Stocks as overvalued now as at 2007 high - By Mark Hulbert

Here’s yet another reason to be worried about the stock market: A valuation model with an impressive record says that stocks are as overvalued today as they were at the 2007 stock market peak.

The model comes from Dan Seiver, a member of the economics faculty at Cal Poly State University. Seiver also is editor of an investment advisory service named The PAD System Report. Though Seiver created the model nearly 30 years ago, he recently co-authored an academic study of the model’s effectiveness that appears in the current issue of the Journal of Wealth Management.

Seiver’s model is based on a single number that is published each week in the famed Value Line Investment Survey, published by Value Line, Inc. The number represents the median of the projections made by Value Line’s analysts of where the 1,700 widely followed stocks they closely monitor will be trading in three to five years’ time. Followers refer to this number as the VLMAP, which stands for Value Line’s Median Appreciation Potential.

The model Seiver devised using VLMAP considers the risk-reward ratio for stocks to be attractive enough to warrant investing new money in the market only when it rises to at least 100. When it drops to 55, in contrast, it’s time to begin building up cash.

The VLMAP recently dropped to just 35%. The last time it was this low was in July 2007. At the top bull market in October of that year, it stood at 40%.

As Seiver recently pointed out to his clients, the VLMAP’s current level “puts it in the worst 5% of all readings since 1966. In the past, a level as low as this has preceded months or years of poor stock returns. We doubt this time will be different.”

To be sure, Seiver’s model is not a short-term market-timing tool. As he pointed out the last time I wrote a column about it, “the stock market can continue to rise for months, if not years, after a sell reading.” Indeed, as documented in his Journal of Wealth Management study, it’s over a four-year horizon that the model has impressive forecasting powers.