Switzerland, Neurofinance, and When to Sell in a Bull Market

“When the music stops, in terms of liquidity, things will be complicated. But as long as the music is playing, you’ve got to get up and dance. We’re still dancing."
~  Chuck Price (then CEO of Citigroup) to the Financial Times on July 9, 2007. 

"The current level of the CAPE ratio 'would suggest reducing your holdings of stocks, especially for a long-term investor. We can't time the market accurately, but we know that when it's this high, over the long term, it usually doesn't do great.'"
~ Robert Shiller quoted in CNBC, February 24, 2017

"Merchant: In this chaos of opinions, which one is the most prudent?
Shareholder: To go in the direction of the waves and not to fight against the currents."
~ Joseph De La Vega.  1688.  "Confusion de las Confusiones."  (The first book about the operations of a stock market, the Amsterdam Exchange).

Is Trump Playing Crazy? Negotiation, the Game of Chicken, & Dollar Sentiment

To achieve their mating goals, male elephants will sometimes play games of chicken, with one individual essentially giving the impression that he is crazy and has become an irrational player in a game premised on shared rationality and predictability.
~ Professor David Barash, Op-Ed in the NYTimes, 2011

Fittingly, this Year of the Rooster corresponds with a surge in a cock-inspired game in international negotiations: playing chicken.  

As a young man I occasionally stood on the bridges across the Rio Grande, practicing Spanish and watching Mexicans commute to work in the United States.  They bagged their clothes, paid a peso or two to a man with an inner tube, and were gently pulled across the river under the eye of inert border patrol agents. U.S. customs wasn't apparently concerned enough to intervene.  I myself climbed under the fence or waded the river a few times out of convenience or curiosity.  Even the Laredo, Texas INS chief's nanny was well-known to commute to work that way.  In subsequent years the border has obviously tightened.  And now we're hearing about The Wall, whose conception has badly punished the Mexican Peso and local stocks.

As active investors it is our job to predict trends and reactions in global economies and markets.  Donald Trump's spontaneity has introduced a degree of unpredictability to our work.  His negotiations around trade agreements, immigration policy, tax policy, military arrangements (NATO), and budgetary allocations are all going to be significant  to the markets over the next year.  Whether one agrees with Trump's proposals or not, it's important to know how he will pursue them, when he will go full force, and when he might back down.  

Trump's tactics are familiar - and perhaps predictable - to students of game theory.  Today's newsletter looks at this important topic - one we have addressed previously - the psychology of negotiation and playing chicken.  Later we look at a turn in U.S. Dollar sentiment around the U.S. election and its aftermath.

Game Theory in the Real World

John Nash is the subject of the Academy Award-winning movie "A Beautiful Mind" and the father of Game Theory involving multiple equilibria in non-cooperative games - exactly what we need to understand the psychology of playing chicken.  

It's a tactic that works surprisingly well, because male elephants can in fact become temporarily "crazy". One of the most terrifying sights in the animal world is an elephant in a state of must: Huge bulls, oozing a weird, foul-smelling, greenish glop from glands near their eyes, behave with violent abandon, taking risks and defying the basic rules of pachyderm propriety (and also giving rise to the term "rogue elephant"). Facing an elephant in must, other elephants — not to mention people — are well advised to get out of the way.

Dr. Barash explains that by playing chicken - as Donald Trump may be inclined to do as he renegotiates terms of existing trade agreements - low-power players can extract additional concessions due to their hardliner stance.  As he puts it, "The trick to winning is for one player to convince the other that under no circumstance will he or she veer off course."  Dr. Barash continues, "Another tactic, favored by the strategist Herman Kahn, is to "throw out the steering wheel," to demonstrate that you are locked into a certain path and can't swerve."

The Seasons of Social Change, S&P 500 Sentiment Rebound, Perspective-shifting

As Brexit before it and the Italian referendum following it, November's U.S. election represents a social turning point.  Some believe the light is fading across Western democracies.  Others sense renewed engagement after a long period of public passivity.  Both camps see this as a pivotal moment in history. 

It's not only democratic engagement that's at a turning point.  This time of year, across the northern latitudes, nature is growing quiet. Plants and animals have stored away food for the cold months and months of dormancy. When the snow comes, the quiet will be even deeper.  During the darkness of winter, this week's solstice marks a turning point in the season.  December's holidays symbolize the renewal of life, light, and growth from the depths of darkness.  

After the November U.S. elections a rapid shift in media sentiment strongly correlated with the rally in U.S. stock prices, and this was surprising to many market-watchers, who anticipated a large correction if Donald Trump was elected.  

Both around strongly felt events and during the dark of winter, the human mind is susceptible to inertia, becomes trapped into believing narratives (E.g., "Trump/Hillary means the end of the world") or ("maybe the light will never return"), and the mind has difficulty shifting perspective.  For the seasonal darkness, societies developed light-themed holidays (Diwali, Hanukah, Christmas, Santa Lucia) to break through inertia during dark days.  For individual investors, some top performers use a technique called "reappraisal" to prevent inertia.  When predicting market prices, impartial machine learning-based systems are proving to be a valuable tool when the majority of human investors are stuck in a rut.  

Today's newsletter examines sentiment shifts around events, the power of machine learning to take advantage of these, and a technique used by top investors to avoid mental inertia. 

Did Artificial Intelligence Predict the U.S. Election?

Although the darkness will continue to lengthen into the solstice this week, light will begin its return on the 22nd.  We described a similar reversal phenomenon in market prices in our last newsletter.  A sell-off into an uncertain event such as an election typically reverses in the subsequent period.  Sometimes prices reverse after the event because the sense of dread and foreboding is gone, replaced by relief that the event has passed.  Sometimes prices revert upwards because of growing optimism about business conditions.  Probably both of those occurred following the U.S. election, juiced onwards by investors who had sold out in advance to reduce their risk exposure, and now jumped back in out of fear of missing out on the post-election rally.

The following image depicts our financial media-derived sentiment data versus the S&P 500 daily prices this year.  From a low point in November before the election, sentiment jumped impressively in the hours following Trump's victory.


Such rapid sentiment reversals are difficult for humans to time accurately.  We tend to become absorbed into the story around the events.  Such event-inflexibility provides an opening for machine-learning-based predictive models.

As we mentioned in our September newsletter, we've developed such a machine learning based model that makes predictions on the S&P 500, and it was extraordinarily accurate not only in the two weeks around Brexit, but also in the week of the U.S. election and the following week.  It was long the day before the election, went short the day of the election through the following opening, and was long over the following week.  However, the system is not perfect.  It had periods of poor performance in October and so far in December this year - please see disclaimers below.  It especially shines around major psychology-driven events such as corrections and referenda.

Our machine learning-based model probably performs so well around uncertain events because it can impartially take advantage of the human biases that blind the majority of traders.  While these collective biases can be disabling, some top investors have found ways to reduce the impact of such vulnerabilities via a practice of "perspective-shifting."

Perspective-Shifting

In his “Belief in Fallibility" George Soros (1995) explains that to others being wrong is a source of shame. But for him, recognizing his mistakes is a source of pride. Soros explains that realizing that imperfect understanding is the human condition leads to no shame in being wrong, only in failing to correct our mistakes.  It requires remarkable courage to consider one's imperfections and mistakes impartially.  And evidence suggests that the ability to reappraise one's circumstances is an important tool for reducing common financial biases.

Researchers have found that cognitive reappraisal reduces the impact of loss aversion on decision making (Sokol-Hessner et al, 2009). Reappraisal refers to readjusting one's perspective of a situation along several dimensions. In an experimental condition, researchers randomly asked subjects to think of / review their individual investments in the following contexts: (1) as part of a portfolio, (2) as one of many in a series, (3) as part of a routine job, (4) as expecting that losses are going to happen (“you win some and you lose some”), and (5) as not having direct consequences for their lives. In aggregate these cognitive reappraisals reduced both physiological reactions to losses (measured via galvanic skin response) and subsequent loss-aversion (biased behavior). According to Sokol-Hessner (2009), “‘perspective-taking,’ uniquely reduced both behavioral loss aversion and arousal to losses relative to gains, largely by influencing arousal to losses.” 

In summary, Soros is right.  To improve ourselves as investors we must learn from our mistakes, and the best perspective to take is one of curiosity and flexibility.  We must shift our perspective from one of "Oh no, another bad mistake!" to "Great, another opportunity to learn!"  

When approaching losses, thinking about the loss as 1) a routine part of the job of investing, 2) as one of many that one will experience over a typical career, and 3) as not affecting one's physical life or health, will help normalize the loss and improve subsequent decision making.

Houskeeping and Closing

We are approaching the dead of winter in the northern climates.  The holidays ahead teach us to maintain hope in the darkness and to celebrate the value of persistence as we carry the light forward into the new year.  

Despite the impressive results of machine learning in financial markets, the victory of the machines is not yet at hand.  Machine learning thrives in environments where humans do not, such as around psychologically fraught events (elections, volatility, etc...).  Where humans are inflexible, machines prosper.  Taking a larger view, these periods of inflexibility can teach us about our own weaknesses such as our propensity to make mistakes in markets with fast-moving prices or when we believe fixed narratives about how things should be.  

We love to chat with our readers about their experience with psychology in the markets.  Please send us feedback on what you'd like to hear more about in this area.  Read more about individual psychology in our books "Inside the Investor's Brain" (Wiley, 2007) and "MarketPsych" (Wiley, 2010).  Market psychology and sentimental markets are examined in our newest book "Trading on Sentiment:  The Power of Minds Over Markets" (Wiley, 2016).

If you represent an institution, please contact us if you'd like to see into the mind of the market using our Thomson Reuters MarketPsych Indices to monitor real-time market psychology and macroeconomic trends for 30 currencies, 50 commodities, 130 countries, 50 equity sectors and indexes, and 9,000 global equities extracted in real-time from millions of social and news media articles daily.

Always seeking new perspectives,
Richard Peterson M.D. and the MarketPsych Team

References

Sokol-Hessner, Peter, Ming Hsu, Nina G Curleya, Mauricio R. Delgado, Colin F. Camerer, and Elizabeth F. Phelps. 2009. “Thinking Like a Trader Selectively Reduces Individuals’ Loss Aversion.” Proceedings of the National Academy of Sciences 106 (13): 5035–5040.