I’ve been thinking a bit more about the volatility in the financial markets over the past two weeks, and I’m uncharacteristically concerned.

Normally, this would be about the time that I would write a post repeating some of my favorite personal investment staples, like:

• Don’t try to time the market
• Diversify your assets across multiple types of countries and classes
• Invest for the long term

And so forth.

Something is bothering me, though, despite the fact that I am personally following all of the above guidelines (and more) with my personal investments.

I’m worried that we haven’t internalized the warning of the Long Term Capital Management bail-out in 1998.  Like the World Trade Center bombing in 1993, we may be unprepared for what that failure really signified.

As usual, Wikipedia has all the good detail on what happened with Long Term Capital Management.  A hedge fund made up of literal Nobel Laureates and masters of financial risk, it utilized incredible financial leverage to take what should have been extremely low-to-no-risk opportunities and turn them into phenomenal investment gains.  Unfortunately, in August 1998, some of those low-to-no-risk opportunities went in historically unpredictable ways, and Alan Greenspan had to orchestrate a multi-billion-dollar bailout from some of the large New York investment banks.

At the time, it wasn’t completely obvious to most people, even those who follow the markets, what the significance of an explosion of an single hedge fund really was.  In the following weeks, months, and years, it became clear that something was fundamentally troubling about what had happened.  This quote comes from Wikipedia:

The profits from LTCM’s trading strategies were generally not correlated with each other and thus normally LTCM’s highly leveraged portfolio benefited from diversification. However, the general flight to liquidity in the late summer of 1998 led to a marketwide repricing of all risk leading these positions to all move in the same direction. As the correlation of LTCM’s positions increased, the diversified aspect of LTCM’s portfolio vanished and large losses to its equity value occurred. Thus the primary lesson of 1998 and the collapse of LTCM for Value at Risk (VaR) users is not a liquidity one, but more fundamentally that the underlying Covariance matrix used in VaR analysis is not static but changes over time.

Despite being a regular reader of the Wall Street Journal, New York Times, and the occasional Economist, I didn’t really understand what had happened until I read When Genius Failed, by Roger Lowenstein (one of the books I recommend in my personal finance education series).   If you haven’t read it, I highly recommend it now.

What Lowenstein explained and what I hadn’t originally appreciated is that the fundamental problem with Long Term Capital Management is a fundamental problem surrounding all of our modern portfolio theory, whether you are a small investor like me or the largest endowment.

The problem has to do with asset diversification and how it is practiced.

Portfolio diversification has become the basis of all modern investment management.  The idea is to diversify your investments across asset classes with different risk factors and returns, ensuring the highest reward for the lowest risk.

For most investors, this was as simple as the traditional mix of stocks, bonds and cash.  But that changed in the late 1990s.

In the late 1990s, all of a sudden, everyone wanted to be David Swensen.  David Swensen was the manager who guided the multi-billion dollar Yale endowment to phenomenal returns from the 1980s through the 2000s.  He even wrote a book.

David made these phenomenal gains by eschewing most traditional types of assets (public stocks & bonds).  Instead, he invested in hedge funds, arbitrage, private equity, venture capital, real assets, and others).  What David realized early was that you could think of many types of invesments as asset classes, and find great investment returns in non-traditional classes with risks that were not correlated to the public stock market.

This decade has seen an amazing boom in investment tolerance for non-traditonal asset classes.  People freely talk about how different new investment assets have a “low correlation” to the stock market.  Real estate, commodities, rare coins, art, collectibles, long/short funds, you name it.   As a result, across the world, trillions of dollars are now factored into different asset classes, prudently distributed to minimize risk and maximize reward.

This would all be fine except for one thing.  And it’s the one thing that more than anything led to LTCM’s demise.

That one thing is that all of these great measures of risk are based on historical records.  And as all mutual fund prospectus readers know, “past history is not necessarily indicative of future performance.”

You see, you can take two things that historically have not been correlated.  Asset A & Asset B.  But the minute that an investor owns both A & B, there is now a correlation that didn’t exist historically.  The investor is that correlation.

If Asset A goes down, and the investor needs to sell something, they may now turn to Asset B for liquidity.  And that means selling pressure for Asset B, based on nothing but the asset price of Asset A.  Voila, correlation.

All of those historical models don’t apply once investor behavior starts changing in mass.  Maybe stocks & gold never traded together historically because the type of investor who bought gold just wasn’t the same type who bought stocks.  But now, in the modern world of portfolio theory, everyone has balance.  Everyone has a little of everything.

OK, ok.  Not everyone.  But I’m worried that enough major players do that we have created historical correlation that didn’t previously exist.  That correlation is risk, and it’s risk that is not built into the models of all of these portfolios.

What’s worse, those historical models lead investors to believe that they have less risk on their books than they do have, which leads rational investors to introduce leverage into their portfolios.  That means when the risk shows it’s ugly head, the results get magnified by the leverage of loans.

That’s what happened to LTCM.  Their models were excellent, but they were based on historical correlation.  The minute some of their investments turned the wrong way, their incredible leverage forced pressure in previously uncorrelated investments.  What’s worse, other investors, smelling the “blood in the water”, discovered this new-found correlation, and pressed trades against them.

So, this scares me a lot, at least intellectually.  There are very good reasons why major investors like hedge funds and other asset managers can’t share their up-to-the-minute holdings.  That means, however, that no one really understands this type of “co-investment risk” that is building in mass across the markets.  Unfortunately, the only way I can imagine to properly handle this risk would be to have a universal monitoring set up to accurately reflect this new type of correlation from mass “co-investment” across assets.

I’m still being a prudent investor.  I still diversify my portfolio for retirement across different assets.  Domestic & International, Large caps and small caps, stocks, real estate, commodities… even a long/short ETF.  I don’t think I’ve sold anything based on short term movements of the markets.  I’m sticking to my long term plans.

But I’m a little worried now.  Intellectually, it seems like the capital markets have potentially a major risk/reward pricing problem in them right now.  And these things tend not to resolve themselves quietly.

Let me know what you think.

BTW Many thanks to Igor, for asking me over dinner last week what I thought of the market volatility, and leading me to think more deeply about it.

One of the great things about travel is that it usually offers me free time to catch up on some reading. On my recent trips to Orange County and Berlin (not in the same weekend), I’ve managed to knock a few more off my reading list. As a result, I’m going to try another book review here on the blog for good measure. Let me know what you think.

The Little Book That Beats The Market by Joel Greenblatt

Overall Rating: Definitely worth the quick read. While the schtick got tiring after a while, the author is clearly intelligent and educated, and the content well thought out. Surprisingly, I found the most interesting part of the book not the “magic formula” itself, but the implicit structure the author put in place to try and help the average investor be successful with the strategy over the long term.

Synoposis: This book is an extremely quick read.  Joel Greenblatt is the founder and managing partner of Gotham Capital and currently teaches at Columbia Business School, so he’s definitely educated in both theoretical and practical aspects of finance.  This book is written in extremely simple and plain language, and he clearly goes out of his way to make it folksy and fun.  I think I finished it in under an hour, appendix included.

Greenblatt’s points are pretty simple:

• The idea that the market is truly efficient is something that only makes sense in theory.  In practice, you can definitely beat the market.
• The key to beating the market is to buy above-average companies at below-average prices.  Rinse, wash, repeat.
• The “magic formula” is an updated method, similar in concept to those outlined by Benjamin Graham (one of my must-read investing books).  The formula is as follows:
  1. Every year, begin with a list of the 3500 largest companies that are publicly traded
  2. Rank them 1-3500 based on their return on invested capital (ROIC).  This tells you how good a business they are, as defined by taking invested money and turning it into more money.
  3. Rank them a second time based on their earnings yield, basically the percent of their stock price you get back every year in their earnings.  This tells you roughly how expensive they are per-dollar of earnings
  4. Add the scores from the two lists together, and then invest in the top 20-30 companies based on the combined score.  Voila, a list of “above average” companies at “below average” prices.
• This formula will not outperform the market every year.  You have to stick to this formula for at least three years if you want a high probability of beating the market average.

Greenblatt has done his homework, using a detailed 17-year history of stock prices to ensure that this formula, based on information actually available at the time, would have outperformed the market handily.  In fact, he goes to some trouble to explain some other variants of the formula.  The one I outlined above returned an average of 30.8% per year.  That’s compared to a 12.4% return for the S&P 500 over the same period, and a 12.3% return for an even investment in all 3500 companies.

I’m guessing that part got your attention.

When I began investing in the mid-1990s, there was a lot of excitement about the Dogs of the Dow strategy.  It basically said, take the Dow 30 stocks, rank them by dividend yield, and buy the 10 cheapest every year.  The Motley Fool took this one step further, and published their own variant called the Foolish Four, based on a similar concept, with some more gaming around the picks.  I actually bought two of those books – I still have them on my shelf, and I actually invested an IRA according to the Foolish Four for 5 years.  (It beat the market during that period, by the way).

If you think about it, all these strategies say: “buy great companies at cheap prices”.  Now, I think Greenblatt’s formula is much more compelling:  ROIC is a much better measure of a “great company” than being in the Dow 30.  And earnings yield is more compelling to me than dividend yield, since a lot of great growth companies don’t pay out dividends proportionally to slow-growth companies.

However, I stopped investing according to the Foolish Four in 2001 largely because of an insight into a common flaw with all of these strategies – data mining.  It turns out that statistically, if you data mine enough for a “winning formula”, odds are that you’ll find some.  I won’t go into the details here, but it is possible using advanced statistics to estimate the likelihood of finding a “winning formula” through data mining.  So, even when you find one, you have to evaluate it’s results against the fundamental odds that if you look at any pattern of data, there will be “winning”  patterns to a certain degree.

In the case of the Foolish Four, to their credit, the Motley Fool published this analysis, and stopped recommending this approach in late 2000.

So, what makes this magic formula different?

First, Greenblatt is clearly more deeply educated about finance than the Motley Fool, thank goodness.  In his appendix, he runs through six or seven of the common flaws with strategies like these, and explains why this approach is still valid.

One of the most compelling pieces of additional analysis he provides is the fact that this formula seems to actually generate linearly predictive results.  In other words, if you take the top 10% of companies ranked by this formula, then the next 10%, then the next, each decile of companies outperforms the groups below it.

That type of consistency is rare for most quantitative approaches to ranking stocks, and is a good sign that this formula may be useful.

In fact, Greenblatt runs through almost all of the critiques I would expect in his appendix.  The only one he doesn’t address, which to me is extremely important, is the time period bias.  Greenblatt has only tested this approach over 17 years of data.  That means he basically just looked at 1988+.  Given that he includes the longest bull market in history, and then a period of outperformance by value over growth, my guess is that there is significant bias in these results.

Still, my guess is that this formula will still generate outperformance over time.  The best thing about this book is that Greenblatt spends a lot of time explaining that in any one year, this formula can and will underperform the market from time to time.  In fact, he advocates a minimum of a three-year window to evaluate its performance.

I think this is great advice, but likely doesn’t even go far enough.  The stock market, in general, is a long term investment.  Investors consistently buy high and sell low, not because they are stupid, but because in the short term, we rationalize investing in the winners (which are bid up because they are popular), and we rationalize selling the losers (which are low because they are not popular).

Buying high and selling low is a very bad investment strategy.

I’m going to check out Greenblatt’s website, and investigate the analysis for this approach further.  In the meantime, I do recommend this book to people who like value investing, or who are thinking about investing in individual stocks.

I’ve read quite a few books on the topics of economics, finance & investing, but I thought it might be good to capture here my recommended books for someone who wants to get started learning more about personal finance & investing.

There are, of course, a lot of great books out there, but there is an endless supply of terrible ones. In general, you want to avoid the trendy, get-rich-quick, fashionable finance books, and instead focus on the ones that can give you the basic foundations to make your own judgements about personal finance & investing decisions. Once you have the basics down, then you can start absorbing the constant barrage of “flavor of the month” financial advice and investing books.

I’m going to run through these in roughly the order that I would recommend. I have a lot more on my shelf, but these are the books that in reflection really changed they way that I look at investing.

1. The Wall Street Journal Guide to Understanding Money & Investing
This book looks quite plain, and it’s only about 100 pages or so. But this book has a clear, visual and concise explanation of almost every important personal finance topic, everything from the basics of money and currency all the way to understanding stock options and derivatives. The great thing about this book is that it also can serve as a simple reference – a mini-encyclopedia of money & investing. The book is structured into easy to digest 2-page sections, and I highly recommend it as a basic entry into money & investing. Yes, I guarantee you that you already know some of the material covered in this book. But I also guarantee that you will learn something from it as well.

2. The Millionaire Next Door
Normally, this book would fall into my “trendy” disclaimer, but I do recommend that people read this book. True, it has chapters that are needlessly dry, reciting endless statistics about the habits and averages among the population of millionaires that were studied to make this book. But the most important thing is that this book emphasizes that a high income does not guarantee wealth, and that being wealthy is living below your means and the long term accumulation of assets. This book shatters a lot of myths that people have about the average millionaire in the United States, and it really highlights the basics of a healthy financial life.

3. A Random Walk Down Wall Street
Our first entry into the world of investing. This book is the absolute must-read to understand the predominant financial theory of the past thirty years: the stock market is efficient, and that efforts to beat the market, either through fundamental or technical analysis are futile. Personally, I believe that markets are not completely efficient due to the lack of rationality of either individuals or crowds. However, understanding efficient market theory is the cornerstone to understanding modern markets, so this book is basically a must-read. If it doesn’t convince you, at minimum, it will leave you with a strong bias against any “easy” way to make money off the stock market.

4. The Essays of Warren Buffett
Now that you’ve internalized efficient market theory, it’s time to listen to the words of probably the single greatest investor of the past fifty years, Warren Buffett. This book is a collection of his annual letters to shareholders. (In fact, you can now get all of his letters from 1977+ online!) Warren Buffett epitomizes why value investing works – his deep understanding of the finances of operating businesses allows him to selectively invest when he sees people selling dollar bills for fifty cents, to borrow a phrase. As a businessman myself, I also deeply appreciate the clarity of Buffett’s insights into what a financially outstanding business looks like, from a capital perspective, and his perspective on what makes a great manager and allocator of capital. I’ve read this collection at least three times.

5. Common Stocks & Uncommon Profits
Warren Buffett comes from the school of value investing, but his methodology and thinking has changed over the years to incorporate more flexible concepts of value than just book value or dividends. In this book, Philip Fisher explains the real fundamental basis for “growth stock” investing – recognizing that in some cases, the dominant factor for successful investing can be finding companies with outstanding growth potential. This may seem obvious to those of you out there who follow the technology industry, but I found this book crucial for my internal rationalization of the logic of both value and growth investing.

6. The Intelligent Investor
Warren Buffett stands on the shoulders of giants, and Ben Graham is the historical giant of value investing. This is the book that Buffett recommends to every investor, and it is fascinating from both a historical as well as financial perspective. When you read this book, you are stepping back in time, to a world before the Great Depression, when common stocks were still relatively new, and people bought them purely based on popularity, growth, or immediate payout. Graham was the one who first evangelized the idea that by looking at the core financials of a company – the assets and the dividends, you can make an informed judgement of the company’s value and the value of the stock.

7. Devil Take the Hindmost
This is not a personal finance book – it’s a history book. This book walks through almost all of the great financial bubbles since the 17th century. Fantastic for perspective on how markets get carried away. For me, the insight from this book was that there is a repeated theme in the history of bubbles. The combination of a new technology with a new innovation in finance leads to a combination of new capital and optimism that leads to an incredible rush and explosion of investment. This book will change your mind about how rational markets really are when crowds get a bit too excited.

8. When Genius Failed
Another history book, and a modern one at that. This is the story of the blow-up of Long Term Capital Management, the single most lauded hedge fund of the late 1990s. For those who have gotten deeply into the math and statistics behind the market, this book should be a wake up call. Any investment strategy can be broken, and any model based on the past will not predict the future once people in the market adapt to that new knowledge. There is a huge insight in this book that may seem esoteric, but it’s likely the biggest new insight into markets of the last decade: When you are a big enough investor, your own investment in the market creates a new correlation between investments that didn’t previously exist – the fact that you own all of them. Similar to quantum mechanics, the investor affects the markets they invest in. This simple truth explains why LTCM fell, and why there is a limit to strategies based on historical analysis of assets.

9. Against The Gods
This is one of my favorite books, bar none. It’s a stretch to say it’s about personal finance, but for me, it was a game changer. This is a history book, specifically about the history of the mathematics of statistics. It’s very interesting to note that just a few hundred years ago, no one understand the math of probability, and yet this is the branch of mathematics that dominates all modern science. Statistics is extremely counter-intuitive. Our brains are hard-wired to get it wrong. By walking through the history of how this branch of mathematics developed, I found I developed a new understanding of statistics, and a better sense of intuition around it.