ECRI Cries Wolf – Again

The Economic Cycle Research Institute (ECRI) is one of the leaders in business cycle forecasting, but they had one spectacular and very public forecasting failure in the fall of 2011 - when they predicted an imminent U.S. recession. Until that time, ECRI had never missed a recession forecast.  Given ECRI's flawless track record, in early 2012 I decided to override several timely and very profitable buy signals from my systematic equity strategies.  The opportunity cost was significant.

I learned an important lesson from this experience.  It is very difficult to integrate external, proprietary research tools and forecasts into my investment process.  While ECRI's track record was impressive, their proprietary process was opaque.  As a result, I had no way of understanding or evaluating their recession forecast or its implications for my strategies.

This realization led me to develop the Trader Edge recession forecasting models.  These models may or may not be superior to ECRI's framework, but at least I know every input variable and the mechanics behind each of the Trader Edge model forecasts.

As you might expect, I am somewhat biased when it comes to ECRI, but I am disappointed that they never revised their recession forecast, despite data from their own weekly leading indicator series that directly contradicted their earlier recession forecast.

Instead of reevaluating their forecast, they recently published a new report based on nominal GDP growth that purports to support their recession forecast from almost two years earlier.  Unfortunately, using nominal GDP growth (in periods with wildly different inflationary environments) to identify recessionary periods is not a fundamentally sound approach.  This article explores this relationship in more detail.

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S&P 500 Overvalued Based on Price to Sales Ratio

In a recent article "Earnings-Price Divergence Always Followed by Negative Returns," I noted that every extreme divergence (-20% or lower) between year-over-year corporate profits and equity prices in the past 50 plus years was followed by negative year-over-year equity returns.  Unfortunately, the earnings-price divergence dropped to -21.3% during the quarter ended 9/30/2012. While the relationship between extreme earnings-price divergences and negative year-over-year equity returns is compelling, the elevated price-to-sales ratio for the S&P 500 index provides even greater evidence the market is currently overvalued.

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Recession Models Indicate Risk Remained Low in April

The following article updates the diffusion index, recession slack index, aggregate recession model, and aggregate peak-trough model through April 2013.

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Posted in Economic Indicators, Fundamental Analysis, Recession Forecasting Model | Tagged , , , , , , , , | 1 Comment

Warning – The Perils of Annuities

The concept is simple: write a single check to an insurance company and receive monthly income for the rest of your life, even if you live to be 100.  No more worries about market crashes, bursting bubbles, interest rate fluctuations, terrorist attacks, financial contagions, recessions, or even depressions.  It sounds pretty appealing - just cash your monthly checks, play golf, travel, and enjoy your retirement years.  Unfortunately, this fairy tale could not be further from the truth.

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Non-Farm Payroll (NFP) Model Forecast – April 2013

This article presents the Trader Edge aggregate neural network model forecast for the April 2013 non-farm payroll data, which will be released tomorrow morning.

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Posted in Economic Indicators, Fundamental Analysis, NFP Forecasting Model | Tagged , , , | 2 Comments

Q1 2013 GDP Model Forecast Below Consensus Estimate

In January, I introduced a new aggregate neural network model that I developed to forecast the seasonally-adjusted, annualized, real rate of change in U.S. GDP.  The GDP growth rate is only reported quarterly, but the model provides a new rolling 3-month GDP growth rate forecast every month (with a one month lag).  As a result, the model generates more timely information about the growth of the U.S. economy than the quarterly GDP data.  The model framework and the forecast for Q1 2013 GDP (which will be released tomorrow) are explained below.

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GDP Model Forecast Improves in March

In January, I introduced a new aggregate neural network model that I developed to forecast the seasonally-adjusted, annualized, real rate of change in U.S. GDP.  The GDP growth rate is only reported quarterly, but the model provides a new rolling 3-month GDP growth rate forecast every month (with a one month lag).  As a result, the model generates more timely information about the growth of the U.S. economy than the quarterly GDP data.

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Earnings-Price Divergence Always Followed by Negative Returns

I recently wrote about the extreme divergence between earnings and equity prices, but did not have access to comprehensive historical earnings data until recently.  In the article above, I referenced the past few years of earnings data, which was provided by FactSet on their website.  I am not a subscriber, but FactSet does offer free access to recent earnings data in graphical form in their weekly online publications.

While doing some economic research on the St. Louis Federal Reserve site (FRED), I discovered a quarterly data series on after-tax corporate profits that originated in 1947.  The data series is titled "Corporate Profits After Tax with Inventory Valuation Adjustment and Capital Consumption Adjustment."  I have only scratched the surface of the data, but the historical link between corporate profits and equity returns is compelling.

Every extreme divergence (-20% or lower) between year-over-year corporate profits and equity prices in the past 50 plus years was followed by negative year-over-year equity returns.  Every one.  This is especially relevant because this divergence dropped to -21.3% during the quarter ended 9/30/2012.

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Posted in Economic Indicators, Fundamental Analysis, Market Commentary, Market Timing | Tagged , , , , | 5 Comments