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Value Investing Strategy (Strategy Overview)

Allocations for May 2024 (Final)
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Allocations for May 2024 (Final)
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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.

Consumer Credit and Consumer Discretionary Sector Returns

“Consumer Credit and Stock Returns” finds that expansion (contraction) of consumer credit, available monthly from the Federal reserve with a delay of about five weeks, has little or no power to predict overall stock market returns. Might consumer credit be useful in predicting returns for just the consumer discretionary sector, as proxied by Consumer Discretionary Select Sector SPDR Fund (XLY)? Using monthly seasonally adjusted total U.S. consumer credit and monthly dividend-adjusted prices for XLY as available during December 1998 (inception of XLY) through January 2022, we find that: Keep Reading

Federal Reserve Holdings and the U.S. Stock Market

Using quarterly data in their April 2013 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, proxied by for SPDR S&P 500 (SPY), a part of this process? To investigate, we relate weekly, monthly and quarterly U.S. stock market returns to 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 as of Wednesday, typically with a 1-day lag. Using weekly (Thursday close) dividend-adjusted prices for SPY and weekly total SOMA holdings during early July 2003 through January 2022, we find that:

Keep Reading

Recent Interactions of Asset Classes with Economic Policy Uncertainty

How do returns of different asset classes recently interact with uncertainty in government economic policy as quantified by the Economic Policy Uncertainty (EPU) Index? This index at the beginning of each month incorporates from the prior month:

  1. Coverage of policy-related economic uncertainty by prominent newspapers (50% weight).
  2. Number of temporary federal tax code provisions set to expire in future years (one sixth weight).
  3. Level of disagreement in one-year forecasts among participants in the Federal Reserve Bank of Philadelphia’s Survey of Professional Forecasters for both (a) the consumer price index (one sixth weight) and (b) purchasing of goods and services by federal, state and local governments (one sixth weight).

Because the historical EPU Index series includes substantial revisions to prior months, we focus on monthly percentage changes in EPU Index and look at lead-lag relationships between change in EPU Index and returns for each of the following 10 exchange-traded fund (ETF) asset class proxies:

  • Equities:
    • SPDR S&P 500 (SPY)
    • iShares Russell 2000 Index (IWM)
    • iShares MSCI EAFE Index (EFA)
    • iShares MSCI Emerging Markets Index (EEM)
  • Bonds:
    • iShares Barclays 20+ Year Treasury Bond (TLT)
    • iShares iBoxx $ Investment Grade Corporate Bond (LQD)
    • iShares JPMorgan Emerging Markets Bond Fund (EMB)
  • Real assets:
    • Vanguard REIT ETF (VNQ)
    • SPDR Gold Shares (GLD)
    • Invesco DB Commodity Index Tracking (DBC)

Using monthly levels of the EPU Index and monthly dividend-adjusted prices for the 10 specified ETFs during December 2007 (limited by EMB) through December 2021, we find that: Keep Reading

Recent Interactions of Asset Classes with Inflation (PPI)

How do returns of different asset classes recently interact with inflation as measured by monthly change in the not seasonally adjusted, all-commodities producer price index (PPI) from the U.S. Bureau of Labor Statistics? To investigate, we look at lead-lag relationships between change in PPI and returns for each of the following 10 exchange-traded fund (ETF) asset class proxies:

  • Equities:
    • SPDR S&P 500 (SPY)
    • iShares Russell 2000 Index (IWM)
    • iShares MSCI EAFE Index (EFA)
    • iShares MSCI Emerging Markets Index (EEM)
  • Bonds:
    • iShares Barclays 20+ Year Treasury Bond (TLT)
    • iShares iBoxx $ Investment Grade Corporate Bond (LQD)
    • iShares JPMorgan Emerging Markets Bond Fund (EMB)
  • Real assets:
    • Vanguard REIT ETF (VNQ)
    • SPDR Gold Shares (GLD)
    • Invesco DB Commodity Index Tracking (DBC)

Using monthly total PPI values and monthly dividend-adjusted prices for the 10 specified ETFs during December 2007 (limited by EMB) through December 2021, we find that: Keep Reading

Labor Force Participation Rate and Stock Market Returns

Does the labor force participation rate, measured monthly by the U.S. Bureau of Labor Statistics along with employment and unemployment rate, predict U.S. stock market returns? An increasing (decreasing) participation rate may may indicate strong (weak) employment demand and therefore a strong (weak) economy. To investigate, we relate participation rate to performance of the S&P 500 Index as a proxy for the stock market. Using monthly participation rate and index level during January 1948 (limited by the former) through December 2021, we find that: Keep Reading

Business Inventories and Stock Market Returns

Do monthly business inventories data, released with a lag of about 1.5 months, reliably predict U.S. stock market behavior? To investigate, we relate monthly change in business inventories to monthly S&P 500 Index return. Using survey-based monthly seasonally adjusted business inventories and the S&P 500 Index during January 1992 (limited by business inventories data) through November 2021, we find that: Keep Reading

Interest Rate Changes Exploitable for Sector Rotation?

A subscriber asked about a strategy that rotates among equity sectors according to changes in interests rate as set by Federal Reserve Bank monetary policy. To investigate, we consider the following nine sector Standard & Poor’s Depository Receipts (SPDR) exchange-traded funds (ETF):

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)

We use monthly effective federal funds rate (EFFR) as the interest rate. We consider two EFFR-based variables: (1) monthly change in EFFR; and, (2) 3-month slope of EFFR for signal smoothing. For each variable and each sector ETF, we consider two tests: (1) correlation of the variable with ETF return each of the next three months; and, (2) average next-month ETF returns across ranked fifths (quintiles) of the EFFR variable. The first test looks for linear relationships, and the second test looks for non-linear relationships. Measurements are at month ends, with a 1-day delay for ETF return calculations to ensure availability of EFFR data. Using monthly levels of EFFR since September 1998 and dividend-adjusted monthly levels of the above sector ETFs and of SPDR S&P 500 (SPY) since December 1998 (limited by sector ETFs), all through November 2021, we find that: Keep Reading

Leading Economic Index Exploitable for Sector Rotation?

A subscriber asked about a strategy that rotates among equity sectors according to the Leading Economic Index (LEI), published monthly by the Conference Board (see “Leading Economic Index and the Stock Market”). To assess LEI usefulness for sector rotation, we consider the following nine sector Standard & Poor’s Depository Receipts (SPDR) exchange-traded funds (ETF):

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)

We consider two LEI-based variables: (1) monthly change in LEI; and, (2) 3-month average change in LEI (average of current value, revised value for prior month and twice-revised value for two months ago) for signal smoothing. For each variable and each sector ETF, we consider two tests: (1) correlation of the variable with ETF return each of the next three months; and, (2) average next-month ETF returns across ranked fifths (quintiles) of the LEI variable. The first test looks for linear relationships, and the second test looks for non-linear relationships. Monthly measurements employ closes on LEI release dates, generally after the market open about three weeks after ends of calendar months reported. Using monthly changes in LEI from archived Conference Board press releases and contemporaneous dividend-adjusted daily levels of the above sector ETFs and of SPDR S&P 500 (SPY) from mid-July 2002 (limited by LEI press releases) through mid-November 2021 (233 monthly LEI observations), we find that: Keep Reading

Testing Wilshire 5000/GDP as Stock Market Predictor

Is the Buffett Indicator, the ratio of total U.S. stock market capitalization (proxied by Wilshire 5000 Total Market Full Cap, W5000) to U.S. Gross Domestic Product (GDP), a useful indicator of future U.S. stock market performance? W5000/GDP clearly has no stable average value over its available history (see the first chart below), so using the level of the ratio as a predictor is not reasonable. To investigate, we therefore consider several variables based on W5000/GDP as predictors of W5000 returns at horizons up to two years, including:

  1. Quarterly change in W5000/GDP.
  2. Average quarterly change in W5000/GDP over the past two years (eight quarters).
  3. Average quarterly change in W5000/GDP over the past five years (20 quarters).
  4. Slope of W5000/GDP over the past two years.
  5. Slope of W5000/GDP over the past five years.

We consider two kinds of tests: (1) a linear test that relates past changes in these variables to future W5000 returns up to two years; and, (2) a non-linear test that calculates average next-quarter W5000 returns by ranked fifths (quintiles) of past changes in these variables. Using quarterly levels of W5000 and quarterly GDP lagged by one quarter to ensure availability during the first quarter of 1971 (limited by W5000) through the third quarter of 2021, we find that: Keep Reading

Job Openings and Stock Market Returns

Do U.S. non-farm job openings, a measurement from the Job Openings and Labor Turnover Survey run monthly by the U.S. Bureau of Labor Statistics, have implications for future U.S. stock market return? High (low) job openings rate may indicate a strong (weak) economy and/or may signal high (low) wage inflation. To investigate, we relate job openings to performance of SPDR S&P 500 (SPY) as a proxy for the stock market. Using monthly job openings (which has a release delay of about six weeks) during December 2000 through September 2021 and monthly dividend-adjusted returns for SPY during December 2000 through October 2021, we find that: Keep Reading

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