Paul Meehl was a versatile academic who held numerous faculty positions, covering the diverse disciplines of psychology, law, psychiatry, neurology, and yes, even philosophy. The crux of his research was focused on how well clinical analysis fared versus statistical analysis. Or in other words, he looked to answer the controversial question, “What is a better predictor of outcomes, a brain or an equation?” His conclusion was straightforward – mechanical methods using quantitative measures are much more efficient than the professional judgments of humans in coming to more accurate predictions.
Those who have read my book, How I Managed $20,000,000,000.00 by Age 32 know where I stand on this topic – I firmly believe successful investing requires a healthy balance between both art and science (i.e., “brain and equation”). A trader who only relies on intuition and his gut to make all of his/her decisions is likely to fall on their face. On the other hand, a quantitative engineer’s sole dependence on a robotic multi-factor model to make trades is likely to fail too. My skepticism is adequately outlined in my Butter in Bangladesh article, which describes how irrational statistical games can be misleading and overused.
As much as I would like to attribute all of my investment success to my brain, the emotion-controlling power of numbers has played an important role in my investment accomplishments as well. The power of numbers simply cannot be ignored. More than 50 years after Paul Meehl’s seminal research was published, about two hundred studies comparing brain power versus statistical power have shown that machines beat brains in predictive accuracy in the majority of cases. Even when expert judgments have won over formulas, human consistency and reliability have muddied the accuracy of predictions.
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Daniel Kahneman, a Nobel Prize winner in Economics, highlights another important decision making researcher, Robyn Dawes. What Dawes discovers in her research is that the fancy and complex multiple regression methods used in conventional software adds little to no value in the predictive decision-making process. Kahneman describes Dawes’s findings more specifically here:
“A formula that combines these predictors with equal weights is likely to be just as accurate in predicting new cases as the multiple-regression formula…Formulas that assign equal weights to all the predictors are often superior, because they are not affected by accidents of sampling…It is possible to develop useful algorithms without any prior statistical research. Simple equally weighted formulas based on existing statistics or on common sense are often very good predictors of significant outcomes.”
The results of Dawes’s classic research have significant application to the field of stock picking. As a matter of fact, this type of research has had a significant impact on Sidoxia’s stock selection process.
How Sweet It Is!
In the emotional roller-coaster equity markets we’ve experienced over the last decade or two, overreliance on gut-driven sentiments in the investment process has left masses of casualties in the wake of losses. If you doubt the destructive after-effects on investors’ psyches, then I urge you to check out my Fund Flow Paradox article that shows the debilitating effects of volatility on investors’ behavior.
In order to more objectively exploit investment opportunities, the Sidoxia Capital Management investment team has successfully formed and utilized our own proprietary quantitative tool. The results were so sweet, we decided to call it SHGR (pronounced “S-U-G-A-R”), or Sidoxia Holy Grail Ranking.
My close to two decades of experience at William O’Neil & Co., Nicholas Applegate, American Century Investments, and now Sidoxia Capital Management has allowed me to build a firm foundation of growth investing competency – however understanding growth alone is not sufficient to succeed. In fact, growth investing can be hazardous to your investment health if not kept properly in check with other key factors.
Here are some of the key factors in our Sidoxia SHGR ranking system:
- Free cash flow yield
- Price/earnings ratio
- PEG ratio
- Dividend yield
- Financials: Profit margin trends; balance sheet leverage
- Management Team: Track record; capital stewardship
- Market Share: Industry position; runway for growth
Contrarian Sentiment Indicators:
- Analyst ratings
- Short interest
- Earnings growth
- Sales growth
Our proprietary SHGR ranking system not only allows us to prioritize our asset allocation on existing stock holdings, but it also serves as an efficient tool to screen new ideas for client portfolio additions. Most importantly, having a quantitative model like Sidoxia’s Holy Grail Ranking system allows investors to objectively implement a disciplined investment process, whether there is a presidential election, Fiscal Cliff, international fiscal crisis, slowing growth in China, and/or uncertain tax legislation. At Sidoxia we have managed to create a Holy Grail machine, but like other quantitative tools it cannot replace the artistic powers of the brain.