Opening Cross: Consumer Power, Or the Power of Consumer Data?

But there has always been a fine line between the retail and institutional markets—which has become even finer in recent years as the dual trends of “consumerization” of institutional technology and “institutionalization” of retail consumption devices have blurred the lines even more between the two. While some say the markets are rigged, no one can deny that retail investors have greater access to the financial markets, and are closer to the action than ever before.

So it’s no surprise that institutions are looking to the opinions of retail investors when creating new datasets. We’ve seen how traders have tried to leverage social media as a leading indicator, tapping into its stream-of-consciousness in search of comments about stocks, companies or macroeconomic and geopolitical events.

Nor is it any surprise to read that researchers at Warwick Business School and Boston University have determined that increases in certain business- and politics-related terms and phrases searched for on Google can predict falls in the stock market. And I won’t be at all surprised when I hear that some quant has found a way to apply this to all types of market movements, by capturing a firehose of search results, analyzing it to get a picture of what investors are thinking of trading, and using that insight to corner a market ahead of predicted demand, or to be able to deliver improved customer service by offering clients something at the very moment they realize they want it.

Of course, this isn’t a new concept to IMD readers: As well as covering vendors that provide social media and sentiment data as leading indicators, such as Social Market Analytics or RavenPack, we’ve also covered companies such as Estimize, which creates consensus earnings estimates and other metrics crowdsourced from both retail and professional investors—sometimes more accurately than the established Wall Street consensus. Luck? If so, then the model won’t last long. Yet, if anything, more vendors are exploring this space. Another example covered recently in IMD is Nous, a startup provider of a mobile trading game that offers monetary incentives for users to contribute price predictions—which Nous then aggregates and provides to users for comparison, as well as to institutional investors to give them insight into the psychology of ordinary investors.

And this week we feature StockViews, a startup investment platform that allows retail users to rate and recommend stocks. Like Nous, the company is planning to sell its content to institutional investors, and once it does so, will incentivize users by paying the top participants.

And is it any wonder that retail investors are being given more of a say in the assessment of financial instruments? After all, the result is perhaps the best representation of the price that the market will bear. It is, if you will, merely a much broader version of the model of polling institutional market participants used by vendors such as Markit and Credit Market Analysis. Typically, the larger and broader your sample, the more accurate the results.

The investing public has traditionally been told what something is worth, or what quality it is, or where and when you can buy it. Now, not only are those traditional inputs being questioned, but we live in the age of companies like Priceline and Progressive Insurance, where consumers get to name their own price, driving the rise of app stores, on-demand models and pay-as-you-go pricing. Ultimately, institutions’ interest in retail traders’ activity is to make money from them—either by serving them better or by taking advantage of them. But at the same time, these other forces mean that investors can also take some advantage of them.