Archive for the ‘QuantCloud’ Category

Mutual fund
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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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Parity - US Dollars Not Accepted
Image by Ian Muttoo via Flickr

Bill Luby at Vix and More seems to be stealing all my post ideas, but I’ll go forward with this one anyway.  Damn you, Bill!

In any case – like Bill, I’ve been spending time looking at the correlation between the US Dollar and Oil (and commodities in general).  Here’s a chart:


That’s the US Dollar at the top, followed by the Oil index, followed by the 100-day correlation of the two.  Almost perfect anti-correlation.  So, with that in mind, I’m watching commodities right now – and also taking a look at FXE as a way to play the dollar.  And, as Bill pointed out, I wonder if this is a strong sign of inflation reemerging due to the endless dollars we are printing to fund Bailout Nation.

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Links of interest today…

Image representing AlphaClone as depicted in C...
Image via CrunchBase, source unknown

Mebane Faber over at WorldBeta has launched his new product – AlphaClone.  Pretty interesting concept that picks up where his blog work left off.  I’ll be taking a look – maybe publish a review.

Michael over at MarketSci does a detailed analysis of the RSI(2) strategy and finds some issues with the approach – I use RSI(2) in some of my work, so what I’m going to be doing is figuring out how to make the performance of the system dynamic/adaptive to deal with the issue.

If you’re interested in options strategies, you need to check out OptionsOracle from SamoaSky software – it’s free and offers a lot of the tools that are found on ThinkorSwim for free.  This is what amazes me about trading these days – a tool like this, that would have cost thousands of dollars even 5 years ago, is now free.  The open source movement will come to trading software – I just think it will take a bit more time.

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While the market is trying to decide whether it is up or down today, I find myself wandering the web in search of new stuff to read.  I found the best political site I’ve seen in a while – not in terms of coverage but uniqueness of mission: DC Fashion.  I give you – Princess Sparkle Pony.

Friggin’ hysterical.  Finally, a blog that addresses Washington, DC’s fashion sense (or lack thereof).  As a friend of mine who lives in DC often quotes (it’s an old line): “DC is Hollywood for ugly people.”

Another site that often makes me laugh is GraphJam – here’s a great example of their user’s fine work:

song chart memes

On the more serious side – here’s some interesting market-related information:

  • Mebane Faber over at World Beta just pushed a link to a paper that looks at his tactical asset allocation method on a daily basis – it’s a good read: Tactical Asset Allocation Using Daily Data.
  • Headline Charts has a good piece on interest rates and offers a simple method for determining whether to be in stocks or bonds.
  • iCharts.net has a interesting site for creating interactive charts – it’s not live yet but I’m interested in using it when it finally launches.

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Nick Gogerty over at designing better futures (via Worldbeta) has an excellent post on the importance of not losing money.  Here’s the chart and the money quote:


The acceleration point for losses requiring greater gains is around a 13% loss.  Think of it as inverting the power of compounding returns.  Currently the S&P is 26% below it highs.  To get back to the previous high point for domestic investors the S&P 500 needs to gain a little over 35%. The long term +80 year historical average return for equities is around 7-8%, so back to break even then in around 4 years.  Based on historical average return would be 2012-2013.The ex dividend annual return for the S&P for a dollar based investor since 1998 has been roughly .3%.  When one factors in an inflation estimate of 2.5% per year, one ends up with an effective loss of purchasing power of 25% over the last decade.  Welcome to the lost decade.

His point is well taken – that when you consider being down 20%, it will not be a 20% gain that takes you back to parity.  Once you cross the 13% rubicon, you’re into needing a huge amount to recover.   This is why I am interested in different approaches to investing – consider that some people who invested in the Nasdaq during the dot.com boom are still underwater.

But what really got me was when he laid it out in terms of time given an average equity return – 4 years to get back the gains.  Now, obviously the S&P has had returns greater than 7% in any given year, but we’re talking average returns which might well be what we are in store for over the next decade (as readers know, I’m not a predictor of future returns).  Nick’s blog has some other great posts and thus will go into the blogroll.

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I like the folks over at Bespoke, but today they committed one of the great sins in statistics – mistaking correlation for causation:

“While fund raising statistics suggest that Barack Obama has strong support in the Wall Street community, the performance of the stock market in relation to Mr. Obama’s popularity suggests that investors may have a different view.  In the chart below we show the S&P 500 (red line) versus the price of the Intrade futures contract for Barack Obama to become president (blue line).”

Clearly what they’re trying to say here is that Obama futures are predictive of the S&P 500.  This, of course, is showing correlation, not causation.  I could find any number of charts which shows the same thing.  For instance, a chart of oil.

Leaving off the problem of relying on data from Intrade (which has been shown to be responsive to events rather than predictive) I could see the right-wing blogs picking this up as “see, some great market (because the Bespoke guys are great) economists are saying that Obama is causing the stock market to sell off!” – which, in any multi-factoral environment, is pretty obviously false. We don’t have to look far for other possibilities – sub-prime, war in Iraq, price of oil.

I don’t really care if you’re for McCain or Republicans in general, or for Obama or Democrats in general – what I can’t stand is stuff like this.  This isn’t the first time I’ve seen this, and it won’t be the last – this same sort of thing was written about by the Stock Chartist a few weeks back.

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Know What’s in Your ETF and How the ETF is Calculated : Trader Mike

Mike looks at the DUG ETF and why it’s been acting so funny.

World Beta – Engineering Targeted Returns and Risk: Rebounding

World Beta takes a look at investing in stocks/ETFs that are down for a given month and presents a strategy.

Quantext – “Humble Arithmetic”

Quantext looks at portfolio construction and risk levels/factors.  Part of a great series by them.

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Quantifiable Edges: Nasdaq Net New Highs Potentially Ominous

Rob worries about the lack of net new highs on the Nasdaq and if this is a bad thing…

Kirzner Fervor: The Hedge Fund strategy that wasn’t?

Kirzner – if you haven’t read him – he’s incredibly smart.  This piece walks through an interesting strategy idea that he ultimately decides it isn’t really working anymore.  Great stuff.

VIX and More: The Big Question for the VIX

I never thought I’d hear of the VIX jumping the shark, but there it is.  What will you do now Bill?  🙂  I kid, I kid.  The VIX certainly has the ability to become the next "dry ships" index or whatever that was – but I think both the VIX and Bill have a longer career ahead of them.


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This will be a regular feature on Skill Analytics – I’ll be providing daily links of interesting quantitative trading ideas from around the web.

Bespoke Investment Group: Mid-Day Sell Off

Bespoke looks at the deciles that sold off of the S&P1500.

IBDIndex: A Closer Look at Profit Targets

IBDIndex, a fellow Tradersstudio user, does a comprehensive look at Profit targets and Stop losses.  The conclusions may seem a bit obvious – but it is important to have this kind of verification.

Quantifiable Edges: High Five

Rob looks at how the market does going forward after making a 5th higher-high.

Quantifiable Edges: Is A Low VIX A Short Trigger?

A day old but very much worth posting – Rob looks at a low VIX short trigger – the conclusion – not good.

The Dogwood Report: Triple MA Cross Over Update

Dogwood updates us on his testing his Triple MA Crossover system.

VIX and More: Strong Bear Signal VXV:VIX Ratio

VIX and More looks at the new VXV and what the ratio to the VIX could mean in terms of buy/sell signals.  I’m in the comments with a project idea based on an idea from another commentator.

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