Quantifying Social Mood
Classifying social mood and labeling it with wave counts is still an expertise, especially if you are new to Elliott Waves. Though Socionomics experts defined and developed an essential treatise on social behavior, quantification of Socionomics (the study of human social behavior) — like behavioral finance — isn’t easy.
My questions about Socionomics theory are basic. Can we rank social mood? How can we do it? Is ranking of social mood indicators (like consumer sentiment index, brands index, demographic indices, movie and entertainment indices, real estate activity, Olympic participation, bankruptcy, investor sentiment, and market breadth indices) different with different time?
Or is social mood, like behaviouralists say, only about long-term reversals? Or can social mood indices be understood and used for investment decisions on shorter multi-week, multi-month time frames?
Performance cyclicality
If relative performance is about quantification, why can’t Socionomics quantify outperformance and underperformance in different social mood indices, pinpointing the time of performance and underperformance? Like it’s time for movies and entertainment sector to outperform the apparel, accessories, and luxury or sugar sectors, the indicator of mood should now start outperforming gold, the crisis commodity.
These questions of pin-pointing performance respective to a time frame — monthly, yearly, multi-year trends — are not only tough for the Socionomics theory to answer, but also for behaviouralists, fundamentalists and economists.
Sam Stovall’s sector rotation, a great idea suggesting performance cyclicality in industry-wide sectors (utilities, energy, staples, capital goods, materials, financials, technology, etc) fails when it comes to illustrating shorter time-frame performance cyclicality (between sectors) for a few months, weeks or days.
Robert Shiller’s performance divergence between fundamental data and traded data suffers from similar gaps. Shiller highlighted performance divergence between fundamental and traded data but did not talk about cyclicality of divergence.
These are still the experts we are speaking about. There are fund managers who talk about Africa as the final destination for investment, without really understanding performance cyclicality. How is the African investment landscape ranked in the Mena (the Middle East & North Africa) region for a yearlong investment? And how does the ranking (relative value) change if we look at the next few years? Very few investment experts can answer these questions. Dynamic relative performance, connected with holding period offering relative rankings, can’t be so simple.
We have illustrated performance cycles on global assets for multiple time frames.
Today, we extend it to social mood indices. We took 11 different indices (see chart, Ranking Mood) and time series, indexed and benchmarked them against gold prices. Sugar and VIX were at the bottom of an average 3.3-year economic cycle, while real estate, movies, and Apple were at the top of the rankings. Performance cycles illustrate the value in the worst and risk in the best.
It is tough to bet against the best performer and bet in favor of the worst performer, but top performers, as a rule, underperform. Sugar and Volatility should outperform Apple, and S&P Real Estate should underperform. Is ranking social mood so simple? Yes.