Objective research to aid investing decisions

Value Investing Strategy (Strategy Overview)

Allocations for July 2020 (Final)
Cash TLT LQD SPY

Momentum Investing Strategy (Strategy Overview)

Allocations for July 2020 (Final)
1st ETF 2nd ETF 3rd ETF

Calendar Effects

The time of year affects human activities and moods, both through natural variations in the environment and through artificial customs and laws. Do such calendar effects systematically and significantly influence investor/trader attention and mood, and thereby equity prices? These blog entries relate to calendar effects in the stock market.

Stock Market and the National Election Cycle

Some stock market experts cite the year (1, 2, 3 or 4) of the U.S. presidential term cycle as a useful indicator of U.S. stock market returns. Game theory suggests that presidents deliver bad news immediately after being elected and do everything in their power to create good news just before ensuing biennial elections. Are some presidential term cycle years reliably good or bad? If so, do abnormal returns concentrate in certain quarters? Finally, what does the stock market do in the period immediately before and after a national election? Using daily and monthly S&P 500 Index levels from January 1928 through February 2020 (about 92 years and 23 presidential terms) and focusing on “political quarters” (Feb-Apr, May-Jul, Aug-Oct and Nov-Jan), we find that: Keep Reading

U.S. Stock Market End-of-Quarter Effect

Does the U.S. stock market have a predictable pattern of returns around ends of calendar quarters? Do funds deploy cash to bid stocks up at quarter ends to boost portfolio values in quarterly reports (with subsequent reversals)? Or, do they sell stocks to raise cash for fund redemptions? Is any end-of-quarter effect distinct from the Turn-of-the-Month (TOTM) effect? To investigate, we calculate average daily stock market (S&P 500 Index) returns before and after ends of calendar quarters and compare those returns to TOTM returns. Using daily closes of the S&P 500 Index during January 1928 through mid-February 2020 (368 quarters), we find that: Keep Reading

Bonds During the Off Season?

As implied in “Mirror Image Seasonality for Stocks and Treasuries?”, are bonds better than stocks during the “Sell-in-May” months of May through October? Are behaviors of government, corporate investment grade and corporate high-yield bonds over this interval similar? To investigate, we test seasonal behaviors of:

SPDR S&P 500 (SPY)
Vanguard Intermediate-Term Treasury (VFITX)
Fidelity Investment Grade Bond (FBNDX)
Vanguard High-Yield Corporate Bond (VWEHX)

Using dividend-adjusted monthly prices for these funds during January 1993 (limited by SPY) through January 2020, we find that: Keep Reading

Effects of Execution Delay on SACEVS

How does execution delay affect the performance of the Best Value and Weighted versions of the “Simple Asset Class ETF Value Strategy” (SACEVS)? These strategies each month allocate funds to the following asset class exchange-traded funds (ETF) according to valuations of term, credit and equity risk premiums, or to cash if no premiums are undervalued:

3-month Treasury bills (Cash)
iShares 20+ Year Treasury Bond (TLT)
iShares iBoxx $ Investment Grade Corporate Bond (LQD)
SPDR S&P 500 (SPY)

To investigate, we compare 22 variations of each strategy with execution days ranging from end-of-month (EOM) per the baseline strategy to 21 trading days after EOM (EOM+21). For example, an EOM+5 variation computes allocations based on EOM but delays execution until the close five trading days after EOM. We include a benchmark that each month allocates 60% to SPY and 40% to TLT (60-40) to see whether variations are unique to SACEVS. We focus on gross compound annual growth rate (CAGR), maximum drawdown (MaxDD) and annual Sharpe ratio as key performance statistics. Using daily dividend-adjusted closes for the above ETFs from the end of July 2002 through January 2020, we find that:

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Stock Market and the Super Bowl

Investor mood may affect financial markets. Sports may affect investor mood. The biggest mood-mover among sporting events in the U.S. is likely the National Football League’s Super Bowl. Is the week before the Super Bowl especially distracting and anxiety-producing? Is the week after the Super Bowl focusing and anxiety-relieving? Presumably, post-game elation and depression cancel between respective fan bases. Using past Super Bowl dates since inception and daily/weekly S&P 500 Index levels for 1967 through 2019 (53 events), we find that: Keep Reading

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 December 2019 (limited by data for IWS/IWP), we find that: Keep Reading

Seasonal, Technical and Fundamental S&P 500 Index Timing Tests

Are there any seasonal, technical or fundamental strategies that reliably time the U.S. stock market as proxied by the S&P 500 Total Return Index? In the February 2018 version of his paper entitled “Investing In The S&P 500 Index: Can Anything Beat the Buy-And-Hold Strategy?”, Hubert Dichtl compares excess returns (relative to the U.S. Treasury bill [T-bill] yield) and Sharpe ratios for investment strategies that time the S&P 500 Index monthly based on each of:

  • 4,096 seasonality strategies.
  • 24 technical strategies (10 slow-fast moving average crossover rules; 8 intrinsic [time series or absolute] momentum rules; and, 6 on-balance volume rules).
  • 18 fundamental variable strategies based on a rolling 180-month regression, with 1950-1965 used to generate initial predictions.

In all cases, when not in stocks, the strategies hold T-bills as a proxy for cash. His main out-of-sample test period is 1966-2014, with emphasis on a “crisis” subsample of 2000-2014. He includes extended tests on seasonality and some technical strategies using 1931-2014. He assumes constant stock index-cash switching frictions of 0.25%. He addresses data snooping bias from testing multiple strategies on the same sample by applying Hansen’s test for superior predictive ability. Using monthly S&P 500 Index levels/total returns and U.S. Treasury bill yields since 1931 and values of fundamental variables since January 1950, all through December 2014, he finds that:

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U.S. Stock Market Performance by Intra-year Phase

The full-year Trading Calendar indicates that the U.S. stock market has three phases over the calendar year, corresponding to calendar year trading days 1-84 (January-April), 85-210 (May-October) and 211-252 (November-December). What are typical stock market returns and return variabilities for these phases? Using daily S&P 500 Index closes from the end of December 1927 through December 2019, we find that: Keep Reading

Sector Performance by Calendar Month

Trading Calendar presents full-year and monthly cumulative performance profiles for the overall U.S. stock market (proxied by the S&P 500 Index) based on average daily behavior. Do monthly behaviors of U.S. stock market sectors deviate from the overall market profile? To investigate, we consider the nine Select Sector Standard & Poor’s Depository Receipts (SPDR) exchange-traded funds (ETF), all of which originate in December 1998:

Materials Select Sector SPDR (XLB)
Energy Select Sector SPDR (XLE)
Financial Select Sector SPDR (XLF)
Industrial Select Sector SPDR (XLI)
Technology Select Sector SPDR (XLK)
Consumer Staples Select Sector SPDR (XLP)
Utilities Select Sector SPDR (XLU)
Health Care Select Sector SPDR (XLV)
Consumer Discretionary Select SPDR (XLY)

Using monthly dividend-adjusted closing prices for these ETFs, along with contemporaneous data for SPDR S&P 500 (SPY) as a benchmark, during December 1998 through December 2019, we find that: Keep Reading

SACEVS and SACEMS Performance by Calendar Month

A subscriber asked whether the Simple Asset Class ETF Momentum Strategy (SACEMS) exhibits monthly calendar effects. In investigating, we also look at the Simple Asset Class ETF Value Strategy (SACEVS)? We consider the “Best Value” (most undervalued asset) and “Weighted” (assets weighted by degree of undervaluation) versions of SACEVS. We consider the Top 1, equally weighted “(EW) Top 2” and “EW Top 3” versions of SACEMS, which each month equally weights the top one, two or three of nine ETFs/cash with the highest total returns over a specified lookback interval. We further compare seasonalities of these strategies to those of their benchmarks: for SACEVS, a monthly rebalanced 60% stocks-40% bonds portfolio (60-40); and, for SACEMS an equally weighted and monthly rebalanced portfolio of the SACEMS universe (EW All). Using monthly gross total returns for SACEVS since August 2002 and for SACEMS since July 2006, both through October 2019, we find that:

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