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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 2018, we find that: Keep Reading

Betting Against Beta, Plus Market Momentum

betting against beta (BAB) portfolio is long low-beta assets and short high-beta assets, with each side leveraged to a beta of one. Do strong past stock market returns (when investors tend to overweight high-beta stocks) predict an increase in BAB returns? In his June 2018 paper entitled “Time-Varying Leverage Demand and Predictability of Betting-Against-Beta”, Esben Hedegaard tests the prediction that BAB performs better in times and in countries after high past stock market returns in three ways: (1) regression of BAB returns versus past market returns; (2) sorts of BAB returns into fifths (quintiles) based on past market returns; and, (3) a timing strategy that is long BAB half the time and short BAB half the time based on detrended inception-to-date past market returns, scaled to 10% annualized volatility for comparability. Using daily and monthly data, including monthly BAB returns, for U.S. common stocks and the U.S. stock market since 1931 and for 23 other countries from as early as 1988, all through January 2018, he finds that: Keep Reading

Yield Curve as a Stock Market Indicator

Conventional wisdom holds that a steep yield curve (wide U.S. Treasuries term spread) is good for stocks, while a flat/inverted curve is bad. Is this wisdom correct and exploitable? To investigate, we consider in-sample tests of the relationships between several yield curve metrics and future U.S. stock market returns and two out-of-sample signal-based tests. Using average monthly yields for 3-month Treasuries (T-bill), 1-year Treasuries, 3-year Treasuries, 5-year Treasuries and 10-year Treasuries (T-note) as available since April 1953, monthly levels of the S&P 500 Index since March 1953 and monthly dividend-adjusted levels of SPDR S&P 500 (SPY) since January 1993, all through May 2018, we find that: Keep Reading

Weekly Summary of Research Findings: 7/2/18 – 7/6/18

Below is a weekly summary of our research findings for 7/2/18 through 7/6/18. 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

Claims of Hard Work/Expertise Sustain Active Funds?

How do so many active managers who underperform passive investment alternatives continue to attract and retain investors? In their June 2018 paper entitled “How Active Management Survives”, J.B. Heaton and Ginger Pennington test the hypothesis that investors fall prey to the  conjunction fallacy, believing that hard work should generate outperformance. Specifically, they conduct two online surveys:

  • Sample 1: 1,004 respondents over 30 with household income over $100,000 choosing which of two propositions is mostly likely true: “(1) ABC Fund will earn a good return this year for its investors. (2) ABC Fund will earn a good return this year for its investors and ABC Fund employs investment analysts who work hard to identify the best stocks for ABC Fund to invest in.”
  • Sample 2: 1,001 respondents over 30 with household income over $100,000 choosing which of two propositions is mostly likely true: “(1) ABC Fund will earn a good return this year for its investors. (2) ABC Fund will earn a good return this year for its investors and ABC Fund was founded by a successful former Goldman Sachs trader and employs Harvard-trained physicists and Ph.D. economists and statisticians.”

Second choices are inherently less likely because they include the first choices and add conditions to them. The authors further ask in both surveys the degree to which respondents agree that a “person or business can achieve better results on any task by working harder than its competitors.” Using responses to these surveys, they find that: Keep Reading

When Machine Learning Works for Investing

In what areas does machine learning have advantages over conventional financial/investment analysis? In his June 2018 presentation entitled “Nine Financial Applications of Machine Learning”, Marcos Lopez de Prado summarizes investing-related areas in which well-supervised machine learning outperforms conventional methods. Based on relevant research and his experience, he asserts that: Keep Reading

T-bills Beat Most Stocks?

Does conventional reward-for-risk wisdom about the long-run performance of the U.S. stock market translate to the typical stock? In the May 2018 update of his paper entitled “Do Stocks Outperform Treasury Bills?”, Hendrik Bessembinder compares the performance of the typical U.S. stock to that of the 1-month U.S. Treasury bill (T-bill) over monthly, annual, decade and life-of-stock horizons. He also performs simulations to gauge the effectiveness of holding just one stock and of diversifying across portfolios of five, 25, 50 and 100 stocks. Using monthly total (dividend-reinvested) returns for 25,967 U.S. common stocks while listed during July 1926 through December 2016, he finds that: Keep Reading

AAII Investor Sentiment as a Stock Market Indicator

Is conventional wisdom that aggregate retail investor sentiment is a contrary indicator of future stock market return correct? To investigate, we examine the sentiment expressed by members of the American Association of Individual Investors (AAII) via a weekly survey of members. This survey asks AAII members each week (Thursday through Wednesday): “Do you feel the direction of the market over the next six months will be up (bullish), no change (neutral) or down (bearish)?” Only one vote per member is accepted in each weekly voting period.” Survey results are available the market day after the polling period. We define aggregate (net) investor sentiment as percent bullish minus percent bearish. Using outputs of the weekly AAII surveys and prior-day closes of the S&P 500 Index from July 1987 through mid-June 2018 (1,615 surveys and 62  independent 6-month forecast intervals), we find that: Keep Reading

Weekly Summary of Research Findings: 6/25/18 – 6/29/18

Below is a weekly summary of our research findings for 6/25/18 through 6/29/18. 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

Alternative Momentum Metrics for SACEMS?

A subscriber asked whether some different momentum metric might improve performance of the “Simple Asset Class ETF Momentum Strategy” (SACEMS), which each month reforms a portfolio of winners from the following universe based on total return over a specified lookback interval:

PowerShares DB Commodity Index Tracking (DBC)
iShares MSCI Emerging Markets Index (EEM)
iShares MSCI EAFE Index (EFA)
SPDR Gold Shares (GLD)
iShares Russell 2000 Index (IWM)
SPDR S&P 500 (SPY)
iShares Barclays 20+ Year Treasury Bond (TLT)
Vanguard REIT ETF (VNQ)
3-month Treasury bills (Cash)

To investigate, we compare performances of the following alternative monthly momentum metrics to that of the original baseline metric:

  • Average monthly total returns over the lookback interval.
  • Slope of the dividend-adjusted price series over the lookback interval.
  • Sharpe ratio of the monthly total return series over the lookback interval (using Cash return as the risk-free rate, and setting the Sharpe ratio of Cash at zero).

We focus on the equally weighted (EW) Top 3 SACEMS portfolio. We consider all the performance metrics used for the baseline, with emphasis on compound annual growth rates (CAGR) and maximum drawdowns (MaxDD). Using monthly dividend adjusted closing prices for the asset class proxies and the yield for Cash over the period February 2006 (the earliest all ETFs are available) through May 2018 (148 months), we find that: Keep Reading

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