How does 'availability bias' affect traders?
Availability bias is the tendency to open or close positions based on information that is easily available, rather than sources that are more difficult to find. It can cause traders to act on false or unverified information, which can lead to higher levels of risk and loss.
Traders tend to lean towards what is personally most relevant, recent or emotional, even long after the event is over. The mind can take a shortcut based on examples that come to mind immediately, rather than on research and analysis. For example, if a person has a family member who recently lost money on a bitcoin trade, they may be less inclined to speculate on the cryptocurrency because it is hard for them to imagine that the market can be profitable.
In fact, a study by Moradia, Meshkib and Mostafaei found that there is a strong correlation between judgement and data availability. By surveying investors of stocks listed on the Tehran Stock Exchange, the researchers concluded that decision-making would likely improve as the amount of information released to the public increased.1
How can traders prevent availability bias?
The most common way to prevent availability bias is to conduct extensive research and analysis. Participants of IG's survey were comfortable using multiple sources to gather information on trading and investing. Although 56% used the internet, some also used newspapers, specialist publications, financial advisers, television and podcasts.
Fundamental analysis is used to examine internal and external factors such as earnings reports, how the sector is performing, and the health of the economy, while technical analysis looks at historic price data and indicators to establish key entry and exit levels for each trade.
If you don't feel confident enough to trade on live markets, you could test your strategy on a demo account first. This enables you to practise trading with indicators and test your strategy using virtual funds.
Things to keep in mind...
Learn how to trade in a risk-free environment with an IG demo account. 1Moradia, Meshkib and Mostafaei, 2012Related articles
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