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ISM PMI and Stock Market Returns

According to the Institute for Supply Management (ISM) ISM, their Manufacturing Report On Business, published since 1931, “is considered by many economists to be the most reliable near-term economic barometer available.” The manufacturing summary component of this report is the Purchasing Managers’ Index (PMI), aggregating monthly inputs from purchasing and supply executives across the U.S. regarding new orders, production, employment, deliveries and inventories. ISM releases PMI for a month at the beginning of the following month. Does PMI predict stock market returns? Using monthly seasonally adjusted PMI data during January 1950 through January 2016 from the Federal Reserve Bank of St. Louis (discontinued and removed) and from press releases thereafter through January 2018, and contemporaneous monthly S&P 500 Index closes (817 months), we find that:

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Weekly Summary of Research Findings: 2/12/18 – 2/16/18

Below is a weekly summary of our research findings for 2/12/18 through 2/16/18. 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.

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Stock Market Valuation Ratio Trends

To determine whether the stock market is expensive or cheap, some experts use aggregate valuation ratios, either trailing or forward-looking, such as earnings-price ratio (E/P) and dividend yield. Operating under a belief that such ratios are mean-reverting, most imminently due to movement of stock prices, these experts expect high (low) future stock market returns when these ratios are high (low). Where are the ratios now? Using the most recent actual and forecasted earnings and dividend data from Standard & Poor’s, we find that: Keep Reading

Optimal Intrinsic Momentum and SMA Intervals Across Asset Classes

What are the optimal intrinsic/absolute/time series momentum (IM) and simple moving average (SMA) measurement intervals for different asset class proxies? To investigate, we use data from the Simple Asset Class ETF Momentum Strategy for the following eight asset class exchange-traded funds (ETF), plus Cash:

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)

For IM tests, we invest in each ETF (Cash) when its return over the past one to 12 months is positive (negative). For SMA tests, we invest in each ETF (Cash) when its price is above (below) its average monthly price over the past two to 12 months. Since SMA rules use price levels and IM rules use returns, IM measurement interval N corresponds to SMA measurement interval N+1. For example, a 6-month IM measurement uses the same start and stop points as a 7-month SMA measurement. We focus on compound annual growth rate (CAGR) and maximum drawdown (MaxDD) as key metrics for comparing different IM and SMA measurement intervals since earliest ETF data availabilities based on the longest IM measurement interval. Using monthly dividend-adjusted closing prices for the asset class proxies and the yield for Cash over the period July 2002 (or inception if not available by then) through January 2018, we find that:

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Inflation Forecast Update

The Inflation Forecast now incorporates actual total and core Consumer Price Index (CPI) data for January 2018. The actual total (core) inflation rate for January is higher than (higher than) forecasted.

January Barometer Over the Long Run

Does long term data support the belief that “as goes January, so goes the rest of the year” (January is the barometer) for the the U.S. stock market? Robert Shiller’s long run sample, which calculates monthly levels of the S&P Composite Stock Index since 1871 as average daily closes during calendar months, offers data for testing. Because average monthly levels differ from monthly closes, we run all tests also on the S&P 500 Index. Using monthly levels of the S&P Composite Stock Index for 1871-2017 (147 years) and monthly and daily closes of the S&P 500 Index for 1950-2017 (68 years), we find that: Keep Reading

Beta Males Make Hedge Fund Alpha

Does appearance-based masculinity predict hedge fund manager performance? In their January 2018 paper entitled “Do Alpha Males Deliver Alpha? Testosterone and Hedge Funds”, Yan Lu and Melvyn Teo use facial width-to-height ratio (fWHR) as a positively related proxy for testosterone level to investigate the relationship between male hedge fund manager testosterone level and hedge fund performance. They each year in January sort hedge funds into tenths (deciles) based on fund manager fWHR and then measure the performance of these decile portfolios over the following year. Their main performance metric is 7-factor hedge fund alpha, which corrects for seven risks proxied by: (1) S&P 500 Index excess return; (2) difference between Russell 2000 Index and S&P 500 Index returns; (3) 10-year U.S. Treasury note (T-note) yield, adjusted for duration, minus 3-month U.S. Treasury bill yield; (4) change in spread between Moody’s BAA bond and T-note, adjusted for duration; and, (5-7) excess returns on straddle options portfolios for currencies, commodities and bonds constructed to replicate trend-following strategies in these asset classes. They collect 3,228 hedge fund manager photographs via Google image searches, choosing the best for each manager based on resolution, degree of forward facing and neutrality of expression. They use these photographs to measure fWHR as the distance between the two zygions (width) relative to the distance between the upper lip and the midpoint of the inner ends of the eyebrows (height). Using these fWHRs, monthly net-of-fee returns and assets under management of 3,868 associated live and dead hedge funds, and monthly risk factor values during January 1994 through December 2015, they find that:

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Doom and the Stock Market

Is proximity to doom good or bad for the stock market? To measure proximity to doom, we use the Doomsday Clock “Minutes-to-Midnight” metric, revised intermittently via the Bulletin of the Atomic Scientists, which “conveys how close we are to destroying our civilization with dangerous technologies of our own making. First and foremost among these are nuclear weapons, but the dangers include climate-changing technologies, emerging biotechnologies, and cybertechnology that could inflict irrevocable harm, whether by intention, miscalculation, or by accident, to our way of life and to the planet.” Using the timeline for the Doomsday Clock since inception (1947) and contemporaneous December levels of Shiller’s S&P Composite Index through early 2018 (25 distinct doom proximity judgments), we find that: Keep Reading

Weekly Summary of Research Findings: 2/6/18 – 2/9/18

Below is a weekly summary of our research findings for 2/6/18 through 2/9/18. 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

Ask for Advisor’s Personal Investing Performance?

Are financial advisors expert guides for their client investors? In their December 2017 paper entitled “The Misguided Beliefs of Financial Advisors”, Juhani Linnainmaa, Brian Melzer and Alessandro Previtero compare investing practices/results of Canadian financial advisors to those of their clients, including trading patterns, fees and returns. They estimate account alphas via multi-factor models. Using detailed data from two large Canadian mutual fund dealers (accounting for about 5% of their sector) for 3,276 Canadian financial advisors and their 488,263 clients, and returns and fees for 3,023 associated mutual funds, during January 1999 through December 2013, they find that:

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