What Are Other Investors Thinking? If You Knew, Would That Be A Great Benefit To You?
The first iPhone was launched on June 29, 2007, and the world has never been the same since. The speed and convenience with which we now communicate created the new levels of urgency, including the urgency to understand and participate in further unbridled innovation. Since the launch of the iPhone, many companies have adopted the so-called Digital One company strategy with the idea to integrate social media, mobile technology, fast analytics and cloud data storage.
Social media alone creates change and not just because of all the new tools connecting billions of individuals worldwide. People use social networks to gain immediate access to information that is important to them. The increased independence that people feel when they can access their networks whenever and wherever they want makes these networks a treasured part of the way someone spends their day.
For investors, the social media may mean wide access to a variety of information on the go. On the train and feel like learning the business model of some obscure public company? Not an issue. At the airport, but thought of investing into a specific municipal bond and need more information on the jurisdiction? Here it is. A successful FinTech business has a social network that reaches investors both proactively and responsively. By offering a social experience, the business can offer traditional services in a setting that is consistent with the social networks way of navigating. Analyzing a customer’s use of the social network allows a company to respond to customers in a tailored fashion offering messages and ideas that are consistent with what the customer wants.
The implications of social media, however, go far beyond the communication and customer service experience a business can have with prospects and clients. Unlike news, social media is a powerful user-generated forum where ideas collide, opinions are formed and beliefs are floated, often completely under the radar of traditional media. The opinion-volunteering participants often join in anonymously, concealing their identity in a degree of masquerade where they feel comfortable to disclose their thoughts honestly and passionately. The same degree of honesty is often impossible in our politically-correct daily interactions, even with the nearest friends behind closed doors. The chatroom-formed opinions then often trickle into the stock markets as people trade on their beliefs, putting their money where their mouths are.
Harvesting and interpreting social media content has thus been a boon for a range of financial businesses. Machine-collected sentiment on specific stocks has been shown to predict intraday volatility and future returns. The AbleMarkets Internet Chatter index, for example, has consistently predicted short-term volatility over the past six years, and is used by investors, execution traders and risk management professionals.
Is all social media content created equal? As you have guessed it, this is very far from being the case. With the proliferation of automatic social media tools, for instance, a lot of the content comprises “reposts” and “retweets” of information found elsewhere. This duplication of materials sometimes is worthwhile and reflects the copying party’s agreement or endorsement of the original content. In many instances, however, duplicate content appears to be streamed simply to fill the informational void of a given social media participant’s stream.
Another social media hazard is fake news. Those may come in the form of individuals’ posts or, much worse, via fraudulent posts on hijacked accounts of other users. A classic in the latter category was a Twitter post on the Associated Press account informing followers of an explosion at the White House.
Separating the wheat from the chaff in the social media space is not a job for dilettantes, and requires advanced machine learning algorithms. In today’s market environment, where the profit margins are thin and every bit of information is valuable, correct inferences are critical and experience in dealing with various circumstances is worth a lot.
Steve Krawciw [kro:sew] is a CEO of AbleMarkets.com, a leader in market microstructure analytics. Prior to AbleMarkets, Steve was building products for Credit Suisse wealth management, CIBC wealth management and, prior to that, helped Fortune 500 companies through consulting at McKinsey and Monitor Companies. Steve holds an MBA from Wharton and a BComm from University of Calgary. Email Steve at firstname.lastname@example.org