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Are Equity Index Covered Call ETFs Working?

Is systematically selling covered call options on equity indexes, as implemented by exchange-traded funds (ETF), attractive? To investigate, we consider four equity covered call ETFs:

  1. Invesco S&P 500 BuyWrite ETF (PBP) – seeks to track the CBOE S&P 500 BuyWrite Index (BXM).
  2. Global X S&P 500 Covered Call ETF (HSPX) – seeks to track the CBOE S&P 500 2% OTM BuyWrite Index (BXY).
  3. Global X NASDAQ 100 Covered Call ETF (QYLD) – seeks to track the CBOE NASDAQ-100 BuyWrite Index (BXN).
  4. First Trust BuyWrite Income ETF (FTHI) – sells at-the-money to slightly out-of-the-money covered calls on the S&P 500 Index, laddered with expirations of less than one year (we use BXM as a benchmark).

We focus on average monthly return, standard deviation of monthly returns, sample period cumulative return and maximum drawdown (MaxDD) based on monthly data. We consider SPDR S&P 500 (SPY) and Invesco QQQ Trust (QQQ) as underlying stock indexes. Using monthly dividend-adjusted returns for the four covered call ETFs since inceptions and for all benchmarks/underlying indexes through June 2019, we find that: Keep Reading

Simple Debt Class Mutual Fund Momentum Strategy

A subscriber requested confirmation of the performance of a simple momentum strategy that each month selects the best performing debt mutual fund based on total return over the past three months. To investigate, we test a simple strategy on the following 12 mutual funds (those with the longest histories from a proposed list of 14 funds):

T. Rowe Price New Income (PRCIX)
Thrivent Income A (LUBIX)
Vanguard GNMA Securities (VFIIX)
T. Rowe Price High-Yield Bonds (PRHYX)
T. Rowe Price Tax-Free High Yield Bonds (PRFHX)
Vanguard Long-Term Treasury Bonds (VUSTX)
T. Rowe Price International Bonds (RPIBX)
Fidelity Convertible Securities (FCVSX)
PIMCO Short-Term A (PSHAX)
Fidelity New Markets Income (FNMIX)
Eaton Vance Government Obligations C (ECGOX)
Vanguard Long-Term Bond Index (VBLTX)

We consider a strategy that allocates funds at the end of each month based on total returns over a specified ranking (lookback) interval to the Top 1, equally weighted (EW) Top 2, EW Top 3, EW Top 4 or EW Top 5 funds. We determine the first winners in November 1988 so that at least nine funds are available for lookback interval sensitivity testing. As a benchmark, we use the equally weighted and monthly rebalanced combination of all available funds (EW All). Using monthly dividend-adjusted closing prices for the 12 mutual funds from inceptions through June 2019, we find that: Keep Reading

Stock Market Earnings Yield and Inflation Over the Long Run

How does the U.S. stock market earnings yield (inverse of price-to-earnings ratio, or E/P) interact with the U.S. inflation rate over the long run? Is any such interaction exploitable? To investigate, we employ the long run dataset of Robert Shiller. Using monthly data for the S&P Composite Stock Index, estimated aggregate trailing 12-month earnings and dividends for the stocks in this index, and estimated U.S. Consumer Price Index (CPI) during January 1871 through June 2019 (over 148 years), and estimated monthly yield on 1-year U.S. Treasury bills (T-bills) since January 1951, we find that:

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Leading Economic Index and the Stock Market

The Conference Board “publishes leading, coincident, and lagging indexes designed to signal peaks and troughs in the business cycle for major economies around the world,” including the widely cited Leading Economic Index (LEI) for the U.S. Does the LEI predict stock market behavior? Using the as-released monthly change in LEI from archived Conference Board press releases and contemporaneous dividend-adjusted daily levels of SPDR S&P 500 (SPY) for June 2002 through mid-July 2019 (206 monthly LEI observations), we find that: Keep Reading

Should Investors Care About “the Way Things Are Going”?

Are broad measures of public sociopolitical sentiment relevant to investors? Do they predict stock returns as indicators of exuberance and fear? To investigate, we relate S&P 500 Index return and 12-month trailing S&P 500 price-operating earnings ratio (P/E) to the percentage of respondents saying “yes” to the recurring Gallup polling question: “In general, are you satisfied or dissatisfied with the way things are going in the United States at this time?” Since individual polls span several days, we use S&P 500 Index levels for about the middle of the polling interval. To calculate market P/E, we use current S&P 500 Index level and most recent quarterly aggregate operating earnings. Using Gallup polling resultsS&P 500 Index levels and 12-month trailing S&P 500 operating earnings as available during July 1990 (when polling frequency becomes about monthly) through June 2019, we find that: Keep Reading

Weekly Summary of Research Findings: 7/29/19 – 8/2/19

Below is a weekly summary of our research findings for 7/29/19 through 8/2/19. These summaries give you a quick snapshot of our content the past week so that you can quickly decide what’s relevant to your investing needs.

Subscribers: To receive these weekly digests via email, click here to sign up for our mailing list. Keep Reading

OFR FSI as Stock Market Return Predictor

Is the Office of Financial Research Financial Stress Index (OFR FSI), described in “The OFR Financial Stress Index”, useful as a U.S. stock market return predictor? OFR FSI is a daily snapshot of global financial market stress, distilling more than 30 indicators via a dynamic weighting scheme. The index drops and adds indicators over time as some become obsolete and new ones become available. Unlike some other financial stress indicators, past OFR FSI series values do not change due to any periodic renormalization and are therefore suitable for backtesting. To investigate OFR FSI power to predict U.S. stock market returns, we relate level of and change in OFR FSI to SPDR S&P 500 (SPY) returns. Using daily and monthly values of OFR FSI and SPY total returns during January 2000 (OFR FSI inception) through June 2019, we find that:

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Investors vs. Matched Robo-investors

Would retail investors improve portfolio performance by using robo-advisors to manage holdings they have selected? In their July 2019 paper entitled “Artificial Intelligence Alter Egos:Who benefits from Robo-investing?”, Catherine D’Hondt, Rudy De Winne, Eric Ghysels and Steve Raymond compare performances of portfolios held by each of a large sample of actual individual investors to that of a robo-investor constrained to the stocks and exchange-traded funds (ETF) held by that investor over a rolling 2-year historical window. They consider three robo-investor strategies:

  1. Mean-variance optimization with guiding average and variance estimates based straightforwardly on 2-year rolling historical windows and parameters set to maximize Sharpe ratio.
  2. Mean-variance optimization guided by machine learning algorithms and sophisticated covariance estimators, with two variations in variance estimation.
  3. Equal weight.

Robo-investors may hold cash, but they may not sell short, with focus on quarterly portfolio rebalancing. They measure portfolio performance monthly and exclude trading frictions. Using common stock/exchange-traded fund (ETF) trading records for 20,622 individual Belgian brokerage accounts during January 2003 through March 2012, they find that:

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The BGSV Portfolio

How might an investor construct a portfolio of very risky assets? To investigate, we consider:

  • First, diversifying with monthly rebalancing of:
    1. Bitcoin Investment Trust (GBTC), representing a very long-term option on Bitcoins.
    2. VanEck Vectors Junior Gold Miners ETF (GDXJ), representing a very long-term option on gold.
    3. ProShares Short VIX Short-Term Futures (SVXY), to capture part of the U.S. stock market volatility risk premium by shorting short-term S&P 500 Index implied volatility (VIX) futures. SVXY has a change in investment objective at the end of February 2018 (see “Using SVXY to Capture the Volatility Risk Premium”).
  • Second, capturing upside volatility and managing drawdown of this portfolio via gain-skimming to a cash position.

We assume equal initial allocations of $10,000 to each of the three risky assets. We execute a monthly skim as follows: (1) if the risky assets have month-end combined value less than combined initial allocations, we rebalance to equal weights for next month; or, (2) if the risky assets have combined month-end value greater than combined initial allocations, we rebalance to initial allocations and move the excess permanently (skim) to cash. We conservatively assume monthly portfolio reformation frictions of 1% of month-end combined value of risky assets. We assume accrued skimmed cash earns the 3-month U.S. Treasury bill (T-bill) yield. Using monthly prices of GBTC, GDXJ and SVXY adjusted for splits and dividends and contemporaneous T-bill yield during May 2015 (limited by GBTC) through June 2019, we find that:

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T-bills Beat Most Global Stocks?

Do most stocks worldwide beat the risk-free rate of return? In their July 2019 paper entitled “Do Global Stocks Outperform US Treasury Bills?”, Hendrik Bessembinder, Te-Feng Chen, Goeun Choi and John Wei  compare returns of individual global common stocks to that of 1-month U.S. Treasury bills (T-bills). They screen stock price data for obvious errors and filter/correct accordingly. For delisted stocks with no delisting return available, they set the final return to -30%. Using monthly returns with reinvested dividends in U.S. dollars for 17,505 U.S. and 44,476 non-U.S. stocks across 41 other countries (25 developed and 16 emerging) and monthly T-bill yield during 1990 through 2018, they find that:

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