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The Junk Rally and Quant Hedge Fund Performance: A Lesson in Asymmetric Risk

Simons Questioned by Investors & Live-Blogging The Renaissance RIEF Call

R/Finance 2009: Applied Finance with R

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A few years ago I found a document put out by DrKW Macro Research called “The Seven Sins of Fund Management” (caution – PDF) – it is truly an awesome piece of work, and a brilliant critique of the mutual fund space (and active managers in general).  I could not remember where I had found it – so I’m going to thank whoever originally posted it and then re-post it here for others.  This paper really formed a lot of my thoughts on why I should either be using a quant strategy or just be passive in my investing approach.

The paper is full of great insights – but my favorite is the analysis they did of stock picking performance relative to confidence in the outcome.  Here, they measured both students/lay people and professionals.  The outcomes are truly eye-opening – in this first chart, you’ll see that the students bested the professional in accuracy, but did so while having a lower confidence rating.  In other words, the professionals were both cocky and wrong.


This one is great as well – it shows what perfect calibration on stock picking accuracy is as confidence rises, and then it shows both lay people and professionals.  While the lay people are static, the professional actually get worse as their confidence goes up.


Anyway – it’s a great read – hope you enjoy it as much as I did.

In a related continuing story, fund managers continue to underperform the market.  Shocking!  😉

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I’ve been crazy busy with my day job and Max – so my apologies for not posting more – that’s just the way it is at the moment.  But in the meantime, I wanted to post a little diatribe I’ve been thinking about.

I’m going to start with a generalization – people that are used to investing based on typical investment metrics (Cash flow, earnings, etc) have a strong distrust of black-box quant strategies.  I’ve seen it first hand.

But here’s my question: for the outside investor, why do they find it comforting that they have invested with, say, a value portfolio manager vs. going with a quant fund?  The answer is pretty obvious: they think they understand what the value PM is looking at, and, more importantly, they have faith in the particular set of metrics that the PM uses.

I’ve read a lot of detailed fund prospectus (some from very large hedge funds), and I find them all pretty, well, general.  “The portfolio manager selects stocks based on value metrics such…blah, blah, blah.”  So why on earth would they have confidence in this methodology?

The answer of course is performance.  This is why people chase performance.  They see a hot hand and they move in.

But in my mind, they have no greater understanding of what the fund manager is doing than in a quant fund.  So given that, is it even important that you understand how a quant fund works?  Isn’t the only judgement the performance?  And even if you did know what the value or quant portfolio manager was doing, how would that help you?  Would you give them a call and say “hey, I know how to fix your issue!” and expect them to welcome the critique with open arms?

I guess what I’m saying is that if you’re investing with someone else, it doesn’t matter if they are a human or a black box quant strategy – they are both equally opaque.  It is just that the value PM has the illusion of being understandable, and the quant strategy has the reputation of being either voodoo or genius.

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The Bankling site is still new to me, but apparently they found me – and they’ve named Skill Analytics to the six sites they mention under Technical Analysis.  I’m in good company there with Ripe Trade and ETF Trends.  I’m going to have to check out the others that they mention.  Thanks to the folks over at Blanking for reading my little blog.

I do find it a bit funny that I’m mentioned in a mutual fund toolbox when I clearly have demonstrated a true dislike of the mutual fund industry.  Ah, the irony!

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It wasn’t even close – Cramer must have come on the show thinking that Stewart was going to be, as I too expected, his normal nice guy in terms of a personal interview.  But I think Stewart took the “comedian” and “variety show” comments very personally, and instead he showed himself for what he truly is: a great political satirist.  I was watching it downstairs and then ran upstairs to see that my wife was also watching it – we were both just amazed that Cramer didn’t get up and walk off the set.  He got creamed.  At best he looked like a bold faced liar. If you missed it – you have to check it out.

One of the main arguments that Stewart brought up was that CNBC (which, for the record, I very rarely watch) should try and do some actual reporting.  I remember an old boss of mine described the blog Engadget (which I read and enjoy) as “snarky comments plus press releases” – and I think CNBC suffers from this same issue.  There is no thoughtful reporting – caused, I would guess (and as Jim pointed out) trying to fill 17 hours of television per day.  So I started to come up with a list of stories that they really should have been ahead of the curve on instead of, as Stewart said, being an infomercial for the financial industry.

  1. Madoff: No shocker here – the evidence was clearly kicking around as was the whistle-blower Markopolos.  They should have been on this one.
  2. The Housing Bubble:  I remember in 2006 watching a CNBC program that was a roadshow on the housing industry where they traveled around talking to real estate “professionals” who all said there was no bubble and no issues with the mortgage industry.  Yet even I knew there was something dramatically wrong with the situation.  All they needed to do here was just ask tougher questions and read some blogs.
  3. FDIC funding:  This just came out a few days ago, but I was amazed they weren’t on this – namely that the banks had not paid any premiums and the FDIC was now, essentially, broke and would require a $500b guarantee from the government.
  4. Leverage: CNBC got lost in the weeds of argument about whether the CRA/Fannie/Freddie caused the housing crisis – but they completely missed the big story – that leverage was being employed all over the place.  First at the banks, then at AIG (via unfunded CDSs) and then by hedge funds using borrowed money to buy assets.  Cramer actually stated last night something to the effect of “if you’re returning 30% a year no one asks questions” – well, if you are actually earning 5% and then using leverage to get it to 30%, that’s a very different story and they should have been asking questions.

Got others?  Post ’em!

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Michael over at Marketsci asked a great question in his latest post – why do mutual funds continue to show no ability to think outside-the-box despite the abundance of alternative investment approaches that are available publicly (either from individuals or via public research) or from individuals that they could potentially hire to help run their fund (particularly in the quant area).  I thought I’d take a post and attempt to answer Michael’s question.

But first, a brief story.  In 2003, I was working in New York City at a start-up and just beginning my “quant journey” when our company was sold.  As Chief Technical Officer of the company, I was out of a job as there was someone at the new company that already held my position.  I was given a nice consulting contract and time to figure out what I was going to do next.  I was approached by one of the original investors my startup who was starting a hedge fund.  He felt my background in technology would make me a good analyst on technology-related stocks (I’d also told him I thought Apple was a buy in 2002 and he’d made a lot of money off that call).  When I told him I had no idea how to be an analyst, he offered to teach me.  Thus began what I can only describe as my on-the-job MBA training.  We were a fundamental-oriented shop, and I learn everything about fundamental analysis.  We did ok – not bad, not great.  And then my boss was offered a job at another fund, and he decided to shut down our fund and get started over at the other firm.  He’s done very well and is still one of the best investors I’ve ever met.

The question then, for me, was what to do next.  I wanted to get into another fund, but my background and experience was unorthodox to say the least.  A few years later I got an introduction, via a family friend, to a large mutual fund company that was looking for a small-cap analyst to join their team.  I was somewhat excited to go in – it would be a job in the right sector – but somewhat concerned about what it would be like working for a mutual fund.

I studied up on the fund for about two weeks.   The fund seemed to have changed strategies multiple times, and had now settled into a strategy of equal weighting sectors, and then using stock picking within each sector based on both quantitative measures and analyst recommendations.  It held 100 stocks across all the sectors.  All this sounds somewhat interesting, but the performance of the fund, to date, had been terrible.  An investor could have outperformed the fund in all time periods simply by buying and holding IWM.  Adding insult to injury, the fund had a huge sales fee of 2.75% (that’s an upfront cost to coming into the fund) and a very high expense fee for the fund itself.  So not only was the fund underperforming a simple index strategy, it was doing at a huge cost.

The interview itself was cordial but I knew, going in, that I was a long, long shot by any stretch of the imagination.  The fund manager asked me his first question: “how would choose stocks for this fund?”  I had given this question a lot of thought, and even run some simple tests to understand what the portfolio would look like.  I proposed to do a momentum ranking of sectors and then choose to overweight the specific sectors that were outperforming over a 12-month time period, and then select stocks within those sectors based on a variety of different criteria, including some fundamental-based quantitative measures as well as some price-based measures.  I then showed what the returns could potentially look like.

The fund manager didn’t seem to really care.  Perhaps it was because he felt the interview was pointless in the first place (because my background didn’t match with his expectation), or that he just so disagreed with my approach, but he then went on to tell me why my approach wasn’t appropriate and why he thought that their approach was superior.  Now, I chose not to be too confrontational with him on this because it was, after all, a family friend that had introduced me, and I didn’t think there was much to be gained by defending my approach too much.

But what I wanted to say to him was this: let me get this straight – you’ve underperformed the index since the inception of your fund while overcharging your customers for the privilege, and you’re telling me that my approach lacks merit? Instead I pointed out some issues with his current approach and refocused on the benefits of my approach – including citing research papers about the momentum effect.  Whatever – the interview was clearly over at that point as I could see him getting ready to move on in his day.

I asked him then what type of candidates they were looking for for the position.  He said that they were looking for someone with 3-4 years of buy-side experience or someone with 5-6 years on the sell-side (an MBA was pretty much implied here).  This was understandable at the time – getting someone from the buy-side to move over to this position in 2006, the height of the exodus from mutual funds to hedge funds, would be challenging – so he was mainly focused on the sell-side analyst community.

He ended by thanking me for coming in, and then suggested that my approaches seemed more appropriate for a hedge fund and that I should focus my job search in that area (remember that comment – I’m going to come back to that in a bit).

Ok – the story was supposed to be shorter and got longer – apologies – but I think this story demonstrates a lot of the issues with mutual funds today.  Let’s break them down.

  1. Small Gene Pool:  The mutual fund community generally hires people out of business school – not people with a background in sciences or any other background (Bill Miller’s degree in philosophy notwithstanding).  As a result, they’ve got a fairly homogeneous group of people that were all trained the same way.  The “craziest” they tend to get is to hire someone from the sell-side – which is interesting because the sell-side is a pretty good contrary indicator to stock performance in my experience.
  2. Reliance on a single approach: The mutual fund industry relies on the marketing idea that stock picking works (whereas research shows it rarely does) and that their particular group of analysts are the best stock pickers year after year.  Watch mutual fund commercials – they all have the same tone: “Experience, driven by the long term investment view, top team, etc.”  They all usually have the same kind of images as well – a team of people rowing together, or some sort of relay race, etc.  Yet any form of analysis of the industry shows the opposite – that any person would be better off with just a collection of index funds with low expense ratios.
  3. Strategy Scaling Requirement:  Mutual funds (and hedge funds) have a large issue in terms of scale.  For a mutual fund to make money – because they make their money on fees – they need to get big.  That means they can’t have very active strategies.  And it limits the companies they can invest in.  And it means that when they buy or sell, they are the “dumb money” – they tend to sell at the bottom and buy at the top because it takes them time to get into and out of a position.  In addition, many of the quantitative strategies that people put forward on the net (including my own) simply won’t scale to the size of a $1b fund.  For the individual investor, this is the advantage they have over these big lumbering giants.  The same is true for hedge funds as well – a friend of mine has a strategy where he simply invests in small hedge funds when they have less than $500m under management and exits when they get bigger than that – because he knows that funds are hungrier when they are smaller and can be more nimble.
  4. Belief that quantitative strategies are more risky: Remember the comment in the interview “maybe your approach would be more appropriate for a hedge fund” –  very interesting.  What he was saying, in my opinion, was actually “your strategy sounds riskier, therefore my clients will be scared” (It could also reference the scale issue mentioned above or that he thought I was a risky individual in terms of my background).  What he failed to understand (or even ask me about) was the risk-adjusted return.  He was just focused on the idea – not the result – as was obvious in the way he was running his own fund.  He was in love with the idea regardless of the results.
  5. Lack of a burning platform: So this fund was able to charge a 2.75% sales fee in addition to the yearly fee, underperform the market and still managed to have some customers?  What that tells me is that the people they’re selling this shit to are either not engaged in the world of investments (pension funds, individual 401k participates), in the pocket of the mutual fund company via some relationship, or they are just stupid.  So what, exactly, would be their incentive to change the way the fund was run?  Exactly – there was no incentive.
  6. Fully invested: This one is easy – most mutual funds have to be fully invested – keep their cash at a minimum amount.  This is a huge disadvantage over the individual investor.  Now, historically they’ve made the argument that timing the market doesn’t work and buy and hold is the way to go.  In general they are correct that most people cannot time the market.  However, if you buy into the buy and hold argument, then you’re still better off going with index funds.
  7. 100 stocks or more = Indexing: Most mutual funds (including the one I was interviewing with) have to hold a rather large number of stocks in order to scale.  In my experience, I’ve learned that approximately 60-65% of returns come from the general market, 20-25% come from the sector, and the remaining returns come from the individual stocks.  But if you’ve got over 100 stocks in a portfolio, you’ll discover that the portfolio starts to become very similar an index (assuming you’re doing equal sector weighting like they were).  So they were, essentially, a closet indexer with a high cost.
  8. Skepticism of quantitative price analysis:  This is a generalization, but I’ve found that most of the people that run mutual funds think that analyzing price action or using some other form of quantitative analysis is either voodoo or stupid.  To me, this is why James Simons over at Renaissance can eat their lunch while charging huge fees.
  9. Belief that they can out-perform the market:  This is a basic one but I think it should be stated – if you completely believe that you can outperform the market through fundamental stock picking, year after year, then that is your world.  If they would do any research on the subject, it would probably cause a cognitive dissonance so large that they would disappear into a deep depression.  Or they would say “fuck it, I’m making money off these chumps”.
  10. Belief that they can understand what is going inside a company:  Enron is an obvious example of this, but I see it all the time – these guys actually believe that they can fully understand these companies from the outside.  Even after SarBox has taken away many of their tools.  To me, what they are actually doing is guessing what is going on inside companies.  And you can never really know as is evident watching companies both beat and miss on earnings.  I can remember sitting at my desk at the hedge fund, waiting for an earnings release and realizing that I was just hoping the results would come out as I thought they would.  Hope, as they say, is a four-letter word.

I’ve rambled on enough in this post – I’d love to hear from readers as to what are other reasons that I may have missed.

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Market Monk has been doing an interesting series on Survivorship Bias – and how much of a problem it can be.  What shocks me is that not one developer of system testing software has dealt with this.  Here’s the deal – if you’re testing on the Nasdaq 100, your test is likely to be invalid because of the stocks that have gone away.  Or if you’re creating an index based on the S&P 500, then that index will likely not be valid going back in time, say, a year before the index has problems.

So what’s the answer here?  One possible answer – create a custom index (with all components) that includes all stocks that have traded in the index.  Now, you can get a list and data for all the delisted stocks – but the issue is creating an index that either includes all of those delisted stocks, or have the list be dynamic – meaning that it updates as changes are made.  As of this writing, I don’t think one data vendor or system software creator has a tool to deal with the issue.  I’ve been chatting with the folks at Norgate Premimum Data services – it sounds like they might be working on something to deal with the issue later this year.

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As part of creating more discipline for myself in terms of posting, I’m going to steal an idea from Headlinecharts and start making specific days of the week the time when I do repeated postings.  So, I’ve decided that Thursdays are for Relative Strength.  I’m posting two views of Relative Strength – one using my proprietary 100-day view and the other using a simple ratio.

New strength: SMH (Semis), Growth over value (IWO), Nasdaq stocks (QQQQ).

Continuing strength: GLD (Gold)

Fading strength: IEF (10 year bonds)

Relative Strength  – Custom Indicator:


Relative Strength – Ratios:


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I love to surf around and discover articles by following Alice down the rabbit hole – meaning – start down a path and just keep going.  I was reading an excellent post by Woodshedder over at ibankcoin.com this morning on position sizing.  I think the post and Van Tharp articles (part 1 and part 2) it references are a good source for understanding position sizing and the effect on a given system.  In fact, I think they should be required reading for any aspiring trader.

The Woodshedder post referred me to a blog I was unaware of – Max Dama – a student/quant.  Max is obviously very, very smart (about 10x my brain power judging by his blog).  Max was profiled in a piece in Porfolio (also available via Wired) on the rise of quant-based strategies in the financial world.  That article referenced Legend Advisory – who offer a quantitative approach to asset allocation.  They use an artificial intelligence model for determining the asset allocations between different sectors and styles – think “should I be in financials?” or “will growth outperform value?”.

I did some more searching on Legend and came across an article in Allbusiness that detailed some of their predictions from December 2007.  Here’s what I find fascinating – for all their math and study, two of their predictions stood out to me as being so, so wrong (and they had others that were right) that it made me question their whole approach.  My comments are [in the brackets].

1. The financial sector should outperform in the second half of 2008. [My comment – wow – stunningly wrong].

2. Corporate earnings growth should continue to decline. [Interesting and correct – but what do you do with it?]

3. P/E multiple expansion will result from lower interest rates. [I don’t have the tools to look at this one to know if it right or wrong – my guess is that it is correct but again, what do I do with it?]

4. The US Dollar should continue to weaken throughout the year, but could reverse its course before the end of 2008. [Correct!]

5. After underperforming the broader markets for almost 6 years, healthcare should surprise investors (positively).  [Healthcare outperformed the general market, but still declined – I’ll give them half-right.]

6. The real US economic growth rate (GDP) will decline in 2008, below its historical trend. [Correct – but then how could you say that financial would do better given that the market is so dependent on the performance of financials?]

7. Growth stocks should outperform value stocks in 2008. [Value actually outperformed growth, at least in the small cap arena, for more than half of 2008]

8. The S&P 500 index should reach 1625 by mid year, 2008. [Stunningly wrong – the index was at 1504 on Dec 7th, the time of the writing of the article]

All of this isn’t to knock Legend specifically – most models (including my own) did not do well in the radically different market that 2008 gave us.  They also may be making some predictions here that didn’t make it into their client’s portfolios or were altered significantly during the year.

The point is this: don’t be too impressed by financial firms that throw a lot of whiz-bangy mathematical jargon out there.  Hell, I’m not that good at math, and, at first, I thought Legend’s approach sounded very interesting.  But in looking at their results, I’m reminded that you can throw all the math you want at the financial puzzle and still end up with a stinker.

It also reinforced, in me, the idea that everyone has to be responsible for their financial future.  You can’t put your financial future on autopilot with someone else and not be involved.  I am consistently surprised by the number of people, in surveys, that spend more time planning vacations than planning their finances.  I am also consistently depressed by the total lack of education prior to graduation from high school and college on these issues.

It sounds all well and good to let a computer model determine everything – but at the end of the day, much of what these firms put out there is mathematical masterbation.  Just remember that next time someone tells you they’ve got a model that can solve all your problems.

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Wow – that was quick.  The Skills Index strikes again on the sell of the market.

I’ve been thinking about something else in relationship to the index which is probably obvious to everyone else out there looking at any index that runs from 0 to 100% where zero is oversold and 100% is overbought: that your position size can/should be determined by, as Dorsey Wright would say, your relative field position.  So when the Skills Index was in positive territory but at or above 70%, then, if you do enter long, you should probably be thinking about doing it at a small size.

Now, I didn’t get a chance to take much advantage of the sell in this case – my new boy Max has been taking up my time (and that is a great thing) – but another interesting aspect of the Skills Index is that when you are in a bear market, you want to play, immediately (not wait for a retracement) to the short side.  The same would be true of a bull market – take the signal with a half position immediately, and then add to the position on confirmation.  And you should wait for a retracement for entry on the long side when the bear market is on, and wait for a retracement to the long side when you’re in a bull market.  Man, that’s confusing.

Anyway, enough of the diatribe – I’m just happy the index is keeping me on the right side of the market.

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