Momentum Investing

Do financial market prices reliably exhibit momentum? If so, why, and how can traders best exploit it? These blog entries relate to momentum investing/trading.

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Models, Trading Calendar and Momentum Strategy Updates

We have updated the S&P 500 Market Models summary as follows:

  • Extended Market Models regressions/rolled projections by one month based on data available through February 2015.
  • Updated Market Models backtest charts and the market valuation metrics map based on data available through February 2015.

We have updated the Trading Calendar to incorporate data for February 2015.

We have updated the the monthly asset class momentum winners and associated performance data at Momentum Strategy.

Preliminary Momentum Strategy Update

The home page and “Momentum Strategy” now show preliminary asset class momentum strategy positions for March 2015. Differences in past returns among the top places are large enough that they are unlikely to change order by the close.

Interaction of Calendar Effects with Other Anomalies

Do stock return anomalies exhibit January and month-of-quarter (first, second or third, excluding January) effects? In his February 2015 paper entitled “Seasonalities in Anomalies”, Vincent Bogousslavsky investigates whether the following 11 widely cited U.S. stock return anomalies exhibit these effects:

  1. Market capitalization (size) – market capitalization last month.
  2. Book-to-market – book equity (excluding stocks with negative values) divided by market capitalization last December.
  3. Gross profitability – revenue minus cost of goods sold divided by total assets.
  4. Asset growth – Annual change in total assets.
  5. Accruals – change in working capital minus depreciation, divided by average total assets the last two years.
  6. Net stock issuance – growth rate of split-adjusted shares outstanding at fiscal year end.
  7. Change in turnover – difference between turnover last month and average turnover the prior six months.
  8. Illiquidity – average illiquidity the previous year.
  9. Idiosyncratic volatility – standard deviation of residuals from regression of daily excess returns on market, size and book-to-market factors.
  10. Momentum – past six-month return, skipping the last month.
  11. 12-month effect – average return in month t−k*12, for k = 6, 7, 8, 9, 10.

Each month, he sorts stocks into tenths (deciles) based on each anomaly variable and forms portfolios that are long (short) the decile with the highest (lowest) values of the variable. He updates all accounting inputs annually at the end of June based on data for the previous fiscal year. Using accounting data and monthly returns for a broad sample of U.S. common stocks during January 1964 to December 2013, he finds that: Keep Reading

Simple Asset Class ETF Momentum Strategy as Diversifier

A subscriber inquired whether the “Simple Asset Class ETF Momentum Strategy” is a good diversifier of the U.S. stock market. This strategy allocates funds at the end of each month to the one (Top 1), equally weighted two (EW Top 2) or equally weighted three (EW Top 3) of the following asset class exchange traded funds (ETF) or Cash with the highest total return over the past five months:

PowerShares DB Commodity Index Tracking (DBC)
iShares MSCI Emerging Markets Index (EEM)
iShares MSCI EAFE Index (EFA)
SPDR Gold Shares (GLD)
iShares Russell 1000 Index (IWB)
iShares Russell 2000 Index (IWM)
SPDR Dow Jones REIT (RWR)
iShares Barclays 20+ Year Treasury Bond (TLT)
3-month Treasury bills (Cash)

To investigate, we first look at correlations between momentum strategy returns and those of SPDR S&P 500 ETF (SPY) and Vanguard Balanced Index Investor Shares (VBINX), with the latter maintaining an approximately 60% allocation to the broad U.S. stock market and a 40% allocation to the U.S. corporate bond market. We then generate return statistics for portfolios that hold equally weighted combinations of: (1) the Top 1 momentum strategy and SPY, and (2) Top 1 and VBINX. Using monthly dividend-adjusted returns for the specified funds and the monthly Treasury bills yield as a proxy for Cash during January 2003 through January 2015, we find that: Keep Reading

Momentum Happens at Night?

Are overnight trading motivations systematically different from those that drive trading during normal trading hours? In the January 2015 version of their paper entitled “Tug of War: Overnight Versus Intraday Expected Returns”, flagged by a subscriber, Dong Lou, Christopher Polk and Spyros Skouras (1) decompose abnormal returns associated with well-known stock return predictors into overnight and intraday components and (2) investigate whether differences between institutional and other traders account for differences. Using return, firm characteristic and institutional ownership data for a broad sample of U.S. stocks (excluding low-priced and the smallest fifth of stocks) during 1993 through 2013, they find that: Keep Reading

Optimal Monthly Cycle for Simple Debt Class Mutual Fund Momentum Strategy?

In reference to “Optimal Monthly Cycle for Simple Asset Class ETF Momentum Strategy?”, a subscriber asked about an optimal monthly cycle for the “Simple Debt Class Mutual Fund Momentum Strategy”. This latter strategy each month allocates the entire portfolio value to the one of the following 12 debt class mutual funds with the highest past total return (optimally over the last two months):

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)

To investigate, we compare 21 variations of the strategy based on shifting the monthly return calculation cycle relative to trading days from the end of the month (EOM). For example, an EOM+5 cycle ranks funds based on closing prices five trading days after EOM each month. We use the historically optimal two-month fund momentum measurement interval. Using daily dividend-adjusted closes for the 12 funds during mid-December 1994 through mid-January 2015 (241 months), we find that: Keep Reading

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)

As proposed, we allocate all funds at the end of each month to the fund with the highest total return over the past three months (3-1). We determine the first winner in February 1995 to accommodate momentum measurement interval sensitivity testing. Using monthly dividend-adjusted closing prices for the 12 funds during February 1994 (as limited by VBLTX) through December 2014 (251 months), we find that: Keep Reading

Extended Simple Momentum Strategy Test of TSP Funds/Proxies

A subscriber asked about extending “Simple Momentum Strategy Applied to TSP Funds” back in time to 1988. That test employs the following five funds all available to U.S. federal government employees via the Thrift Savings Plan (TSP) starting in January 2001:

G Fund: Government Securities Investment Fund (G)
F Fund: Fixed Income Index Investment Fund (F)
C Fund: Common Stock Index Investment Fund (C)
S Fund: Small Cap Stock Index Investment Fund (S)
I Fund: International Stock Index Investment Fund (I)

S Fund and I Fund data limit the sample period. To extend the test back to first availability of G Fund, F Fund and C Fund data in February 1988 (January 1988 data is partial for TSP funds), we use Vanguard Small Cap Index Investors Fund (NAESX) as a proxy for the S Fund and Vanguard International Value Investors Fund (VTRIX) as a proxy for the I Fund prior to 2001. The subscriber requested first a sensitivity test of ranking intervals (one to 12 months), and then performance tests using the optimal ranking interval on portfolios consisting of the one fund with the highest past total return (Top 1), an equally weighted portfolio of the top two funds (EW top 2) and an equally weighted portfolio of the Top 3 funds (EW Top 3). Using monthly returns for the five TSP funds as available during February 1988 through December 2014 (323 months) and monthly returns for NAESX and VTRIX during February 1988 through December 2000, we find that: Keep Reading

Simple Asset Class ETF Momentum Strategy with SHY Return Filter

A subscriber suggested using iShares 1-3 Year Treasury Bond ETF (SHY) as a return filter for the“Simple Asset Class ETF Momentum Strategy” as a way to suppress maximum drawdown. The basic strategy each month allocates funds to the one, two or three of the following eight exchange-traded funds (ETF) plus cash, as proxied by U.S. Treasury bills (T-bills), with the highest returns over the past five months:

PowerShares DB Commodity Index Tracking (DBC)
iShares MSCI Emerging Markets Index (EEM)
iShares MSCI EAFE Index (EFA)
SPDR Gold Shares (GLD)
iShares Russell 1000 Index (IWB)
iShares Russell 2000 Index (IWM)
SPDR Dow Jones REIT (RWR)
iShares Barclays 20+ Year Treasury Bond (TLT)
3-month Treasury bills (Cash)

The T-bill yield is an approximation of the (non-negative) yield paid on cash by brokers. SHY can have negative returns in response to a rise in interest rates because it holds U.S. Treasury notes of terms 1-3 years. We investigate in two steps: (1) substitute SHY for T-bills in the basic strategy; and, (2) apply the SHY filter, substituting SHY for any winning ETF with a lower past return than SHY. Using monthly dividend-adjusted closing prices for the specified ETFs and the yield on T-bills during February 2006 (when all ETFs become available) through December 2014 (107 months), we find that:

Keep Reading

Doing Momentum with Style (ETFs) Robustness/Sensitivity Tests

How sensitive is the performance of “Doing Momentum with Style (ETFs)” to selecting ranks other than winners and to choosing a momentum ranking interval other than six months? This strategy each month ranks the following six style exchange-traded funds (ETF) on past return and rotates to the strongest style:

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.

Available data are so limited that sensitivity test results may mislead. With that reservation, we perform two robustness/sensitivity tests: (1) comparison of returns for all six ranks of winner through loser based on a ranking interval of six months and a holding interval of one month (6-1); and, (2) comparison of winner returns for ranking intervals ranging from one to 12 months (1-1 through 12-1) and for a six-month lagged six-month ranking interval (12:7-1) per “Isolating the Decisive Momentum (Echo?)”, all with one-month holding intervals. Using monthly adjusted closing prices for the style ETFs and SPDR S&P 500 (SPY) over the period August 2001 through December 2014 (161 months), we find that: Keep Reading

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Current Momentum Winners

ETF Momentum Signal
for March 2015 (Final)

Momentum ETF Winner

Second Place ETF

Third Place ETF

Gross Compound Annual Growth Rates
(Since August 2006)
Top 1 ETF Top 2 ETFs
15.0% 15.8%
Top 3 ETFs SPY
15.2% 8.0%
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