Time of the contrarian

Braced for bursts of profit-booking, they might do better than traders

A start-up recently seeded the Internet with some blatantly fake news. It created a website and bought a URL similar to a well-known American media site. On the fake website, it claimed Azim Premji had invested a huge sum in it.

The business model: The start-up would collect and analyse social media posts about listed corporates to see if the comments were ‘net-positive’ or ‘net-negative’ for specific companies. It would trade long on corporates with net-positive posts, and trade short on corporates with net-negative posts. It claimed it did this with 87 per cent success.  Subscribers were asked to pay $1,000 a year for access to the analytics and advice.  

Using Premji’s name is criminal and the business model looks like a scam. The numbers are absurd. But, the underlying idea is interesting to explore. Let’s see what’s feasible and what’s flawed. 

It’s easy to set up bots to trawl Facebook, Google, Twitter, YouTube, etc, for posts on listed corporates. It doesn’t require much tech-savvy to sort such posts to assign positive/negative ratings and sum up for net-negative or net-positive. But, betting on either net-positive or net-negative is unlikely to work more often than 50 per cent of the time. This is especially true in a developed, efficient market (the start-up is US-focused). 

Let’s say many small traders dislike a given company and make loud “net-negative” noises. But, one “whale” — a large investment house or a large individual investor — likes that company and buys it with zero fanfare.  Each small trader can sell a lot or two. The big guy can buy hundreds, or thousands of lots.

On the other hand, dozens of small traders might like a company but a bearish whale could sell volumes that they cannot absorb.  We are talking short-term trades. The crowd may be right. In that case, the whale will lose money in the long term. But, the traders who backed a net-negative/ net-positive formula will lose money instantly and due to exigencies of leverage, they will be forced to cut their losses. 

 The wisdom of crowds is a cliche but so is the “madness of crowds”. When somebody expresses an opinion about some business, the credibility of that commentator is often pertinent. One commentator with expertise may count for more than a number of ignorant people. 

Going against the crowd is emotionally difficult but necessary in bubble or panic situations. The sensible person is in a minority. In a bubble, the crowd drives prices much higher than the fundamentals warrant. In a panic, people sell, pushing prices well below intrinsic values. 

More generally, this “net negative/positive” algorithm will break down across the spectrum of efficient and inefficient markets. In an inefficient market, favoured entities receive sensitive news early and these parties will trade before there’s social media commentary. In an efficient market, everybody receives price-sensitive news at about the same time. But, the short-term price trends are random. The commentary on social media will again make no difference. 

Long-term investors seem to do best when they identify good businesses and buy at reasonable valuations. It isn’t glamorous doing this but works well.  In contrast, traders can make or lose vast amounts quickly by using leverage.  But, the most successful trading methods assume any selection criteria is, at best, marginally better than a coin-toss. The key to being a successful trader is managing money. Good trading systems focus on cutting losses early and letting profits run for maximal gain. 

The internet and its forums have been used to discuss stock trading ever since the web’s inception. Social media just adds another dimension. But, this is not new. Information and opinions about stocks have always been available. Traders and investors must develop their own methods to judge their quality and credibility. 

The market is now at record highs (both in the US and in India). Many stocks are at record highs as well. Social media seems to be overwhelmingly bullish. When everyone is bullish, many of them are also fully invested — they have no cash to spare. The demand for shares often falls in such situations and eventually the prices also fall. Contrarians braced for bursts of profit-booking might do better than traders who run with the herd.