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Quantitative Analysis: Not Just Numbers


I’m a big fan of the work of Cliff Asness and AQR (Applied Quantitative Research).  Cliff was interviewed by Barry Ritholtz on his podcast here. About twelve minutes in Barry asked Cliff what it means to be a quantitative investor. 

 

Cliff replied that “quantitative investment managers are about two things – averages and diversification.” Diversification is broadly accepted in finance, often called “the only free lunch” in investing. Quant managers care about what works in trading and investing and what has statistically significant historical evidence to prove it. For example, value, momentum, and trend have held up under rigorous tests. Many in finance hold their beliefs about one particular style of investing (for example “active vs passive”) so closely that it’s like debating politics. Many people have a hard time holding two different points of view on investing in their head at the same time as we seem to be programmed to want to pick sides.


But quantitative analysis is not only about performance data. When done properly only modest and general conclusions should be drawn about the likelihood of the future to be like the past. Let’s look at an example:


Portfolio visualizer is a nice web site for backtesting asset allocations. I took a few minutes to create a simple asset allocation of the following:

 

20% US equity

20% Global Ex-US equity

60% 10-year US Treasuries


Cliff also talked about how quant managers like to do in sample and out of sample testing to confirm the validity of an investment strategy on both past data that you have seen as well as data you haven’t. This eliminates or at least reduces hindsight. Let’s go back in time a few years and assume for a moment it’s 12/31/2007. From 1986 to 2007 this simple asset allocation, rebalanced annually, produced impressive risk-adjusted results (Gross of fees and taxes. Past performance doesn’t guarantee future results, and that’s one of the major points in this post):

 

Annualized return: 9.63%

Annualized volatility: 7.31%

Sharpe Ratio: .68

Max Drawdown: -9.32%

 

Here is the wrong way to review this information: “Wow, this portfolio makes over 9% per year and can only lose 9.32%? I can easily handle that kind of risk!”

 

The reason I place emphasis on the words "makes" and "can only lose" is that they actually imply something about the future, which unknowingly permeates the minds of investors and can be problematic because it creates rigid expectations.


Image result for Quantitative Analysis


Now let’s look at 2008-2017 and consider it “out of sample” results:

 

Annualized return: 5.56%

Annualized volatility: 6.87%

Sharpe: .78

Max Drawdown: -15.12%


Since 2008, this simple portfolio has produced materially less return (albeit, a slight increase in risk-adjusted performance) while it also set a new maximum drawdown. But is there actually anything “wrong” with this portfolio? Not at all. 2008 was a historic global sell-off in asset classes, making even a 40% allocation to equities risky in the eyes of many investors. The problem that investors run into is focusing WAY too much on past performance without taking into consideration market conditions from a much higher level.  Humans tend to think the recent past will continue on forever, which is known as recency bias. Now analyzing this simple portfolio over the entire period of 1986-2017 gives an annualized return of 8.34%, and it will continue to change every year. So what return should we "expect" then?

The only thing I’d be confident in is that a portfolio like this will continue to provide real returns over the long term. Quantitative analysis can be an extremely powerful process for building evidence based investment portfolios. But there is a right way and a wrong way to do it, and investors are well served to have a fundamental understanding of why a portfolio is likely to continue to produce positive returns in the future, in addition to knowing historical returns, and then maintain flexible expectations along the way. The future will always produce surprises that were not present in historical data. 


“Thus timing, and in particular the selection of the beginning point and end point for studying a performance record – plays an incredibly important role in perceptions of success or failure” -Howard Marks


“No strategy is so good that it can’t have a bad year or more. You’ve got to guess at worst cases: No model will tell you that. My rule of thumb is double the worst that you have ever seen.” - Cliff Asness, AQR


“When investing over the long run, all you can have confidence in is that…holding assets should provide a return above cash…That’s it. Anything else (asset class returns, correlations, or even precise volatilities) is an attempt to predict the future.” -Ray Dalio, Bridgewater Associates


“You must be rigid in your rules and flexible in your expectations. Most traders (and investors) are flexible in their rules and rigid in their expectations.” -Mark Douglas
 
 
Jesse Blom is a licensed investment advisor and Vice President of Lorintine Capital, LP. He provides investment advice to clients all over the United States and around the world. Jesse has been in financial services since 2008 and is a CERTIFIED FINANCIAL PLANNER™. Working with a CFP® professional represents the highest standard of financial planning advice. Jesse has a Bachelor of Science in Finance from Oral Roberts University. Jesse is managing the LC Diversified portfolio and forum, the LC Diversified Fund, as well as contributes to the Steady Condors newsletter. 

 

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