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Home / Opinion / Columns /  It's tough making forecasts in an uncertain world

It’s that time of the year when forecasts of how different investment asset classes are likely to perform during the year are made. Market insiders, as usual, are positive.

Real estate prices are expected to go up, as per owners of real estate companies and consultants, brokers and analysts. Stock prices are expected to go up, if one is ready to believe fund managers of mutual funds and analysts at stock brokerages, as well as big individual investors. Cryptos are also expected to do well, as per managers of crypto exchanges. Further, the economy is expected to do well, if one believes the economists who work for corporates, stock brokerages and the government. Being positive is part of being an insider in the business of managing what economist John Kay calls OPM or ‘other people’s money’. If any investment asset class does well, the insiders benefit.

As Charles Kindleberger writes in Manias, Panics and Crashes: “The purchases of [financial] securities or real estate by ‘outsiders’ means that the insiders—those who owned or purchased these assets earlier—sell the same securities and real estate and take some profits." So, insiders need to be perpetually positive.

This is not to say that their forecasts are always wrong. They aren’t. But even a broken clock is right twice a day, and the trend can be a friend.

Predicting the economic and financial future is a tricky business. As John Galbraith writes in The Economics of Innocent Fraud: “There are more than ample predictions but no firm knowledge. All contend with a diverse combination of uncertain government action, unknown corporate and individual behaviour… There is the variable effect of exports, imports, capital movements and corporate, public and government reaction thereto."

This led Galbraith to conclude that the combined result of what is unknown cannot be known and this was true both for the economy and for specific industries or firms.

What makes forecasting harder is the fact that our beliefs about the system influence the way the system behaves. This is the theory of reflexivity put forward by the philosopher Karl Popper.

John Kay and Mervyn King explain this through an example in Radical Uncertainty: “The collapse of Lehman Brothers on 15 September 2008 could not have been widely predicted because if it had been it would not have happened on that date. Either the bank would have collapsed earlier, or the regulators or Lehman itself would have taken steps to avoid... the event."

Hedge fund manager George Soros puts it in a slightly different way in The New Paradigm for Financial Markets: “The crux of the theory of reflexivity… asserts that market prices can influence the fundamentals."

Take the case of a company on which analysts are bullish and its stock price goes up. Its management, wanting to cash in on the good times, ends up borrowing a lot of money. Banks are happy to lend under the prevailing spirit of good times. Nonetheless, the company turns out to lack execution skills and government permissions are slow to come by. Pretty soon, it will find it difficult to repay the loan.

If this sounds familiar, then it shouldn’t come as a surprise because this is how the bad loans crisis, which Indian banks have been struggling with over the last decade, essentially emanated and became systemic.

Further, it makes sense for those in the forecasting business to go with the herd or what Galbraith refers to as a shared error. As Kay and King explain: “It is often the case that decisions are made on the basis of what is easiest to justify rather than what is the right thing to do. ‘No one ever got fired for buying IBM’ was for long a mantra among mid-ranking executives, and a crucial factor in the success of that company’s technically unremarkable PC." Similarly, no analyst ever got fired for being wrong when most others were also wrong.

Of course, all this doesn’t stop people employed in the business of forecasting from making confident and very specific forecasts, instead of giving ranges and building in enough ifs and buts. Take the case of stock prices. They generally tend to go up. But they can also remain flat for a few years at a time. This disclaimer is rarely made.

Let’s consider economic growth forecasts for the current financial year. Almost no forecast built in the possibility of a new covid strain hitting the world. While no one could have known this exactly in advance, but looking at the history of pandemics, economists should at least have considered this possibility and provided a range, instead of a specific growth forecast right down to one decimal point.

It isn’t fair to blame only those in the business of forecasting, because ultimately they are catering to an audience. As Galbraith puts it: “What is predicted is what others wish to hear and what they wish to profit… from. Thus in the financial markets we celebrate, even welcome essential error... Past accidental success and an ample display of charts, equations and self-confidence affirm depth of perception." And so things go, as people look for certainty in what is a volatile, uncertain, complex and ambiguous world.

Vivek Kaul is the author of ‘Bad Money’.

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