Monday, July 14, 2008

Anchoring Bias

Anchoring bias is a common but fascinating cognitive bias, and it’s highly relevant to be aware of it now.

Anchoring bias in the narrowest sense refers to the phenomenon when the mind fixates on a number brought to its attention, and how when a person is asked to estimate a given, possibly unrelated figure, that person unconsciously uses the anchoring number as a point of reference for those estimates. The truly amazing thing about this cognitive bias is that the anchoring number need not bear any relevance to the figure that needs to be estimated.

Anchoring bias, like many cognitive biases, probably has its roots in evolutionary adaptations in what Gerd Gigerenzer terms “fast and frugal” thinking. It may be a heuristic designed to allow humans to process information quickly and accurately (in a prehistoric environment).

Why is anchoring bias highly relevant now? Because the global economy and stock markets around the world are now at or past an inflexion point.

Unless you’ve been living in a cave, it should be common knowledge that economic problems are in focus around the world now. Stock markets have been tumbling far below their peaks in the wake of the (continuing) credit crisis, inflation is ravaging countries around the world when it formerly was not a problem, oil and food commodity prices have blown past their historic highs, and growth is slowing everywhere. We are entering a period of stagflation, with anemic growth accompanied by high inflation, when we were in an economic boom only several quarters ago.

At inflexion points when the direction of the economy and stock markets change, econometric forecasts and models are notoriously unreliable, and this is arguably when their forecasting performance is most vital.

And how does anchoring bias figure in all this? Think of all the economic numbers that are important to you, and then consider how anchoring bias has affected how you perceive these numbers, or how they are generated.

If you invest in stocks, think of how the target price of your favorite stock has changed since the go-go times of yesteryear. Is applying a ‘discount’ to the anchor of last year sufficient now that the external environment has changed so drastically?

If you rely on financial analyst reports, be especially wary of target prices that have been ‘revised’ and backed up by ‘adjustments’ to various models. What goes for the target price also applies to the entry price. If I had a penny for every analyst that I’ve read or heard say “such and such a stock is now great value since it’s corrected by X% from such and such a price”…well, let’s just say that the historic peak price is one helluva anchor for those unaware of anchoring bias.

If you’re watching the prices of oil, gold and other commodities, historic highs (whether inflation adjusted or not) also constitute huge anchors.

If you run a business, you’d better be aware of what goes into your sales and profit projections, instead of just extrapolating from your experiences in previous years.

Economists who do inflation or economic forecasts might want to re-look their entire model or all the underlying assumptions instead of just tweaking their previous forecasts.

If you’re bothered by higher prices for everything, well, I have no solution for you. However, you may want to note that your misery stems directly from anchoring bias and reality not matching up with expectations. We are lightyears away from the low inflation [in necessities, but not in assets] environment of the past decade.

If you’re looking to buy or sell a property, you should already be aware that real estate prices are especially sticky. Sellers are unwilling to let go at too low a price or too low a cash-over-valuation because the booming (in contrast to this year) property market of last year was full of anchors to reference from. A cooling property market is not so much marked by lower prices as it is by low liquidity.

[Incidentally, if you’re watching the US subprime mortgage crisis as closely as I am, you might be interested in research from iTulip here and here. The research has been made available free for one week only due to wide ramifications on the US economy, so you might want to read it now.]

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