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Don’t ignore the tweets from the hill

Ignore social media messages from politicians at your peril, says Roberto Gomez Cram

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In 30 seconds:

  • New research shows that the social media output of members of Congress affects asset prices in both directions, up and down
  • Regardless whether financial services professionals are monitoring Congressional tweets, prices move in the wake of them
  • This shows that investors or traders believe such communications contain new and valuable information
  • Findings show the tone of politicians’ viewpoints strongly predicts subsequent surprises in terms of sales and earnings.

Wall Street may not monitor the Twitter accounts of US lawmakers, but it ought to. Our research shows that the social media output of members of Congress affects asset prices in both directions, up and down.

This applies both to individual companies and to the stock of firms in the same line of business. Supportive tweets from Senators and Representatives lift stock prices in the minutes following the tweet, while critical ones decrease prices. The price response lasts for several days, during which time analysts modify forecasts of the cash flows of the business in question.

Put another way, whether or not financial services professionals are monitoring Congressional tweets, someone is, and they clearly believe that social media output is a rich source of political news. A closer look is highly revealing.

Here is one example. Senator Ron Wyden of Oregon, the leading Democrat on the Senate Finance Committee, tweeted at 12.01 pm on October 24 2019: “@SenWarren and I are demanding the FTC [Federal Trade Commission] investigate whether Amazon’s reckless treatment of Americans’ personal data broke the law.” This referred to concerns that Amazon neglected security warnings regarding its cloud computing system.

Within minutes of the tweet, Amazon’s stock dropped by 33 basis points.

Time lag

Our high-frequency approach looks at price changes in a narrow time frame to screen out possible other influences on the asset in question. But this may not fully measure the effects of the tweet on the price, so we also looked at daily share-price data.

Here, we found that the effect is about six times larger. Our conclusion is that, while prices react within minutes of the tweet, it takes several days for the information disclosed by the viewpoints of politicians to be incorporated into stock values.

This begs the question what sort of information can be contained in the brevity of a tweet. It is not as if deep corporate analysis is likely to be transmitted via Twitter – but that is to look at the issue back to front. The fact that prices have moved in the wake of each tweet tells us that investors or traders believe such communications to contain new and valuable information.

The response of stock prices to the tweets is related to revised expectations concerning the cash flows of the company in question. Our finding is that the tone of the politicians’ viewpoints strongly predicts subsequent surprises in terms of sales and earnings.

Perhaps unsurprisingly, analysts use the tone of these political opinions to revise their forecasts in the week following the tweet. Thus, we can see, again, that such communications are seen to contain valuable information.

Such information is at its most pertinent when the tweets target a specific firm and are related to legislation. In terms of proposed laws, such tweets can be identified from their hashtags.

To take one example, the Twitter traffic related to President Donald Trump’s Tax Cuts and Jobs Act 2017 was clearly labelled on both sides of the political divide. Republican lawmakers’ hashtags include #TaxReform, #TaxCutsandJobs Act and #Tax Cuts when tweeting in support of the legislation, while Democrats responded with #GOPTaxScam and #TrumpCut when tweeting in opposition to the Bill.

Tweets targeting a single firm and not related to legislative news tend to affect only the stock price of that firm; whereas legislative and fiscal proposals rarely impact just one business, thus stock prices in the same industry or sector as the firm in question are similarly affected.

Not all tweets are equally valuable in informational terms, because not all Twitter users are equally influential and because timing is key. For tweets related to legislation, we find that the estimated effects on share prices are enhanced when the tweet comes from a committee chair or someone who is likely to vote independently of the party line. In the latter case, the tweet may signal a shift in the Congressional arithmetic that, in turn, may make a big difference if a vote is expected to be tight.

Partisan patterns

Such enhancement is seen also when the tweet links a hashtag that has appeared for the first time and is associated with significant user-generated activity.

We set out different political viewpoints on a timeline and selected tweets in order to capture Congressional opinions in real time, closely tracking the legislative process. Tweets targeting firms in relation to a particular bill highlight the precise information regarding any proposed policy change, thus identifying the effect of a “policy shock”, such as an abrupt change in legislative direction.

The example we have chosen is the Crapo Bill, which passed into law as the Economic Growth, Regulatory Reform and Consumer Protection Act.

This Bill aimed to ease some of the restrictions imposed in the wake of the 2007-2008 financial crisis and subsequent Great Recession by the Dodd-Frank Act, named after its sponsors, Senator Christopher Dodd and Member of the House of Representatives Barney Frank.

The Act was signed into law in 2010 and, as the identities of the sponsors suggest, enjoyed a measure of bipartisan support. The Crapo Bill, by contrast, was introduced in the much more partisan atmosphere of the 2017-2021 Trump presidency – a much more social-media-aware era than was the case just a few years earlier.

‘Those who do not listen to the social-media pronouncements of Senators and Representatives are ignoring a valuable source of information’

Tweet tone as vote predictor

The Bill’s broad rationale was that Dodd-Frank risked hobbling American banks in relation to their foreign competitors. Two pillars of the Crapo Bill were to raise the threshold in terms of assets which made banks subject to extra-stringent regulation, and to repeal an aspect of the so-called Volcker Rule, named after former Federal Reserve chair Paul Volcker.

The first pillar raised the threshold from $50 billion in assets to $250 billion. Dodd-Frank had intended to prevent a repeat of the “too-big-to-fail” phenomenon of the financial crisis, whereby banks that some believed had behaved recklessly had to be bailed out, but banks complained that the Act’s regulatory burdens were too onerous.

The second pillar exempted banks with less than $10 billion in assets from the bans imposed by the Volcker Rule on engaging in certain investment activities and in dealing with hedge funds and private-equity operators. The Bill was supported by the Trump White House and broadly opposed by Democratic lawmakers.

Given that it was favourable for the banking industry, we looked at share-price reactions in this sector to Congressional tweets concerning the legislation and noted strong price increases for bank shares in response to supportive tweets from Republicans in Congress and the opposite reaction to Democrat tweets criticising the Bill. We also found that the tone of the tweets in each case strongly predicted the actual voting behaviour of the politician in question. President Trump signed the bill into law in May 2018.

Quantifying significance

To put our conclusions to the test, we constructed a long/short portfolio strategy that used Congressional tweets as trading signals. Not only did this seek to support our analysis of the importance of such tweets, it also sought to quantify the economic significance of our findings.

Our strategy bought the stock of targeted firms when a politician tweeted supportively and sold the stock when a politician was critical. Where a firm was targeted by more than one politician, we computed a daily average tone and used this mean opinion as our trading signal.

A value-weighted portfolio was constructed at the end of each day and was rebalanced daily. Our strategy earned mean returns of 22 basis points a day, underlining our view that Congressional tweets contain valuable information.

To conclude where we began, there are people in the financial services industry who are listening to the social-media pronouncements of Senators and Representatives. Those who do not are ignoring a valuable and potentially profitable source of information.

Roberto Gomez Cram is Assistant Professor of Finance at London Business School

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