Economic Indicators

A reader, citing the book Ahead of the Curve by Joseph Ellis, inquired about the hypothesis that consumer spending drives economic cycles and is therefore a leading indicator for the stock market. For example, Mr. Ellis presents a chart showing annual change in Personal Consumption Expenditures (PCE) and annual change in S&P 500 operating earnings based on quarterly data. The chart also shows bear markets for U.S. stocks. The chart discussion states: “Most bear markets begin…when the Y/Y [year-over-year] rate of growth in consumer spending is peaking… Most bear markets then proceed as (the rate of growth in) consumer spending continues to slow, and are largely over by the time recessions…are under way. Importantly, most bear markets end…when consumer spending and S&P 500 profits are at, or even prior to, their worst Y/Y comparisons.” Does PCE usefully predict stock market behavior? The Bureau of Economic Analysis (BEA) releases seasonally adjusted, annualized total PCE monthly with a lag of about one month (Summary Table 2.85, Line 1: “Personal Income and Its Disposition, Monthly”). Using this series and monthly S&P 500 Index levels for January 1959 through August 2015 (680 months), we find that…

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Does the ratio of aggregate U.S. stock market valuation (MV) to U.S. Gross National Product (GNP) or Gross Domestic Product (GDP), the approximate value of goods and services produced by U.S. companies, reliably indicate stock market overvaluation? In their July 2015 paper entitled “Can Warren Buffett Also Predict Equity Market Downturns?”, Sebastien Lleo and William Ziemba investigate whether MV/GNP accurately predicts peak-to-trough declines of more than 10% in daily closes of the S&P 500 Total Return Index within a year. They consider: (1) a simple static model based on a 120% overvaluation threshold; and, (2) two dynamic statistical confidence models based on mean and standard deviation during a four-quarter rolling historical window. They consider both MV/GNP and the logarithm of MV/GNP (relating variable changes) as predictive variables. Using quarterly, seasonally-adjusted GNP and Wilshire 5000 Full Capitalization Price Index level as a proxy for MV (the limiting series) and daily level of the S&P 500 Total Return Index from the fourth quarter of 1970 through the first quarter of 2015 (177 quarters), they find that: Keep Reading

In the introduction to their 2015 book entitled Invest with the Fed: Maximizing Portfolio Performance by Following Federal Reserve Policy, authors Robert Johnson, Gerald Jensen and Luis Garcia-Feijoo state: “Our purpose in writing this book is to provide a general overview of the Fed’s role in the financial markets, but, more important, to offer investors a road map that can be used in designing an investment portfolio that takes account of Fed policy. In detailing our road map for investors, we offer a rationale for each investment strategy along with empirical evidence supporting the efficacy of the strategy. Most important, the recommended strategies come with clear explanations and easy-to-follow descriptions of the processes needed to execute the strategies.” The essential Fed policy discriminator they use is whether monetary conditions are expansive (decreasing discount rate and decreasing federal funds rate), restrictive (increasing discount rate and increasing federal funds rate) or indeterminate (one rate increasing and the other decreasing). Based on their research, they conclude that: Keep Reading

Does fourth quarter global economic data set the stage for asset class returns the next year? In their February 2015 paper entitled “The End-of-the-year Effect: Global Economic Growth and Expected Returns Around the World”, Stig Møller and Jesper Rangvid examine relationships between level of global economic growth and future asset class returns, focusing on growth at the end of the year. Their principle measure of global economic growth is the equally weighted average of quarterly OECD industrial production growth in 12 developed countries. They perform in-sample tests 30 countries and out-of-sample tests for these same 12 countries (for which more data are available). Out-of-sample tests: (1) generate initial parameters from 1970 through 1989 data for testing during 1990 through 2013 period; and, (2) insert a three-month delay between economic growth data and subsequent return calculations to account for publication lag. Using global industrial production growth as specified, annual total returns for 30 country, two regional and world stock indexes, currency spot and one-year forward exchange rates relative to the U.S. dollar, spot prices on 19 commodities, total annual returns for a global government bond index and a U.S. corporate bond index, and country inflation rates as available during 1970 through 2013, they find that: Keep Reading

Is the reward for holding risky bonds material and distinct from the reward for holding stocks and the reward for holding longer term bonds? In their February 2015 paper entitled “Credit Risk Premium: Its Existence and Implications for Asset Allocation”, Attakrit Asvanunt and Scott Richardson measure and explore the predictability and diversification power of the credit (or default) risk premium associated with corporate bonds. They focus on the premium associated with creditworthiness of bonds by first removing the influence of duration/interest rates. They also test whether the credit risk premium diversifies the equity risk premium and the bond term premium. Using data for U.S. corporate bonds, the U.S. stock market, U.S. Treasury securities and economic indicators during 1927 through 2014 and for credit default swaps (CDS) during 2004 through 2014, they find that: Keep Reading

Some experts argue that high (low) gasoline prices mean that consumers must allocate more (less) spending power to fuel, and therefore less (more) to other industries and stocks. Do data support this argument? To check, we relate U.S. stock market returns to changes in U.S. gasoline price changes. Using weekly average retail prices for regular gasoline in the U.S. and contemporaneous levels of the S&P 500 Index from late August 1990 through early February 2015 (1,279 weeks, with a six-week gap in gas prices at the turn of 1990 and a one-week gap in the S&P 500 Index in 2001), we find that: Keep Reading

Do any of the various U.S. stock market size and value/growth styles systematically lead or lag the overall market, perhaps because of some underlying business/economic cycle? To investigate, we consider the the following six exchange-traded funds (ETF) that cut across capitalization (large, medium and small) and value versus growth:

iShares Russell 1000 Value Index (IWD) – large capitalization value stocks.
iShares Russell 1000 Growth Index (IWF) – large capitalization growth stocks.
iShares Russell Midcap Value Index (IWS) – mid-capitalization value stocks.
iShares Russell Midcap Growth Index (IWP) – mid-capitalization growth stocks.
iShares Russell 2000 Value Index (IWN) – small capitalization value stocks.
iShares Russell 2000 Growth Index (IWO) – small capitalization growth stocks.

Using monthly dividend-adjusted closing prices for the style ETFs and S&P Depository Receipts (SPY) over the period August 2001 through December 2014 (161 months, limited by data for IWS/IWP), we find that: Keep Reading

Referring to “Leading Economic Index and the Stock Market”, a subscriber inquired about using the Conference Board’s Leading Economic Index (LEI) for the U.S. to generate long-term U.S. stock market timing signals, as follows:  

“How about using the LEI in the following fashion?

Buy when the LEI rises by 1.0 % from its lowest point in the prior six months.
Sell when the LEI falls by 1.5% from its highest point in the last six months.

I used 1% as a buy because bear markets can end abruptly, not because I was torturing the data to confess. You could use 1.5% and I think still have robust results…changes in trend, which are rare, seem to be helpful. I bought the LEI data from the Conference Board and did some testing by hand using the above going back to 1969. I think I found some interesting results. …It gave early sell in 2006… The signal date was the date of the release… Most of the benefit of the trading system comes within the last 14 years.”

Using the monthly change in LEI data from archived Conference Board press releases during June 2002 through October 2014 (146 months), we find that: Keep Reading

How do the major components of U.S. stock market performance behave over time? In his October 2014 paper entitled “Long-Term Sources of Investment Returns and a Simple Way to Enhance Equity Returns”, Baijnath Ramraika decomposes long-term returns from the U.S. stock market (as proxied by Robert Shiller’s S&P Composite Index) into four components:

1. Dividend yield
2. Inflation
3. Real average change in 10-year earnings (E10)
4. Change in the Cyclically Adjusted Price-Earnings ratio (CAPE, or P/E10)

He further segments this decomposition by decade. Using his decomposition by decade for 1881 through 2010 (13 decades), we find that: Keep Reading

Can the U.S. stock market continue to deliver its historical return? In the preliminary draft of his paper entitled “A Pragmatist’s Guide to Long-run Equity Returns, Market Valuation, and the CAPE”, John Golob poses two questions:

1. What long-run real return should investors expect from U.S. equities?
2. Do popular metrics reliably indicate when the U.S. equity market is overvalued?

He notes that the body of relevant research presents no consensus on the answers to these questions, which both relate to long-term growth in corporate earnings per share. Recent forecasts for real stock market returns range from as low as 2% to about 6% (close to the 6.5% average since 1871), reflecting disagreements about how slow GDP growth, low dividends, share buybacks and the profitability of retained earnings affect earnings per share growth. The author introduces Federal Reserve Flow of Funds (U.S. Financial Accounts) and S&P 500 aggregate book value to gauge effects of stock buybacks. He also assesses the logic of using Shiller’s cyclically adjusted price-earnings ratio (CAPE or P/E10) as a stock market valuation metric. Using S&P 500 Index price and dividend data, related earnings data and U.S. financial and economic data as available during 1871 through 2013, he concludes that: Keep Reading