Objective research to aid investing decisions

Value Investing Strategy (Strategy Overview)

Allocations for December 2020 (Final)
Cash TLT LQD SPY

Momentum Investing Strategy (Strategy Overview)

Allocations for December 2020 (Final)
1st ETF 2nd ETF 3rd ETF

Investing Expertise

Can analysts, experts and gurus really give you an investing/trading edge? Should you track the advice of as many as possible? Are there ways to tell good ones from bad ones? Recent research indicates that the average “expert” has little to offer individual investors/traders. Finding exceptional advisers is no easier than identifying outperforming stocks. Indiscriminately seeking the output of as many experts as possible is a waste of time. Learning what makes a good expert accurate is worthwhile.

Do ETFs Following Gurus/Insiders Work?

Do exchange-traded funds (ETF) that attempt to mimic holdings of hedge fund gurus and/or firm insiders offer attractive performance? To investigate, we consider seven ETFs, four live and three dead, in order of introduction:

    • Invesco Insider Sentiment (NFO) – focuses on stocks attracting interest of insiders such as company executives, fund managers and sell side analysts. This fund is dead as of February 2020.
    • Invesco BuyBack Achievers (PKW) – tracks the Nasdaq US BuyBack Achievers Index, comprised of stocks of U.S. firms with a net decline in shares outstanding of 5% or more in the last 12 months.
    • Direxion All Cap Insider Sentiment (KNOW) –  tracks the S&P Composite 1500 Executive Activity & Analyst Estimate Index, comprised of U.S. stocks that have favorable analyst ratings and are being acquired by firm insiders (top management, directors and large institutions). This fund is dead as of October 2020.
    • AlphaClone Alternative Alpha – (ALFA) – tracks the proprietary AlphaClone Hedge Fund Masters Index, comprised of U.S. securities held by the highest ranked managers of  hedge funds and institutions.
    • Global X Guru Index (GURU) – tracks the Solactive Guru Index, comprised of the highest conviction ideas from a select pool of hedge funds.
    • Direxion iBillionaire (IBLN) –  tracks the proprietary iBillionaire Index, comprised of 30 U.S. mid and large cap securities. This fund is dead as of April 2018.
    • Goldman Sachs Hedge Industry VIP (GVIP) – tracks the proprietary GS Hedge Fund VIP Index, comprised of stocks appearing most frequently among the top 10 equity holdings of fundamentally driven hedge fund managers.

We use SPDR S&P 500 (SPY) as a simple benchmark for all these ETFs. We focus on monthly return statistics, along with compound annual growth rates (CAGR) and maximum drawdowns (MaxDD). Using monthly returns for the above guru/insider-following ETFs and SPY as available through October 2020, we find that: Keep Reading

Online, Real-time Test of AI Stock Picking

Will equity funds “managed” by artificial intelligence (AI) outperform human investors? To investigate, we consider the performance of AI Powered Equity ETF (AIEQ), which “seeks long-term capital appreciation within risk constraints commensurate with broad market US equity indices.” Per the offeror, the EquBot model supporting AIEQ: “…leverages IBM’s Watson AI to conduct an objective, fundamental analysis of U.S.-listed common stocks and real estate investment trusts…based on up to ten years of historical data and apply that analysis to recent economic and news data. Each day, the EquBot Model…identifies approximately 30 to 125 companies with the greatest potential over the next twelve months for appreciation and their corresponding weights… The EquBot model limits the weight of any individual company to 10%. At times, a significant portion of the Fund’s assets may consist of cash and cash equivalents.” We use SPDR S&P 500 (SPY) as a simple benchmark for AIEQ performance. Using daily and monthly dividend-adjusted closes of AIEQ and SPY from AIEQ inception (October 18, 2017) through October 2020, we find that: Keep Reading

Skillful Advice from Seeking Alpha?

Do non-professional analysts who publish on Seeking Alpha offer valuable stock-picking advice? In their August 2020 paper entitled “The Cross-Section of Non-Professional Analyst Skill”, Michael Farrell, Russell Jame and Tian Qiu measure skill among such analysts as the hypothetical abnormal return an investor would earn by following reports/recommendations that focus on one common stock over 5-day or 63-day post-publication holding intervals. They classify recommendations as buy or sell using either: (1) disclosed author positions, or (2) sentiment of associated reports inferred from word usage. They measure abnormal return for each recommendation as its 6-factor alpha, adjusting for market, size, book-to-market, profitability, investment and momentum factors calculated from daily returns from 13 months to one month before the recommendation. They further test an implementable trading strategy that buys (sells) at the ask (bid) and subsequently sells (buys) at the bid (ask) price at the end of the holding period, with and without delays of 24 to 72 hours after publication. Using 123,120 Seeking Alpha research reports prepared by 1,879 non-professional analysts (each with at least 10 qualifying reports) and focused on single common stocks, along with contemporaneous stock and factor returns, during 2005 through 2017, they find that:

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How Canadian Pension Funds Outperform

Which institutional investors do best and why? In the September 2020 update of their paper entitled “The Canadian Pension Fund Model: A Quantitative Portrait”, Alexander Beath, Sebastien Betermier, Chris Flynn and Quentin Spehner compare performances of Canadian pension funds and those of other countries, focusing on Sharpe ratio of the fund assets, Sharpe ratio of the fund net portfolio (long assets and short liabilities) and correlation between fund assets and liabilities. They look at both large (over $10 billion U.S. dollars in assets as of 2018) and small funds. They consider two test periods, five years (2014-2018) and 15 years (2004-2018), excluding funds with missing annual data. The 5-five year sample has 250 funds from 11 countries. The 15-year sample has 105 funds. After comparing performance, they look for reasons why Canadian performance differs. Using performance data, asset allocation strategies and cost structures for the selected 250 pension funds, they find that:

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Choosing Investment Managers Poorly?

Do sophisticated investors choose investment managers wisely? In their July 2020 paper entitled “Choosing Investment Managers”, Amit Goyal, Sunil Wahal and Deniz Yavuz investigate how institutional investors select investment managers for public equity and fixed income portfolios. For each actual selection, they construct a group of non-selected investment managers competing in the same geographic region, style and year (average 94 for equity and 72 for fixed income). They focus on two selection criteria:

  1. Investment manager past performance (returns and assets under management for each product offered as collected by eVestment).
  2. Relationships among institutional investors, investment managers and consultants (as collected by Relationship Science).

Using 6,939 investment manager selections (5,005 equity and 1,934 fixed income) by 2,005 global institutions delegating over $1.6 trillion in assets to 775 unique managers during 2002 through 2017, they find that:

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Performance of Yield Enhancement Products

Should investors buy yield enhancement products (YEP), which typically offer higher-than-market yields from a package comprised of an underlying stock or equity index and a series of short put options? In the August 2020 version of her paper entitled “Engineering Lemons”, Petra Vokata examines gross and net performances of YEPs, which embed fees as a front-end discount (load) allocated partly to issuers and partly to distributing brokers as a commission. Using descriptions of underlying assets and cash flows before and at maturity for 28,383 YEPs linked to U.S. equity indexes or stocks and issued between January 2006 and September 2015, and contemporaneous Cboe S&P 500 PutWrite Index (PUT) returns as a benchmark, she finds that:

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Active Investment Managers and Market Timing

Do active investment managers as a group successfully time the stock market? The National Association of Active Investment Managers (NAAIM) is an association of registered investment advisors. “NAAIM member firms who are active money managers are asked each week to provide a number which represents their overall equity exposure at the market close on a specific day of the week (usually Wednesday). Responses can vary widely [200% Leveraged Short; 100% Fully Short; 0% (100% Cash or Hedged to Market Neutral); 100% Fully Invested; 200% Leveraged Long].” The association each week releases (usually on Thursday) the average position of survey respondents as the NAAIM Exposure Index (NEI).” Using historical weekly survey data and Thursday-to-Thursday weekly dividend-adjusted returns for SPDR S&P 500 (SPY) over the period July 2006 through August 2020 (736 surveys), we find that: Keep Reading

When Institutional Investors Seek Safety

How do mutual funds and hedge funds change their stock holdings in response to a sharp market crash? In their July 2020 paper entitled “Where Do Institutional Investors Seek Shelter when Disaster Strikes? Evidence from COVID-19”, Simon Glossner, Pedro Matos, Stefano Ramelli and Alexander Wagner analyze changes in institutional and retail stock holdings during the first quarter of 2020. Using a February-March 2020 snapshot of returns and firm accounting data for non-financial stocks in the Russell 3000 Index, institutional holdings of these stocks as percentages of shares outstanding during the fourth quarter of 2018 through the first quarter of 2020, and number of Robinhood clients (representing retail investors) holding these stocks on December 31, 2019 and March 31, 2020, they find that:

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Allocations and Returns of Endowments

How do U.S. non-profit endowment funds allocate and perform? In their November 2019 paper entitled “The Risk, Reward, and Asset Allocation of Nonprofit Endowment Funds”, Andrew Lo, Egor Matveyev and Stefan Zeume examine recent asset allocations and investment returns of U.S. public non-profit endowment funds. Due to the unstructured nature of asset reporting, they manually assign each asset in each fund to one of nine categories: (1) public equity; (2) fixed income; (3) private equity; (4) cash instruments; (5) hedge funds; (6) real estate; (7) real assets and real return; (8) trusts; and, (9) cooperative investments. Using tax return data encompassing 34,170 endowment funds during 2009 through 2018, they find that: Keep Reading

GMO Forecast Accuracy Test

A subscriber suggested an update of “GMO’s Stunningly Accurate Forecast?” with out-of-sample testing of GMO forecasts. To investigate, we test GMO’s 7-Year asset class real return forecasts of December 31, 2010 and July 31, 2013. We first match the 11 GMO asset classes covered in these forecasts to exchange-traded funds (ETF), as follows:

  1. U.S. equities (large cap) – SPDR S&P 500 ETF Trust (SPY).
  2. U.S. equities (small cap) – iShares Russell 2000 ETF (IWM).
  3. U.S. high quality – Invesco S&P 500 Quality ETF (SPHQ).
  4. International equities (large cap) – iShares MSCI EAFE ETF (EFA).
  5. International equities (small cap) – iShares MSCI EAFE Small-Cap ETF (SCZ).
  6. Emerging equities – iShares MSCI Emerging Markets ETF (EEM).
  7. U.S. bonds (government) – iShares 20+ Year Treasury Bond ETF (TLT).
  8. International bonds (government) – SPDR Bloomberg Barclays International Treasury Bond ETF (BWX).
  9. Emerging bonds – iShares J.P. Morgan USD Emerging Markets Bond ETF (EMB).
  10. Inflation-indexed bonds – iShares TIPS Bond ETF (TIP).
  11. Short-term U.S. Treasuries (30 days to 2 years) – iShares 1-3 Year Treasury Bond ETF (SHY).

We adjust monthly ETF returns for inflation using monthly changes in U.S. Consumer Price Index (CPI), with change in CPI for July 2020 estimated as the monthly average for the rest of the sample. In contrast, GMO apparently assumes constant annualized inflation of 2.5% for both forecasts. We then calculate real compound annual growth rates (CAGR) for each over specified forecast horizons. Using GMO forecasts, dividend-adjusted ETF prices and CPI data during December 2020 through July 2020, we find that: Keep Reading

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