Forget Wall St analysis, mine Twitter for trades

Forget Wall St analysis, mine Twitter for trades

Saturday, 5 September 2015
By: JAMES SAFT

INVESTORS might want to put aside all that Wall Street research and instead turn their eyes to Twitter.
A new study by academics at Johns Hopkins University finds that crowd-sourced company earnings estimates and sentiment data generated by tweets may be both more accurate than Wall Street’s offerings and help generate trading profits.
The study examined crowd-sourced earnings estimates gathered by analysis firm Estimize, which allows users to make earnings estimates and then crunches the data, as well as tweet company sentiment data produced by ISentium, a firm specialising in such work.
“It appears that tweet sentiment has power to predict post-earnings risk-adjusted excess returns,” Jim Kyung-Soo Liew, Shenghan Guo, and Tongli Zhang of Johns Hopkins write in the paper.
“There appears to be some indication that a well formulated strategy incorporating both data sets could be an interesting avenue of future research and may lead to annualised excess gross returns in the 10%-20% range.”
This conclusion comes, inevitably, with many caveats, but first let’s look at the findings.
The study, based on earnings announcements between November 2011 to December 2014, used ISentium linguistic analysis data to create a positive or negative tweet sentiment value for companies in the run-up to their earnings release.
So, taking all tweets on a given company, the data was reduced to a number which is intended to give a reading of how positive or downbeat the Twitterverse is towards that firm. They then looked at what happened to company shares after the release of earnings.
For example, shorting stocks with negative tweet sentiment which record a negative earnings surprise generates a bit more than half a per cent of risk-adjusted excess returns in the following five trading days.
That equates to an annual excess return of about 26%, which is huge.
Risk-adjusted excess returns are what a stock generates compared to a portfolio of similar stocks.
Other strategies, such as going “long” stocks with positive sentiment and positive earnings surprises also generate excess returns, though on lower scales.
To be sure, these results are gross of fees. As well, some of these stocks may not be large capitalisation, meaning that they could be hard to borrow for a “short” sale or that a trade could not be done in very large size.
As well, note that the effects here are short term.
The market tends to move on the news but the gains from such a strategy would need to be realised in a matter of days before the effects reverse.
Beat the street
The Estimize earnings estimates are purely crowd sourced, but appear to be better than those Wall Street generates at great expense.
“Over the whole period of our data we find that Estimize’s consensus is 56.4% more accurate than Wall Street’s consensus – similar to earlier findings,” the authors write.
Fewer estimates in the Estimize data “lowball” earnings and more overestimate, something which few Wall Street firms do. This makes the crowd sourced estimate more accurate.
That the crowd can do a better job estimating earnings is not surprising. The financial services industry has a well documented history of underestimating earnings going into announcements.
This may be so that companies can “beat” expectations and please their constituencies.
Some of this is about agency problems, the misaligned incentives of the financial services industry.
In other words, equity analysts are likely not telling you what they really think because they have other interests to advance and protect.
This kind of reliable, metronomic underestimating is unlikely to be solely driven by incompetence. Companies that miss their numbers have a tendency to fire their executives, while companies who exceed them will tend to reward them. An analyst who helps keep executives happy is one who may keep lines of access open and help to smooth the way for investment banking business for her firm.
“Not being overly influenced by the need to gain access and favour from company executives appears to be a reasonable explanation supported by the data,” the authors write.
“Additionally, building relationships over time with conference calls, equity research events, and social gatherings may have led many Wall Street analysts to lose their objectivity when forecasting company’s earnings.”
It remains to be seen if the results of the study can be replicated and the extent to which the strategies it suggests will work in real life.
Some may disappear as they are recognised and arbitraged away, some may simply not be practicable.
That said, it is a great example of a larger trend: the threat that the financial industry faces, across multiple fronts, from disintermediation through technology.
Twitter, and other means of open sourced information, are going to drive down the margins of middlemen in and outside of the financial industry. – Reuters

Forget Wall St analysis, mine Twitter for trades

Forget Wall St analysis, mine Twitter for trades

Forget Wall St analysis, mine Twitter for trades

Forget Wall St analysis, mine Twitter for trades :: Comments