Sounds good. In the interest of not having to backtrack, please go back a few days and read the other posts I made to this journal. There are some issues raised there I think we need to address. Looking at those posts before you attempt the analyses will save us some time down the road. Thanks. Looking forward to a constructive discussion.
Damn it... Right when it starts getting fun... You guys back off and become all nice and polite... I wanted to see people go head to head all insanely egoistic on me and everyone else... Magna... can I insult bwolinsky so that he gets all emotional and berkserk on me??? I've been acting all nice recently and I think I need to offset some stress on people... Added: talon sent me a PM and I figured that I should step back... so I'll let you guys discuss things in a civil manner... Just tell me when I can make bwolinsky's blood pressure to go up...
I have two requests for this discussion. I would ask that you refrain from hyperbole in describing yourself. I realize this is your style... the kind of self-talk you do in the mirror that gets you going in the morning. I'm not denying the benefit of talking yourself up when you don't yet have the P&L or career achievements to provide positive feedback, but I don't think outrageous claims further this discussion. You obviously do not believe you are the best system developer in the world, so let's try to have a rational discussion without exaggeration. Can we do that? My second request is that you refrain from comments like this, attacking my business or ability as a trader. We will have a discussion later about annualized returns and the interaction of raw expectancy and position sizing, but that discussion should be later. APR must be a statistic Wealth Lab provides you? It certainly is not a system statistic that I have ever attached any significance to... for a number of reasons. For the record, you're wrong... the system my trainee developed (you have several months' returns in the spreadsheet) is on track to return well over 80% annualized... and keep in mind this is a system developed by someone with no finance background. Intraday returns on accounts can dazzle you when you aren't used to thinking about intraday systems, so it may require some adjustment to think about them properly. For now, let's let the system returns stand on their own and avoid petty attacks. Cool? And what institutional system are you talking about? Did I post something one night drunk off my ass and I don't remember it? (Always possible lol...)
LOL... weren't you banned a while back? You should know that Beau won't believe any returns unless he sees them on C2 or covestor... in effect you'll end up arguing into a wall. I don't know what it is about this thread that keeps me coming back. Normally I ignore people like Beau, but, he's just such an easy target... Also, I've learned something from this thread: if you write down how awesome you are over and over and over and over and over again you will eventually become awesome, right? I mean look at Beau, he's so awesome he has to tell everyone here, again... LOL
There is some element of egotistical thought I find very positive, but please don't forget passing Level I of the CFA Exam by itself <b> is a significant accomplishment.</b> Respecting that will further the dialogue I plan to have. I promise you guys I will come back to this day after tomorrow. For personal reasons, I have an anniversary to celebrate tomorrow, so I will not be available. Till then.
Congrats on your anniversary... have a good celebration. CFA level 1 is a good start... but you can walk out the door in this city and one of the first 10 people you see will have their full CFA. Half the resumes I get are CFA candidates and I would say 20% are full CFA's. So... I'm not belittling your accomplishment... but these are table stakes and, frankly, not a grand achievement. Again, not meaning to be insulting, but that's just the truth. And... btw... I'm more likely to hire someone without a CFA than with. Why might that be? (That's a real question and the answer is important.)
When you start going through old posts, please specifically respond to the items I highlighted in bold. This is disturbing coming from someone with a strong math background as it, frankly, is nonsense. 1. What is "lagging kurtosis"? This is not a meaningful term. 2. How do you generalize from skewness to the weight in the tails? 3. Is this assumption valid for distributions other than normal? How about for a distribution such as Cauchy with non-finite variance? 4. The normal distribution has a kurtosis of 3 and some software packages subtract 3 (wrongly) from kurtosis to give you excess kurtosis. Excel is one of those packages that does this, but in these packages a kurtosis of 0, not 1 as you state is normal. I can construct a multitude of leptokurtic distributions with heavy left tail risk that exhibit positive skewness so I do not understand the sense of what you're saying here. 5. And on a more philosophical level, do you really think skewness and kurtosis have any meaning for the complex distributions we see in actual trade returns? Aren't there better measures of tail risk? Why, aside from these stats being readily supplied (albeit with incorrect values (see earlier post)) by Excel's Data Analysis module, are you focusing on these and not at least doing a visual inspection of the histograms? Please clarify the math behind these points when you get a chance because these concepts are so fundamental to understanding the mathematics of expectancy and chance. I'm not trying to be confrontational, but these issues must be addressed.
I guess I haven't posted any tradelog (I actually did post a few but got lost somewhere with all the profanity that came along with it) in the past journal/thread so I went ahead and outputted a tab delimited text file (it's got over 50,000 trades and adding stuff and porting it to xls goes over the upload limit...). Because Bwolinsky has some odd interest in "Institutional Level" trading... I thought that I should just pull out one of my models I use on BATS (It's on the blotter). It is an intraday Cash Arb model (with Rebate), does around 60-90 trades a day across different symbols. It's not a Single Leg Gamma but it's a pure text book Pairs / Stat. Arb.. This is a live result that's been risk adjusted with commissions. (Posting results with sizing does skew the model). Considering that bwolinsky's model in the first post was about 3 years old, I chose the model with the highest 3 year Sharpe, for the sake of bragging and showing off. Anyways... you can just drag the txt into your xls and do whatever tests you like to run with it... Then you can start telling me all the negative things about the result, telling me that it doesn't prove jack shit... (and I know... but I think it'll be fun...) etc. etc. etc.
I'd also ask how one can extrapolate into the future, from a *limited* sample size, that one is or is not actually dealing with a Cauchy distribution? Tests for normalcy are qualitative... and, assuming one can convince oneself that the variance is in fact finite, well, even in such a case, how do you determine worst case risk? Lots and lots of data helps... as does a rock-solid fundamental basis for the model...
Per 1) Lagging Kurtosis is any kurtosis value below 1. It's not a normal description, but the best I could describe how you know there are fat tails in the distribution. ex-post edit: Your other posts mention 0 being the normal kurt value, but I really swear I remember vividly a class where the instructor had to mention excel calculates kurtosis differently, and subtracts three, but as you see, I'm not sure why I thought 0. The memory is a little distorted. I'm still confident that 1 in excel is the measure of normal distribution. Per 2) It's very obvious to me, if the skew is positve, it might be that there are "more peakedness" at the other end. Perhaps it will be more obvious to you if I present the graphical representation of the distribution. I think it's <b>extremely obvious as to where the skew is, and why there are fat tails at the positive end.</b> Just have a look at the enclosed chart, if you think otherwise, I'd need to re-think what I know about statistics. Per 3)http://en.wikipedia.org/wiki/Cauchy_distribution I don't believe this applies to anything but physics, and I don't really care to comment about it. <b>I would say any distribution of a financial dataset can be converted from non-covariance stationary <i>to covariance stationary through several transformations.</i> </b> I describe mine as a "normalized z-score", requiring probability theory to understand, and not much more. If you're good at statistics, you should know what I'm talking about. Per 4) For some reason, I recall vaguely in a class that 1 in Excel was actually where the normal distribution laid from kurtosis. Mean of zero, sigma of 1 was a normal distribution. Maybe I'm just remembering or misinterpreting an old memory. Per 5) The visual inspection confirms my analysis as well. Thank you for confirming it with the histogram below. ex-post edit: While re-reading this post, I discovered, you maybe wanted a histogram. It's pretty obvious to me. I just started. Please let me get through these posts, as there is a bit of dialogue I need to address.