Equity Premium

Can investors exploit information about business credit tightening/loosening as reported since 1990 in the Federal Reserve’s quarterly Senior Loan Officer Survey to time the U.S. stock market? In the January 2023 draft of his paper entitled “Profitable Timing of the Stock Market with the Senior Loan Officer Survey”, Linus Wilson examines the power of “Net Percentage of Domestic Banks Tightening Standards for Commercial and Industrial Loans to Large and Middle-Market Firms” to predict S&P 500 Index next-quarter returns. A positive (negative) reading means that credit conditions are tightening (loosening) for large and medium-sized firms. Specifically, he relates January survey results to subsequent April-June stock market returns, May survey results to July-September returns, August survey results to October-December returns and November survey results to January-March returns. He considers the full sample of 32 years, two subperiods of 15 years and three subperiods of 10 years. For portfolio tests, he uses the first 15-year subperiod to model allocation decisions to the S&P 500 Index/3-month U.S. Treasury bills (either long-short the stock index or long-only the index) and applies the model to a July 2005 through March 2022 test period. Using quarterly survey results, monthly S&P 500 Index levels and monthly estimated S&P 500 dividends (from Shiller’s data) during April 1990 through March 2022, he finds that: Keep Reading

A subscriber requested confirmation that a strategy of holding SPDR S&P 500 ETF Trust (SPY) at all times except options expiration week beats holding SPY all the time. To investigate, we look at holding SPY at all times except from the close on the second Friday of each month to the close on the third Friday of each month (Strategy). When the market is closed on Friday, we use the Thursday or next earliest close. We focus on compound annual growth rate (CAGR) and maximum drawdown (MaxDD) as essential performance statistics. We apply round-trip trading frictions of 0.1% for SPY-cash switches. Given settlement/cash-sweep delays, we assume zero return on cash. Using daily dividend-adjusted closes of SPY from inception in January 1993 through December 2022, we find that: Keep Reading

A subscriber asked about an assertion that bitcoin (BTC) price trend/return predicts return of the S&P 500 Index (SP500). To investigate, we relate BTC returns to SP500 returns at daily, weekly and monthly frequencies. We rationalize the different trading schedules for these two series by excluding BTC trading dates that are not also SP500 trading days. Most results are conceptual, but we test three versions of an SP500 timing strategy based on prior BTC returns focused on compound annual growth rate (CAGR) and maximum drawdown (MaxDD). Using daily SP500 levels and (pruned) BTC prices during 9/17/2014 (limited by the BTC series) through 12/21/2022, we find that:

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A subscriber requested evaluation of a strategy that seeks to exploit U.S stock market reversion after dips by temporarily applying margin. Specifically, the strategy:

• At all times holds the U.S. stock market.
• When the stock market closes down more than 7% from its high over the past year, augments stock market holdings by applying 50% margin.
• Closes each margin position after two months.

To investigate, we assume:

• The S&P 500 Index represents the U.S. stock market for calculating drawdown over the past year (252 trading days).
• SPDR S&P 500 (SPY) represents the market from a portfolio perspective.
• We start a margin augmentation at the same daily close as the drawdown signal by slightly anticipating the drawdown at the close.
• 50% margin is set at the opening of each augmentation and there is no rebalancing to maintain 50% margin during the two months (42 trading days) it is open.
• If S&P 500 Index drawdown over the past year is still greater than 7% after ending a margin augmentation, we start a new margin augmentation at the next close.
• Baseline margin interest is U.S. Treasury bill (T-bill) yield plus 1%, debited daily.
• Baseline one-way trading frictions for starting and ending margin augmentations are 0.1% of margin account value.
• There are no tax implications of trading.

We use buying and holding SPY without margin augmentation as a benchmark. Using daily levels of the S&P 500 Index, daily dividend-adjusted SPY prices and daily T-bill yields from the end of January 1993 (limited by SPY) through November 2022, we find that: Keep Reading

A subscriber asked whether currency exchange rates exhibit reliable seasonality that may be used to time equities (with a stronger currency implying lower asset prices). To investigate, we look for reliable calendar month effects for the U.S. dollar (USD)-euro exchange rate and for Invesco DB US Dollar Index Bullish Fund (UUP). We further look at how monthly returns for these variables relate to those for SPDR S&P 500 ETF Trust (SPY) as a proxy for the U.S. stock market. Using monthly data for the USD-euro exchange rate since January 1999 and for UUP since March 2007, and corresponding data for SPY, all through November 2022, we find that: Keep Reading

Are models based on advanced machine learning adept at predicting returns for individual emerging market stocks? In the November 2022 version of their paper entitled “Machine Learning and the Cross-section of Emerging Market Stock Returns”, Matthias Hanauer and Tobias Kalsbach compare abilities of machine learning models to predict emerging market stock returns. They consider nine alternatives: two traditional linear models (ordinary least squares and elastic net); two tree-based models (gradient boosted regression trees and random forest); and, five neural networks (one to five layers). Tree-based methods and neural networks identify non-linearities and variable interactions. They further consider a combination of the five neural networks and a combination of all tree-based plus neural network methods. For each model at the end of each month, they rank stocks into country-neutral fifths, or quintiles, based on next-month expected returns and reform a portfolio that is long (short) the quintile with the highest (lowest) expected returns. For tests of long-only net performance, they assume 1-way trading frictions are half the estimated bid-ask spread and apply trading cost mitigation rules. Using returns and 36 accounting/trading variables for 15,152 unique stocks from 32 emerging market countries as included in the MSCI Emerging Markets Index during July 1995 through December 2021 (with out-of-sample testing starting January 2002), they find that:

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Do annual stock market swing returns swing around their average like a pendulum? In the November update of his 2022 paper entitled “Periodic Structure of Equity Market Annual Returns and Their Predictability”, Daniel Pinelis investigates whether annual returns of the S&P 500 Index and the NASDAQ Composite Index exhibit reliable periodicity. Specifically, he models an oscillator indicator that accumulates directional imbalances in annual stock index returns and applies the indicator, in combination with statistical, graphical and machine learning methods, to estimate extent and timing of further market declines from the current levels. Using annual returns for the S&P 500 Index since the mid-1960s and for the NASDAQ Composite Index since the early 1970s, both through late 2022, he finds that:

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Is option gamma, which indicates how aggressively option market makers must trade underlying stocks to hedge their option positions, a systematic driver of those stock returns? In his October 2022 paper entitled “Option Gamma and Stock Returns”, Amar Soebhag investigates the relationship between option gamma for individual stocks and future returns of those stocks. He defines net gamma exposure of a stock as a hedge-adjusted, gamma-weighted sum of open interest for options written on the stock. He each month sorts stocks into value-weighted tenths (deciles) by net gamma for the previous month and calculates next-month returns on the decile portfolios, with focus on the difference in returns between extreme deciles. He then looks at behavior of net gamma across stocks, interactions of net gamma with other stock return predictors and time variation of aggregate net gamma. Using daily gamma, open interest, implied volatility and trading volume for each option contract on listed U.S. common stocks price over $5 as available during January 1996 through December 2021, as well as contemporaneous returns for underlying stocks and data for other widely accepted stock return predictors, he finds that:

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Is the level, or changes in the level, of Federal Reserve (Fed) holdings of U.S. Treasuries (bills, notes, bonds and TIPS, measured weekly as of Wednesday) an indicator of future stock market and/or Treasuries returns? To investigate, we take dividend-adjusted SPDR S&P 500 (SPY) and iShares Barclays 20+ Year Treasury Bond (TLT) as tradable proxies for the U.S. stock and Treasuries markets, respectively. Using weekly Fed holdings of Treasuries, and SPY and TLT total returns during mid-December 2002 through late October 2022, we find that: Keep Reading

Are many accepted equity factors/return anomalies artifacts of the secular decline in interest rates during their discovery sample periods? In their September 2022 paper entitled “The Factor Multiverse: The Role of Interest Rates in Factor Discovery”, Jules van Binsbergen, Liang Ma and Michael Schwert study the role of the secular decline in interest rates since the early 1980s in the discovery of equity factors/return anomalies. They use value-weighted long-short portfolios and monthly reformation for all factors/anomalies. They apply duration-matched fixed income portfolio return adjustments to returns for each anomaly portfolio to model returns for the latter if there had been no interest rate decline. They then classify each anomaly as false positive (present for unadjusted returns, but not adjusted returns), false negative (present for adjusted returns, but not unadjusted returns) or robust to the effect of interest rates (present for both unadjusted and adjusted returns). Using monthly returns for 153 accepted factors/anomalies over respective original test periods and for 1,395 potential undiscovered factors/anomalies based on firm accounting variables during July 1962 through December 2020, along with contemporaneous yield data for zero coupon U.S. Treasury bonds and notes, they find that:

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