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Economic Indicators

The U.S. economy is a very complex system, with indicators therefore ambiguous and difficult to interpret. To what degree do macroeconomics and the stock market go hand-in-hand, if at all? Do investors/traders: (1) react to economic readings; (2) anticipate them; or, (3) just muddle along, mostly fooled by randomness? These blog entries address relationships between economic indicators and the stock market.

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Globalization Effects on Asset Return Comovement

Is global diversification within asset classes disappearing as worldwide economic and financial integration increases? In their August 2016 paper entitled “Globalization and Asset Returns”, Geert Bekaert, Campbell Harvey, Andrea Kiguel and Xiaozheng Wang examine whether economic and financial integration increases global comovement of country equity, bond and currency exchange market returns. They examine three measures of return comovement for each asset class: average pairwise correlation, average beta relative to the world market and average idiosyncratic volatility. They apply these measures separately to developed markets and emerging markets. Using monthly equity, bond and currency exchange market returns in U.S. dollars for 26 developed markets and 32 emerging markets as available from various inceptions through December 2014, they find that: Keep Reading

Money Velocity and the Stock Market

Regarding “Money Supply (M2) and the Stock Market”, a subscriber responded: “I’ve always thought…that both M2 and velocity were needed. If there’s more money, but it is not circulating, then it doesn’t have a chance to have much impact. That’s the situation we have right now for the most part.” The Federal Reserve Bank of St. Louis tracks money velocity based either M1 or M2 money supplies at a quarterly frequency, stating that: “Velocity is a ratio of nominal GDP to a measure of the money supply. It can be thought of as the rate of turnover in the money supply–that is, the number of times one dollar is used to purchase final goods and services included in GDP.” Specifically, the bank calculates money velocity as quarterly nominal GDP divided by average money supply during the quarter. Using quarterly values for seasonally adjusted Velocity of M1Velocity of M2 and the S&P 500 Index as available from the last quarter of 1958 through the second quarter of 2016 (232 quarters), we find that: Keep Reading

Money Supply (M1) and the Stock Market

A reader commented: “I couldn’t find an analysis for the M1 money supply similar to the one for M2. How about it? M2 cannot be an accurate money supply measure because it includes non-cash investments such as money market mutual funds. When the stock market corrects and people are exchanging stocks for say, money market mutual fund shares, the M2 figure will actually increase. The money supply is not literally increasing in such cases as no new cash is being created; there is merely an exchange of existing assets. Technically, only increasing the monetary base would increase the money supply, but M1 is a reasonable substitute for that as it includes the cash part of bank reserves.” The M1 money stock consists of funds that are readily accessible for spending: currency in circulation, traveler’s checks, demand deposits and other checkable deposits. Is there a reliable relationship between historical variation in M1 and stock market returns? Using weekly data for seasonally adjusted M1 and the S&P 500 Index during January 1975 through June 2016 (2,165 weeks), we find that: Keep Reading

Money Supply (M2) and the Stock Market

Some investing experts cite change in money supply as a potentially important driver of future stock market behavior. When the money supply grows (shrinks), they theorize, nominal asset prices tend to go up (down). Or conversely, money supply growth drives inflation, thereby elevating discount rates and depressing equity valuations. One measure of money supply is the M2 money stock, which consists of currency, checking accounts, saving accounts, small certificates of deposit and retail money market mutual funds. Is there a reliable relationship between historical variation in M2 and stock market returns? Using weekly data for seasonally adjusted M2 and the S&P 500 Index during November 1980 through June 2016 (1,861 weeks), we find that: Keep Reading

Real Bond Returns and Inflation

A subscriber asked (more than four years ago): “Everyone says I should not invest in bonds today because the interest rate is so low (and inflation is daunting). But real bond returns over the last 30 years are great, even while interest rates are low. Could you analyze why bonds do well after, but not before, 1981?” To investigate, we consider the U.S. long-run interest rate and the U.S. Consumer Price Index (CPI) series from Robert Shiller. The long-run interest rate is the yield on U.S. government bonds, specifically the constant maturity 10-year U.S. Treasury note after 1953. We use the term “T-note” loosely to refer to the entire series. We apply the formula used by Aswath Damodaran to the yield series to estimate the nominal T-note total returns. We use the CPI series to calculate inflation (12-month change in CPI). We subtract inflation from the T-note nominal total return to get the T-note real total return. Using annual Shiller interest rate and CPI data for 1871 through 2015, we find that: Keep Reading

Gold Price Drivers?

What drives the price of gold: inflation, stock market behavior, public sentiment? To investigate, we relate spot gold price to non-seasonally adjusted Consumer Price Index (CPI), the S&P 500 Index and University of Michigan Consumer Sentiment. We start sampling in 1975 because: “On March 17, 1968, …the price of gold on the private market was allowed to fluctuate…[, and] in 1975…the price of gold was left to find its free-market level.” We lag CPI and consumer sentiment measurements by one month to ensure they are known to the market when calculating gold returns. Using monthly data from January 1975 (January 1978 for consumer sentiment) through June 2016 (498 or 461 months), we find that: Keep Reading

Testing 25 U.S. Stock Market Return Predictors

What variables best predict U.S. stock market returns? In his June 2016 paper entitled “Which Variables Predict and Forecast Stock Market Returns?”, David McMillan examines the power of 25 variables to predict excess return (relative to the 3-month U.S. Treasury bill yield) of Shiller’s S&P Composite Index both in-sample and out-of-sample. He chooses variables based on connectedness to expected cash flow/dividends and risk and assigns them to five groups:

  1. Financial ratios: dividend-price, price-to-earnings, cyclically adjusted price-to-earnings (CAPE or P/E10), Tobin’s Q and market capitalization-to-Gross Domestic Product (GDP).
  2. Economic:  GDP cycle, GDP acceleration (rate of change in GDP growth), consumption growth, 10-year to 3-month Treasuries term spread and inflation.
  3. Labor: wage growth, unemployment, natural rate of unemployment, productivity growth and labor market conditions.
  4. Housing: house price growth, house affordability, home ownership, housing supply and new house sales.
  5. Other: University of Michigan Consumer Sentiment, Purchasing Managers Index, National Financial Conditions Index, leverage and non-financial leverage.

He employs regressions to test in-sample predictive power. He then tests out-of-sample forecasts starting in 2000 using various forecast methods and accuracy measures and considering both single-variable and multi-variable models. Using the specified data series as available during 1973 through 2014, he finds that: Keep Reading

ADP Employment Report and Stock Returns

Since May 2006, the monthly ADP National Employment Report has released a monthly estimate of U.S. nonfarm private sector employment growth using actual payroll data. The report is designed “to predict private-sector employment prior to the release of the CES [Bureau of Labor Statistics’ monthly Current Employment Statistics survey] report.” Do the ADP estimates affect or predict U.S. stock market returns on the release day or over the next month? To investigate, we consider both as-released (from press releases) and as-revised ADP data (from the extended downloadable historical dataset). Using monthly ADP report release dates and as-released employment growth estimates commencing April 2006, historically modeled ADP employment growth estimates commencing April 2001 and contemporaneous daily opening/closing and monthly dividend-adjusted closing prices of SPDR S&P 500 (SPY) through early June 2016, we find that: Keep Reading

Productivity and the Stock Market

Financial media often cite Bureau of Labor Statistics (BLS) productivity growth news releases as relevant to investment outlook. Does the quarter-to-quarter change in U.S. labor force productivity predict U.S. stock market behavior? Specifically, does a rise (decline) in productivity portend strong (weak) earnings and therefore an advance (decline) for stocks? Using annualized quarterly changes in non-farm labor productivity from BLS and end-of quarter S&P 500 Index levels during January 1950 through March 2016 (265 quarters), we find that: Keep Reading

Federal Reserve Holdings and the U.S. Stock Market

Using quarterly data in their April 2013 preliminary paper entitled “Analyzing Federal Reserve Asset Purchases: From Whom Does the Fed Buy?” Seth Carpenter, Selva Demiralp, Jane Ihrig and Elizabeth Klee find that some categories of investors appear to sell U.S. Treasuries to the Federal Reserve and rebalance toward riskier assets (corporate bonds, commercial paper, and municipal debt). Are stocks a part of this process? To investigate, we relate weekly, monthly and quarterly U.S. stock market returns to comparable changes in the Federal Reserve’s System Open Market Account (SOMA) holdings, comprised of U.S. Treasury bills, U.S. Treasury notes and bonds, U.S. Treasury Inflation-Protected Securities (TIP) and Mortgage-Backed Securities (MBS). The Federal Reserve reports these holdings with a small lag. Using weekly (Wednesday close) data for SPDR S&P 500 (SPY) as a stock market proxy and total SOMA holdings during early July 2003 through mid-May 2016, we find that: Keep Reading

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