Recession Models and the Fiscal Cliff

Last week I introduced two new probit models to forecast recessions and the period between the market’s peak and trough associated with each recession – as defined by the National Bureau of Economic Research (NBER). In response to that article, a reader posed a timely and insightful question:

“According to the Congressional Budget Office the probability of a near term recession is directly related to the outcome of the current sequestration problem. Would the probit model address that kind of circumstance?”

While I responded to the reader’s question in the comment section of the post, I felt the question was important enough to warrant a stand-alone post.  Probit models are valuable tools, but all forecasting models are limited when faced with discrete, exogenous events.

Probit Model Limitations

The beginning and end of NBER recessions are defined (after the fact) by the trends in the economic data, which should be captured by the probit recession model.

However, if the recession were triggered by an instantaneous rise in taxes and a discrete drop in spending (the fiscal cliff), it would be very difficult if not impossible for the peak-trough probit model to provide any advance warning of the market decline.

A failure to resolve the fiscal cliff would greatly accelerate the normal cyclical transition from expansion to contraction, which would compromise the performance of the peak-trough model and reduce the value of the recession model.

Nevertheless, if the recession were long and severe (which it could be given the fragile state of the global economy), both models should still provide some downside protection. They would also be useful in timing the end of the recession, regardless of the cause.

Unfortunately, forecasting models in general cannot deal with external shocks that are not directly captured by the data. This includes terrorist attacks, conflict in the Middle East, political disruptions, exits from the Euro, country defaults, etc.

In addition, as I mentioned in the previous article, “given the precarious state of the global economy, if a U.S. recession were to occur, it could come on quickly and it could be severe.” Failure to resolve the fiscal cliff would only accelerate that process, making it even more challenging for the models.

I should have explained this issue more fully. The reader’s question illustrates the significant limitations of all forecasting models when faced with discrete, exogenous events – and the probit models are no exception.

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Brian Johnson

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About Brian Johnson

I have been an investment professional for over 30 years. I worked as a fixed income portfolio manager, personally managing over $13 billion in assets for institutional clients. I was also the President of a financial consulting and software development firm, developing artificial intelligence based forecasting and risk management systems for institutional investment managers. I am now a full-time proprietary trader in options, futures, stocks, and ETFs using both algorithmic and discretionary trading strategies. In addition to my professional investment experience, I designed and taught courses in financial derivatives for both MBA and undergraduate business programs on a part-time basis for a number of years.
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