You will want to sit down for this one. The modern financial services industry and their computer generated investment models, have been driven by 50 year old, flawed research. Let me take you on a little financial services adventure in this post. It all started back in the 1950s with a man named Markowitz.
MPT
Harry Markowitz is considered the “father” of Modern Portfolio Theory (MPT). MPT is a mathematical formulation of diversification in investing. The aim of MPT is to select a collection of investments that has collectively lower risk than any individual investment. A few decades back the financial services industry caught on to MPT as a very useful marketing tool. Then in 1990 the story for MPT got even better because Markowitz won a portion of a Nobel Prize for his research in economics.
Marketing Machine
How do the vast majority of investment advisors make money? The answer is by managing a lot of money for a lot of people. The only way to do that effectively is to have an investment strategy that requires very little attention. So, the financial services industry created a great story and found research to support their cause.
The story
The pitch from the investment advisor goes something like this:
“To build our portfolios, we follow Modern Portfolio Theory which was developed by a Nobel Prize winning professor. Simply put modern portfolio theory states that you can lower the risk in your portfolio by diversifying your holdings. Mr. Client that makes sense to you right?” What we have also found is that the best strategy is to not “time” the market. Meaning jumping in and out of investments. No one has been able to do that successfully over any long period of time.”
In the midst of the story the investment advisor will pull out pictures of pie charts and graphs about how well diversification works. Then the really nice marketing piece comes out that shows how if you missed the best days in the market over some period of time you would have a lower return than if you held on the whole time.
Debunking the story
Lets put the story from above through the B.S. screen and see what was really said. Here is the real story behind the pitch.
“Mr. Client in order for me to make lots of money for myself I need a lot of clients. The only way to have a lot of clients is to spend most of my time marketing not managing money. Therefore, I need an investment strategy I can set and forget. The buy and hold investment strategy works well for me and I will show you a few marketing pieces that have been scrubbed of material facts and will convince you that it works for you in theory but not in practice.”
The true story Part 1 – Buy and Hold
Buy and hold as an investment strategy in the last 10 years has resulted in losses. Why? The answer is because buy and hold does not identify exit points. There is a popular marketing piece that many financial advisors use that show what would happen if you missed the 10, 20, 30, 40 best days in the market over the last 10 years. The result is a much lower return than if you bought and held the whole time. What the advisors do not show you is if you missed both the best and worst days and if you only missed the worst days. Lets look at the full story.
| Days Missed | Missing Best | Missing Worst | Missing Best & Worst |
|---|---|---|---|
| 10 Days | 4.10% | 11.23% | 8.15% |
| 20 Days | 2.15% | 13.80% | 8.58% |
| 30 Days | 0.54% | 15.83% | 8.61% |
| 40 Days | -0.93% | 17.59% | 8.82% |
(Source: NAAIM, Inc., This data is for illustrative purposes only and is not indicative of the actual performance of any investment. S&P 500 Index returns do not reflect reinvested dividends.)
As you can plainly see the best option is missing the worst days. In reality no one is good enough to get all the good and no bad or the opposite. But what it does show is that if you can find a way to miss some of the worst periods in the market you can do much better than the market. I know one simple way to miss some of the worst days in the market. Click here for my study of the utility of using the 200 day exponential moving average (EMA) for trading.
The true story Part 2 – Modern Portfolio Theory
Harry Markowitz was on the right track in the 1950s. He academically proved that diversification was good when it comes to investment portfolios. I would not argue that diversification is good. The problem is that in the 1950s computing horse power did not exist. Therefore, in order to model risk in a security Markowitz used standard deviation as the measure of volatility of a security. Standard deviation is not a good proxy for risk because it looks at both extreme highs and lows as equally undesirable. Last time I checked with my clients they like the highs and not the lows. The problem is that Markowitz knew that semi-deviation produced better outcomes and he wrote it in his book Portfolio Selection on page 193.
“Variance (aka standard deviation) is superior with respect to cost, convenience, and familiarity. For example, roughly two to four times as much computing time is required (on a high speed computer) to derive efficient sets based on semi-variance (aka semi-deviation) than is required to derive efficient sets based on variance.”
He continued on page 194 of his book to state:
“Analysis based on semi-variance tend to produce better portfolios than those based on variance. Variance considers extremely high and extremely low returns equally undesirable. An analysis based on variance seeks to eliminate both extremes. An analysis based on semi-variance, on the other hand, concentrates on reducing losses.”
So, since Markowitz was dealing with computers powered by mice he settled for a second best approach. I can forgive him for that. What is not acceptable is that the financial services industry is still going on flawed research. With modern computing power the financial services industry could be doing things the right way now. The question is why are they not? That question was answered by Dr. Frank Sortino.
“…the business of providing financial advice is driven by marketing and not technology…the incentive [to change] is not there so long as people are making money.” – Dr. Frank Sortino Founder of the Pension Research Institute
I could not have said it better myself.
Thanks to Dr. Sortino and Brian Rom we have the Sortino Ratio. The Sortino Ratio takes an MPT statistic like the Sharpe ratio and modernized it.
The Sharpe Ratio is a a measure of excess return per unit of risk. The formula is (Investment Return – Risk Free Return) / Standard Deviation. The higher the resulting number the better.
The Sortino Ration is the actual rate of return in excess of the investor’s target rate of return, per unit of downside risk. The formula is (Investment Return – Minimum Acceptable Return) / Downside Risk. Downside risk measures returns below the minimum acceptable return.
The conclusion
So, the next time you hear about standard deviation, modern portfolio theory, or buying and holding run the other way. Better yet call me for a modern portfolio.
