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.
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 a few days after the end of the first month of each quarter (January, April, July and October). Using as-released “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 fourth quarter of 2025 (144 surveys), and contemporaneous S&P 500 Index quarterly returns (aligned to survey months), we find that: Keep Reading
A subscriber requested confirmation of the following relationship between U.S. M2 Money Stock and gold offered in “Why Gold May Be Looking Cheap”: “[O]ne measure I’ve found useful is the ratio of the price of gold to the U.S. money supply, measured by M2, which includes cash as well as things like money market funds, savings deposits and the like. The logic is that over the long term the price of gold should move with the change in the supply of money… That equilibrium level is also relevant for future price action. When the ratio is low, defined as 25% below equilibrium, the medium 12-month return has been over 12%. Conversely, when the ratio is high, defined as 25% above equilibrium, the 12-month median return has been -6%. …This measure can be refined further. [G]old tends to trade at a higher ratio to M2 when inflation is elevated.” Because it retrospectively defines specific valuation thresholds using the full sample, this approach impounds lookahead bias and data snooping bias in threshold selection. We consider an alternative setup that relates monthly change in M2 to monthly gold return. We also consider the effect of inflation on this relationship. Using monthly seasonally adjusted M2 and spot gold price as available during December 1974 (to ensure a free U.S. gold market) through September 2025, we find that:
Conventional wisdom holds that a steep yield curve (wide U.S. Treasuries term spread) is good for stocks, while a flat/inverted curve is bad. Is this wisdom correct and exploitable? To investigate, we consider in-sample tests of the relationships between several yield curve metrics and future U.S. stock market returns and two out-of-sample signal-based tests. Using average monthly yields for 3-month Treasuries (T-bill), 1-year Treasuries, 3-year Treasuries, 5-year Treasuries and 10-year Treasuries (T-note) as available since April 1953, monthly levels of the S&P 500 Index since April 1953 and monthly dividend-adjusted levels of SPDR S&P 500 (SPY) since January 1993, all through September 2025, we find that:Keep Reading
Since January 2010, the ADP National Employment Report, in collaboration with the Stanford Digital Economy Lab, has published a monthly estimate of U.S. nonfarm private sector employment using actual payroll data. “The ADP National Employment Report is an independent and high-frequency view of the private-sector labor market based on the aggregated and anonymized payroll data of more than 26 million U.S. employees.” Do ADP estimates usefully predict U.S. stock market returns at the monthly release frequency? To investigate, we relate monthly changes in raw ADP employment estimates and in seasonally adjusted ADP employment estimates to monthly SPDR S&P 500 ETF (SPY) total returns. Using the specified monthly data during January 2010 (limited by ADP data) through August 2025, we find that:
The U.S. Bureau of Economic Analysis (BEA) each quarter estimates economic growth via changes in Gross Domestic Product (GDP) and its Personal Consumption Expenditures (PCE), Private Domestic Investment (PDI) and government spending components. BEA releases advance, preliminary and final data about one, two and three months after quarter ends, respectively. Do these estimates of economic growth usefully predict stock market returns? To investigate, we relate economic growth metrics to S&P 500 Index returns. Using quarterly and annual seasonally adjusted nominal final GDP data from BEA National Income and Product Accounts Table 1.1.5 as available during January 1929 through September 2025 and contemporaneous levels of the S&P 500 Index, we find that:
Does bitcoin (BTC) return exhibit any exploitable leading or lagging roles with respect to gold (SPDR Gold Shares – GLD) return, change in the all-items consumer price index (CPI) or change in the effective federal funds rate (EFFR) for a monthly measurement interval? To investigate, we compute correlations between monthly BTC return and each of monthly GLD return, change in CPI and change in EFFR for various lead-lag relationships, ranging from BTC return leads other variables by six months (-6) to other variables lead BTC return by six months (6). Using monthly BTC, GLC, CPI and EFFR levels during September 2014 (limited by BTC) through July 2025, we find that:Keep Reading
How do returns of different asset classes recently interact with the Effective Federal Funds Rate (EFFR)? We focus on monthly changes (simple differences) in EFFR and look at lead-lag relationships between change in EFFR and returns for each of the following 10 exchange-traded fund (ETF) asset class proxies:
Using end-of-month EFFR and dividend-adjusted prices for the 10 ETFs during December 2007 (limited by EMB) through July 2025, we find that:Keep Reading
How do different asset classes interact with euro-U.S. dollar exchange rate? To investigate, we consider relationships between Invesco CurrencyShares Euro Currency (FXE) and the exchange-traded fund (ETF) asset class proxies used in the Simple Asset Class ETF Momentum Strategy (SACEMS) or the Simple Asset Class ETF Value Strategy (SACEVS) at a monthly measurement frequency. Using monthly dividend-adjusted closing prices for FXE and the asset class proxies since February 2006 as available through May 2025, we find that:Keep Reading
How do different asset classes interact with U.S. dollar valuation? To investigate, we consider relationships between Invesco DB US Dollar Index Bullish Fund (UUP) and the exchange-traded fund (ETF) asset class proxies used in the Simple Asset Class ETF Momentum Strategy (SACEMS) or the Simple Asset Class ETF Value Strategy (SACEVS) at a monthly measurement frequency. Using monthly dividend-adjusted closing prices for UUP and the asset class proxies since March 2007 as available through May 2025, we find that:Keep Reading
“Invest with the Fed?” finds that indexes based on the Invest With the Fed (IFED) stock selection strategy beat reasonable benchmarks. How does that finding translate to investable assets? To investigate, we look at performances since inception of two exchange-traded note (ETN) offerings:
We focus on average monthly return, standard deviation of monthly returns, monthly reward/risk (average return divided by standard deviation), compound annual growth rate (CAGR) and maximum drawdown (MaxDD) as key performance metrics. Using monthly dividend-adjusted returns for IFED, SPY, FEDL and SSO during September 2021 through May 2025, we find that:Keep Reading
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