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Equity Premium

Governments are largely insulated from market forces. Companies are not. Investments in stocks therefore carry substantial risk in comparison with holdings of government bonds, notes or bills. The marketplace presumably rewards risk with extra return. How much of a return premium should investors in equities expect? These blog entries examine the equity risk premium as a return benchmark for equity investors.

Fama-French 5-factor Model and Global Stocks

Does the Fama-French  5-factor model (market, size, book-to-market, profitability, investment) of stock returns work for stocks worldwide? In their May 2021 paper entitled “Size, Value, Profitability, and Investment Effects in International Stock Returns: Are They Really There?”, Nusret Cakici and Adam Zaremba test the performance of the 5-factor model in global developed markets. They consider big and small stocks separately. They consider four regions (North America, Europe, Japan and Asia-Pacific), as well as the global market. They lag all accounting data by six months and calculate returns in U.S. dollars. Using data in U.S. dollars for 65,000 stocks from 23 countries during December 1987 through March 2019 (with tests starting July 1990), they find that:

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Are Low Volatility Stock ETFs Working?

Are low volatility stock strategies, as implemented by exchange-traded funds (ETF), attractive? To investigate, we consider eight of the largest low volatility ETFs, all currently available, in order of longest to shortest available histories:

We focus on monthly return statistics, along with compound annual growth rates (CAGR) and maximum drawdowns (MaxDD). Using monthly returns for the low volatility stock ETFs and their benchmark ETFs as available through April 2021, we find that: Keep Reading

Are Equity Momentum ETFs Working?

Are stock and sector momentum strategies, as implemented by exchange-traded funds (ETF), attractive? To investigate, we consider eight momentum-oriented equity ETFs, all currently available, in order of longest to shortest available histories:

We focus on monthly return statistics, along with compound annual growth rates (CAGR) and maximum drawdowns (MaxDD). We assign benchmark ETFs according to momentum fund descriptions. Using monthly returns for the eight momentum funds and respective benchmarks as available through April 2021, we find that: Keep Reading

Best Equity Risk Premium

What are the different ways of estimating the equity risk premium, and which one is best? In his March 2021 paper entitled “Equity Risk Premiums (ERP): Determinants, Estimation and Implications – The 2021 Edition”, Aswath Damodaran updates a comprehensive overview of equity risk premium estimation and application. He examines why different approaches to estimating the premium disagree and how to choose among them. Using data from multiple countries (but focusing on the U.S.) over long periods through the end of 2020, he concludes that: Keep Reading

Are IPO ETFs Working?

Are exchange-traded funds (ETF) focused on Initial Public Offerings of stocks (IPO) attractive? To investigate, we consider three of the largest IPO ETFs and one recent Special Purpose Acquisition Company (SPAC) ETF, all currently available with moderate trading volumes, in order of longest to shortest available histories:

We focus on monthly return statistics, along with compound annual growth rates (CAGR) and maximum drawdowns (MaxDD). For all these ETFs, we use SPDR S&P 500 (SPY) as the benchmark. Using monthly returns for the IPO ETFs and SPY as available through March 2021, we find that:

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SPAC Returns

Should investors consider adding Special Purpose Acquisition Company (SPAC) Initial Public Offerings (IPO), which boomed in 2020, to their portfolios? In the March 2021 revision of their paper entitled “SPACs”, Minmo Gahng, Jay Ritter and Donghang Zhang examine investor returns on SPACs during the two phases of their lifecycle:

  1. SPAC phase– from SPAC IPO to five trading days before completion of target business merger or, if no merger within 24 months, liquidation. To measure investor returns for this phase, they assume purchases of one SPAC unit (usually a common share and warrants) at IPO prices for 114 SPACs during January 2010 through May 2018. The investor sells each component at the higher of the market price or the redemption price.
  2. deSPAC phase – from the first trading day as a merged company. For this phase, there are 114 completed mergers (105 having warrants), including 97 from the above SPAC phase plus 17 additional SPACs.

Using price data for U.S. SPACs (not those traded in Over-The-Counter markets) during January 2010 through October 2020, they find that:

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Impacts of Frictions on Factor Models of Stock Returns

How much does accounting for equity factor portfolio maintenance frictions affect usefulness of factor models of stock returns. In their March 2021 paper entitled “Model Selection with Transaction Costs”, Andrew Detzel, Robert Novy-Marx and Mihail Velikov examine effects of transaction costs on six leading models of stock returns:

  1. FF5 – Fama-French 5-factor model (market, size, book-to-market , investment and accruals-based profitability, reformed annually).
  2. FF6 – FF5 plus a momentum factor.
  3. HXZ4 – Hou, Xue, and Zhang 4-factor model (market, size, investment and profitability, all reformed monthly).
  4. BS6 – Barillas-Shanken 6-factor model (market, size, book-to-market reformed monthly, investment, return on equity and momentum).
  5. FF5C – FF5 with a cash flow-based profitability factor.
  6. FF6C – FF6 with a cash flow-based profitability factor.

They compare model effectiveness based on maximum squared Sharpe ratio (SR2), which measures how closely a model approaches the in-sample efficient frontier for all test assets. They measure transaction costs using stock-level effective bid-ask spread. Using data to calculate all factors employed by the six models and effective spreads during January 1972 through December 2017, they find that: Keep Reading

Re-examining Equity Factor Research Replicability

Several recent papers find that most studies identifying factors that predict stock returns are not replicable or derive from snooping of many factors. Is there a good counter-argument? In their January 2021 paper entitled “Is There a Replication Crisis in Finance?”, Theis Ingerslev Jensen, Bryan Kelly and Lasse Pedersen apply a Bayesian model of factor replication to a set of 153 factors applied to stocks across 93 countries. For each factor in each country, they each month:

  1. Sort stocks into thirds (top/middle/bottom) with breakpoints based on non-micro stocks in that country.
  2. For each third, compute a “capped value weight” gross return (winsorizing market equity at the NYSE 80th percentile to ensure that tiny stocks have tiny weights no mega-stock dominates).
  3. Calculate the gross return for a hedge portfolio that is long (short) the third with the highest (lowest) expected return.
  4. Calculate the corresponding 1-factor gross alpha via simple regression versus the country portfolio.

They further propose a taxonomy that systematically assigns each of the 153 factors to one of 13 themes based on high within-theme return correlations and conceptual similarities. Using firm and stock data required to calculate the specified factors starting 1926 for U.S. stocks and 1986 for most developed countries (in U.S. dollars), and 1-month U.S. Treasury bill yields to compute excess returns, all through 2019, they find that: Keep Reading

Factor Model of Stock Returns Based on Who Owns the Stocks

Is following the lead of certain types of equity investors as effective as using widely accepted factor models of stock returns? In their March 2021 paper entitled “What Do the Portfolios of Individual Investors Reveal About the Cross-Section of Equity Returns?”, Sebastien Betermier, Laurent Calvet, Samuli Knüpfer and Jens Kvaerner construct a factor model of stocks returns based on demographics of the individual investors who own them. They construct investor factors by each year reforming portfolios that are long (short) the 30% of stocks with the highest (lowest) expected returns based on holdings-weighted investor demographics and then measuring returns of these hedge portfolios the following year. They compare these investor factors to conventional factors constructed from firm/stock characteristics. Using anonymized demographics and direct stock holdings of Norwegian investors (an average 365,000 per year), and associated firm/stock characteristics and returns (over 400 stocks listed on the Oslo Stock Exchange), during 1997 through 2018, they find that:

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New Subclass of Retail Investors?

How has the market environment changed with the introduction of zero-commission trading and associated interest in trading among many inexperienced users? In their January 2021 paper entitled “Zero-Commission Individual Investors, High Frequency Traders, and Stock Market Quality”, Gregory Eaton, Clifton Green, Brian Roseman and Yanbin Wu examine market implications of growth in trading by a new subclass of retail investors represented by Robinhood users, focusing on January 2020 through August 2020 when the number of Robinhood users becomes very large. They isolate Robinhood user impacts by comparing market behaviors during Robinhood outages (real-time complaints by at least 200 Robinhood users on DownDetector.com) to those during similar times of day the prior week. They rely on the Reddit WallStreetBets forum and lagged trading activity to identify which stocks Robinhood users would have traded during outages. Using hourly (normal market hours) breadth of stock ownership data for Robinhood users from Robintrack (stocks with minimum average ownership 500 and daily minimum owners 50) and associated stock trading data during July 2018 through August 2020 (when the RobinTrack dataset ends), they find that:

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