Monday, 10 September 2007

Yet more evidence on the folly of forecasting, or why we don't need economists!

First a quick comment on the change of colour scheme. Multiple readers have told me that they struggle reading the white font on a background. To make life easier I have switched to this format. Let me know if this is easier on the eye - design never was by strong point!

One of the seven sins of fund management (section III of Behavioural Investing) concerns the folly of forecasting (Chapter 9). This is our obsession with trying to forecast the future. Yet there is an enormous amount of evidence to suggest that we simply can't forecast with any more accuracy than a coin toss (a frequently we perform worse than even chance!).

One of the papers that didn't make it into the Behavioural Investing book (but with hindsight perhaps should have been added in) was on the performance of economists in forecasting recession. In it I pointed that economists are simply hopeless when it comes to forecasting recessions (I could have stopped that sentance before the word recessions).

Their track record is truly appalling. The chart below shows that in recent history (1980 onwards) the consensus of economists has not managed to forecast either of the recessions that have occurred. The data for this charts from the Philly Fed Survey of Professional Forecasters.




In the past I have proposed that simple quant models often have the edge of human judgement (see Chapter 22 of Behavioural Investing). Some new research by the San Francisco Fed shows that my supposition that economists would be no different than many other fields in finding their subjective forecasts outperform by a simple model was correct.

In a new paper Glen Rudebusch and John Williams show that a simple model based on the slope of the yield curve has significantly outperformed economists in forecasting recessions. They show that even if we use the economists own probability of recession estimate (rather than their spot forecast), the simple model wins hands down.

The chart below shows the so called anxious index, which is the economists stated probability of recession over the next four quarters. As Rudebusch and Williams state "Even at a horizon of two quarters, and certainly at three and four quarters ahead, the probability forecasts appear to have little relationship with historical recessions."

Compare these economists probabilities with the probability of a recession from a two variable model (using the level of short rates and the slop of the yield curve). The economists say their is currently a 19% chance of a recession in the next 4 quarters, the simple model says it is closer to a 30% probability.



Of course, economists have been aware of such simple models for many years. But this begs the question why they don't use/follow them? My own answer is overconfidence. This seems to be supported by the Rudebusch and Williams paper which concludes "It is interesting to note that many times during the past twenty years forecasters have acknowledged the formidable past performance of the yield curve in predicting expansions and recessions but argued that this past performance did not apply in the current situation. That is, signals from the yield curve have often been dismissed because of supposed changes in the economy or special factors in‡uencing interest rates. This paper, however, shows that the relative predictive power of the yield curve does not appear to have diminished much, if at all. "

Yet another example of just how poor forecasting really is. We need to find a better way to invest than relying upon our disproven and discredited forecasting abilities.

112 comments:

Anonymous said...

James: Thanks for the template change. It is indeed much easier on the eye, and one can concentrate on the content much better.

Steve said...

I agree, this is much easier to read than before. On predicting recessions I guess you know the paper by Jonathan Wright of the Fed which looks at the yield curve (10y - 3 mth) PLUS level of Fed Funds which has not failed as an indicator.

josh reich said...

(Apologies for placing this comment here, rather than via email - but I couldn't locate your email address)

I recently started reading Behavioural finance (Jan 2006 ed.) and I simply must comment on your use of tables and figures. They tend to distract rather that illuminate - causing the reader to interrupt their flow to take time to interpret what is being illustrated; often when the text alone makes the point crystal clear. As a text, the book is a great read, but the charts make the experience painful.

I may be somewhat of a chart fusspot, but there are few basic rules that would go a long way in helping your readers. Essentially, charts and tables should be free standing. I should be able to look at a chart and at the very least understand what is being plotted, if not the deeper point being made.

For this to happen all charts should have their axes labeled. Take Figure 1.12 "Stock brokers' loss aversion". As with many of your charts, the title speaks to the point you are trying to make, rather than what is being charted. This is acceptable if the axes are labeled. In this case I assume your are presenting a histogram where the horizontal axis is Pounds and the vertical axis is number of respondents.

Even after I work out what you are plotting, the chart still proves a mystery. The value labels on the 'Pound' axis are terrible. You (or your editor) has chosen a completely arbitrary scale. The equally spaced tick marks read: 50, 100, 101, 110, 150... This is neither linear nor logarithmic and thus the reader has absolutely no way of interpreting the unlabeled bars.

There are also a number of issues with your use of whitespace, but I will not comment too much on this apart from referring you to the works of Edward Tufte.

While I restrict these specific comments to your figures, your tables could also be spruced up. Again, in chapter 1, tables 1.6 and 1.7 could be greatly clarified. The use of row and column labels would present the data in a less cluttered fashion allowing the reader to see the impact of the data without having to do more than glance at text. In this case, column labels of Low/High and row labels of Accruals/Cash Flow would leave the body of the table much cleaner.

Please don't take this the wrong way. The book is clearly an outstanding text on the subject, but I feel that you make the assumption that all readers are purely linear and rational when they read, whereas the human eye has behavioural quirks of its own - a fact patently ignored by the creators of Microsoft Excel. As such some information presentation heuristics can go a long way.

Eddie Bravo said...

If further proof that making predictions about the future is very difficult look at this interesting blog. Nothing to do with financial predictions, instead it looks at general political predictions and sees how often they miss the mark, fascinating reading...
http://paleo-future.blogspot.com/

Anonymous said...

Steve, that yield curve graph does look like it's based on the Wright model.
RB

Anonymous said...

Look at the last chart here -- based on the Wright model -- looks to be the same as the one on this post.
http://www.incrediblecharts.com/free/trading_diary/trading_diary.htm

RB

Anonymous said...

Truncated link, sorry:

http://fon.gs/twiggsmodel

RB

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