“The ability to crunch numbers is typically a key to becoming a billionaire. Often, mathematical prowess is hereditary. Some of the most common professions among the parents of American billionaires for whom we could find that information were engineer, accountant and small-business owner.”

My dad has a graduate degree in math and taught college-level math. I won’t complain if the trend continues and I end up with a billion dollars.

Seriously, I never thought that math would make me rich. And it hasn’t yet, at least not enough to be part of the Forbes study (only a billion more and it will!).

But somehow I always knew it would open doors.

And it has. I was able to receive a graduate engineering degree from a good university because of math. I believe a big reason I was accepted into a good law school is because of math. I use math every day in my business and in countless other ways. 

I don’t know if it was nature or nurture. Probably a combination of the two. But I think it’s fair to say my love for math has affected my life more than anything other than the Three F’s, family, friends, and faith.

It’s important for all parents to help their kids develop a love for math. And if not a love, then at least a working knowledge and an appreciation.

They won’t become billionaires, but they will find more doors opened for them. They might not become rich, but they will avoid the anxiety that many people feel every time they are asked to do a math problem. They might not become a successful entrepreneur, but they will avoid the easy (and sometimes costly) mistakes made by the math illiterate.

A few highlights:

Responding to critics that the recent volatility has ”killed” the EMH: 

“The market can only know what’s knowable. It can’t resolve uncertainties that are unresolvable. So when there’s a large amount of economic uncertainty out there, there’s going to be a large amount of volatility in prices. As far as I’m concerned that’s exactly what we’d expect an efficient market to look like.”

Paraphrasing other interesting comments:

Most behavioral finance advocates like to point out inefficiencies, but usually conclude that it’s too impractical to take advantage of these inefficiencies and therefore you’re better off to do your risk-return tradeoff.  In other words they conclude that you’re better off to presume the EMH is an accurate description of the way markets work.

The top insiders do better trading on their own company’s stock but interestingly only by about 1%.

The most potent challenge to the EMH is evidence of momentum in stocks that can’t be easily explained. Secondly, movements due to earnings announcements tend to persist longer that expected.  Those are the two biggest challenges. Remember, EMH is a model, not truth. It’s a simplification of the world that does a good job on almost everything, but a few things it doesn’t do a good job on, e.g. insider trading, momentum, and movement from earnings announcement.

The EMH is not a perfect explanation of everything that happens in the market, but it is the best working proposition for use by investors.  Most investors should presume that the only way to reliably affect the expected return from their portfolio is by varying the level of risk they’re prepared to take.  Nothing in the last 12 months has altered that. Some people are claiming the market isn’t efficient, but they aren’t claiming there are easy profit opportunities out there.  It’s one or the other.

Whether you agree or disagree with Fama and EMH, this is a must-see interview in light of the recent volatility in the debate about EMH (ha ha).

If you want to learn more about Ibbotson, read the intro to the article.

In case you don’t have time to read the whole interview, here are the highlights and money quotes:

• Because many hedge funds had (have?) a similar strategy, many hedge funds had to unlever at the same time in summer 2007, contributing to the meltdown “as they rushed to the same exits.” 
• “In both cases, the quant funds that were able to stick with their strategies were able to quickly recover. But those who targeted volatility got whiplashed. Those who kept their leverage intact did reasonably well. Unfortunately, many investors lumped quant funds into one big category, and have become wary of the whole group.”
• “Investors often select funds with the highest returns, without tracing where the returns came from. Most hedge fund returns are actually associated with beta, rather than alpha….. they do not really provide alpha and can be replicated for less than typical hedge fund fees.”
• “The drop exposed the fact that many hedge funds are really not absolute return vehicles, but actually contain a lot of beta.”
• And the most interesting quote in the interview:  “[H]edge fund alphas are still positive, although not as high or significant as before….  [T]he majority of the returns can be classified as beta, then fees, then net alpha, in that order. Despite the fact that alpha makes up the minority of the return, it is still noteworthy that the net alphas are positive. This is in contrast to the mutual fund industry where there is little evidence of aggregate positive alpha, even on a gross level. On a net level, aggregate mutual fund alpha is usually negative.”

The last quote is interesting for a few reasons.  First, it shows that hedge funds are not about “hedging,” as most of their returns is beta.   

Second, it contradicts another study I’ve seen that concluded the hedge fund industry has net negative alpha.  Unfortunately I didn’t save a link to the study.  If I come across it I’ll post it.

Third and most intersting, it’s more ammo that mutual funds in general are bad investments. There’s too much to say about this topic.  I’ll save it for a future post, or series of posts.

There are two graphs. 

The first shows a timeline from 1994-2009 showing the correlations over time.  The striking feature of the graph is the rise in correlation of just about every asset class with the S&P500.  For equities, it’s been increasing for several years.  For bonds, it’s a more recent rise (although notice that bonds were even more highly correlated with the S&P500 in the mid-1990’s).

The second graph shows similar data, except aggregated from 1973 to 2009. It also shows the correlation of each asset class with the S&P500 for 2008.  The point of the graph is the correlations became more extreme in 2008, either more positive (most asset classes) or more negative (short-term treasuries and TIPS).

The conclusion is that most asset classes become more correlated during a crisis, reducing the benefits of diversification.

Unfortunately I can only read the first 3 paragraphs of the attached WSJ article because I don’t have a subscription.  It seems to conclude that asset allocation as a strategy is not effective because the correlations rise during a crisis. 

I suppose there’s some truth to it if you only invest during crises.  But do you know anyone that only invests during crises?

On the other hand if you plan to invest long-term, the relevant data is the long-term correlation (the grey bar on the graph) and not the 2008 correlation (the blue bar).  I’m in the market long-term.  I don’t care if the blue bar rises during a crisis. It’s temporary.

And there’s one more salient point.  A well-thought-out asset allocation strategy, coupled with low fees/expenses and a strategic tax approach, is the only way to beat the market in the long-term that is : 1) Easily accessible to most investors, and 2) Legal. 

If you abandon an asset allocation strategy, you’re left with the problem of figuring out a better strategy. 

A few other points worth noticing on the second graph, going from right to left:

• The “U.S. Stock Market” to the right only shows a 0.64 correlation with the S&P500.  I would have expected something in the 0.90’s given that the S&P500 is often considered “the market.”  Not sure if their data is bad, or if there’s some other reason for the discrepancy.
• Hedge funds have a 0.35 correlation.  This shouldn’t be news to anyone, but hedge funds are not really for “hedging.”  There are half a dozen asset classes on the graph with correlations closer to zero, all of which would be better hedges.
• The emerging market stocks correlation is shockingly high at 0.99.  I would have expected much lower. 
• European stocks correlation is shockingly low at 0.05.  I would have expected much higher, perhaps in the 0.80’s.
• Junk bonds are essentially uncorrelated to the market, making them a good hedge against general market risk.

“Using your contacts without making them feel used” by Nadira A. Hira

It’s well worth a read, especially if you are “hitting up the network” looking for a job or for some other reason.

I wish my name rhymed.

Problem is, he already ordered the 400-foot tall giant wind turbines.   687 of them.  He has nowhere to put them. 

Via the AP:

“When I start receiving those turbines, I’ve got to … like I said, my garage won’t hold them.  They’ve got to go someplace.”

He calculates that revenues will exceed expenses in the social security trust fund beginning in 2018, rather than the federal government’s current forecase of 2016.

It’s a pretty interesting idea, and seems to have some merit.  Older workers working longer is a long-term trend over the last few decades.   That trend should only be strengthened by older workers with 401(k)’s and other stock-based accounts that have lost significant value over the last 18 months.

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