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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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EFFR and the Stock Market

Do changes in the Effective Federal Funds Rate (EFFR), the actual cost of short-term liquidity derived from a combination of market demand and Federal Reserve open market operations designed to maintain the Federal Funds Rate (FFR) target, predictably influence the U.S. stock market over the intermediate term? To investigate, we relate smoothed (volume-weighted median) monthly levels of EFFR to monthly U.S. stock market returns (S&P 500 Index or Russell 2000 Index) over available sample periods. Using monthly data as specified since July 1954 for EFFR and the S&P 500 Index (limited by EFFR) and since September 1987 for the Russell 2000 Index, all through January 2018, we find that: Keep Reading

Commercial and Industrial Credit as a Stock Market Driver

Does commercial and industrial (C&I) credit fuel business growth and thereby drive the stock market? To investigate, we relate changes in credit standards from the Federal Reserve Board’s quarterly Senior Loan Officer Opinion Survey on Bank Lending Practices to future U.S. stock market returns. Presumably, loosening (tightening) of credit standards is good (bad) for stocks. The Federal Reserve publishes survey results about the end of the first month of each quarter (January, April, July and October). Using the “Net Percentage of Domestic Respondents Tightening Standards for C&I Loans” for large and medium businesses from the Senior Loan Officer Opinion Survey on Bank Lending Practices Chart Data for the second quarter of 1990 through the first quarter of 2018 (113 surveys), and contemporaneous S&P 500 Index quarterly returns (aligned to survey months), we find that: Keep Reading

ISM NMI and Stock Market Returns

Each month, the Institute for Supply Management (ISM) compiles results of a survey “sent to more than 375 purchasing executives working in the non-manufacturing industries across the country.” Based on this survey, ISM computes the Non-Manufacturing Index (NMI), “a composite index based on the diffusion indexes for four…indicators with equal weights: Business Activity (seasonally adjusted), New Orders (seasonally adjusted), Employment (seasonally adjusted) and Supplier Deliveries.” ISM releases NMI for a month on the third business day of the following month. Does the monthly level of NMI or the monthly change in NMI predict U.S. stock market returns? Using monthly seasonally adjusted NMI data during January 2008 through January 2016 from the Federal Reserve Bank of St. Louis and from press releases thereafter through January 2018, and contemporaneous monthly S&P 500 Index closes (121 months), we find that: Keep Reading

ISM PMI and Stock Market Returns

According to the Institute for Supply Management (ISM) ISM, their Manufacturing Report On Business, published since 1931, “is considered by many economists to be the most reliable near-term economic barometer available.” The manufacturing summary component of this report is the Purchasing Managers’ Index (PMI), aggregating monthly inputs from purchasing and supply executives across the U.S. regarding new orders, production, employment, deliveries and inventories. ISM releases PMI for a month at the beginning of the following month. Does PMI predict stock market returns? Using monthly seasonally adjusted PMI data during January 1950 through January 2016 from the Federal Reserve Bank of St. Louis (discontinued and removed) and from press releases thereafter through January 2018, and contemporaneous monthly S&P 500 Index closes (817 months), we find that:

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Should the “Anxious Index” Make Investors Anxious?

Since 1990, the Federal Reserve Bank of Philadelphia has conducted a quarterly Survey of Professional Forecasters. The American Statistical Association and the National Bureau of Economic Research conducted the survey from 1968-1989. Among other things, the survey solicits from economic experts the probabilities of U.S. economic recession (negative GDP growth) during each of the next four quarters. The survey report release schedule is mid-quarter. For example, the release date of the survey report for the fourth quarter of 2017 is November 13, 2017, with forecasts for the first quarter of 2018 through the fourth quarter of 2018. The “Anxious Index” is the probability of recession during the next quarter. When professional forecasters are relatively optimistic (pessimistic) about the economy, does the stock market go up (down) over the coming quarters? Rather than relate the probability of recession to stock market returns, we instead relate one minus the probability of recession (the probability of good times). If the forecasts are accurate, a relatively high (low) forecasted probability of good times should arguably indicate a relatively strong (weak) stock market. Using survey results and quarterly S&P 500 Index levels ( measured from survey release date to survey release date as available, and from mid-quarter to mid-quarter before availability of release dates) from the fourth quarter of 1968 through the fourth quarter of 2017 (197 surveys), we find that:

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Chemical Activity Barometer as Stock Market Trend Indicator

A subscriber proposed: “It would be interesting to do an analysis of the Chemical Activity Barometer [CAB] to see if it has predictive value for the stock market. Either [look] at stock prices when [CAB makes] a two percent pivot down [from a preceding 6-month high] as a sell signal and one percent pivot up as a buy signal…[or when CAB falls] below its x month moving average.” The American Chemistry Council claims that CAB “determines turning points and likely future trends of the wider U.S. economy” and leads other commonly used economic indicators. To investigate its usefulness for U.S. stock market timing, we consider the two proposed strategies, plus two benchmarks, as follows:

  1. CAB SMAx Timing – hold stocks (the risk-free asset) when monthly CAB is above (below) its simple moving average (SMA). We consider SMA measurement intervals ranging from two months (SMA2) to 12 months (SMA12).
  2. CAB Pivot Timing – hold stocks (the risk-free asset) when monthly CAB most recently crosses 1% above (2% below) its maximum value over the preceding six months. We look at a few alternative pivot thresholds.
  3. Buy and Hold (B&H) – buy and hold the S&P Composite Index.
  4. Index SMA10 – hold stocks (the risk-free asset) when the S&P Composite Index is above (below) its 10-month SMA (SMA10), assuming signal execution the last month of the SMA measurement interval.

Since CAB data extends back to 1912, we use Robert Shiller’s S&P Composite Index to represent the U.S. stock market. For the risk-free rate, we use the 3-month U.S. Treasury bill (T-bill) yield since 1934. Prior to 1934, we use Shiller’s long interest rate minus 1.59% (the average 10-year term premium since 1934). We assume a constant 0.25% friction for switching between stocks and T-bills as signaled. We focus on number of switches, compound annual growth rate (CAGR) and maximum drawdown (MaxDD) as key performance metrics. Using monthly data for CAB, the S&P Composite Stock Index, estimated dividends for the stocks in this index (for calculation of total returns) and estimated long interest rate during January 1912 through December 2017 (about 106 years), and the monthly T-bill yield since January 1934, we find that: Keep Reading

Stock Market Earnings Yield and Inflation Over the Long Run

How does the U.S. stock market earnings yield (inverse of price-to-earnings ratio, or E/P) interact with the U.S. inflation rate over the long run? Is any such interaction exploitable? To investigate, we employ the long run dataset of Robert Shiller. Using monthly data for the S&P Composite Stock Index, estimated aggregate trailing 12-month earnings and dividends for the stocks in this index, and estimated U.S. Consumer Price Index (CPI) during January 1871 through June 2017 (about 147 years), and the monthly yield on 3-month U.S. Treasury bills (T-bills) since January 1951, we find that:

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Do Copper Prices Lead the Broad Equity Market?

Is copper price a reliable leading indicator of economic activity and therefore of future corporate earnings and equity prices? To investigate, we employ the monthly price index for copper base scrap (not seasonally adjusted) from the U.S. Bureau of Labor Statistics, which spans multiple economic expansions and contractions. Using monthly levels of the copper scrap price index and the S&P 500 Index during January 1957 through December 2017 (61 years), we find that: Keep Reading

Do Any Sector ETFs Reliably Lead or Lag the Market?

Do any of the major U.S. stock market sectors systematically lead or lag the overall market, perhaps because of some underlying business/economic cycle? To investigate, we examine the behaviors of the nine sectors defined by the Select Sector Standard & Poor’s Depository Receipts (SPDR) exchange traded funds (ETF), all of which started trading in December 1998:

Materials Select Sector SPDR (XLB)
Energy Select Sector SPDR (XLE)
Financial Select Sector SPDR (XLF)
Industrial Select Sector SPDR (XLI)
Technology Select Sector SPDR (XLK)
Consumer Staples Select Sector SPDR (XLP)
Utilities Select Sector SPDR (XLU)
Health Care Select Sector SPDR (XLV)
Consumer Discretionary Select SPDR (XLY)

Using monthly dividend-adjusted closing prices for these ETFs, along with contemporaneous data for SPDR S&P 500 (SPY) as a benchmark, during December 1998 through December 2017 (229 months), we find that: Keep Reading

Combining Market, Unemployment and Interest Rate Trends

In reaction to “Combine Market Trend and Economic Trend Signals?”, a subscriber suggested adding an interest rate trend signal to those for the U.S. stock market and U.S. unemployment rate for the purpose of timing the S&P 500 Index (SP500). To investigate, we look at combining:

We consider scenarios when the SP500 trend is positive, the UR trend is positive, the T-bill trend is positive, at least one trend is positive (>=1), at least two trends are positive (>=2) or all three trends are positive (All). For total return calculations, we adjust the SP500 monthly with estimated dividends from the Shiller dataset. When not in the index, we assume return on cash from the broker is the specified T-bill yield. We focus on gross compound annual growth rate (CAGR), maximum drawdown (MaxDD) and annual Sharpe ratio as key performance metrics. We use the average monthly T-bill yield during a year as the risk-free rate for that year in Sharpe ratio calculations. While we do not apply any stocks-cash switching frictions, we do calculate the number of switches for each scenario. Using the specified monthly data through October 2017, we find that: Keep Reading

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