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Big Reward for Risk in Initial Coin Offerings?

Should investors pursue initial coin offerings (ICO), special-purpose crypto-tokens? In their May 2018 paper entitled “Digital Tulips? Returns to Investors in Initial Coin Offerings”, Hugo Benedetti and Leonard Kostovetsky study the market for crypto-tokens, focusing on: initial pricing; returns from buying at ICO and selling at date of listing on an exchange; and, returns from buying at listing date and holding for various fixed intervals. ICOs typically originate with an offeror’s prospectus detailing a goal, plan, team and offering schedule. Interested parties then register for the offering, with execution typically in stages over several months, some restricted to preferred users, angel investors, venture capitalists and/or accredited investors. The authors also employ Twitter accounts of ICO offerors to test the relationship between Twitter activity and price and to measure post-ICO attrition rate of offerors. Using data for 2,390 ICOs completed by May 2018, including offeror Twitter histories as of May 8, 2018, they find that:

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Better Five-factor Model of Stock Returns?

Which factor models of stock returns are currently best? In their June 2018 paper entitled “q5,  Kewei Hou, Haitao Mo, Chen Xue and Lu Zhang, introduce the q5 model of stock returns, which adds a fifth factor (expected growth) to the previously developed q-factor model (market, size, asset growth, return on equity). They measure expected growth as 1-year, 2-year and 3-year ahead changes in investment-to-assets (this year total assets minus last year total assets, divided by last year total assets) as forecasted monthly via predictive regressions. They define an expected growth factor as average value-weighted returns for top 30% 1-year expected growth minus bottom 30% 1-year expected growth, calculated separately and further averaged for big and small stocks. They examine expected growth as a standalone factor and then conduct an empirical horse race of recently proposed 4-factor, 5-factor (including q5) and 6-factor models of stock returns based on their abilities to explain average return differences for value-weighted extreme tenth (decile) portfolios for 158 significant anomalies. Using monthly return and accounting data for a broad sample of non-financial U.S. common stocks during July 1963–December 2016, they find that:

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Stock Market Behavior Around Mid-year and 4th of July

The middle of the year might be a time for funds to dress their windows and investors to review and revise portfolios. The 4th of July celebration might engender optimism among U.S. investors. Are there any reliable patterns to daily U.S. stock market returns around mid-year and the 4th of July? To check, we analyze the historical behavior of the S&P 500 Index from five trading days before through trading days after both the end of June and the 4th of July. Using daily closing levels of the index for 1950-2017 (68 years), we find that: Keep Reading

Weekly Summary of Research Findings: 6/18/18 – 6/22/18

Below is a weekly summary of our research findings for 6/18/18 through 6/22/18. 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

SACEVS Input Risk Premiums and EFFR

The “Simple Asset Class ETF Value Strategy” seeks diversification across a small set of asset class exchanged-traded funds (ETF), plus a monthly tactical edge from potential undervaluation of three risk premiums:

  1. Term – monthly difference between the 10-year Constant Maturity U.S. Treasury note (T-note) yield and the 3-month Constant Maturity U.S. Treasury bill (T-bill) yield.
  2. Credit – monthly difference between the Moody’s Seasoned Baa Corporate Bonds yield and the T-note yield.
  3. Equity – monthly difference between S&P 500 operating earnings yield and the T-note yield.

Premium valuations are relative to historical averages. How might this strategy react to increases in the Effective Federal Funds Rate (EFFR)? Using monthly values of the three risk premiums, EFFR, total 12-month U.S. inflation and core 12-month U.S. inflation during July 2000 (limited by availability of EFFR) through May 2018 (215 months), we find that: Keep Reading

Currency Exchange Style Factors for Incremental Diversification

Do currency exchange factor strategies usefully diversify a set of conventional asset classes? In their May 2018 paper entitled “Currency Management with Style”, Harald Lohre and Martin Kolrep investigate the systematic harvesting of currency exchange carry, value and momentum strategies, specified as follows and applied to the G10 currencies:

  • Carry – buy (sell) the three equally weighted currency forwards with the highest (lowest) short-term interest rates, reformed monthly.
  • Momentum – buy (sell) the three equally weighted currency forwards with the greatest (least) appreciation over the past three months, reformed monthly.
  • Value (long-term reversion) – buy (sell) the three equally weighted currency forwards with the lowest (highest) change in their real exchange rates, based on purchasing power parity, over the past 60 months, reformed monthly.

They examine in-sample (full-sample) mean-variance relationships for these strategies to assess their value as diversifiers of five conventional asset classes (U.S. stocks, commodities, U.S. Treasury bonds, U.S. corporate investment-grade bonds and U.S. corporate high-yield bonds). They also look at potential out-of-sample benefits of these strategies based on information available at the time of each monthly rebalancing as additions to a risk parity portfolio of the five conventional assets from the perspective. For this out-of-sample test, they consider both minimum variance (tail risk hedging) and mean-variance optimization (return seeking) for aggregating the three currency strategies. Using monthly data for the selected assets from the end of January 1999 through December 2016, they find that: Keep Reading

Doubling Down on Size

“Is There Really an Size Effect?” summarizes research challenging the materiality of the equity size effect. Is there a counter? In their June 2018 paper entitled “It Has Been Very Easy to Beat the S&P500 in 2000-2018. Several Examples”, Pablo Fernandez and Pablo Acin double down on the size effect via a combination of market capitalization thresholds and equal weighting. Specifically, they compare values of a $100 initial investment at the beginning of January 2000, held through April 2018, in:

  • The market capitalization-weighted (MW) S&P 500.
  • The equally weighted (EW) 20, 40, 60 and 80 of the smallest stocks in the S&P 1500, reformed either every 12 months or every 24 months.

All portfolios are dividend-reinvested. Their objective is to provide investors with facts to aid portfolio analysis and selection of investment criteria. Using returns for the specified stocks over the selected sample period, they find that:

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Style Performance by Calendar Month

Trading Calendar presents full-year and monthly cumulative performance profiles for the overall stock market (S&P 500 Index) based on its average daily behavior since 1950. How much do the corresponding monthly behaviors of the various size and value/growth styles deviate from an overall equity market profile? To investigate, we consider the the following six exchange-traded funds (ETF) that cut across capitalization (large, medium and small) and value versus growth:

iShares Russell 1000 Value Index (IWD) – large capitalization value stocks.
iShares Russell 1000 Growth Index (IWF) – large capitalization growth stocks.
iShares Russell Midcap Value Index (IWS) – mid-capitalization value stocks.
iShares Russell Midcap Growth Index (IWP) – mid-capitalization growth stocks.
iShares Russell 2000 Value Index (IWN) – small capitalization value stocks.
iShares Russell 2000 Growth Index (IWO) – small capitalization growth stocks.

Using monthly dividend-adjusted closing prices for the style ETFs and S&P Depository Receipts (SPY) over the period August 2001 through May 2018 (202 months, limited by data for IWS/IWP), we find that: Keep Reading

Doing Momentum with Style (ETFs)

“Beat the Market with Hot-Anomaly Switching?” concludes that “a trader who periodically switches to the hottest known anomaly based on a rolling window of past performance may be able to beat the market. Anomalies appear to have their own kind of momentum.” Does momentum therefore work for style-based exchange-traded funds (ETF)? To investigate, we apply a simple momentum strategy to the following six ETFs that cut across market capitalization (large, medium and small) and value versus growth:

iShares Russell 1000 Value Index (IWD) – large capitalization value stocks.
iShares Russell 1000 Growth Index (IWF) – large capitalization growth stocks.
iShares Russell Midcap Value Index (IWS) – mid-capitalization value stocks.
iShares Russell Midcap Growth Index (IWP) – mid-capitalization growth stocks.
iShares Russell 2000 Value Index (IWN) – small capitalization value stocks.
iShares Russell 2000 Growth Index (IWO) – small capitalization growth stocks.

We test a simple Top 1 strategy that allocates all funds each month to the one style ETF with the highest total return over a set momentum measurement (ranking or lookback) interval. We focus on the baseline ranking interval from “Simple Asset Class ETF Momentum Strategy”, but test sensitivity of findings to ranking intervals ranging from one to 12 months. As benchmarks, we consider an equally weighted and monthly rebalanced combination of all six style ETFs (EW All), buying and holding S&P Depository Receipts (SPY), and holding SPY when the S&P 500 Index is above its 10-month simple moving average and U.S. Treasury bills (T-bills) when the index is below its 10-month simple moving average (SPY:SMA10). We consider the performance metrics used in “Momentum Strategy (SACEMS)”. Using monthly dividend-adjusted closing prices for the style ETFs and SPY, monthly levels of the S&P 500 index and monthly yields for 3-month T-bills during August 2001 (limited by IWS and IWP) through May 2018 (202 months, ), we find that:

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Weekly Summary of Research Findings: 6/11/18 – 6/15/18

Below is a weekly summary of our research findings for 6/11/18 through 6/15/18. 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

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