It has been an unusually disruptive year so far for the financial trading industry. From novel revelations about the pip-rigging high frequency trading ‘Flash Boys’, through the annuities bombshell in the UK budget, to the recently reported ‘panic’ in the fund management industry over Facebook and Google’s emerging data mining power to offer innovative financial products, the hits just keep on coming.
 
As Too Big To Fail banks cut their proprietary trading teams, another slow burn disruptive force in 2014 for financial traders might well be the launch of Saxo Markets social trading platform TradingFloor.com. This electronic information bazaar aims to “set free the peer-to-peer power of traders around the globe by enabling them to connect online with experienced and like-minded investors who are tired of input from salespeople from traditional banks.” When coupled with the strength of technically driven instant trading alerts that make sense of the content that gushes from the social data fire hose (Twitter, Instagram, Blogs, Facebook, LinkedIn), social trading platforms will democratise financial trading.
 
If, according to Flash Boys author, Michael Lewis, boxes, lines and logic are the key elements of a successful HFT strategy, a natural language programme configurator, actionable content and community platforms that offer real time human intelligence that give context for open source trading signals are the technology equivalents for successful and profitable social trading platforms.
 
In fact, the quest to build the ultimate NLP configurator which generates actionable open source trading signals has been on for some time and until now was a relatively expensive proposition. As early as 2006, Monitor110 made the front page of the Financial Times as “an aggregator and filter for hedge funds trying to keep up with the explosion of information sources on the Internet.” Back then, this configurator was mainly aimed at making sense of blog posts since Twitter and other social media platforms were nascent at that time.
 
Now however, open source configurator development has gone mainstream, costs have fallen and core functionality can be licensed with everyone from enterprise software companies (SAP and IBM) and the giants of the business information industry (Bloomberg, Reuters, DnB) seeking to give client subscribers a trading edge through technology that makes sense of massive amounts of social data. The recent decision by struggling IBM to open up its game-show-Jeopardy-and-Garry-Kasparov beating Watson configurator to third party developers is potentially transformative for any social trading platform looking to grow its community by providing quality, real time, open source trading alerts. In short, the technology widely available today is now less a barrier to entry to social trading platform provision than the content analysis delivered by the brain power of the platform’s numerous community participants.
 
Naturally, the value of any configurator technology is judged by the quality of the data points that it returns. The world’s biggest hedge fund Bridgewater has been using "everything that is available" online, from social media to real-time Internet prices, to model economic activity in what is effectively real-time. Example of content of interest to Bridgewater includes tweets mentioning the purchase of new vehicles which can be used to estimate, calibrate and lead announcements of car manufacturers’ official figures. In commodities, aggregating social comments from farmers on the ground may also deliver tradable properties in Futures. What used to be gathered and assessed by highly paid travelling analyst teams of fund managers can be teed up for assessment by the crowd sharing thinking of a social trading platform.
 
Eventually, it this wisdom of the self-selecting crowds that use the most attractive of these platforms which will be seen as providing the missing operational piece for monetising open source trading alerts. This is, real time collective human intelligence that give these data points context. This does not mean that social trading platforms will level the playing field but that they will provide more open access to information. Market participants can then either directly trade signals as they arrive if they are confident that they confirm aspects of their own world view, thereby front running other traders who need further confirmation of what they are seeing from the crowd before they take a position. No matter what the risk appetite of individual traders, the powers of emerging social trading platforms to make sense of information flows will transform global markets.

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Like this? See: The 'InfoWorker Bullseye'

Sometimes you have to rethink things as new facts emerge. When the Alibaba IPO was announced (I'm a big fan of Jack Ma!) it seemed like a slam duck investment opportunity that should feature in any portfolio. But since Alibaba's IPO document is likely to reveal a structure closely akin to that of Chinese micro-blogging, Twitter-like, giant Weibo (Alibaba owns 18 percent of Weibo), I am now more wary. Quite openly Weibo’s IPO filing shows that investors will not be able to appoint directors to key operating companies in the ownership chain and the regulations governing the money making ends of the company will naturally be set by the Chinese government. This Bloomberg graphic shows the complex layers between IPO investors and the cash generating entities.

Since this is where these companies make their money I missed this obvious point, hence the rethink. It makes Weibo shares riskier and, although Alibaba is a quantatively different operation, it will still have a convoluted structure out of necessity no doubt (like any national government the Chinese clearly have the right to lay down regulations in their own jurisdiction). 

The bottom line is, if you invest in either of these two IPOs, you are taking a punt on 'trusting the numbers and the managers to do the right thing'. There is little by way of comprehensive regulatory oversight. In short it's more about TRUST than VERIFY!