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Is Financial Analysis Doomed in Twitter Era?
Inspired by Trump's tweets, UC Davis MBA grad partners on published study on stock market disruption

Early on a Monday morning in 2016, Donald Trump took to Twitter.

Trump tweetThe then-presidential candidate fired off a 140-character missile that sank Lockheed Martin’s stock market value by $4 billion, only to bounce back by the closing bell, as market movers determined that nothing substantive had actually changed with the company to affect its equity value.

Shares of other big defense contractors Boeing and General Dynamics also dipped.

It is “a very archaic view of the world,” says Mohammedi Padaria MBA 17 of the traditional financial analysis model used to value companies. He says the standard valuation model doesn’t keep up with the speed that news travels today:  A tweet from a president, a political candidate or an off-handed remark by a CEO can have a dramatic and immediate impact on high-frequency, low-cost trading.

“The financial industry as a whole is still very much dealing with this new paradigm shift,” says Padaria. “The information flow, in as simple as 140 characters, can have tremendous impacts in the short-term—and potentially long-term—on how we see or value a company.”

Following Trump’s tweets, CNBC called it “the new reality for American businesses.”  

The Birth of “Reactive Valuation”

Drawing on a 20-year career at the LexisNexis research database, where he is now the vice president of business process and systems, Padaria coined a new term for this: “Reactive Valuation.” His phrase describes the type of “ultra-short-term” financial analysis—from a few seconds to a few hours—that is based on unverified information from social media posts or influential commentators.

As a student in the Sacramento MBA program, Padaria had the opportunity to study this phenomenon with his advisor, Accounting Professor Paul Griffin. Their research, “Is Financial Analysis Doomed? The Birth of ‘Reactive Valuation’ Analysis,” was recently published in the journal Accounting and Finance Research.

“I’m an engineer that did an MBA and has a computer science degree,” he says. “I thought I would never have anything published.”

Robots and Artificial Intelligence

Padaria and Griffin contend that traditional financial analysis, rooted in Depression Era economics, has been all but “swept away by the inexorable forces of change cast upon it by robots, Big Data, and artificial intelligence. The financial world is now cluttered with Twitter posts, instant media blogs, direct regulator feeds, and ‘robo’ news reports.” This impacts trillions of dollars in asset management, which is “the largest single industry in modern society.”

It’s also costing jobs on Wall Street and global investment banks, which are paring down their staffs of traditional analysts who report on company fundamentals, according to recent commentary in Financial Times.

The chaos can only be managed but never fully contained, Padaria and Griffin predict. Those who survive and master the tools of artificial intelligence and natural language processing will “greatly transform the field of financial analysis and valuation.”

For Padaria, this opens up a goldmine of potential research for scholars. “It would be earth shattering,” says Padaria. “The existing model has been around, well, too long. To go in and even tweak it a little would go a long way in how we see valuations happen.”