Volfefe index

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Donald Trump's Twitter activity from his first tweet in May 2009. (Retweets are not included.)

The Volfefe Index was a stock market index of volatility in market sentiment for US Treasury bonds caused by tweets by President Donald Trump.[1][2][3]

Bloomberg News observed Volfefe was created due to the statistical significance of Trump tweets on bond prices.[1] ABC News Online posited Volfefe could help analyze interest rate risk in the face of "unpredictable" activity on social media by Trump.[2]

Etymology

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The name "Volfefe" is a portmanteau of the words volatility and covfefe, the latter being a word (widely presumed to be a typographical error) posted in a 2017 tweet by Trump.[3][4][5]

Creation

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Volfefe was launched by JPMorgan Chase on September 9, 2019.[1][3][4]

Methods

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In forming the basis of the methodology behind Volfefe, JPMorgan Chase used software to analyse the corpus of Trump's tweets.[6][7][8] 14,000 tweets were used in the analysis to form the initial projections for their software.[6] Their analysts determined that there were direct correlations between tweets and subsequent market movements.[5][7][8] These market movements were most notably evidenced when the tweet specifically references financial matters including the US Federal Reserve.[2][9] The tweets issued during the working day of the New York Stock Exchange were more likely to cause a change in market sentiment; however, it was noted that the tweets can come at any time of day and thus have an effect on markets around the world.[2][9] Key words in tweets include "China", "billion", "products", "Democrats", "great", "dollars", "tariffs" and "trade".[2][9]

Analysis

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Bloomberg News noted, "JPMorgan’s 'Volfefe Index,' named after Trump’s mysterious covfefe tweet from May 2017, suggests that the president’s electronic musings are having a statistically significant impact on Treasury yields."[1]

ABC News Online commented JP Morgan created Volfefe, "to measure how much impact Mr Trump's unpredictable tweets have on US interest rates".[2]

See also

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References

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