Sorry, Harry. This thread should be moved to Chit-Chat or Trash Bin. It certainly doesn't belong in Technical Analysis.
Poor guy ... did you go further than college, I wonder. And if equity curve doesn't concern you, you're surely not a trader haha !
My equity curve certainly doesn't look like any of those in your chart! Why do you even bring up this nonsense? (Once again, I'll give you the last word as I've already spent too much time trying to find any meaning in your posts.)
This nonsense like you call it is exposed in the book of famous Hedge Fund Peter Berstein "The improbable origin of Modern Wall Street" on the difficulty to judge a trader's performance because of this law . This the second time that you ask me for some lesson : I hope you have taken the first one : http://www.elitetrader.com/vb/showthread.php?s=&postid=380628&highlight=armstrong#post380628
That's Tony Crabel is right when he says that http://www.elitetrader.com/vb/showthread.php?s=&threadid=24680&perpage=6&pagenumber=1 "TOTAL NET PROFIT: ....is of very little value when it comes to evaluating a trading strategy's estimated future performance, no matter how rigorous the testing or how robust the system." And that's why I said that it is necessary to look only cumulative but above all at detailed samples: http://www.elitetrader.com/vb/showthread.php?s=&threadid=25063&perpage=6&pagenumber=4 Re: Stragedy break down: If you make 2000 trades per year and that it is not beneficial each year it can be very doubtfull: not only it should be beneficial each year but almost each month since more than 100 hundred trades per month must show something significantly different from 0 : statistical significance grows with the size of sample so if it is not positive (nearly) each month it is already doubtfull. More generally it is more important to look at the distribution of subsamples means (of each month, week,...) rather than the one based on total aggregated datas. -------------------------------------------------------------------------------- Quote from amigasearch: Hi. I am new to systems development, i started because I have ideas I would like to make mechanical. I have posted before with some questions, and now, i have others. I hope I can get other system developers opinions/experience. I have a programmed system, which preforms very well for all of 2003 (backtest). 65/35 winners to losers, $12 avg. trade, 10 percents max DD and max DD avg. is around 4 percent. I factor in commsisions, and the like. Trades on S&P emini, and does avg. 10 roundtrips a day (2000 trades a year). --------------------------------------------------------------------------------
I already said that : http://www.elitetrader.com/vb/showthread.php?s=&threadid=25053&perpage=6&pagenumber=3 There is 2 things to distinguish: Risk management and Money Management in the restricted sense of optimisation (position sizing,..) used by Ralph Vince for example - the author of the classical "New Money Management". Of course there is some overlap between the two. The most important one is the Risk Management because it relates to the alpha risk type in term of probability theory which is the risk of being in error whereas optimisation relates to the beta risk type which is only the risk of missing some opportunity. Missing opportunity cannot conduct you to go broke (although it should be modulated in details but I simplify here) whereas not knowing the alpha risk can get you broke. People focus too much on Money Management thinking that it is the "secret" of wealth - perhaps because of sellers of books/systems which have interest to put the accent on Money management rather than on risk management. Yes you will see people who become rich suddenly because they applied martingale rule (BTW so called anti-martingale rule is also a martingale rule mathematically it is amusing how marketing tried to disguise to people things through fake name !) but what you see is the "survival bias" of chance that's why the same person when ruined later is incapable to reproduce the same exploit. Money Management is only useful when Risk Management is already under state control. Then it becomes easy to optimise that is to say use Money Management (using probability with or without Monte-carlo, Linear Programming). In conclusion: "PREMATURE optimisation is the root of all evil" It is in fact Knuth's famous maxim in software programming but as you can see it can apply to other field since Money management is about optimisation. Doing Money Management before doing the essential part of Risk management is also the root of all evil (it will conduct to overfitting and constant tweaking for example).
Harry, the only lesson you could give me is "what NOT to study to become a great trader". The stuff you spend your time on will only lead you to "analysis paralysis". You seem like a decent guy, Harry, so let me suggest that you spend your time researching the more useful elements of trading and leave the conspiracy theories and macro economic analysis to some other dimwit. Good luck to you, Harry.
Harry lets say your copulation of other peoples work on the theory of "clumping" in statistical distribution being perceived as cause for trend when viewed on a micro basis holds water. Furthermore, lets say that a trader who is using TA and has been profitable for 20 years in a row is just living a statistical anomaly in the grand scheme of things. This leads me to ask: how do you view your econometric models success at this point? Is it random clumping as well since your system is only a couple of years old (I'm assuming the origin of your model of course) and therefore, its success so far is nothing more than an anomaly itself? Or do you consider it above these inherent laws of statistical distribution and to actually have a real edge? If you answer that is has a real edge, please explain why in detail. Thanks Harry.
Cher Harry, Tu es infatiguable! Harry, how do I long to see another one of your beautiful and colorful little graphs you used to publish about half a year ago. I don't mean to say that Fibonnaci and Arcsinus are not interesting but these graphs were much more fun to look at. Ton fidèle lecteur, nononsense