The Financial Merits of Emotional Trading

New software will analyze language more accurately to gauge the emotions of humans in the world of trading and finance. The software, a sentiment reading tool, was developed through a partnership of Thomas Reuters and MarketPsych. The process is called behavioral economics, and it reaches a variety of investors, regardless of class or assets. The software targets key words to identify emotional levels, which are typically adverbs and adjectives. Also targeted are the subjects of statements like a location, such as Greece, or currency amounts. For example, the software can identify if traders are experiencing anxiety over a financial issue, like Greece leaving the Eurozone. Developers say the software is almost human-like.

The range of emotions, which are scored by the software, vary from fear to joy to trust to urgency and uncertainty, and other emotions. The scores are then integrated into models of trading, which will assist the decisions of traders and investors. The models are updated on the Internet every minute of every day, and are divided to show the psychological variables of the different asset classes. The software provides top investors with the mental state of individuals, and where the emotions stem from. If individuals are expressing uncertainty because war in Iran could be declared, the software records the emotion and the reason for it. The behavioral technology also uses language to spot likely bubbles for traders.

How the Software Works

Although sentiment reading tools that tell the difference between positive and negative emotions have been established for some time, psychological analysis states the tools work from the top down to identify emotions related to currency,  populations and commodities. The new software of Thomas Reuters starts at the bottom. If conversations on the Internet center on specific stocks like Apple or Google, the software informs investors. This doesn’t mean thinking from the top down should be brushed aside. It is important to know how stocks are performing, whether positive or negative. The reason for the bottom approach is because everybody handles emotions differently. Just because one investor is complaining, doesn’t mean a second investor will on the same issue.

If the market is viewed as uncertain or optimistic, it is highly unlikely the opposite emotion will influence the temperament. Developers set out to expand how the language processing worked. They wanted to identify the emotions in detail, instead of the general overview the existent software gave. Developers used imaging to study how the brains of traders reacted to financial dilemmas. For example, a group of traders were given the option to accept $10 in cash, or take a chance on flipping a coin for $30. The developers’ answers lie in the presentation of the dilemmas. Depending on how the dilemmas were presented, experiment traders would change their minds. The developers “primed” their questions. In one instance, they asked if traders would be more content to leave immediately, or stay and lose without worries. The developers said by tweaking the words, they changed the actual behaviors. They also said traders change their minds based on emotional images, but this was denied by the traders when asked.

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