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I have never tried that, but it could be a cheaper option.
I used to be in the camp of "one strategy, all markets." I used that approach when I had success a few years back in trading contests. Now I tend to be in the "one strategy, one market" because I like the diversification aspect. So, I have no preference against either approach. I do think the "one strategy, all markets" will be tougher to develop, since once it fails in one market, you theoretically have to ditch the system.
The issue of incubation is an interesting Rorschach test. Let's say you have a gut aversion to it. Forget about the intellectual reasons you would give for that aversion and consider the emotional motivations for that aversion instead.
I am instinctively in favor of it, because I am risk averse. I don't like trading, in itself, very much, so anything that puts a control between me and risk exposure always looks good to me.
(confession: reading this thread, and making this post even, is a diversion - I am presently fighting the desire to close a system trade early with a small profit. Get behind me Satan!)
I mean I think that can be avoided if you have numbers based and pre-set benchmarks. it only becomes a Rorschach test if you are making the judgements purely on a whim rather than a set of pre defined criteria. I personally use my monte carlo results and historical std dev and expectancy to determine my bounds of system performance if it exits these bounds then it turns off. but not until then. I think that's a very important aspect that can not be ignored.
One of the interesting side benefits of performing Monte Carlo analysis is that you can get an idea of your profit consistency. Imagine you were manager of a casino. Over the course of 5 minutes, your casino might make or lose money at the gambling tables. There is some randomness to the results, so even the house could lose money in a given short timeframe. As the time increases, your chances of profitability go up, and eventually approach near certainty. Your casino probably makes money every week, and almost certainly makes money every month - unless of course the criminal underworld is skimming from you!
The concept of a casino got me thinking that I'd really like to be profitable over a week, or month, or year with my trading systems.. Obviously, that is a function of my "roulette wheel" - my trading system, and how much of an edge it provides. If I assume that my historical results will match my future results, I can use the Monte Carlo analysis to determine my odds of profitability. From that number, I can determine how consistently profitable I am over any given time period.
Using this idea, I ran the analysis on my NGEC system. Before I reveal the results, keep in mind that this system on average will generate over $12,000 profit per year. It is a pretty good system. But will it provide a steady return stream? Here is what the results show:
Weekly - 59.6% of weeks should be profitable. So, within one year's time, I'll should make money 31 weeks, and lose money 21 weeks. That's OK, but not really a great way to try to make a living.
Monthly - 74.8% of months should be profitable. In one year, 3 months will be down months. Again, not very steady returns - what if all 3 down months came in a row?
Quarterly - 86.2% of quarters should be profitable. I like that.
Yearly - 98.8% of years should be profitable. 1 losing year in a 30 to 40 year trading career. That is very nice. The analysis says if I can live with the weekly and monthly uncertainty, then I'll be rewarded almost every year with at least some profit.
Obviously, before I ran this analysis I had to make some simplifying assumptions. For example, on average there are 151 trades per year in my NGEC system. That equates to 3 trades per week, on average. However, the actual number in any week could be 0, it could be 5, or anywhere in between. Forcing it to be 3 every week leads to some error. But, I don't think it would change the results by much. If I am looking for 90% of my weeks to be profitable, then NGEC obviously won't cut it, regardless of the assumptions I made.
The next obvious question is "what numbers should I require for each time period?" That will depend on the trader, and his goals and objectives. A trader used to living paycheck to paycheck may require 95% winning weeks, or 3 losing weeks per year. He might know that more losing weeks than that will lead to eviction. A professional Commodity Trading Advisor (CTA) is measured on a monthly basis, so she might desire 95% of months to be profitable. A longer term trader, though, might only care about winning quarters or winning years. It all depends on the trader's circumstances.
To take the whole analysis a step further, as you add good systems to your portfolio, your chances for profitable periods goes up. Sort of like the casino adding new table games to complement the roulette wheel.
I'll admit, this is not an analysis I really looked at in great deal until recently. It is pretty interesting, and my plan is to take a look at my current systems and see where they stand (I probably won't be sharing those results, though).
@Big Mike was kind enough to run analysis with MSA software. He ran both strategies of the NGEC system separately, and then together as a portfolio. Before are the portfolio results.
The biggest concern I see from this analysis is that the results are very dependent on outliers - big winning trades. Without those big winners, the system is not so good. This is consistent with my experience in the Combine, where I waited and waited for a big winner that never came until after the Combine.
A BIG thanks to Big Mike for doing this!!!
100k starting, s + c included, combine #1 and #2
Correlation
Equity Monaco, after having combined the systems into a portfolio
As the MSA analysis performed by @Big Mike showed, eliminating the outlier trades from the history makes a huge difference in the results.
In the history, there are 614 trading days represented. There are 20 days of profits greater than $1000. In 1 year of trading, I'd expect to see 5 of those "big" days. If they don't come, the system on average becomes only slightly profitable.
Below are some graphs that show the impact of eliminating the top X winning days.
My conclusion is that I am in deep trouble without those big winning days. The question is: Is there a reason why I should not expect these kinds of days in the future? Maybe my system rules and variables basically were curve fit to find these big trades. With 10-20 big trades, I suppose that is a distinct possibility. On the other hand, it is not like these trades are due to a data anomaly or some backtest issue. Strategy #2 was specifically setup to let profits run, and not to cap it. If I saw only a handful of large profit trades, I might suspect some sort of data or backtest issue.
One other interesting question: since I am relying on these "outliers" to generate most of the profit, how likely is it that I even see many of them in a given year? I'll look at that on the next post.
Since I know that the performance of my NGEC system is going to be driven by large winning trades (outliers), I thought it would be interesting to see how many of these I could expect in a trading year.
The results are shown in the table and chart below. Here's what I found:
1. In a year's time, I am likely to see 4-6 large winning trades. That is only 1 large trade every other month!
2. There is less than 10% (actually, 6.6%) chance of seeing 8 or more large winning trades in a year.
3. There is a 13.6% chance that I will only have 0, 1 or 2 big winners in a year's time.
This analysis is a bit sobering, and it does make one thing crystal clear: if I am to succeed with this system, I have to take every single trade, because the one I miss just may be the big winner that only comes around once in a while.
Based on this data, my expectation for the system is a lot of flat to slightly up or slightly down periods, punctuated by a large winner every once in a while. Why is this important to know? Having proper expectations is crucial to long term success. With the NGEC system, I can't get discouraged or lose confidence in the system when I am not immediately making money. Knowing what to expect will help me a great deal as I watch very little happening day to day.
Thanks Kevin, as a host, and the others, as visitors, for this thread and your posts; very insightful.
Hopefully not too much off-topic, but how should I read this chart? It shows the confidence interval widening as the number as trades grows (as should be expected since the larger the sample size, the wider the range of possible end values). But how come the confidence interval shrinks near the end of the chart? Or does the confidence interval plot something different than ending equity?
Thanks for the kind words. I hope it is giving people some ideas and tools. I know I am getting quite a bit out of it.
As far as the curves converging to the equity curve at the last point, perhaps someone familiar with MSA can explain.
My explanation is that it looks like he is doing a Monte Carlo type simulation without replacement. So, the equity path can vary along the way (as shown by the upper and lower curve bounds), but in the end it will converge to the same final equity value as each trade is picked once.
Correct, MSA Monte Carlo randomizes the order but the start and end point equity are the same.
That is why I also posted Equity Monaco's version. Kevin, that image is missing from your post because you put URL bbcode instead of IMG bbcode for the opening code before the URL.
