S&P 500 Overvalued Based on Price to Sales Ratio

Posted on May 23, 2013 by

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

Posted on May 16, 2013 by

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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Warning – The Perils of Annuities

Posted on May 9, 2013 by

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

Posted on May 2, 2013 by

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

Posted on April 25, 2013 by

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

Posted on April 21, 2013 by

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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Posted in Economic Indicators, Fundamental Analysis, GDP Forecasting Model, Market Timing | Tagged , , , , , | Leave a comment