The Perils of Investment Forecasting - Three Things to Consider
PUBLISHED
2022-10-14
Content
Introduction
I am regularly called on to provide forecasts for economic and investment variables like growth, interest rates, currencies and shares. These usually come in the form of point forecasts as to where the variable will be in, say, a year’s time or its rate of return. Such point forecasts are part & parcel of the investment industry. In fact, forecasts – from the environment to economics to politics to coronavirus – have become part of everyday life.
Economic and investment forecasts are useful as a means of communicating a view, as an input to the construction of budgets and as a base case against which to assess risks and formulate economic policy. But relying too much on precise forecasts can be dangerous. This was demonstrated through the pandemic and now with the surge in inflation globally and rise of geopolitical uncertainty, but it’s nothing new.
If forecasting was easy you wouldn’t be reading this...
- Three economists went target shooting. The first missed by a metre to the right, the second missed by a metre to the left and the third exclaimed “we got it!”.
- Economists exist to make weather forecasters & astrologers look good. Maybe epidemiologists fall in there too now.
- An economist is a trained professional paid to guess wrong about the economy.
- An economist will know tomorrow why the things she or he predicted yesterday didn’t happen.
- Economic forecasting is like driving blindfolded with instruction from a person looking out the rear window.
- Economics is the only field in which two people can share a Nobel Prize for saying the complete opposite.
- For every economist there exists an equal and opposite economist.
- Economists have predicted six of the last two recessions.
- There are two classes of forecasters: those who don’t know and those who don’t know they don’t know (J.K. Galbraith).
- Forecasters create the mirage the future is knowable (Peter Bernstein).
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- It ain’t what you don’t know that gets you into trouble. It’s what you know for sure that just ain’t so (Mark Twain).
Hit and miss – particularly around dislocations
Surveys of economic forecasts are regularly compiled and published. It is well known that when the consensus (or average) forecast is compared to the actual outcome, it is often wide of the mark. This is particularly so when there has been a major change in direction (or dislocation) for the variable being forecast – such as around events like the tech wreck in the early 2000s, the GFC and the recent surge in inflation. So just when you rely most on forecasts can be when they get it most wrong. This applies not only to economists’ forecasts for economic variables, but also to share analysts’ forecasts for company profits and to most forecasts across most disciplines. Where precise linear relationships apply - where A = B, eg, in predicting the date and time of the next eclipse – forecasting is easy. But where relationships can be non-linear and complex as in economics, investing and in most things people like to forecast - where a slight shift in the balance can result in A = B or C or ? - forecasting is far more difficult.
And of course, the bigger the call, invariably the bigger the miss.[2] There are numerous examples of gurus using grand economic, demographic or financial theories – usually resulting in forecasts of “new eras” or “great depressions” or with assessments like “too much debt will cause an implosion”, “house or share prices are too high and are guaranteed to crash” or “the Eurozone will break up” – who may get their time in the sun but who also usually spend years before, or after, losing money. For example, the gurus who foresaw a “new era” in the late 1990s – with books like Dow 36,000 – looked crazy in the early 2000's tech wreck. And many of those who did get the tech wreck or GFC “right” were bearish for years before and would have lost their fortune if they had shorted shares when they first got bearish.
Grand prognostications of doom can be particularly alluring, and wrong. Calls that the world is about to bump into some physical limit, causing some sort of “great disruption” (famine, economic catastrophe!), have been made with amusing regularity over the last two hundred years: Thomas Malthus; Paul Ehrlich’s The Population Bomb of 1968; the Club of Rome report on The Limits to Growth in 1972; and the “peak oil" fanatics who have been telling us for decades that global oil production will soon peak and when it does the world will be plunged into chaos. Such Malthusian analyses underestimate resources, the role of price increases in driving change and human ingenuity in facilitating it. (Hopefully, worst case predictions of a “climate catastrophe” will prove wrong for similar reasons!)And when you're reading books like those from Harry S Dent about The Great Depression Ahead (2009), etc, all of which had disaster happening well before now, just recall there has been a long list of prognostications for a great depression, often linked to a debt-related implosion, the bulk of which turned out to be wrong. Amongst my favourites are Ravi Batra’s The Great Depression of 1990 - well, that didn't happen so it was just delayed to The Crash of the Millennium that foresaw an inflationary depression, which didn't happen either. Google “the coming depression” and you’ll find 370 million search results (up from 72.3 million five years ago)!
The psychology of forecasting
Forecasts need to be treated with care for several reasons:
- Forecasters, like everyone, suffer from psychological biases: the tendency to assume the current state of the world will continue; the tendency to look mostly for confirming evidence; the tendency to only slowly adjust forecasts to new information; and excessive confidence in their ability to forecast accurately. As Warren Buffett has said “forecasters usually tell us more of the forecaster than of the future”.
- Point forecasts – eg, that the ASX200 will be 7000 by December 31 - convey no information about risks. They are conditional upon information available when the forecast is made. As new information appears, the forecast should change. Setting an investment strategy for the year based on forecasts at the start of the year and not adjusting for new information is a great way to lose money. This is particularly a problem if you only access forecasts periodically.
- In investment management, what counts is the relative direction of one investment alternative versus others – precisely where they end up is of less consequence in the short term.
- The difficulty in forecasting financial variables is made harder by the need to work out what is already factored into markets. Sometimes the market sets sensible share prices based on economic developments. At other times it is unstable, swinging from euphoria to pessimism. Trying to distil that into a precise forecast is not easy.
In the quest to be right, the danger is that clinging to a forecast will end up losing money. As Ned Davis has pointed out, for investors the key is to make money, not to be right with some forecast.
So why are forecasts treated with such reverence?
What to do? Three things for investors to consider
First, minimise the reliance on expert forecasts - particularly point forecasts and grand prognostications - when undertaking investment decisions. While point forecasts can help communicate a view, the real value in investment experts – the good ones at least – is to provide a better understanding of the issues around investing, a better understanding of what’s going on now and to put things in context so as to help avoid silly investment mistakes. While financial history does not repeat, it does rhyme and so in many cases we have seen a variant of what may be currently concerning the market before. This is particularly important in being able to turn down the noise and focus on a long-term investment strategy to meet your investment goals.
Second, invest for the long term. In the 1970s, Charles Ellis, a US investment professional, observed that for most of us investing is a loser’s game. A loser’s game is where bad play by the loser determines the victor. Amateur tennis is an example where the trick is to avoid stupid mistakes and win by not losing. The best way for most investors to avoid losing at investments is to invest for the long term. Get a long-term plan that suits your level of wealth, age, tolerance of volatility, etc, & stick to it.
Finally, if you are going to actively manage your investments, make sure you have a disciplined process. Ideally, this should rely on a wide range of indicators, such as: valuation measures (ie, whether markets are expensive or cheap); indicators that relate to where we are in the economic and profit cycle; measures of liquidity (or some guide to the flow of funds available to invest); measures of market sentiment (the crowd is often wrong); and technical readings based on historic price patterns. The key to having a disciplined process is to stick to it and let the “weight of indicators” filter the information that swirls around investment markets, so you are not distracted by the day-to-day soap opera engulfing them. Forecasting should not be central to your process. My preference is to focus on key themes as opposed to precise point forecasts.
Conclusion
It is tempting to believe that you or someone else can perfectly forecast the market. Getting markets right is hard enough and even then, there are plenty of investors who have been “right” on some market call but lost a bundle by executing too early or hanging on to it for too long. The key is to know where expert views can be of use, be humble and stick to a long- term investment strategy designed to attain your goals and, if you are going to actively manage your investments, have a disciplined process.
ENDNOTES
- See “Making money versus being right in the loser’s game”, Oliver’s Insights, September 2006 and “The Perils of forecasting and the need for a disciplined investment process”, Oliver’s Insights, May 2017.
- Future Babble by Dan Gardner, Plume, 2011 is an excellent and entertaining read on the issues around forecasting.
Author
Name | Shane Oliver |