Practical analysis for investment professionals
04 March 2019

10 Rules for Forecasting

Joachim Klement, CFA, is the author most recently of Geo-Economics: The Interplay between Geopolitics, Economics, and Investments from the CFA Institute Research Foundation.

The nice thing about being an investor is that the forces that drive the markets change all the time. However, there are different “market regimes” in which a major narrative dominates market action.

Over the last 20 years of my career, there have been several ascendant market narratives: technology companies revolutionizing the world, followed by the “jobless recovery” of the early 2000s, and then the “Great Moderation” a few years later. Suddenly in 2007, we all had to become experts in housing and mortgage markets as subprime mortgages blew up the world.

Then it was back to central bankers and such unconventional monetary policy as quantitative easing (QE) and “Operation Twist” that created a “new normal.” Then came the European debt crisis and austerity, which was replaced in recent years by geopolitics and the rise of populism.

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And while I am generally skeptical that individual geopolitical events will have a lasting influence on financial markets, there are clearly circumstances — the US–China trade tensions or Brexit, for example — that can and do have a material influence on investments.

The challenge then is how to forecast these events and their impact. For forecasting rules, the gold standard is described in Dan Gardner and Philip Tetlock’s Superforecasting — a mandatory read for anyone who forecasts. But there are other great resources, including Steve LeVine’s 14 rules.

Personally, I have created my own set of 10 rules that I try to use as guidance when forecasting economic or political events:

1. Data matters.

We humans are drawn to anecdotes and illustrations, but looks can be deceiving. Always base your forecasts on data, not qualitative arguments. Euclid’s Elements was one of the earliest texts on geometry, yet none of its oldest extant fragments include a single drawing.

  1. Torture the data until it confesses, but don’t frame the data to the story. The data-mining trap is easy to fall into.
  2. Start with base rates. The assumption that nothing changes and that an event is as likely in the future as it was in the past is a good starting point, but not the end point. Adjust this base rate with the information you have at the moment.

Tile for Geo-Economics

2. Don’t make extreme forecasts.

Predicting the next financial crisis will make you famous if you do it at the right time. It will cost you money and reputation at all others. Remember that there are only two kinds of forecasts: Lucky and wrong.

3. Reversion to the mean is a powerful force.

In economics as well as politics, extremes cannot survive for long. People trend toward average, and competitive forces in business lead to mean reversion.

4. We are creatures of habit.

If something has worked in the past, people will keep doing it almost forever. This introduces long-lasting trends. Don’t expect them to change quickly even with mean reversion. It is incredible how long a broken system can survive. Just think of Japan.

5. We rarely fall off a cliff.

People often change their habits in the face of a looming catastrophe. But for that behavioral change to occur, the catastrophe must be salient, the outcome certain, and the solution simple.

6. A full stomach does not riot.

Revolutions and uprisings rarely occur among people who are well fed and feel relatively safe. A lack of personal freedom is not enough to spark insurrections, but a lack of food or water or widespread injustice all are. The Tiananmen Square protests in China were triggered by higher food prices. So too was the Arab Spring.

7. The first goal of political and business leaders is to stay in power.

Viewed through that lens, many actions can easily be predicted.

8. The second goal of political and business leaders is to get rich.

Combined with the previous rule, this explains about 90% of all behavior.

9. Remember Occam’s razor.

The simplest explanation is the most likely to be correct. Ignore conspiracy theories.

10. Don’t follow rules blindly.

This applies to these rules as well as all others.

For more from Joachim Klement, CFA, don’t miss Risk Profiling and Tolerance: Insights for the Private Wealth Manager, from the CFA Institute Research Foundation, and sign up for his regular commentary at Klement on Investing.

If you liked this post, don’t forget to subscribe to the Enterprising Investor.

All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer.

Image credit: ©Getty Images/andrewgenn

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About the Author(s)
Joachim Klement, CFA

Joachim Klement, CFA, offers regular commentary at Klement on Investing. Previously, he was CIO at Wellershoff & Partners Ltd., and before that, head of the UBS Wealth Management Strategic Research team and head of equity strategy for UBS Wealth Management. Klement studied mathematics and physics at the Swiss Federal Institute of Technology (ETH), Zurich, Switzerland, and Madrid, Spain, and graduated with a master’s degree in mathematics. In addition, he holds a master’s degree in economics and finance.

7 thoughts on “10 Rules for Forecasting”

  1. I have three rules of forecasting:

    1. If you must forecast, forecast often.

    2. Given ’em a date, or give ’em a number, but never give ’em both.

    3. In the unlikely case that any of your forecasts is ever accurate, no matter how big a fluke it is, never, Never, NEVER let ’em forget it!

    1. Since my post on March 4, 2019, I have added a fourth ‘rule of forecasting’ which I now list as #1:

      “Forecasting may be subject to error, especially if it is related to the future.”


  2. Kirk Cornwell says:

    Processing available information legitimizes a “forecast”, but the nature of supposed “outcomes” may demonstrate that the original inputs were not the most important part of the story. An intelligent, well-considered prediction can be way off the mark when the black swan flies in.

  3. Tony says:

    If i may add one forecasting rules that i live by is that a forecast is as strong as the rationale of the theory behind it. The theory could be an existing theory or original, it doesn’t matter. what matters is if the rationale, behind, stands the test of logic.

  4. Following the herd is a behavioural weakness that is a career winner but doesn’t lead to outperformance. All models have an element of fantasy. Investment science is a new subject that will go through similar disproves as physics “laws” eg the world is flat.

  5. Omid Shahraki says:

    When it comes to forcasting, we can find farm of rules which seasonal farmers planted to be harvested when too late. Such plants are non organic and chemical used accordingly. It is us to bring rules to surface and implant them in economic environment including conditions and constraints. But what if we could put a basis in an architecture manner as a building block and framework applicable to variety of problems without any sort of limitation.

    Breathing, that’s right. How do you feel when your breathing rhythm changes? Do you feel good or bad? Ofcourse it depends on. When exercising, we feel good and energized but in panic, vice versa. In quants manner, both are same. But in qualitative manner they are different.

    Economy is functioning like that. And it could be translated to a cycle with 4 stages. Decline, accumulation, advance and distribution. This is always happening, all the time. It could get fast or slow, accelerated or deceleratied because of many many events behind such behavioural change. This could be considered as a framework to base other forecasting methods on. This is just to show how to develop a framework to be efficient and elegant enough to be used as a basis in different economic conditions with constraints.

    Now the question is how to forecast such events and their impacts on economic cycle concerning our basic framework, not going through complexities, super computing, grid computing, quantum computing, AI and other approaches demanding a lot of resources and energy? Is there a basic, simple, efficient and elegant solution for such problem?

    I think there is. What about you?

    Omid Shahraki

  6. duong trong thang says:

    We humans are drawn to anecdotes and illustrations, but looks can be deceiving. Always base your forecasts on data, not qualitative arguments

    above is rule 1. I dont like it.
    if competition landscape dose not change, we can apply above words. but seldom competition landscape stand still. environment changes because everyting changes and competitors changes.

    there are two kind of changes . changes in competition and changes in environment. these two kind change the future of companies and stock prices. these two kinds of change affect each other.

    if there is no change, we focast on the basis of data only. but if there are no change, we now still use black and white tivi set

    nature of business is competition . we buy a stock mean we open a company. competition is based on strategy , which is qualitative argument. how can we not base our business on qualitative argument.

    I am a person who finish one year of two year MBA and have read some books of CFA. I have many years investing in stocks

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