turn to a Monte Carlo analysis. The idea is to put the results from those 58 trades into a hat and pull them out one by one until a year’s worth of trading is simulated. Then, put those trades that were used back into the hat and repeat the procedure. In fact, you pull the trades out of the hat 10,000 times to simulate 10,000 years of trading.
Now, we have enough samples to be statistically significant. Importantly, these trading results are from recent trades so that they are pertinent to current market conditions. I doubt if market activity in 1933, for example, has much relevance to today’s markets due to changes in technology, regulations, and so forth. Software to do this Monte Carlo analysis is commercially available. The results of the Monte Carlo analysis for eMESA are shown in Figure 2.
Figure 2. Monte Carlo Results for eMESA, Trading the ES Contract
The net profit statistics of the Monte Carlo simulation have the familiar bell-shaped curve of a Gaussian Probability Density Function. The most likely annual profit is a little more than the average annual profit over the last three years. More importantly, the analysis shows that the one sigma profit ranges from approximately $4,500 to approximately $8,500.
There is a small, but finite, possibility that your losses could exceed your initial $10,000 margin. This is balanced by the small, but finite, possibility of profiting by $25,000 in one year. Figure 2 also shows that the most likely drawdown of $4,832 is substantially less than our maximum drawdown experienced over the last three years. The drawdown curve also shows a small, but finite, possibility of losing your initial $10,000 margin.
Both the historical results and the Monte Carlo analysis show that eMESA is robust across time when trading the S&P E-Mini futures contract. But, is it robust across other trading instruments?
I first ran eMESA in hypothetical back tests against two other electronically traded mini contracts -- the mini DOW and the mini Russell. The equity curves resulting from those back tests are shown in Figure 3. Clearly, eMESA has outstandingly consistent performance.
Figure 3. eMESA Shows Robust Performance on Other Mini Contracts
Mini DOW
Mini Russell
As a further test of robustness, I applied eMESA to trading the three most popular ETFs -- the SPY, DIA and QQQQ Funds. Results of these back tests are shown in Figure 4.
Figure 4. eMESA Is a Viable System for Trading ETFs
SPY
DIA
QQQQ
The performance on the QQQQ is less than outstanding, but it does prove I am honest. As a matter of fact, breaking even over the last year is way better than most systems performed. The point is that, if you are trading ETFs, you are most likely trading a portfolio of funds to diversify and thereby mitigating risk. When eMESA is applied to such a portfolio, the results can only be called outstanding.
eMESA applies basic principles in generating its trading rules, and this makes it a generic system that can trade a wide variety of instruments. The fact that it is generic is proven by the robust performance, not only across time but also across a range of popular trading instruments.
I invite you, therefore, to sign up for eMESA with eSignal and see how it can add to your own bottom line.
Find out more about eMESA and the MESA Indicators.
John Ehlers can be contacted at ehlers@mesasoftware.com
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