Anchoring

Anchoring is the use of irrelevant information, such as the purchase price of a security, as a reference for evaluating or estimating an unknown value of a financial instrument.

Anchoring is a behavioral bias in which the use of a psychological benchmark carries a disproportionately high weight in a market participant’s decision-making process. The concept is part of the field of behavioral finance, which studies how emotions and other extraneous factors influence economic choices.

In the context of investing, one consequence of anchoring is that market participants with an anchoring bias tend to hold investments that have lost value because they have anchored their fair value estimate to the original price rather than to fundamentals. As a result, market participants assume greater risk by holding the investment in the hope the security will return to its purchase price. Market participants are often aware that their anchor is imperfect and attempt to make adjustments to reflect subsequent information and analysis. However, these adjustments often produce outcomes that reflect the bias of the original anchors.

An anchoring bias can cause a financial market participant, such as a financial analyst or investor, to make an incorrect financial decision, such as buying an undervalued investment or selling an overvalued investment. Anchoring bias can be present anywhere in the financial decision-making process, from key forecast inputs, such as sales volumes and commodity prices, to final output like cash flow and security prices.

Historical values, such as acquisition prices or high-water marks, are common anchors. This holds for values necessary to accomplish a certain objective, such as achieving a target return or generating a particular amount of net proceeds. These values are unrelated to market pricing and cause market participants to reject rational decisions.

Anchoring can be present with relative metrics, such as valuation multiples. Market participants using a rule-of-thumb valuation multiple to evaluate securities prices demonstrate anchoring when they ignore evidence that one security has a greater potential for earnings growth.

Some anchors, such as absolute historical values and values necessary to accomplish an objective, can be harmful to investment objectives, and many analysts encourage investors to reject these types of anchors. Other anchors can be helpful as market participants deal with the complexity and uncertainty inherent in an environment of information overload. Market participants can counter anchoring bias by identifying the factors behind the anchor and replacing suppositions with quantifiable data.

Comprehensive research and assessment of factors affecting markets or a security's price is necessary to eliminate anchoring bias from decision-making in the investment process.

• Anchoring is a behavioral finance term to describe an irrational bias towards a psychological benchmark.
• This benchmark generally takes the form of irrelevant information, such as an estimate or figure or event, that skews decision-making regarding a security by market participants, such as analysts or investors.

It is easy to find examples of anchoring bias in everyday life. Customers for a product or service are typically anchored to a sales price based on the price marked by a shop or suggested by a salesperson. Any further negotiation for the product is in relation to that figure, regardless of its actual cost.

Within the investing world, anchoring bias can take on several forms.

In one instance, traders are typically anchored to the price at which they bought a security. For example, if a trader bought stock ABC for $100, then she will be psychologically fixated on that price for a sale or further purchases of the same stock, regardless of ABC's actual value based on an assessment of relevant factors affecting it.

In another, analysts may become anchored to the value of a given index at a certain level instead of considering historical figures. For example, if the S&P 500 is on a bull run and has a value of 10,000, then analyst propensity will be to predict values closer to that figure rather than considering standard deviation of values, which have a fairly wide range for that index.