Objective research to aid investing decisions

Value Investing Strategy (Strategy Overview)

Allocations for July 2024 (Final)
Cash TLT LQD SPY

Momentum Investing Strategy (Strategy Overview)

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

Equity Premium

Governments are largely insulated from market forces. Companies are not. Investments in stocks therefore carry substantial risk in comparison with holdings of government bonds, notes or bills. The marketplace presumably rewards risk with extra return. How much of a return premium should investors in equities expect? These blog entries examine the equity risk premium as a return benchmark for equity investors.

Equity Industry/Sector Price Run-ups and Future Returns

A subscriber suggested review of the February 2017 paper “Bubbles for Fama”, in which Robin Greenwood, Andrei Shleifer and Yang You assess Eugene Fama’s claim that stock prices do not exhibit bubbles. They define a bubble candidate as a value-weighted U.S. industry or international sector that rises over 100% in both raw and net of market returns over the prior two years, as well as 50% or more raw return over the prior five years. They define a crash as a 40% drawdown within a two-year interval. They also look at characteristics of industry/sector portfolios identified bubble candidates, including level and change in volatility, level and change in turnover, firm age, return on new versus old companies, stock issuance, book-to-market ratio, sales growth, price-earnings ratio and price acceleration (abruptness of price run-up). They evaluate timing strategies that switch from an industry portfolio to either the market portfolio or cash (with risk-free yield) based on a price run-up signal, or a signal that combines price run-up and other characteristics. Their benchmark is buying and holding the industry portfolio. Using value-weighted returns for 48 U.S. industries (based on SIC code) during January 1926 through March 2014 and for 11 international sectors (based on GICS codes) during October 1985 through December 2014, they find that:

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Are ESG ETFs Attractive?

Do exchange-traded funds selecting stocks based on environmental, social, and governance characteristics (ESG ETF) typically offer attractive performance? To investigate, we compare performance statistics of eight ESG ETFs, all currently available, to those of simple and liquid benchmark ETFs, as follows:

  1. iShares MSCI USA ESG Select ETF (SUSA), with SPDR S&P 500 ETF Trust (SPY) as a benchmark.
  2. iShares MSCI KLD 400 Social ETF (DSI), with SPY as a benchmark.
  3. iShares ESG MSCI EM ETF (ESGE), with iShares MSCI Emerging Markets ETF (EEM) as a benchmark.
  4. iShares ESG Aware MSCI EAFE ETF (ESGD), with iShares MSCI EAFE ETF (EFA) as a benchmark
  5. iShares ESG MSCI USA ETF (ESGU), with SPY as a benchmark.
  6. Nuveen ESG Small-Cap ETF (NUSC), with iShares Russell 2000 ETF (IWM) as a benchmark.
  7. Vanguard ESG U.S. Stock ETF (ESGV), with SPY as a benchmark.
  8. Vanguard ESG International Stock ETF (VSGX), with Vanguard FTSE All-World ex-US Index Fund ETF (VEU) as a benchmark.

We focus on average return, standard deviation of returns, reward/risk (average return divided by standard deviation of returns), compound annual growth rate (CAGR) and maximum drawdown (MaxDD), all based on monthly data. Using monthly dividend-adjusted returns for all specified ETFs since inceptions and for all benchmarks over matched sample periods through June 2024, we find that: Keep Reading

Add Utilities to SACEVS?

What happens if we extend the “Simple Asset Class ETF Value Strategy” (SACEVS) with a utilities risk premium, derived from the yield on Utilities Select Sector SPDR Fund (XLU)? To investigate, we apply the SACEVS methodology to the following asset class exchange-traded funds (ETF), plus cash:

3-month Treasury bills (Cash)
iShares 20+ Year Treasury Bond ETF (TLT)
iShares iBoxx $ Investment Grade Corporate Bond ETF (LQD)
XLU
SPDR S&P 500 ETF Trust (SPY)

This set of ETFs relates to four risk premiums, as specified below: (1) term; (2) credit (default); (3) utilities; and, (4) equity. We focus on effects of adding the utilities risk premium on gross compound annual growth rates (CAGR), maximum drawdowns (MaxDD) and annual Sharpe ratios of the Best Value (picking the most undervalued premium) and Weighted (weighting all undervalued premiums according to degree of undervaluation) versions of SACEVS. Using lagged quarterly S&P 500 earnings, monthly S&P 500 Index levels and monthly yields for 3-month U.S. Treasury bill (T-bill), the 10-year Constant Maturity U.S. Treasury note (T-note), Moody’s Seasoned Baa Corporate Bonds since March 1989 (limited by availability of earnings data), XLU prices and dividends since December 1998 (inception) and monthly dividend-adjusted closing prices for the above asset class ETFs since July 2002, all through May 2024, we find that: Keep Reading

Use Short-term S&P 500 Index Indicators to Predict VIX Futures?

Does the S&P 500 Index (SPX) or the CBOE Volatility Index (VIX) yield better short-term trading signals for stocks and VIX futures? In the May 2024 revision of his paper entitled “Chicken and Egg: Should you use the VIX to time the SPX? Or use the SPX to time the VIX?”, Robert Hanna explores mutual predictive relationships between SPX and VIX, with an eye toward exploitation via market timing strategies. He considers several long-term trend indicators to investigate whether SPX or VIX data offers better SPX return predictions. He considers two types of short-term overbought/oversold predictive rules: (1) short-term relative strength index (RSI) readings of 2, 3 and 4 days; and, (2) short-term high and low readings of 5 to 25 days in length. He applies both sets of short-term rules separately to SPX and VIX to predict movements of SPX and VIX futures. Using daily SPX and VIX levels since 1990 and short-term VIX futures prices since 2007, all through 2023, he finds that: Keep Reading

Testing a Countercyclical Asset Allocation Strategy

“Countercyclical Asset Allocation Strategy” summarizes research on a simple countercyclical asset allocation strategy that systematically raises (lowers) the allocation to an asset class when its current aggregate allocation is relatively low (high). The underlying research is not specific on calculating portfolio allocations and returns. To corroborate findings, we use annual mutual fund and exchange-traded fund (ETF) allocations to stocks and bonds worldwide from the 2024 Investment Company Fact Book data tables to determine annual countercyclical allocations for stocks and bonds (ignoring allocations to money market funds). Specifically:

  • If actual aggregate mutual fund/ETF allocation to stocks in a given year is above (below) 60%, we set next-year portfolio allocation below (above) 60% by the same percentage.
  • If actual aggregate mutual fund/ETF allocation to bonds in a given year is above (below) 40%, we set next-year portfolio allocation below (above) 40% by the same percentage.

We then apply next-year allocations to stock (Fidelity Fund, FFIDX) and bond (Fidelity Investment Grade Bond Fund, FBNDX) mutual funds that have long histories. Based on Fact Book annual publication dates, we rebalance at the end of April each year. Using the specified actual fund allocations for 1984 through 2023 and FFIDX and FBNDX May through April total returns and end-of-April 1-year U.S. Treasury note (T-note) yields for 1985 through 2024, we find that: Keep Reading

Using Peer Firm Information/Relationships to Rank Stocks

Are the industry membership of a firm, as designated by Standard Industrial Classification (SIC) code, and the position of the firm within its industry good predictors of the performance of its stock? In their May 2024 paper entitled “Decoding Cross-Stock Predictability: Peer Strength versus Firm-Peer Disparities”, Doron Avramov, Shuyi Ge, Shaoran Li and Oliver Linton devise the following two industry related stock metrics and test their abilities to predict stock returns:

  1. Peer Index (PI) – calculated for each firm via a multi-input, inception-to-date regression to predict next-month stock return, replacing firm characteristics by the contemporaneous average values for all firms in its industry as inputs.
  2. Peer-Deviation Index (PDI) – calculated for each firm via a multi-input, inception-to-date regression to predict next-month stock return using firm characteristics minus the contemporaneous average values of these characteristics for all firms in its industry as inputs (indicating the standing of the firm within its industry).

Inputs consist of 94 firm-specific characteristics and 8 industry-related characteristics, organized into six groups: momentum, value versus growth, investment, profitability, trading frictions and intangibles. Using monthly values for the selected 102 firm/industry characteristics and monthly returns for common stocks in the top 80% of AMEX/NYSE/NASDAQ  market capitalizations during January 1980 through March 2022, they find that: Keep Reading

Add REITs to SACEVS?

What happens if we extend the “Simple Asset Class ETF Value Strategy” (SACEVS) with a real estate risk premium, derived from the yield on equity Real Estate Investment Trusts (REIT), represented by the FTSE NAREIT Equity REITs Index? To investigate, we apply the SACEVS methodology to the following asset class exchange-traded funds (ETF), plus cash:

3-month Treasury bills (Cash)
iShares 20+ Year Treasury Bond (TLT)
iShares iBoxx $ Investment Grade Corporate Bond (LQD)
SPDR Dow Jones REIT (RWR) through September 2004 dovetailed with Vanguard REIT ETF (VNQ) thereafter
SPDR S&P 500 (SPY)

This set of ETFs relates to four risk premiums, as specified below: (1) term; (2) credit (default); (3) real estate; and, (4) equity. We focus on effects of adding the real estate risk premium on gross compound annual growth rates (CAGR), maximum drawdowns (MaxDD) and annual Sharpe ratios of the Best Value (picking the most undervalued premium) and Weighted (weighting all undervalued premiums according to degree of undervaluation) versions of SACEVS. Using lagged quarterly S&P 500 earnings, monthly S&P 500 Index levels and monthly yields for 3-month U.S. Treasury bill (T-bill), the 10-year Constant Maturity U.S. Treasury note (T-note), Moody’s Seasoned Baa Corporate Bonds and FTSE NAREIT Equity REITs Index since March 1989 (limited by availability of earnings data), and monthly dividend-adjusted closing prices for the above asset class ETFs since July 2002, all through May 2024, we find that: Keep Reading

Are Low Volatility Stock ETFs Working?

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:

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 2024, we find that: Keep Reading

Are IPO ETFs Working?

Are exchange-traded funds (ETF) focused on Initial Public Offerings of stocks (IPO) attractive? To investigate, we consider three of the largest IPO ETFs and one recent Special Purpose Acquisition Company (SPAC) ETF, one of which is no longer available, in order of longest to shortest available histories:

We focus on monthly return statistics, along with compound annual growth rates (CAGR) and maximum drawdowns (MaxDD). For all these ETFs, we use SPDR S&P 500 (SPY) as the benchmark. Using monthly returns for the IPO ETFs and SPY as available through April 2024, we find that:

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Correlations of Stock and Bond Returns Globally

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:

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