Equity Premium

A subscriber asked about the relationship between the high-yield bond spread and stock market return, with focus on when the latter is entering a bear market. To investigate, we use the ICE BofA US High Yield Index Option-Adjusted Spread (HY Spread) as a proxy for the high-yield bond spread and SPDR S&P 500 ETF Trust (SPY) as a proxy for the U.S. stock market. We look at the following interactions between HY Spread and SPY:

• Daily lead-lag correlations between HY Spread/change in HY Spread and SPY return.
• Monthly lead-lag correlations between HY Spread/change in HY Spread and SPY return.
• Average next-month SPY return by range of monthly changes in HY Spread.
• Monthly changes in HY Spread before the worst next-month SPY returns.
• Next-month SPY returns after the biggest monthly jumps in HY Spread.

Using daily values of HY Spread and daily dividend-adjust SPY prices from the end of December 1996 (limited by HY Spread) through mid-June 2022, we find that: Keep Reading

Are preferred stock strategies, as implemented by exchange-traded funds (ETF), attractive? To investigate, we consider seven of the largest preferred stock ETFs, all currently available, in order of longest to shortest available histories:

• Invesco Financial Preferred (PGF) – generally invests at least 90% of assets in preferred securities of financial institutions.
• iShares Preferred and Income Securities (PFF) – tracks an index composed of U.S. dollar-denominated preferred and hybrid securities.
• Invesco Preferred (PGX) – tracks performance of fixed-rate preferred securities issued in the U.S.
• SPDR ICE Preferred Securities (PSK) – seeks exposure to non-convertible preferred securities with par $25 and aggregate minimum par value $250 million.
• VanEck Vectors Preferred Securities ex Financials (PFXF) – tracks performance of U.S. exchange-listed hybrid debt, preferred stock and convertible preferred stock issued by non-financial corporations.
• First Trust Preferred Securities and Income (FPE) – normally invests at least 80% of assets (including borrowings) in preferred securities and income-producing debt securities, including corporate bonds, high-yield securities and convertible securities.
• Global X U.S. Preferred (PFFD) – invests in a broad basket of U.S. preferred stocks.

We use a monthly rebalanced portfolio of 60% SPDR S&P 500 (SPY) and 40% iShares iBoxx $ Investment Grade Corporate Bond (LQD) (60-40) as a simple hybrid benchmark for all these funds except PGF, for which we use Financial Select Sector SPDR (XLF). We focus on monthly return statistics, along with compound annual growth rates (CAGR) and maximum drawdowns (MaxDD). Using monthly returns for the preferred stock ETFs and benchmarks as available through May 2022, we find that: Keep Reading

What are current estimates of equity risk premiums (ERP) and risk-free rates around the world? In their May 2022 paper entitled “Survey: Market Risk Premium and Risk-Free Rate Used for 95 Countries in 2022”, Pablo Fernandez, Teresa García de Santos and Javier Acin summarize results of a May 2022 email survey of international 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 4,337 specific and credible premium estimates spanning 95 countries for which there are at least six estimates, they find that: Keep Reading

Are low volatility stock strategies, as implemented by exchange-traded funds (ETF), attractive? To investigate, we consider eight of the largest low volatility ETFs, all currently available, in order of longest to shortest available histories:

• Invesco S&P 500 Low Volatility Portfolio (SPLV) – the 100 stocks from the S&P 500 Index with the lowest realized volatility over the past 12 months, reformed quarterly. The benchmark ETF for SPLV is SPDR S&P 500 (SPY).
• iShares Edge MSCI Min Vol USA (USMV) – seeks to track an index composed of U.S. equities that, in the aggregate, have lower volatility characteristics relative to the broader U.S. equity market. The benchmark ETF for USMV is iShares Russell 3000 (IWV).
• iShares Edge MSCI Min Vol EAFE (EFAV) – seeks to track an index composed of developed market equities that, in the aggregate, have lower volatility characteristics relative to the broader developed equity markets, excluding the U.S. and Canada. The benchmark ETF for EFAV is iShares MSCI EAFE Index (EFA).
• iShares Edge MSCI Min Vol Emerging Markets (EEMV) – seeks to track an index composed of emerging market equities that, in the aggregate, have lower volatility characteristics relative to the broader emerging equity markets. The benchmark ETF for EEMV is iShares MSCI Emerging Markets Index (EEM).
• iShares Edge MSCI Min Vol Global (ACWV) – seeks to track an index composed of developed and emerging market equities that, in the aggregate, have lower volatility characteristics relative to the broader developed and emerging equity markets. The benchmark ETF for ACWV is iShares MSCI ACWI (ACWI).
• Invesco S&P International Developed Low Volatility Portfolio (IDLV) – the 200 least volatile stocks of the S&P Developed excluding U.S. and South Korea LargeMid Cap BMI Index over the past 12 months, reformed quarterly. The Index is computed using net return, which withholds taxes applicable to non-resident investors. The benchmark ETF for IDLV is Vanguard FTSE All-Wld ex-US ETF (VEU).
• Invesco S&P MidCap Low Volatility Portfolio (XMLV) –  the 80 out of 400 medium-capitalization stocks from the S&P MidCap 400 Index with the lowest realized volatility over the past 12 months, reformed quarterly. The benchmark ETF for XMLV is SPDR S&P MidCap 400 (MDY).
• Invesco S&P SmallCap Low Volatility Portfolio (XSLV) – the 120 out of 600 small-capitalization stocks from the S&P SmallCap 600 Index with the lowest realized volatility over the past 12 months, reformed quarterly. The benchmark ETF for XSLV is SPDR S&P 600 Small Cap (SLY).

We focus on monthly return statistics, along with compound annual growth rates (CAGR) and maximum drawdowns (MaxDD). Using monthly returns for the low volatility stock ETFs and their benchmark ETFs as available through May 2022, we find that: Keep Reading

Can investors beat the market by exploiting preannounced (anti-value) changes to traditional capitalization-weighted indexes, generally comprised of additions with recent strong performance and deletions with recent weak performance? In their May 2022 paper entitled “The Avoidable Costs of Index Rebalancing”, Robert Arnott, Chris Brightman, Vitali Kalesnik and Lillian Wu examine ways to exploit any momentum and/or reversion in these potentially overvalued additions and undervalued deletions. They focus on the period since October 1989, when S&P began preannouncing (announcement date) changes to the index days or weeks before the effective date of the changes (trade date). They further focus on discretionary changes, distinct from those driven by spinoffs and divestitures (nondiscretionary additions) or bankruptcies and mergers (nondiscretionary deletions). They note that changes in index holdings were made at the market close on the effective date until February 2017, and the prior close thereafter. Using data for 663 S&P 500 Index additions and 299 discretionary deletions during October 1989 through June 2021, they find that:

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

• Invesco DWA Momentum Portfolio (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 (IWV).
• Invesco DWA SmallCap Momentum (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 (IWM).
• iShares Edge MSCI USA Momentum Factor (MTUM) – holds U.S. large-capitalization and mid-capitalization stocks with relatively high momentum. Benchmark is iShares Russell 1000 (IWB).
• First Trust Dorsey Wright Focus 5 (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 (IMTM) – holds international developed market large-capitalization and mid-capitalization stocks with relatively high momentum. Benchmark is iShares MSCI ACWI ex U.S. (ACWX).
• SPDR Russell 1000 Momentum Focus (ONEO) – tracks the Russell 1000 Momentum Focused Factor Index, picking U.S. stocks that have recently outperformed. Benchmark is IWB.
• First Trust Dorsey Wright Dynamic Focus 5 (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 (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 benchmark ETFs according to momentum fund descriptions. Using monthly returns for the eight momentum funds and respective benchmarks as available through April 2022, we find that: Keep Reading

In response to “Best Equity Risk Premium”, a subscriber asked whether the annual equity risk premium estimates of Aswath Damodaran predict stock market returns one year ahead. The cited source offers two 61-year series of annual estimates of the U.S. equity risk premium implied by an S&P 500:

1.  Dividend Discount Model (DDM).
2.  Free Cash Flow to Equity (FCFE).

We calculate S&P 500 Index total annual returns from this source as capital gains plus dividends and then relate this total return series to each of these two implied equity risk premium series. Using the specified data during 1960 through 2021, we find that: Keep Reading

What are the different ways of estimating the equity risk premium, and which one is best? In the April 2022 revision of his paper entitled “Equity Risk Premiums (ERP): Determinants, Estimation and Implications – The 2022 Edition”, Aswath Damodaran updates a comprehensive overview of equity risk premium estimation and application. 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 2021, he concludes that: Keep Reading

How should investors think about surprises in economic data? In their March 2022 paper entitled “Caught by Surprise: How Markets Respond to Macroeconomic News”, Guido Baltussen and Amar Soebhag devise and investigate a real-time aggregate measure of surprises in economic (not financial) variables around the world. Each measurement for each variable consists of release date/time, initial as-released value, associated consensus (median) forecast, number and standard deviation of individual forecasts and any revision to the previous as-released value across U.S., UK, the Eurozone and Japan markets from the Bloomberg Economic Calendar. They classify variables as either growth-related or inflation-related. They apply recursive principal component analysis to aggregate individual variable surprises separately into daily nowcasts of initial growth-related and inflation-related announcement surprises and associated revision surprises. They investigate the time series behaviors of these nowcasts and then examine their interactions with returns for four asset classes:

1. Stocks via prices of front-month futures contracts rolled the day before expiration for S&P 500, FTSE 100, Nikkei 225 and Eurostoxx 50 indexes.
2. Government bonds via prices of front-month futures contracts rolled the day before first notice on U.S., UK, Europe and Japan 10-year bonds.
3. Credit via returns on 5-year credit default swaps for U.S. and Europe investment grade and high yield corporate bond indexes.
4. Commodities via excess returns for the Bloomberg Commodity Index.

Specifically, they test an investment strategy that takes a position equal to the 1-day lagged value of the growth surprise nowcast or the inflation surprise nowcast on the last trading day of each month. They pool regions within an asset class by equally weighting regional markets. Using daily as-released data for 191 economic variables across global regions and the specified monthly asset class price inputs during March 1997 through December 2019, they find that: Keep Reading

Has the quick reaction of exchange-traded funds (ETF) to marketwide news made the stocks they hold more efficient than other stocks, thereby suppressing the strength of anomalies in stocks held? In their March 2022 paper entitled “ETFs, Anomalies and Market Efficiency”, Ilias Filippou, Songrun He and Guofu Zhou investigate effects of ETF ownership within the holdings of previously constructed hedge (long-short) portfolios for 205 stock return anomalies. Each month, they:

• For each anomaly:
  • Partition holdings of each anomaly hedge portfolio into equal-weighted high, middle and low ETF ownership groups.
  • Compare performances of the high and low groups.
• To aggregate anomalies:
  • Subtract the number of times a stock appears in the short sides of the 205 individual anomaly hedge portfolio holdings from the number of times it appears in the long sides to obtain net stock mispricing scores. 
  • Reform a hedge portfolio that is long (short) the tenth of stocks with the highest (lowest) mispricing scores.
  • Partition this aggregate anomaly hedge portfolio into equal-weighted high, middle and low ETF ownership groups.
  • Compare performances of the high and low groups.

Using monthly data for a broad sample of U.S. stocks, 1,509 U.S. equity ETFs and the 205 anomaly hedge portfolios during January 2000 through December 2020, they find that: Keep Reading