## Not Even Wrong

I had a bit of a disagreement the other day with a colleague about the interpretation of beta and correlation.  He claimed that if a fund has a high beta to a particular index, that meant that it also has a high correlation to the index.  He even cited a Wikipedia article to support his point of view.  Unfortunately, it’s rather common to believe the whole story is, as the article states, that “correlation measures direction, not magnitude” and “beta takes into account both direction and magnitude.”  If that’s most of what you know about beta and correlation, then it’s easy to make the conclusion that my friend made.

Why do so many people make this mistake? Beta and Correlation are commonly used terms in traditional investing – mainly by mutual funds – and they’ve been thrown around long enough that people are familiar with the terms, so they think they understand them.  “Oh sure, I’ve heard of that before” and therefore, the person thinks to him/herself, I don’t need to know anything more about the topic.  In what’s called the Long Only world (think mutual funds), beta is regarded as a risk measure because of a simple relationship between the fund and its benchmark: beta is correlation times the fund’s volatility divided by the benchmark’s volatility.  Benchmarks are chosen to closely resemble the fund – for a technology fund, you pick a tech index as the benchmark.  For a health-care fund, you pick a health-care index.  Obviously.  A mutual fund’s benchmark is chosen because the two are highly correlated.  Mathematically, that means the correlation is close to 1.00.  So, in this case (and in this case only) beta is basically the ratio of the volatility of the fund to the volatility of the benchmark.  If beta is 1.1, that means the fund is 10% more volatile than the benchmark, and if the beta is 0.9, that means it’s 10% less volatile than the benchmark.  It all works because of the formula beta = correlation * (vol_fund / vol_index).  The problem is that people forget important aspects of the formula – like that correlation is baked into the beta – and they only remember “beta is a relative measure of volatility” or “beta is the slope of the regression line.”  Please keep in mind everything I’ve written in this past paragraph is only true for traditional long-only funds, like mutual funds. Read more of this post

## Chocolate or Vanilla?

Risk Measures basically comes in two flavors: chocolate or vanilla.  Really.  Sometimes it’s described as two styles: “Impact” or “Probability”, but I think of them as flavors.

One school of thought is that the best way to estimate a portfolio’s risk is to identify what drives each security’s value and then stress all those factors.  This tells you what impact you can expect on your portfolio for each of those different stresses.  Let’s call this Vanilla.

The chocolate school says that the best way to estimate a portfolio’s risk is not to treat each asset class separately like the plain vanilla people, but rather to estimate probabilities of various losses. Read more of this post

## The Risk of Not Arbitraging

Comments are more than welcome – please take a moment to comment.

## I’ll Gladly Pay You Tuesday for a Hamburger Today

Yesterday’s Wall Street Journal article about Facebook’s privacy issues and this morning’s NPR story about people giving up private information in order to play games got me thinking about the risks people face by agreeing to something pleasureful today, only to pay for it some time later.

Pay Tuesday, Play Today.

Just like poor old Wimpy, Facebook users are being tempted by something they want immediately – in this case, it’s not about a moist delicious burger but about playing one of the popular games that a friend just invited them to play, like MafiaWars or Farmville.  Never mind if you like these games or not – the point is that many people play them and that means we can learn something about risky behavior from them.  The price for access to the game is giving up some personal information – birthday, location, friend list, possibly income info, etc.  The risk, of course, is that the information is used in ways the person doesn’t approve, such as targeted advertising or examining friends’ credit ratings to estimate your likelihood of defaulting (after all, we are judged by the company we keep).  In order to be allowed into the game, you have to agree to share the information.  And given how many people play these games, it’s quite clear that many feel it’s worth the price.

## Risk at the Limit

You have a problem.  A big problem.  And it’s unfortunately a common problem for a Risk Officer.  What do you do when your risk measures are all in the red zone except for one of them, which happens to be your boss’s favorite?  And he just happens to be the Head Trader of your fund.  It’s like an engineer telling the captain of the ship that the engines can’t go any faster – “Captain (in good Scottish brogue), I’m givin’ it all she’s got.”  To which the Captain replies “No, Scotty, look at this other gauge – it says we’re only at half capacity.”  Which gauge is right – the captain’s or the engineer’s?  Fortunately, there is a way to tell.  Unfortunately, captains don’t like to accept it when they’re wrong.

## Alphabet Soup

Note: this posting originally appeared in IPE (Investment & Pensions Europe) on January 4, 2010.  This version differs only in that I converted spellings to standard American English.

04 Jan 2010

W, U, V, L? It’s all a symptom of the misleading ‘patternicity’ that dogs traditional macroeconomic thinking, argues Damian Handzy

Much has been written about the shape of the recovery. Will it be ‘V-shaped’, implying as swift a return as we had a drop? Will it be ‘U’-shaped, implying a period of low economic activity before a swift return? Will it be ‘W’-shaped, implying a second crash before an eventual recovery? Perhaps it will be €-, £-, ¥-, or \$- shaped, implying that some lucky country will lead the way and benefit handsomely while it does so. If I am forced to pick some symbol for the shape of the recover, then my choice is the Chinese characters 不 and 複, the first of several that together represent ‘uncertainty’ and ‘complexity.’