Equity Premium

How should investors think about the correlation between stock market returns and bond market returns when constructing a diversified portfolio? In their April 2024 paper entitled “Stock-Bond Correlation: Theory & Empirical Results”, Lorenzo Portelli and Thierry Roncalli examine theoretical and empirical relationships between the stocks-bonds return correlation and other variables/conditions. They focus on:

• Monthly returns of long-term government bonds and country stock markets (for example 10-year U.S. Treasury notes and the S&P 500 Index for the U.S.), but consider other choices for bond duration and stock portfolio.
• 48-month rolling returns when assessing correlation dynamics.

Using government bond and country stock market returns for the U.S. during 1965 through 2023 and for other developed, developing and emerging markets across Europe, the Americas and Asian as available through 2023, they find that:

Keep Reading

Are stock and sector momentum strategies, as implemented by exchange-traded funds (ETF), attractive? To investigate, we consider nine momentum-oriented equity ETFs, all currently available, in order of longest to shortest available histories:

• Invesco Dorsey Wright Momentum ETF (PDP) – invests at least 90% of assets in approximately 100 U.S. common stocks per a proprietary methodology designed to identify powerful relative strength characteristics, reformed quarterly. Benchmark is iShares Russell 3000 ETF (IWV).
• Invesco Dorsey Wright SmallCap Momentum ETF (DWAS) – invests at least 90% of assets in approximately 200 small-capitalization U.S. common stocks per a proprietary methodology designed to identify powerful relative strength characteristics, reformed quarterly. Benchmark is iShares Russell 2000 ETF (IWM).
• iShares Edge MSCI USA Momentum Factor ETF (MTUM) – holds U.S. large-capitalization and mid-capitalization stocks with relatively high momentum. Benchmark is iShares Russell 1000 ETF (IWB).
• First Trust Dorsey Wright Focus 5 ETF (FV) – holds five equally weighted sector and industry ETFs selected via a proprietary relative strength methodology, reformed twice a month. Benchmark is IWV.
• iShares MSCI Intl Momentum Factor ETF (IMTM) – holds international developed market large-capitalization and mid-capitalization stocks with relatively high momentum. Benchmark is iShares MSCI ACWI ex U.S. ETF (ACWX).
• SPDR Russell 1000 Momentum Focus ETF (ONEO) – tracks the Russell 1000 Momentum Focused Factor Index, picking U.S. stocks that have recently outperformed. Benchmark is IWB.
• Alpha Architect U.S. Quantitative Momentum ETF (QMOM) – seeks to buy stocks with the highest quality momentum via a portfolio that generally holds 50 stocks. Benchmark is IWV.
• First Trust Dorsey Wright Dynamic Focus 5 ETF (FVC) – similar to FV but with added risk management via an increasing allocation to cash equivalents when relative strengths of more than one-third of the universe diminish relative to a cash index, reformed twice a month. Benchmark is IWV.
• JPMorgan U.S. Momentum Factor ETF (JMOM) – holds U.S. common stocks with strong risk-adjusted momentum. Benchmark is IWB.

We focus on monthly return statistics, along with compound annual growth rates (CAGR) and maximum drawdowns (MaxDD). We assign broad market benchmark ETFs according to momentum fund descriptions. Using monthly dividend-adjusted returns for the nine momentum funds and respective benchmarks as available through April 2024, we find that: Keep Reading

What are the different ways of estimating the equity risk premium, and which one is best? In the March 2024 update of his paper entitled “Equity Risk Premiums (ERP): Determinants, Estimation and Implications – The 2024 Edition”, Aswath Damodaran updates a comprehensive overview of equity risk premium estimation. He examines why different approaches to estimating the premium disagree and how to choose among them. Using data from multiple countries (but focusing on the U.S.) over long periods through the end of 2023, he concludes that: Keep Reading

What are current estimates of equity risk premiums (ERP) and risk-free rates around the world? In their March 2024 paper entitled “Survey: Market Risk Premium and Risk-Free Rate used for 96 countries in 2024”, Pablo Fernandez, Diego García de la Garza and Javier Acin summarize results of a February 2024 email survey of international finance and economic professors, analysts and company managers “about the Risk-Free Rate and the Market Risk Premium (MRP) used to calculate the required return to equity in different countries.” Results are in local currencies. Based on 4,064 specific and credible premium estimates spanning 96 countries for which there are at least six estimates, they find that: Keep Reading

Are sentiments conveyed in Seeking Alpha articles useful for stock picking? In their January 2023 paper entitled “Seeking Alpha: More Sophisticated Than Meets the Eye”, Duo Selina Pei, Abhinav Anand and Xing Huan apply two-pass natural language processing to test the informativeness of articles from Seeking Alpha incremental to publicly available earnings data. Specifically, they each month:

• Associate articles with one or more specific stocks.
• Extract positive and negative sentiment at both phrase and aggregate levels for each article/stock.
• Calculate a standardized net sentiment for each article/stock based on the difference between positive and negative mentions, emphasizing event sentiment over general sentiment.
• Rank articles/stocks based on standardized net sentiment over the last month. Reform equal-weighted portfolios of articles/stocks by ranked tenths (deciles). Calculate both immediate [-1,+1] and 90-day future [+2,+90] average gross raw returns and average gross abnormal returns adjusted for size, book-to-market and momentum.
• Sort stocks into 20 groups based on monthly standardized net sentiments up to two days before portfolio selection, excluding stocks with few articles or neutral sentiment. Reform an equal-weighted hedge portfolio that is long stocks with the highest sentiments and short stocks with the lowest (on average, 105 long and 86 short positions).

Using 350,095 articles published on Seeking Alpha since its inception in 2004 through the beginning of October 2018, daily returns of matched stocks and their options and associated earnings surprise data as available, they 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:

• 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 end-of-month EFFR and dividend-adjusted prices for the 10 ETFs during December 2007 (limited by EMB) through March 2024, we find that: Keep Reading

Does pricing of options on leveraged exchange-traded funds (ETF) predict future returns of the underlying 1X ETFs? In the March 2024 version of their paper entitled “Lever Up! An Analysis of Options Trading in Leveraged ETFs”, Collin Gilstrap, Alex Petkevich, Pavel Teterin and Kainan Wang examine options trading in leveraged equity ETFs and its implications for future performance of underlying funds. They hypothesize that the compounded leverage of such options attracts especially sophisticated investors. Specifically, they test a risk-on/risk-off strategy that, at the end of each month:

1. Calculates the difference in changes in implied volatilities between at-the-money (ATM) call options and ATM put options on a leveraged ETF (and separately for comparison, on its underlying 1X ETF).
2. If this difference is greater (smaller) than its median value over the prior 12 months, specifies the next month as bullish (bearish) for the 1X ETF, and invests in a synthetic 3X ETF (the risk-free asset) next month. The synthetic 3X ETF earns three times the monthly returns of the underlying 1X ETF.

They also consider a more realistic test using SPDR S&P 500 ETF (SPY) as the underlying 1X ETF and Direxion Daily S&P 500 Bull 3X Shares (SPXL) as the associated leveraged ETF. They assume 0.2% trading frictions for portfolio turnover. Using daily returns for 76 leveraged equity ETFs matched to 30 underlying 1X ETFs and daily implied volatilities for associated ATM call and put options during January 2007 through December 2021, they find that: Keep Reading

Can holders of popular large-capitalization stocks improve portfolio performance by systematically buying or selling options on these stocks? In their February 2024 paper entitled “The Performance of Options-Based Investment Strategies: Evidence for Individual Stocks from 2004 to 2019”, Zhuo Li and Thomas Miller, Jr. compare to buy-and-hold the performances of four strategies that augment a long stock position with options, as follows:

1. Buy and hold the stock.
2. Covered call  – long stock plus short call.
3. Protective put – long stock plus long put.
4. Collar – long stock plus short call plus long put.
5. Covered combination – long stock plus short call plus short put.

They focus on 10 stocks widely held in 401(k) plans: ExxonMobil, Comcast, Berkshire Hathaway (Class B), Oracle, Microsoft, Coca-Cola, Amazon, Wells Fargo, Google (Class A) and Apple. They roll at the end of each calendar month from the standard monthly option that expires during the next month to the one that expires during the subsequent month. They choose option strike prices that are at least 5% out-of-the-money but as close to 5% as possible, with exceptions when no such options are available. They assume option buys and sells are at the daily closing bid-ask midpoint. They ignore the possibility of early option exercise. Using monthly data for the selected 10 stocks and specified options as available during January 2004 through November 2019, they find that: Keep Reading

Does finance professor David Kass, who presents annual lists of stock picks on Seeking Alpha, make good selections? To investigate, we consider his picks of:

• “10 Stocks for 2020”: APPL, BAC, BRK-A, WBD, JPM, MSFT, OXY, PH, SWK, STNE
• “16 Stocks For 2021”: GOOG, ABBV, AMZN, APPL, BAC, BRK-A, CABO, CHTR, LSXMK, META, MU, MSFT, PCG, PSTH, RBAC, RH
• “12 Stocks For 2022”: GOOG, AMZN, APPL, BAC, BRK-A, CVS, GPN, META, MSFT, NU, NVDA, TECK
• “10 Stocks For 2023”: ATVI, APPL, BRK-A, CVX, DHR, HSY, KHC, OXY, PEP, PGR

We compare the average return for stocks picks each year with that for SPDR S&P 500 ETF Trust (SPY) for the same year as a benchmark. Using dividend-adjusted returns from Yahoo!Finance for SPY and most stock picks and returns from Barchart.com and Investing.com for three picks during their selection years, we find that: Keep Reading

How different are stock market performance metrics for:

• Capital gains only, capital gains plus dividends accrued as cash (spent or saved), and capital gains plus dividends reinvested in the stock market?
• Nominal versus real returns?
• Simple return-to-risk calculations versus Sharpe ratio?

Using quarterly S&P 500 Index levels and dividends, quarterly U.S. Consumer Price Index (CPI) data (all items) and monthly 3-month U.S. Treasury bill (T-bill) yield as the risk-free rate/return on cash during the first quarter of 1988 through the fourth quarter of 2023, we find that: Keep Reading