The Permanent Portfolio, Investing, Finance and Random Thoughts.
Posts tagged risk management
Article: Lessons for investors from Japan’s lost decades
Hat Tip to Odysseusa for this article from Globe and Mail:
Lessons for investors from Japan’s lost decades
The lesson? Broad diversification works.
A Japanese investor who held government bonds, foreign stocks, precious metals and cash, in addition to domestic shares, would have blunted the Nikkei’s fall and even earned a profit. That may not be the most exciting take-away from Japan’s experience, but it’s one time-tested result that investors should keep in mind as they seek a refuge from today’s market weakness.
(emphasis added)
Couldn’t agree more. Portfolios should hold stocks, bonds, cash and gold at all times no matter what we may think will happen in the markets.
Taking the Turns
In relation to yesterday’s post on portfolio firewalls, it reminded me of something…
I knew a guy that was a seasoned network architect. We were talking one day about network design and highest performance. Being young and dumb, I thought that highest performance was all that needed to be considered. He looked at me though and said:
“Speed is fine, just be sure you can take the turns.”
The point being that you can optimize for highest performance, but the reality of the world is you need to have proper fault tolerance, redundancy, etc. built into a design in case things don’t go according to plan. Speed is only one consideration.
Yet, the problem with many portfolio strategies is that they just can’t take the turns.
How do you get a portfolio that can take the turns? Here are my thoughts:
- Don’t fixate on backtested high performance numbers. They tell only one part of the story.
- Consider the worst case scenarios and imagine how your portfolio will react to them if they should happen.
- Complex portfolios (and complex trading strategies) are usually the result of people looking to get more speed. They have a lot of moving parts that can send you over a cliff in bad markets. Keep your portfolio as simple as possible to get the job done.
- Own assets from the four major asset classes (stocks, bonds, cash and gold) and don’t worry about slicing assets into tiny specialty sector pieces.
- Finally, investor emotions are a major factor in long term portfolio performance. Don’t underestimate the importance of a stable portfolio that can absorb bad market shocks or even prolonged bad markets. Even if that means giving up some theoretical (and that’s all it is) performance.
Investors often look so much at ultimate high speed performance and never consider what happens when things don’t go according to plan. Then they slam into the jersey wall when a hair pin turn shows up. Speed is fine, just make sure your life savings can take the turns.
Stop Losses and the Permanent Portfolio
5 months ago
Someone wanted to know if using stop losses is a good idea for the Permanent Portfolio. In short, no they aren’t.
For the uninitiated, a stop loss is an automatic order in place at the broker to sell a security when a certain low price has been reached. The theory is that you can set a stock price that is, say, 20% below your purchase price and if the stock drops to that level it is sold automatically. The idea is it limits your losses in any one position.
Sounds good in theory. Yet in practice it has the following issues:
Whipsaws – This is a fancy way of saying that you could sell out of a position automatically only to see the price recover almost as fast. For instance, a price could drop suddenly on bad news one day but as the markets digest the information the price could quickly recover. This happens frequently in the markets. This is a very bad thing in a taxable account because it can drop a tax bill in your lap if you just happen to lock in some gains in that position.
Delayed Order Execution – In a large and fast market drop your order is not executed immediately. It will be executed when many other orders are flooding in and you will get the market price. So you may set your stop loss at $15 per share for instance, but your order may execute at the $10 price. If the stock recovers even to $15 at this point you’ve taken a serious bath vs. just leaving things alone.
Automates Bad Portfolio Management – When you automate sales in your portfolio it takes away what is frequently your best option during a volatile market: Doing nothing. I’ve made a ton of money by just ignoring market goings on and sticking to my plan. Doing nothing is a big part of successful investing.
Makes Panicking Easier – When the stop losses kick in it is easy to go into panic mode. You now have this bundle of cash sitting there that this circuit breaker has thrown into your lap. Now you have an awful decision to make:
- Do I keep it out or get back in?
Then you have the second awful decision to make:
- Is it too expensive to get back in now or do I wait a little longer and see if it drops more?
Then you have the third awful decision to make:
- I knew I was too early because the price just dropped when I bought back in. Should I sell out again or leave it alone?
Why torture yourself repeatedly with this cycle? Not just this, but it’s never a good idea to react in a panic and stop losses force you to react right when it’s usually the worst time (in a panic).
Finally the above isn’t just theory. In 1987 we had a 25% market decline that caused a huge sell-off. Yet by the end of the year the stock market was in positive territory. Selling out during the panic was not a good idea. And more recently in 2010 we had the Flash Crash where the market dropped nine percent in a few minutes, but then snapped back within minutes after. A stop loss there would have resulted in almost certain losses.
The best way to manage risk in the Permanent Portfolio is to use rebalancing bands and avoid any kind of automated trading. Orderly rebalancing will not only likely result in better performance, but will be much better for your sanity.
A ship in the storm…
6 months ago
The markets are very volatile. I will remind readers that your portfolio is a package made up of very volatile assets. But put together they make a smoother ride. The individual assets may move in strong directions, but the overall portfolio value is all that matters in the end.
Don’t focus on the waves causing the bobbing of the ship in the storm. Instead, focus on the direction the ship is heading.
The direction of the portfolio is still looking good so don’t worry about it and mind your rebalancing bands.
Asset Class Correlations: It’s All Bunk
7 months ago
Asset Class Correlations
Ever hear about asset class correlations? Well, it’s all bunk.
The idea of asset correlations is this: A 1.0 is perfect correlation. Meaning if Asset X moves up then Asset Y moves up in lockstep. A correlation of -1.0 is perfect negative movement. If Asset Y moves up then Asset Z moves down. Usually the range of correlations falls between the perfect positive correlation of 1.0 and perfect negative of -1.0.
You see this in investing books all the time. Stock asset classes X and Y have a correlation of 0.67 while bonds A and B have a correlation of 0.22, etc. You just throw them together and you get instant diversification! It looks so scientific being two decimal places and all.
Well, allow me to let you in on a secret: This information is worthless at best and dangerous at worst.
A World of Correlations
In the investing world many decide to build a portfolio using historical correlation data. They look at all of these assets over the years and assign a correlation number between them to try to figure out a relationship and how much of each you should own.
For instance over the past 30 or so years:
Total Stock Market and the Total Bond Market have a correlation of about 0.34. Meaning that some of the time are they moving upward at the same time but sometimes they aren’t.
Total Stock Market and Total International Stock Market have a correlation of 0.66. A stronger correlation indicating that if one is going up the other probably is, too.
Total Stock Market and Gold have a correlation of -0.27. Meaning that if the stock market is going up in value that gold is probably going down and vice versa.
Now you take a bunch of assets with different correlations and you are hoping that when one zigs the other zags. This diversification effect means over time that as one is gaining in value another is falling. During good markets you may give up some gains, but in down markets you have some assets that should do well to offset the losses.
Good theory, but normally used poorly in practice.
The reality is that asset class correlation data is irrelevant and can get you in trouble. In 2008 for instance many people held assets that supposedly had low correlation historically. Yet, when the markets crashed the correlations went up sharply and they all went down together. The diversification selected failed and large losses followed. Many claimed that “Diversification failed in 2008.”
Diversification didn’t fail. What failed are how portfolios were built to diversify the risks.
There are two primary failures with looking at asset class correlation alone:
1) Looking at correlation data without considering the underlying economy at the time covered.
2) Correlation data encapsulates big blocks of multi-decade returns which loses visibility into the specific events happening under the covers.
Let’s talk about these two things.
It’s Hot in Miami and New York – Who Cares?
What about the underlying economy? Why is this a big deal?
Let me explain using the weather. Below is a list of average temperatures in Fahrenheit in three cities:
| New York | Miami | Sydney |
| 30.7 | 67.2 | 71.8 |
| 31.5 | 68.5 | 71.6 |
| 39 | 71.7 | 69.6 |
| 49.8 | 75.2 | 64.9 |
| 60.8 | 78.7 | 59.4 |
| 70.2 | 81.4 | 55 |
| 75.6 | 82.6 | 53.2 |
| 73.8 | 82.8 | 55.4 |
| 66.9 | 81.9 | 59.4 |
| 55.9 | 78.3 | 63.7 |
| 44.8 | 73.6 | 66.9 |
| 34.5 | 69.1 | 70.2 |
I run this through my spreadsheet and these are the correlations I receive:
New York to Miami Correlation: 0.99
New York to Sydney Correlation: -0.98
What this tells me are that the temperatures of New York and Miami are highly correlated and the temperatures in New York and Sydney are not. When temps are going up in New York they are going up in Miami and when they are going down in New York they are going up in Sydney.
But why should this be? To many I see talking about asset class correlation the analysis stops here. They would simply say (if you built portfolios from cities) is:
“Just buy a little New York, a little Sydney to diversify and some Miami to boost returns.”
But when you ask a more fundamental question about why these cities are or are not correlated you may not get an answer. So you look further and think that perhaps it’s related to the months of the year. Hmmm…now that’s interesting.
Let’s add months to our chart:
| Month | New York | Miami | Sydney |
| Jan | 30.7 | 67.2 | 71.8 |
| Feb | 31.5 | 68.5 | 71.6 |
| Mar | 39 | 71.7 | 69.6 |
| Apr | 49.8 | 75.2 | 64.9 |
| May | 60.8 | 78.7 | 59.4 |
| Jun | 70.2 | 81.4 | 55 |
| Jul | 75.6 | 82.6 | 53.2 |
| Aug | 73.8 | 82.8 | 55.4 |
| Sep | 66.9 | 81.9 | 59.4 |
| Oct | 55.9 | 78.3 | 63.7 |
| Nov | 44.8 | 73.6 | 66.9 |
| Dec | 34.5 | 69.1 | 70.2 |
Ok that adds some more context. Clearly you see the month of September, then October, then November, then December. What’s this? Why are the temps in New York and Miami falling but Sydney is going up? The months are all the same.
In Some Places, Santa Claus Wears a Bathing Suit
Let’s look deeper. Let’s ignore the months and look at the seasons instead. As you probably know, the Northern and Southern hemispheres have seasons that are reversed (When I was in New Zealand for instance, Santa Claus in December was shown to be in summer shorts carrying a surfboard and not wearing a big heavy coat):
Northern Seasons
Winter: December, January, February
Spring: March, April, May
Summer: June, July, August
Fall: September, October, November
Southern Seasons
Summer: December, January, February
Fall: March, April, May
Winter: June, July, August
Spring: September, October, November
With more context this correlation data now makes sense. The temperatures fall in New York and go up in Sydney because of the seasonal differences. It has nothing to do with the cities being correlated, the months of the year, etc. The temperature changes are due to the seasons and if I ran a correlation of temperature changes to seasons of the year you’d find that it is almost a perfect 1.0 match regardless of location on this planet.
What’s the Point?
Asset classes don’t move because of each other. Asset classes move because of the seasons in the economy.
Asset class correlations without an economic explanation why they move is pointless. This is the problem of using asset class correlations alone to build a portfolio. It’s also why you should ignore tables of asset class correlation data you see in books, articles and other places. If they aren’t tying those assets to the economy then it’s all wasted ink.
Changing Seasons of the Economy
We come then to a core concept of the Permanent Portfolio. It is not built around this idea of asset class correlations. It is built around the idea of looking at the changing seasons of the economy:
1) Prosperity
2) Deflation
3) Inflation
4) Recession
Bonds don’t move up sharply in price because stocks moved down. Bonds move up because deflationary forces make it a good investment. Gold doesn’t move up because bond prices are falling. Gold moves up when people think inflation is becoming a threat. Stocks don’t move up because gold prices have come down. Stocks move up in price when people think the economy is going to be prosperous.
This is the difference between the Permanent Portfolio allocation and others. The assets chosen respond the best to the four conditions of the economy outlined above. Those assets are (for US Investors) Stocks, Long Term Treasury Bonds, Treasury Money Market Funds and Gold.
A Five Foot Deep Creek Can Still Kill You
So what about the second error I talked about above? The one where I said asset class correlation data masks some truly ugly details by bundling everything up over multiple decades?
Well it’s just something that averages do. They’re average. Taken as weather you may think the average January temperature above for New York is 30.7 degrees. However what you don’t see are those nasty years when it was in the low twenties with plenty of days in the single digits or lower.
It’s related to that old saw in statistics that a six foot tall man that can’t swim can still drown in a creek that is an average depth of five feet. What this average ignores is the creek is one foot deep in some places but 10 feet deep in others. It’s these extremes that can really burn investors and you don’t see them when you look at some correlation number that spans 40 years. The extremes are buried in the data and until you look you won’t see when the correlation of assets suddenly went to 1.0 perfect and huge losses incurred in certain years (witness 2008′s losses in what some thought were diversified investments).
Correlations Don’t Change Over Time
Incidentally, the changing of the economy is also why advocates of correlation data say “Correlations change over time.”
Actually, correlations don’t change. At least not when you look at the data from an economic cycle standpoint.
Stocks and bonds don’t suddenly become correlated out of the blue. What these folks are seeing is the economy shifting underneath that causes periods of over and underperformance for assets. The correlations though are not “changing.” The only thing changing is the time period they are analyzing and what the economy was doing and they are coming away with the wrong conclusions. Statistical tools are powerful when used correctly, but here they fall flat on their face because they are being mis-applied.
“Correlation does not equal causation” - Asset class correlations provide no explanation for cause and effect. Only tying the assets to the economy explains their price movements.
An Epiphany – At Least for Me
I took time to explain this because it was really an epiphany for me personally and answered many questions about how diversification can be made to work by applying economic understanding to the problem. In fact, I firmly believe it is a serious and grave error to not consider economic impacts on the asset classes you own and rely on correlation data only.
So ignore this asset class correlation stuff. It doesn’t answer the questions you need to have answered about investments and can get you into trouble by supplying you with a false sense of security. Instead, own assets that correlate to what the economy underneath is doing. This is where the power of diversification can really work for you.
