The Physics Of Investing In Expensive Markets: How to Apply Simple Statistical Models

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By: greenbackd

Butler|Philbrick|Gordillo and Associates’ argue in Valuation Based Equity Market Forecasts – Q1 2013 Update that “there is substantial value in applying simple statistical models to discover average estimates of what the future may hold over meaningful investment horizons (10+ years), while acknowledging the wide range of possibilities that exist around these averages.”

Butler|Philbrick|Gordillo use linear regression to examine several variations of the Shiller PE (and other cyclically adjusted PE ratios over periods ranging from one to 30 years), Tobin’s q ratio and Buffett’s total market capitalization-to-gross national product ratio (“TMC/GNP”). They have analyzed the power of each measure to explain inflation-adjusted stock returns including reinvested dividends over subsequent multi-year periods, setting their findings out in the following matrix:

Matrix 1. Explanatory power of valuation/future returns relationships

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Source: Shiller (2013), DShort.com (2013), Chris Turner (2013), World Exchange Forum (2013), Federal Reserve (2013), Butler|Philbrick|Gordillo & Associates (2013).

Butler|Philbrick|Gordillo comment:

Matrix 1. contains a few important observations. Notably, over periods of 10-20 years, the Q ratio, very long-term smoothed PE ratios, and market capitalization / GNP ratios are equally explanatory, with R-Squared ratios around 55%.  The best estimate (perhaps tautologically given the derivation) is derived from the price residuals, which simply quantify how extended prices are above or below their long-term trend.The worst estimates are those derived from trailing 12-month PE ratios (PE1 in Matrix 1 above). Many analysts quote ‘Trailing 12-Months’ or TTM PE ratios for the market as a tool to assess whether markets are cheap or expensive. If you hear an analyst quoting the market’s PE ratio, odds are they are referring to this TTM number. Our analysis slightly modifies this measure by averaging the PE over the prior 12 months rather than using trailing cumulative earnings through the current month, but this change does not substantially alter the results.As it turns out, TTM (or PE1) Price/Earnings ratios offer the least information about subsequent returns relative to all of the other metrics in our sample. As a result, investors should be extremely skeptical of conclusions about market return prospects presented by analysts who justify their forecasts based on trailing 12-month ratios.

Butler|Philbrick|Gordillo note:

Our analysis provides compelling evidence that future returns will be lower when starting valuations are high, and that returns will be higher in periods where starting valuations are low.

So where are we now? Table 1 below from the post provides a snapshot of some of the results from Butler|Philbrick|Gordillo’s analysis. The table shows estimated future returns based on an aggregation of several factor models over some important investment horizons:

Table 1. Factor Based Return Forecasts Over Important Investment Horizons
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Source: Shiller (2013), DShort.com (2013), Chris Turner (2013), World Exchange Forum (2013), Federal Reserve (2013), Butler|Philbrick|Gordillo & Associates (2013)

Butler|Philbrick|Gordillo note that:

You can see from the table that, according to a model that incorporates valuation estimates from 4 distinct domains, and which explains over 80% of historical returns since 1871, stocks are likely to deliver 1% or less in real total returns over the next 5 to 20 years. Yikes.

They conclude:

[T]he physics of investing in expensive markets is that, at some point in the future, perhaps years from now, the market has a very high probability of trading back below current prices; perhaps far below.

The post is a well-researched, and comprehensive analysis of several long-term market-level valuation measures. It is a worthy contribution to the research in this area. Read Valuation Based Equity Market Forecasts – Q1 2013 Update.

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