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Momentum Strategy, Value Strategy and Trading Calendar Updates

We have updated monthly Simple Asset Class ETF Momentum Strategy (SACEMS) winners and associated performance data at “Momentum Strategy”. We have updated monthly Simple Asset Class ETF Value Strategy (SACEVS) allocations and associated performance data at “Value Strategy”. We have also updated performance data for the “Combined Value-Momentum Strategy”.

We have updated the “Trading Calendar” to incorporate data for September 2018.

Weekly Summary of Research Findings: 9/24/18 – 9/28/18

Below is a weekly summary of our research findings for 9/24/18 through 9/28/18. 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

Preliminary Momentum Strategy and Value Strategy Updates

The home page“Momentum Strategy” and “Value Strategy” now show preliminary Simple Asset Class ETF Momentum Strategy (SACEMS) and Simple Asset Class ETF Value Strategy (SACEVS) positions for October 2018. For SACEMS, the top three positions are very unlikely to change by the close, but their order may change. For SACEVS, allocations are very unlikely to change by the close.

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 the effects of adding the real estate risk premium on Compound annual growth rates (CAGR) and Maximum drawdowns (MaxDD) 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 during March 1989 through August 2018 (limited by availability of earnings data), and monthly dividend-adjusted closing prices for the above asset class ETFs during July 2002 through August 2018 (194 months, limited by availability of TLT and LQD), we find that: Keep Reading

Predicting Crypto-asset Returns with Past Returns-Volume

Do crypto-asset trading volumes usefully predict returns? In the August 2018 draft of their paper entitled “Trading Volume in Cryptocurrency Markets”, Daniele Bianchi and Alexander Dickerson investigate the power of crypto-asset trading volumes to predict future returns. They calculate volumes and returns based on either 12-hour or 24-hour intervals. They process these inputs as follows:

  • To detect volume abnormalities, they estimate its log deviation from trend over a rolling 21-interval window. To put different crypto-assets on an equal footing, they then standardized by dividing by its log standard deviation over the same window.
  • They measure past returns over the same interval, denominated in bitcoins, (thereby including Bitcoin only indirectly). To emphasize the most liquid exchanges, they weight returns by volume when aggregating.

To assess economic significance of findings, they double-sort crypto-assets first into two to four groups ranked by the return metric and then within each group into three or four subgroups ranked by the volume metric. Using intraday (10-minute) price and volume data for 26 crypto-assets from over 150 exchanges (90% of total crypto-asset market capitalization), each denominated in bitcoins, during January 1, 2017 through May 10, 2018, they find that:

Keep Reading

Are Managed Futures ETFs Working?

Are managed futures, as implemented by exchange-traded funds (ETF), attractive? To investigate, we consider three managed futures ETFs, all currently available:

  1. WisdomTree Managed Futures Strategy (WTMF).
  2. First Trust Morningstar Managed Futures Strategy (FMF).
  3. ProShares Managed Futures Strategy (FUT).

We focus on compound annual growth rate (CAGR), maximum drawdown (MaxDD) and correlation of returns with those of SPDR S&P 500 (SPY) as key performance statistics. We use Eurekahedge CTA/Managed Futures Hedge Fund Index (the index) as a benchmark. Using monthly returns for the three funds as available through August 2018, and contemporaneous monthly returns for the benchmark index and SPY, we find that: Keep Reading

Are Equity Put-Write ETFs Working?

Is systematically selling equity put options, as implemented by exchange-traded funds (ETF), attractive? To investigate, we consider four equity put-write ETFs, two dead and two living:

  1. US Equity High Volatility Put Write (HVPW) – oriented toward individual stocks (dead).
  2. ALPS Enhanced Put Write Strategy (PUTX) – index-oriented (dead).
  3. WisdomTree CBOE S&P500 PutWriteStrat (PUTW) – index-oriented (living).
  4. BMO US Put Write (ZPW.TO) – oriented toward individual stocks (living).

Because available samples are short, we focus on average daily return, standard deviation of daily returns and sample period cumulative return. For the living ETFs, we include maximum drawdowns (MaxDD) based on daily data. We consider SPDR S&P 500 (SPY) and CBOE S&P 500 PutWrite Index (PUT) as benchmarks. Using daily returns for the four ETFs as available through early September 2018, and contemporaneous daily returns for SPY and PUT, we find that: Keep Reading

Lunar Cycle and Stock Returns

Does the lunar cycle still (since our last look seven years ago) affect the behavior of investors/traders, and thereby influence stock returns? In the August 2001 version of their paper entitled “Lunar Cycle Effects in Stock Returns” Ilia Dichev and Troy Janes conclude that: “returns in the 15 days around new moon dates are about double the returns in the 15 days around full moon dates. This pattern of returns is pervasive; we find it for all major U.S. stock indexes over the last 100 years and for nearly all major stock indexes of 24 other countries over the last 30 years.” To refine this conclusion and test recent data, we examine U.S. stock returns around new and full moons since 1990. When the date of a new or full moon falls on a non-trading day, we assign it to the nearest trading day. Using dates for new and full moons for January 1990 through August 2018 as listed by the U.S. Naval Observatory (355 full and 354 new moons) and contemporaneous daily closing prices for the S&P 500 Index, we find that: Keep Reading

Weekly Summary of Research Findings: 9/17/18 – 9/21/18

Below is a weekly summary of our research findings for 9/17/18 through 9/21/18. 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

A Few Notes on Muscular Portfolios

Brian Livingston introduces his 2018 book, Muscular Portfolios: The Investing Revolution for Superior Returns with Lower Risk, as follows: “What we laughingly call the financial ‘services’ industry is a cesspool filled with sharks intent on siphoning your money away and making it their own. The good news is that it is absolutely possible to grow your savings with no fear of financial sharks or stock market crashes. In the past few years, we’ve seen an explosion of low-cost index funds, along with serious mathematical breakthroughs in how to combine these funds into low-risk portfolios. …This book shows you how.  …You can start with just a little money and make it grow.” Based on research from multiple sources and extensions of that research, he concludes that: Keep Reading

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