it seems like a lot of your trading can be automated. i know you mentioned that you have a swing strategy that is more discretion, but are the other systems automated?
Talon, While this thread has been interesting in that you have survived the typical ET flame-assault before people even realized you might have something positive to contribute, I find your continued revelations to be somewhat... disturbing. I say this because there are those of us who may be trading many strategies of a remotely similar nature, that (while seemingly simplistic in this thread) were a pain in the ass to develop with 0 help. So while I tend to avoid making ad hominem attacks (particularly on the Internet), I will say that you sir, are a bastard! Let me make one more attack in a different direction if you please, and say that while the concepts here are somewhat "incomplete", anyone here who dismisses this stuff out of hand or is too damn lazy to do the work... I say to you: You are an idiot and/or not yet ready to succeed (I've certainly been both before)! This friggin guy is providing you with a (imho sound) methodology and working examples on a god damned silver platter! (and doing Q&A to boot!) Now with that out of the way, I must say I like your style and approach, and while I'm not up to your level of notional success yet, I have been following a similar approach (properly develop a portfolio of systems, the less correlated to each other the better) which I believe is sound and will continue to yield a net-positive result. Please carry on and hopefully avoid happening across one of my more robust/profitable approaches. -TD80 P.S. Mod's: I apologize for the general nature of this post in retrospect.
LOL. Thank you for your kind words. I hope this helps someone. It was hard to decide how to do this because it doesn't make sense to give half baked ideas handicapped in some weird way so they won't really work. On the other hand I don't see posting the exact systems I trade with the exact parameters, etc... just doesnt make sense. That's why I tried to keep this discussion on a conceptual level as much as possible. I think that's probably more useful than giving an exact ready to use system (though maybe I've also done that...) I know I owe this thread several posts and will get to it over the weekend. This was a brutal trading week... not so much from the P&L perspective (P&L was actually pretty good), but nothing behaved as it should have so it was hard work. more later.
As a true freshman in the backtesting area, I can say that this is hands down the best system I have tested to date. When I added a few additional techniques, itâs off the charts. Wow! Most kind of you sir! Please know that I am indebted and appreciative. (Anyone â¦. show me a system posted on ET that has => results right out of the bag and I will thank that person too.) So, I ran a number of stocks in Excel using your buy/sell criteria, and then visually looked at the charts. Over and over the buy occurs when a) the closes were as you described; b) the 50 dma is over the 200 and the 20 dma is over the 50; c) todayâs close is < last 13 closes as of yesterday. Performance increased a great deal by having todayâs close > than the 50 dma and only buying if the next dayâs high is a bit over todayâs high. I ran the above on the Russell 3000 for the last 1000 days and simply sold at the close of day 5. There were 3929 total setups and 56.68% winners! (What a start before any exit strategies.) I also modified the closes a bit and ran three red candles in one and another was 3 red candles and all the closes were lower (2408 setups and 54.65% winners.) Now, as Iâve begun slightly changing entries and employing various exits the results are really something. This is simple but yet much better than 50/50. Thank you.
Ok I'm going to try to address these questions in order in separate posts. That way I am sure I will get to everything. Yes we do have some automated stuff... but most of it is a blend of automated and discretionary. The sad fact is, purely automated trading doesn't work as well as people in these forums would like to believe. The fantasy of writing, say a pairs trading strategy in Wealth Lab, that will just automatically do trades and make you money that will compound ad infinitum, is just that -- largely fantasy. Markets change, systems must change, and people do the act of trading. Even pure quant shops tweak and often have traders between the systems and the market... even if it's just to sometimes pull the plug and say conditions are not right for the system to trade. So... no.
No... you compare the shape of the distributions from the market's returns and the system's returns. There are a number of good books on non-parametric statistics... even someone with no background can be pretty comfortable with these techniques after a few month's hard study.
Thank you... one thing that kind of surprised me was the number of posts I received from people saying they are trading strategies like the ones I have "revealed" here. These are sound approaches... but not the holy grail. They'll at least get you pointed in the right direction. What you're doing here is an important part of the research process, but you have to be careful. Every time you add something and see how it works, and then tweak or take it away... every time you do that you are optimizing and taking another cut through the data. Now... if you don't do this you can't find good systems... but do be careful with this. Does that make sense? Yes you're doing exactly the right thing in the way you're thinking and the kinds of questions you're asking. yes, the only way to get answers to these (correct) questions is to see what the data say. But that process of asking the data is dangerous and multiple answers to multiple questions erode your edge and the validity of the process. It's a fine line. Also, make sure your universe of stocks includes some disasters like Bear Stearns, Lehman, and Enron. Running this, for instance, only on AAPL, XOM, and PCLN would give you a pretty distorted view.
Ok I may have done a bad thing here lol... I was reading BoWo's thread on Pairs Trading and saw a post where he made serious errors in analysis... I am reposting something I posted to his thread here because I think it includes valuable lessons about how to analyze a backtest: Sorry for the repost: Wow.... I didn't realize he had posted his complete trade set already. FYI I am going to cross post this in my thread because I hope to give some valuable information on how we look at distribution of system returns... and I know the little turd deletes my posts from his thread so I can't count on it staying here. C'est la vie, ne c'est pas? Anyway... first things first. There aren't enough trades here to analyze properly. If we have a system that trades this infrequently, we must be very convinced of two things to put money behind it. 1) it's fundamental validity and 2) the development process. Let's accept those at face value here even though this particular approach is profoundly flawed and I have reason to believe the development process involved a fair degree of optimization. We will proceed as if this is were not true though. So... One at a time... BoWo's quotes in bold and my answers below. Sorry to do this to him, but I honestly think there is a valuable lesson for everyone here... a reminder of basic statistics and approach... and hopefully for him a lesson on hubris: Quote from bwolinsky: I have done some research on the profit percent distribution of the trades and find the average profit accross all trades is 2.575%, with a standard deviation of 5.7665%. This implies that 95% of the trades will be 2.575+/-5.7665*1.96=13.87734% or -5.53%. I believe it's good that 95% of the trades approximately already fall into this distribution, and especially the low value is a little beyond my stop of 5 and an 8th percent. Well... um... no. Your simple rule of thumb is correct if and only if the data are distributed normally. In market data and trade returns, pretty much nothing is normally distributed. This is a rookie mistake. However, let's take a look at the data. See attached file. The bars are the returns of your actual trades, the red line is a "what if" the returns were normally distributed, and the dark green line is the empirical distribution of your sample. As you can see from the shape of the graph, these returns arent even close to being normally distributed. (This in itself is fine... exactly what we would expect from real market generated information.) However, the "eyeball" test isn't a good one.. there are a number of other tests we can run: Without boring you with the details, running Shapiro Wilk test on this data set gives a probability of <.00000 for the data being normally distributed. A formality, but one we should be in the habit of conducting. Going back to the old eyeball test though, I see a problem. The "left tail" of your distribution is severely truncated. This is a problem... This is a characteristic I have seen time and time again in system development that is either done on an incomplete data set or without enough trades. In simple English, a distribution like this assumes you'll always be able to get out at your stop... and you won't. So in actual practice you can expect worse losses than your system results predict. How big of a problem this is depends on a number of factors... I can't give a good rule of thumb without knowing the system intimately. So... be careful of your standard deviation assumption... it is not correct... your returns are likely to be much wilder than your system development leads you to believe. This is a problem. I also examined the kurtosis of the distribution and found that it is a less peaked distribution as evidenced by it's value being less than 1 at exactly .749182809. Many people would then conclude that that would imply there are fat tails possible in my system, but, you would have to look at the "skewness" to determine where those tails are, and, based on the skew of 0.927014752, I can conclude that negative values are quite limited compared to the huge profits on the right, positive side of the distribution. This is a good thing, and one day I hope somebody will realize just how good of a distribution that is. I also, at some point, hope others would share their distributions with me, as I have, to compare. I believe there are tons of systems who may be exhibit lagging kurtosis with negatively skewed distributions that imply the system has "hidden risks" inherent in the system. A kurtosis below one, as I have said, means the distribution is "less peaked", and the step most forget then is to examine the skewness to determine "where the fat tails are at." In this case, if you had found a system with kurtosis below 1, and resoundingly positive skewness, you may conclude that the so-called "fat tails" are actually benefiting you in that they are "positively skewed, fat tails." No. No. No. No. and NO! I am sorry, I cannot be polite here... this guy claims to be the "best system developer" and then makes such a fundamental error... it has to be pointed out. First of all, let's deal with your math. You can't use Excel for analysis because the statistics in Excel are wrong. Here are the actual results from Excel's Data Analysis module: Mean 2.575227273 Median 1.71 Standard Deviation 5.766540423 Sample Variance 33.25298845 Skewness 0.927014752 Kurtosis 0.749182809 And here are the correct results from another piece of software: Mean 2.575227 Median 1.71 Std. Dev. 5.76654 Variance 33.25299 Skewness 0.9111379 Kurtosis 3.639872 Note that Excel gives incorrect values for Kurtosis and Skewness. In this case, not fatal, but there is an important lesson here. DO NOT USE EXCEL FOR DATA ANALYSIS. Now, on to your analysis of kurtosis. "Positive excess" kurtosis (Excel gives .75 vs Stata's .64... both are positive at least) may be generalized to mean that the tails are heavier, shoulders lighter, and more values cluster around the mean. So you are exactly wrong when you say "I also examined the kurtosis of the distribution and found that it is a less peaked distribution as evidenced by it's value being less than 1" Leptokurtic (excess kurtosis > 0 (not 1)) distributions are MORE PEAKED and have FATTER TAILS. What you mean to say is that this distribution has fat tails. Next you say "you would have to look at the "skewness" to determine where those tails are, and, based on the skew of 0.927014752, I can conclude that negative values are quite limited compared to the huge profits on the right, positive side of the distribution." This is not what the skew tells you... and you're still trying to incorrectly apply rules that apply only to the normal distribution here. I won't go on with the math lesson, but this is simply incorrect... there are number of books on descriptive statistics that can help. I encourage anyone to examine this distribution, and provide their current system for analysis. Done BoWo. Attached find a txt file of actual percentage returns from an intraday system one of our trainee traders developed. I'll leave you to do the analysis (and, ahem, encourage you to not use Excel.) Point being, these are actual returns not theoretical backtest... and 1 year ago this person couldn't even tell you what a bid/ask spread was. This is a testament to the power of doing the right thing, learning the right things, and focus focus focus. The point I'm making about "fat tails" is the proverbial "Black Swan" argument that really denies basic statistics. Certainly there are always outliers, but they don't happen very often. Once in a 1000 years even for some calculations of financial events, so the probability you hold it on that day is not even something to consider in your approach, and the "Black Swan" theory really has no basis in my opinion, because all it says is that <b>if there's always the possibility of a large move, you must not ever take risk</b>, which is a false assumption. Given that the probability of such events is so unlikely then if it does happen to you, you shouldn't change anything with what you were previously doing, as it can be considered economically and essentially a "sunk cost" so that it does not enter your strategic investment decisions. You're obviously referring to Taleb's book and the joke my friend is on you. The whole point of Taleb's writing is that people who have an elementary understanding of statistics don't understand Black Swans. You have proven that here. I sure wouldn't want you managing my money since your answer seems to basically be dont worry about the big tail risks... I mean... yeah sure... these black swans only happen about once every 10 years and they almost bring down the whole financial system. Why try to understand these risks when they are so trivial, right? Obviously that was an unkind joke, but the real point is that we never understand our risks. They are always FAR worse than we expect them to be... In your case you might consider the risks involved in these leveraged products in terms of counterparty risks, etc... So called Black Swans, and respect for the risks and possibilities inherent in these events, are one of the central problems in trading. I'm sorry you have chosen to ignore the possible lessons here so completely. I hope I wasn't too big of a d*ck to BoWo here... I was partially responding to him but also hoping to correct some misinformation.
Dear Talon, I had read this thread with the utmost care, and I have two brief questions. You mentioned you wish to help us with system development, and I really and truly feel you want to help, and I admire that. And I appreciate it. I wondered what made you suggest the parameters of the following: Buy the close of this bar when: 1. it is above the 50th percentile of the past 200 days' closes. 2. it is below the 10th percentile of the last 15 days' closes. 3. It is the third consecutive close down. Exit conditions: 1. Sell when today's close is higher than the 50th percentile of the past 5 day's closes. I mean, why not 60th percentile of the past 200 day's closes or "below the 8th percentile"... etc. and the second consecutive close down? Is it just personal experience when you wish to construct a new system idea?? And second, on the original system of the S&P add/drop, wasn't it supposed to be LONG PCLN since it was ADDED to the S&P500, and short the SPY?? That would make your original system idea profitable up to this day. Could you quickly answer these two questions?