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Value Investing Strategy (Strategy Overview)

Allocations for April 2024 (Final)
Cash TLT LQD SPY

Momentum Investing Strategy (Strategy Overview)

Allocations for April 2024 (Final)
1st ETF 2nd ETF 3rd ETF

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.

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 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 variations in M2 and stock market returns? Using weekly data for seasonally adjusted M2 and the S&P 500 Index during November 1980 through January 2021, we find that: Keep Reading

Diversifying across Growth/Inflation States of the Economy

Can diversification across economic states improve portfolio performance? In their November 2020 paper entitled “Investing Through a Macro Factor Lens”, Harald Lohre, Robert Hixon, Jay Raol, Alexander Swade, Hua Tao and Scott Wolle study interactions between three economic “factors” (growth, defensive/U.S. Treasuries and inflation) and portfolio building blocks (asset classes and conventional factor portfolios). Their proxies for economic factors are: broad equity market for growth; U.S. Treasuries for defensive; and, spread between inflation-linked bonds and U.S. Treasuries for inflation. To diversify across economic states, they calculate historical performance of each portfolio building block during each of four economic regimes: (1) rising growth and rising inflation; (2) rising growth and falling inflation; (3) falling growth and rising inflation; and, (4) falling growth and falling inflation. They then look at benefits of adding defensive and inflation economic factor overlays to a classis 60%/40% global equities/bonds portfolio. Using monthly economic factor data and asset class/conventional factor portfolio returns during February 2001 through May 2020, they find that: Keep Reading

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 November 2020 (nearly 64 years), we find that: Keep Reading

U.S. Economy and Equity Market Linkage Weakening?

How connected are principal measures of U.S. economic activity and U.S. stock market performance? In their October 2020 paper entitled “Has the Stock Market Become Less Representative of the Economy?”, Frederik Schlingemann and René Stulz model and measure relationships between market capitalizations of U.S. publicly listed firms and their contributions to U.S. employment and Gross Domestic Product (GDP). They estimate employment contribution directly based on firm reports, with modeled adjustments. They measure contribution to GDP based on firm value-add, approximated as operating income before depreciation plus labor costs (with labor costs often modeled). They also try other ways of measuring value-add. Using annual non-farm employment and GDP data for the U.S., annual employment and value-add data for U.S. publicly listed firms and annual stock prices for those firms during 1973 (limited by firm employment data) through 2019, they find that:

Keep Reading

Combining Economic Policy Uncertainty and Stock Market Trend

A subscriber requested, as in “Combine Market Trend and Economic Trend Signals?”, testing of a strategy that combines: (1) U.S. Economic Policy Uncertainty (EPU) Index, as described and tested separately in “Economic Policy Uncertainty and the Stock Market”; and, (2) U.S. stock market trend. We consider two such combinations. The first combines:

  • 10-month simple moving average (SMA10) for the broad U.S. stock market as proxied by the S&P 500 Index. The trend is bullish (bearish) when the index is above (below) its SMA10 at the end of last month.
  • Sign of the change in EPU Index last month. A positive (negative) sign is bearish (bullish).

The second combines:

  • SMA10 for the S&P 500 Index as above.
  • 12-month simple moving average (SMA12) for the EPU Index. The trend is bullish (bearish) when the EPU Index is below (above) its SMA12 at the end of last month.

We consider alternative timing strategies that hold SPDR S&P 500 (SPY) when: the S&P 500 Index SMA10 is bullish; the EPU Index indicator is bullish; either indicator for a combination is bullish; or, both indicators for a combination are bullish. When not in SPY, we use the 3-month U.S. Treasury bill (T-bill) yield as the return on cash, with 0.1% switching frictions. We assume all indicators for a given month can be accurately estimated for signal execution at the market close the same month. We compute average net monthly return, standard deviation of monthly returns, net monthly Sharpe ratio (with monthly T-bill yield as the risk-free rate), net compound annual growth rate (CAGR) and maximum drawdown (MaxDD) as key strategy performance metrics. We calculate the number of switches for each scenario to indicate sensitivities to switching frictions and taxes. Using monthly values for the EPU Index, the S&P 500 Index, SPY and T-bill yield during January 1993 (inception of SPY) through September 2020, we find that:

Keep Reading

Asset Class ETF Interactions with the Yuan

How do different asset classes interact with the Chinese yuan-U.S. dollar exchange rate? To investigate, we consider relationships between WisdomTree Chinese Yuan Strategy (CYB) and the exchange-traded fund (ETF) asset class proxies used in the Simple Asset Class ETF Momentum Strategy (SACEMS) and the Simple Asset Class ETF Value Strategy (SACEVS) at a monthly measurement frequency. Using monthly dividend-adjusted closing prices for CYB and the asset class proxies during May 2008 (when CYB is first available) through August 2020 (147 months), we find that: Keep Reading

Interest Rates and the Equity Value Premium

Do interest rate effects explain/predict the poor performance of value stocks over the past decade, and especially during 2017 through early 2020? In their May 2020 paper entitled “Value and Interest Rates: Are Rates to Blame for Value’s Torments?”, Thomas Maloney and Tobias Moskowitz investigate interactions between equity value factors and the interest rate environment. They first examine theoretical relationships and then explore relationships between several ways to measure the U.S. equity value premium and interest rates empirically, including interest rate level, change in short-term rates, change in long-term rates and slope of the yield curve. They look at subperiods and some international evidence. Finally, they assess ability of interest rate variables to predict the value premium and thereby inform factor timing strategies. Using U.S. interest rate and firm/stock data inputs for several ways of estimating the value premium as available since January 1954, and similar data for Japan, Germany and the UK since 1988, all through December 2019, they find that: Keep Reading

Combining Market Trend and Chicago Fed NFCI Signals

In response to “Exploiting Chicago Fed NFCI Predictive Power”, which tests practical use of the Federal Reserve Bank of Chicago’s National Financial Conditions Index (NFCI) for U.S. stock market timing, a subscriber suggested combining this strategy with stock market trend as in “Combine Market Trend and Economic Trend Signals?”. To investigate, we use the 40-week simple moving average (SMA40) for the S&P 500 Index to measure stock market trend. We then test two strategies that are each week in SPDR S&P 500 (SPY) or cash (U.S. Treasury bills, T-bills), as follows:

  1. Combined (< Mean): hold SPY (cash) when either: (a) prior-week S&P 500 Index is above (below) its SMA40; or, (b) prior-week change in NFCI is below (above) its mean since since the beginning of 1973.
  2. Combined (< Mean+SD): hold SPY (cash) when either: (a) prior-week S&P 500 Index is above (below) its SMA40; or, (b) prior-week change in NFCI is below (above) its mean plus one standard deviation of weekly changes in NFCI since the beginning of 1973.

The return week is Wednesday open to Wednesday open (Thursday open when the market is not open on Wednesday) per the NFCI release schedule. SMA40 calculations are Tuesday close to Tuesday close to ensure timely availability of signals before any Wednesday open trades. We assume SPY-cash switching frictions are a constant 0.1% over the sample period. Using weekly NFCI data since January 1973, weekly S&P 500 Index levels since April 1992, weekly dividend-adjusted opens of SPY and weekly T-bill yield since February 1993 (limited by SPY), all as specified through April 2020, we find that:

Keep Reading

Returns After QE Announcements

In reaction to “Federal Reserve Holdings and the U.S. Stock Market”, a subscriber suggested analysis of market reactions to announcements (starts/ends) of major Federal Reserve System interventions, such as the series of quantitative easing (QE) initiatives. Reactions to such announcement should precede changes in actual holdings. To investigate, we look at cumulative returns of SPDR S&P 500 (SPY) and iShares Barclays 20+ Year Treasury Bond (TLT) during the 30 trading days after each of the following announcements:

  • 11/25/08: QE-1 initiated
  • 3/16/09: QE-1 expanded
  • 3/31/10: QE-1 terminated
  • 11/3/10: QE-2 initiated
  • 6/29/12: QE-2 terminated
  • 9/13/12: QE-3 initiated
  • 12/12/12: QE-3 expanded
  • 10/29/14: QE-3 terminated
  • 3/23/20: “QE-4” initiated

Using daily dividend-adjusted prices for SPY and TLT spanning these dates, we find that: Keep Reading

Exploiting Chicago Fed ANFCI Predictive Power

“Chicago Fed ANFCI as U.S. Stock Market Predictor” suggests that weekly change in the Federal Reserve Bank of Chicago’s Adjusted National Financial Conditions Index (ANFCI) may be a useful indicator of future U.S. stock market returns. We test its practical value via two strategies that are each week in SPDR S&P 500 (SPY) when prior change in ANFCI is favorable and in cash (U.S. Treasury bills, T-bills) when prior change in ANFCI is unfavorable, as follows:

  1. Change in ANFCI < Mean [aggressive]: hold SPY (cash) when prior-week change in ANFCI is below (above) its mean since the beginning of 1973, providing an initial 20-year calculation interval.
  2. Change in ANFCI < Mean+SD [conservative]: hold SPY (cash) when prior-week change in ANFCI is below (above) its mean plus one standard deviation of weekly changes in ANFCI since the beginning of 1973.

The return week is Wednesday open to Wednesday open (Thursday open when the market is not open on Wednesday) per the ANFCI release schedule. We assume SPY-cash switching frictions are a constant 0.1% over the sample period. We use buying and holding SPY as the benchmark. Using weekly levels of ANFCI since January 1973 and weekly dividend-adjusted opens of SPY and T-bills since February 1993 (limited by SPY), all through April 2020, we find that: Keep Reading

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