Tag: behavioral-finance

You are always right in some universe

In recent years a number of investigators have developed the view that those supposedly irrational choices that people make merely reflect the fact that their brains are guided by the mathematical principles of quantum physics.
 
Quantum cognition has proved to be able to account for puzzling behavioral phenomena that are found in studies of a variety of human judgments and decisions.
 
Human judgments “are often not simply read out from memory, but rather, they are constructed from the cognitive state for the question at hand.” Consequently drawing a conclusion about one question alters the context, disturbing the cognitive system just as a quantum measurement disturbs an electron. Such disturbances will influence the answer to the next question, so that “human judgments do not always obey the commutative rule of Boolean logic.”

Source: Quantum math makes human irrationality more sensible

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Ego: The Single Biggest Impediment to Successful Investing

From Why Inexperienced Investors Do Not Learn: They Do Not Know Their Past Portfolio Performance (Glaser, Weber)

A necessary condition to learn is that investors actually know what happened in the past and that the views of the past are not biased. Investors are hardly able to give a correct estimate of their own past realized stock portfolio performance. People overrate themselves. On average, investors think, that they are better than others.

Here’s a telling chart on what investors “thought” they made vs what they actually made:

realized vs estimated returns

I loved the academic euphemism for “most investors are clueless”: The correlation coe±cient between return estimates and realized returns is not distinguishable from zero. And this gem: The correlation between self ratings and actual performance is also not distinguishable from zero.

Read the whole thing here (pdf) and open a StockViz account and start tracking your portfolio now!

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Musings on stock-market forecasts

Traffic jams

Say there’s a traffic jam on a busy road. When new vehicles try to enter the same route, the drivers hear on the radio that there’s a jam ahead and adapt by finding another route. Suppose there is only one alternate route. What happens now? The alternate route forms a second jam!

Later entrants have to choose between the two jams. Predicting the actions of this new group is very hard to do. Maybe the second jam is worse than the first. By the time we hit this third layer of participants, predicting the behavior of the system has become extremely difficult, if not impossible.

Complex vs. Complex Adaptive

Weather is a complex system. However, if, on Thursday, the forecast is for rain on Sunday, is the rain any less likely to occur? No. The act of predicting has not influenced the outcome. Although near-term weather is extremely complex, with many interacting parts leading to higher order outcomes, it does have an element of predictability.

The stock-market is a complex adaptive system. Traders and investors in the market are interacting with one another constantly and adapting their behavior to what they know about others’ behavior. The key element of a complex adaptive system is the social element.

For example, Meredith Whitney predicted the crash of Citibank in late 2007.

citi chart

She went on to setup her own advisory firm, Meredith Whitney Advisory Group, and made a similar call on American municipal bonds in late 2010 on national television. Retail investors sold in panic. But for the the most parts, nothing happened.

MUB chart

Reflexivity

Reflexivity refers to circular relationships between cause and effect. A reflexive relationship is bidirectional with both the cause and the effect affecting one another in a situation that does not render both functions causes and effects. It flies in the face of equilibrium theory, which stipulates that markets move towards equilibrium and that non-equilibrium fluctuations are merely random noise that will soon be corrected.

Reflexivity asserts that prices do in fact influence the fundamentals and that these newly-influenced set of fundamentals then proceed to change expectations, thus influencing prices; the process continues in a self-reinforcing pattern.

Takeaway

Behavioral dynamics is key to understanding complex adaptive systems. One should have a mental model that incorporates higher-order thinking when it comes to navigating the markets.

The big question is, how different is listening to stock-market predictions from listening to an astrologer, reading horoscopes or believing in vastu?

To quote German theologian and martyr Dietrich Bonhoeffer:

“…how wrong it is to use God as a stop-gap for the incompleteness of our knowledge. If in fact the frontiers of knowledge are being pushed further and further back (and that is bound to be the case), then God is being pushed back with them, and is therefore continually in retreat. We are to find God in what we know, not in what we don’t know.”
Sources
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Of whatsnexters, horoscopes and personal experiences

Can Stock Market Forecasters Forecast?

It’s time we stopped listening to the “whatsnexters.” These folks are everywhere in the financial media pontificating confidently about what they can’t possibly know — what’s next for the economy or the stock market.

Read: Don’t let market pundits lead you astray

Good to Great

The story of success swarms statistics. And there’s always enough random success to justify almost anything to someone who wants to believe.

Read: Stories triumph Statistics

A case for rules-based investment methodology

Our personal experiences disproportionately impact our investing behavior. By simply repeating investing behaviors that resulted in good outcomes for us in the past, and avoiding those that resulted in poor outcomes, we’re potentially eliminating important information that could help future investment performance.

Read: Bad Investor Behavior: Overemphasizing Experience

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Study reveals why economists suck at making predictions

The ability of forecasters to predict turning points is limited. Forecasts from the official sector, either from national sources or international agencies, are no better at predicting turning points.

So the explanation for why recessions are not forecasted ahead of time lies in three other classes of theories, which are not mutually exclusive.

  • One class says that forecasters do not have enough information to reliably call a recession. Economic models are not reliable enough to predict recessions, or recessions occur because of shocks (e.g. political crises) that are difficult to anticipate.
  • A second class of theories says that forecasters do not have the incentive to predict a recession, which – though not a tail – event are still relatively rare. Included in this class are explanations that rely on asymmetric loss functions: there may be greater loss – reputational and other kinds – for incorrectly calling a recession than benefits from correctly calling one.
  • The third class stresses behavioural reasons for why forecasters hold on to their priors and only revise them slowly and insufficiently in response to incoming information.

A more than a healthy dose of skepticism is always warranted when dealing with these so called “expert forecasts.”

Source: “There will be growth in the spring”: How well do economists predict turning points?

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