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Latest Market Research Articles

Path Dependence of Satisfying Returns

What makes investors happy with investment returns? In the April 2015 version of their paper entitled “All’s Well That Ends Well? On the Importance of How Returns Are Achieved”, Daniel Grosshans and Stefan Zeisberger employ a series of surveys to investigate how investor satisfaction depends on investment price path. Their main survey asks participants to imagine that they bought three winner stocks (10% terminal gain) and three loser stocks (10% terminal loss) one year ago, with the three in each set having distinct price paths: (1) down-up, (2) straight line (monotonic) and (3) up-down (see the figures below). It also asks how likely participants would be to hold or sell each stock, their minimum selling price and an estimate of the stock’s price after one more year. Using results from surveys of participants recruited via Amazon Mechanical Turk (MTurk) and of students in advanced finance courses, they find that: Keep Reading

“What Works Best?” Update

We’ve updated “What Works Best?” to incorporate some recent research summaries and adjust interpretation of the body of research.

Weekly Summary of Research Findings: 4/20/15 – 4/24/15

Below is a weekly summary of our research findings for 4/20/15 through 4/24/15. 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

Long-term Tests of Simple X% Rules

A subscriber requested long-term tests of simple versions of the strategy described by Jason Kelly in The 3% Signal: The Investing Technique that Will Change Your Life, We start with a general strategy targeting an X% quarterly increase in a stock fund, as follows:

  1. Initiate X% rules with either 80%-20% or 60%-40% allocations to a stock fund and a bond fund.
  2. If over the next quarter the stock fund increases by more than X%, transfer the excess from the stock fund to the bond fund.
  3. If over the next quarter the stock fund increases by less than X%, make up the shortfall by transferring money from the bond fund to the stock fund.
  4. If at the end of any quarter the bond fund does not have enough money to make up a shortfall in the stock fund: either draw the bond fund down to 0 and add cash to make up the rest of the shortfall; or, draw the bond fund down to 0 and bear the rest of the shortfall in the stock fund.
  5. Consider two benchmarks: a 100% allocation to the stock fund (B&H); and, 60%-40% allocations to the stock and bond funds, rebalanced quarterly (60-40). Whenever adding cash to the bond fund per Step 4, add equal amounts to the benchmarks.

We consider for X% a range of 2% to 4% in increments of 0.5%. We employ stock and bond mutual funds with long histories: Fidelity Magellan (FMAGX) and Fidelity Investment Grade Bond (FBNDX). We assume there are no trading frictions when adding or withdrawing money from these funds. Using quarterly returns for these funds from the first quarter of 1972 (limited by FBNDX) through the first quarter of 2015 (43.25 years), we find that:

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Effects of Execution Delay on Simple Asset Class ETF Value Strategy

“Effects of Execution Delay on Simple Asset Class ETF Momentum Strategy” investigates how delaying signal execution affects strategy performance. How does execution delay affect the performance of the complementary Best Value version of the “Simple Asset Class ETF Value Strategy”? This latter strategy each quarter allocates all funds to the one of the following asset class exchange-traded funds (ETF) associated with the most undervalued risk premium (term, credit or equity), or to cash if none are undervalued:

3-month Treasury bills (Cash)
iShares 7-10 Year Treasury Bond (IEF)
iShares iBoxx $ Investment Grade Corporate Bond (LQD)
SPDR S&P 500 (SPY)

To investigate, we compare 23 variations of the strategy that all use end-of-quarter (EOQ) to determine the best value asset but shift execution from the contemporaneous EOQ to the next open or to closes over the next 21 trading days (about one month). For example, an EOQ+5 Close variation uses an EOQ cycle to determine winners but delays execution until the close five trading days after EOQ. Using daily dividend-adjusted opens and closes for the risk premium proxies and the yield for Cash from the end of September 2002 through the end of March 2015 (51 quarters), we find that:

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Effects of Execution Delay on Simple Asset Class ETF Momentum Strategy

“Optimal Monthly Cycle for Simple Asset Class ETF Momentum Strategy?” investigates whether using a monthly cycle other than end-of-month (EOM) to determine the winning asset improves performance of the “Simple Asset Class ETF Momentum Strategy”. This strategy each month allocates all funds to the one of the following eight 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)

In response, a subscriber asked whether sticking with an EOM cycle for determining the winner, but delaying signal execution, affects strategy performance. To investigate, we compare 23 variations of the strategy that all use EOM to determine the winning asset but shift execution from the contemporaneous EOM to the next open or to closes over the next 21 trading days (about one month). For example, an EOM+5 Close variation uses an EOM cycle to determine winners but delays execution until the close five trading days after EOM. Using daily dividend-adjusted opens and closes for the asset class proxies and the yield for Cash from the end of July 2002 (or inception if not available then) through the end of March 2015 (153 months), we find that: Keep Reading

Optimal Monthly Cycle for Simple Asset Class ETF Momentum Strategy?

As explored for a 10-month simple moving average (SMA) in “Optimal Cycle for Monthly SMA Signals?”, subscribers have inquired whether there is a best time of the month for measuring momentum in the “Simple Asset Class ETF Momentum Strategy”. This strategy each month allocates all funds to the one of the following eight 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 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 assets based on closing prices five trading days after EOM each month. Using daily dividend-adjusted closes for the asset class proxies and the yield for Cash from late July 2002 (or inception if not available then) through early April 2014 (about 153 months), we find that: Keep Reading

Timing of Asset Class Allocations by Multi-class Funds

Do multi-class mutual funds exhibit good asset class allocation timing? In their April 2015 paper entitled “Multi-Asset Class Mutual Funds: Can They Time the Market? Evidence from the US, UK and Canada”, Andrew Clare, Niall O’Sullivan, Meadhbh Sherman and Steve Thomas investigate whether mutual fund managers time allocations across asset classes skillfully. They focus on three asset classes: equities, government bonds and corporate bonds. They apply two alternative methodologies: (1) returns-based, relating each asset class beta for a fund to next-month return for that class; and, (2) holdings-based, relating changes in asset class weights within a fund to next-month class returns. Using monthly returns and holdings for 617 U.S., UK and Canadian multi-asset class mutual funds during 2000 through 2012, they find that:

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Continue to archive for older articles

Editor Archive Picks

“Sell in May” Still Working?

…voiding stocks during May through October work in recent years? In their July 2012 paper entitled “‘Sell in May and Go Away’ Just Won’’t Go Away”, Sandro Andrade, Vidhi Chhaochharia and Michael Fuerst test the sell-in-May anomaly (or Halloween effect) based on data unambiguously available only after publication of the anomaly. They compute returns in adjacent six-month periods, the beginning of May to end of October…

“Sell in May” Over the Long Run

Does the conventional wisdom to “Sell in May” (and “Buy in November”, hence also termed the “Halloween Effect”) work over the long run, perhaps due to biological/psychological effects of seasons (such as Seasonal Affective Disorder)? To check, we turn to the long run data set of Robert Shiller. This data set includes monthly levels of the S&P Composite Index, calculated as average of daily closes during th…

An Annual Worldwide Optimism Cycle (Sell in May)?

Does the conventional wisdom to “sell in May,” with the average stock return during November-April far exceeding that for May-October, work for the world equity market? If so, why? In the November 2005 version of his paper entitled “The Optimism Cycle: Sell in May”, flagged by a reader, Ronald Doeswijk examines the hypothesis that this seasonal pattern derives from an annual optimism cycle. Using monthly return data for m…

Simulating the Halloween Effect with Recent Data

Does the Sell-in-May/Halloween effect hold in recent data? In their April 2014 paper entitled “Sell in May and Go Away: Still Good Advice for Investors?”, Hubert Dichtl and Wolfgang Drobetz explore whether holding one of several stock indexes (cash) during November-April (May-October) beats buying and holding the index. They focus on sample periods since: (1) liquid index proxies are readily available for each index to both instituti…

Halloween Indicator Out-of-sample Test

Does the Halloween effect (sell in May) still hold? In the June 2013 version of their paper entitled “Are Stock Markets Really so Inefficient? The Case of the ‘Halloween Indicator’”, Hubert Dichtl and Wolfgang Drobetz investigate whether true out-of-sample results confirm that the Halloween effect persists for five total return indexes: S&P 500, DAX 30, FTSE 100, CAC 40 and Euro Stoxx 50. They consider both regression tests…

Popular Articles

    Momentum Strategy, Value Strategy and Trading Calendar Updates

    We have updated the the monthly asset class momentum winners and associated performance data at Momentum Strategy. We have updated the quarterly asset class value allocations and associated performance data at Value Strategy. We have updated the Trading Calendar to incorporate data for March 2015.  

    Preliminary Momentum Strategy and Value Strategy Updates

    The home page and “Momentum Strategy” now show preliminary asset class momentum strategy positions for April 2015. Differences in past returns among the top places are large enough that they are unlikely to change by the close. The home page and “Value Strategy” now show preliminary asset class value strategy allocations for the second quarter of 2015. These allocations More

    Inflation Forecast Update

    The Inflation Forecast now incorporates actual total and core Consumer Price Index (CPI) data for March 2015. The actual total (core) inflation rate for March is about the same as (a little higher than) forecasted.

    A Few Notes on The 3% Signal

    In the introduction to his 2015 book entitled The 3% Signal: The Investing Technique that Will Change Your Life, author Jason Kelly states: “Ideas count for nothing; opinions are distractions. The only thing that matters is the price of an investment and whether it’s below a level indicating a good time to buy or above a level indicating a More

    A Few Notes on Irrational Exuberance

    In the preface to the 2015 Third Edition of Irrational Exuberance, author Robert Shiller states: “…evidence of bubbles has accelerated since the [2007-2009 world financial] crisis. Valuations in the stock and bond markets have reached high levels in the United States and some other countries, and valuations in the housing market have been increasing rapidly in many countries. …The More

    Stock Returns Around Easter

    Does the seasonal change marked by the Easter holiday, with the U.S. stock market closed on the preceding Good Friday, tend to produce anomalous returns? To investigate, we analyze the historical behavior of the S&P 500 Index before and after the holiday. Using daily closing levels of the S&P 500 index for 1950-2014 (65 events), More

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Current Momentum Winners

ETF Momentum Signal
for April 2015 (Final)

Winner ETF

Second Place ETF

Third Place ETF

Gross Compound Annual Growth Rates
(Since August 2006)
Top 1 ETF Top 2 ETFs
15.1% 15.8%
Top 3 ETFs SPY
15.3% 7.7%
Strategy Overview
Current Value Allocations

ETF Value Signal
for 2nd Quarter 2015 (Final)

Cash

IEF

LQD

SPY

The asset with the highest allocation is the holding of the Best Value strategy.
Gross Compound Annual Growth Rates
(Since September 2002)
Best Value Weighted 60-40
13.7% 9.6% 8.6%
Strategy Overview
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