Objective research to aid investing decisions

Value Investing Strategy (Strategy Overview)

Allocations for March 2024 (Final)
Cash TLT LQD SPY

Momentum Investing Strategy (Strategy Overview)

Allocations for March 2024 (Final)
1st ETF 2nd ETF 3rd ETF

Strategic Allocation

Is there a best way to select and weight asset classes for long-term diversification benefits? These blog entries address this strategic allocation question.

Add Position Stop-loss to SACEMS?

Does adding a position stop-loss rule improve the performance of the “Simple Asset Class ETF Momentum Strategy” (SACEMS) by avoiding some downside volatility? SACEMS each months picks winners from among the a set of eight asset class exchange-traded fund (ETF) proxies plus cash based on past returns over a specified interval. To investigate the value of stop-losses, we augment SACEMS with a simple rule that: (1) exits to Cash from any current winner ETF when its intra-month return falls below a specified threshold; and, (2) re-sets positions per winners at the end of the month. We focus on gross compound annual growth rate (CAGR) and gross maximum drawdown (MaxDD) as key performance statistics for the Top 1, equally weighted (EW) Top 2 and EW Top 3 portfolios of monthly winners. Using monthly total (dividend-adjusted) returns and intra-month drawdowns for the specified assets during February 2006 through September 2021, we find that: Keep Reading

Testing a Countercyclical Asset Allocation Strategy

“Countercyclical Asset Allocation Strategy” summarizes research on a simple countercyclical asset allocation strategy that systematically raises (lowers) the allocation to an asset class when its current aggregate allocation is relatively low (high). The underlying research is not specific on calculating portfolio allocations and returns. To corroborate findings, we use annual mutual fund and exchange-traded fund (ETF) allocations to stocks and bonds worldwide from the 2021 Investment Company Fact Book, Data Tables 3 and 11 to determine annual countercyclical allocations for stocks and bonds (ignoring allocations to money market funds). Specifically:

  • If actual aggregate mutual fund/ETF allocation to stocks in a given year is above (below) 60%, we set next-year portfolio allocation below (above) 60% by the same percentage.
  • If actual aggregate mutual fund/ETF allocation to bonds in a given year is above (below) 40%, we set next-year portfolio allocation below (above) 40% by the same percentage.

We then apply next-year allocations to stock (Fidelity Fund, FFIDX) and bond (Fidelity Investment Grade Bond Fund, FBNDX) mutual funds that have long histories. Based on Fact Book annual publication dates, we rebalance at the end of April each year. Using the specified actual fund allocations for 1984 through 2020 and FFIDX and FBNDX May through April total returns and end-of-April 1-year U.S. Treasury note (T-note) yields for 1985 through 2021, we find that: Keep Reading

Testing a 2-12 Asset Class Absolute Momentum Strategy

A subscriber asked about the performance of a strategy that each month has five equal-weighted positions:

We designate this strategy 2-12 Absolute. As requested, we also consider two variations that substitute Invesco DB Commodity Index Tracking Fund (DBC) for either TLT or LQD, and we compare 2-12 Absolute performance to that of a portfolio that each month allocates 50% to Simple Asset Class ETF Value Strategy (SACEVS) Best Value and 50% to Simple Asset Class ETF Momentum Strategy (SACEMS) equal-weighted (EW) Top 2. We begin tests at the end of March 2009, limited by inception of ACWI. We exclude monthly rebalancing/switching frictions for all strategies. Using monthly dividend-adjusted prices for GLD, ACWI, VNQ, TLT, LQD, DBC and SHY starting March 2009 and monthly gross returns for 50-50 SACEVS Best Value and SACEMS EW Top 2 starting April 2009, all through August 2021, we find that: Keep Reading

Performance of Statewide Pension Funds

When a public pension fund reports beating its benchmark, does that signify a job well done? In his July 2021 paper entitled “Cost, Performance, and Benchmark Bias of Public Pension Funds in the United States: An Unflattering Portrait”, Richard Ennis analyzes net returns of statewide pension funds in the U.S. He calculates both (1) net Sharpe ratio and (2) return versus a matched benchmark constructed via regression as the best-fit combination of the Russell 3000 stock index, the MSCI ACWI ex-U.S. stock index and the Bloomberg Barclays US Aggregate bond index. He compares performance relative to this benchmark and estimated costs for each fund. He then assesses performance of the funds versus the benchmarks they themselves construct and report against. Using self-reported data for a sample of 24 such funds self-reported via the Public Plans Data website during July 2010 through June 2020, he finds that: Keep Reading

Testing a SPY-EEMV-VT-TLT-PBBBX Allocation Strategy

In reaction to “Testing the EFA-SPY-TLT-PBBBX EW Strategy”, a subscriber asked about the performance of a strategy that each year rebalances to 25% SPDR S&P 500 (SPY), 10% iShares MSCI Emerging Markets Min Vol Factor (EEMV),  15% Vanguard Total World Stock Index Fund (VT), 25% iShares Barclays 20+ Year Treasury Bond (TLT) and 25% PIA BBB Bond Fund (PBBBX). Annual rebalancing avoids short-term capital gains for taxable accounts. We again compare performance of this alternative to that of a portfolio that each month allocates 50% to Simple Asset Class ETF Value Strategy (SACEVS) Best Value and 50% to Simple Asset Class ETF Momentum Strategy (SACEMS) equal-weighted (EW) Top 2. We begin the test at the end of 2011, limited by EEMV data and the annual rebalancing rule. We ignore rebalancing frictions for both strategies. Using monthly dividend-adjusted prices for SPY, EEMV, VT, TLT and PBBBX starting December 2011 and monthly gross returns for 50-50 SACEVS Best Value and SACEMS EW Top 2 starting January 2012, all through June 2021, we find that:

Keep Reading

Asset Class 12-month Reversion?

A subscriber, hypothesizing that asset classes with weak past returns should revert, requested testing of a strategy that each month holds the equal-weighted three of the Simple Asset Class ETF Momentum Strategy (SACEMS) universe with the lowest cumulative returns over the past 12 months (12-month EW Bottom 3). For comparison, we use the SACEMS EW Top 3 portfolio as specified. We begin the test at the end of February 2007, limited by SACEMS inputs with a 12-month lookback interval. We ignore monthly rebalancing frictions for both strategies. Using monthly dividend-adjusted prices of the nine SACEMS asset class proxies during February 2006 through June 2021, we find that: Keep Reading

Testing the EFA-SPY-TLT-PBBBX EW Strategy

A subscriber asked about the performance of a strategy that each month rebalances to 25% international equities, 25% U.S. equities, 25% U.S. Treasuries and 25% BBB bonds, and how this performance compares to that of a portfolio that each month allocates 50% to Simple Asset Class ETF Value Strategy (SACEVS) Best Value and 50% to Simple Asset Class ETF Momentum Strategy (SACEMS) equal-weighted (EW) Top 2. To investigate, we use:

We begin the test at the end of June 2006, limited by SACEMS inputs. We ignore monthly rebalancing frictions for both strategies. Using monthly dividend-adjusted prices for EFA, SPY, TLT and PBBBX starting June 2006 and monthly gross returns for 50-50 SACEVS Best Value and SACEMS EW Top 2 starting July 2006, all through June 2021, we find that: Keep Reading

Fixing Institutional Investing?

Why have U.S. public pension, endowment and other non-profit funds (institutional investors) consistently underperformed simple, investible passive benchmarks since 2008? How should they remedy that underperformance? In his April 2021 paper entitled “How to Improve Institutional Fund Performance”, Richard Ennis summarizes prior papers quantifying post-2008 institutional investor returns and recommends how institutions can improve this performance. Extending performance estimates from prior analyses through June 2020, he finds that: Keep Reading

Assessment of the Dragon Portfolio

A subscriber provided promotional materials for, and requested assessment of, the Artemis Capital Management Dragon portfolio. General allocations for this portfolio are:

  • 24% to secular growth such as U.S. and international stocks.
  • 21% to “long volatility and convex hedging” such as the Artemis Vega Fund and tail risk hedges (probably options and/or futures).
  • 19% to commodity trend following.
  • 18% to interest rate-sensitive assets such as U.S. Treasury bonds, Treasury Inflation-Protected Securities (TIPS) and investment grade bonds.
  • 18% to inflation protection such as gold and potentially crypto-assets.

Apparently, the fund has not yet launched and all performance data are backtested (hypothetical). Lacking detail to replicate the Dragon portfolio, we look at its hypothetical monthly returns per promotional materials. We use a 60% SPDR S&P 500 Trust (SPY) – 40% iShares 20+ Year Treasury Bond (TLT) portfolio, rebalanced monthly, as a simple hybrid benchmark. For reference, we also compare results for SPY, the Simple Asset Class ETF Value Strategy (SACEVS) Best Value portfolio and the Simple Asset Class ETF Momentum Strategy (SACEMS) equal-weighted (EW) Top 2 portfolio. Using gross monthly total returns for the Dragon portfolio, SPY, TLT, SACEVS Best Value and SACEMS EW Top 2 during January 2012 through April 2021, we find that: Keep Reading

SACEMS with Overnight Return Capture

In view of research indicating that overnight (close-to-open) returns are on average significantly higher than open-to-close returns, a subscriber proposed an enhancement to the Simple Asset Class ETF Momentum Strategy (SACEMS), as follows:

  • Instead of ranking SACEMS assets at the market close on the last trading day of each month, rank them at the open.
  • Sell any assets leaving SACEMS portfolios at the open.
  • Buy any assets entering SACEMS portfolios at the close.

Due to complexity of precisely programming a backtest of this setup, we instead run the following tests:

  1. Compare average daily open-to-close and close-to-open returns for each SACEMS non-cash asset over available sample periods since July 2002.
  2. Compare SACEMS portfolio performances during July 2006 through May 2021 for: (a) ranking assets at the open on the last trading day of each month and executing all trades at the open; and, (b) ranking assets at the close on the last trading day of each month and executing all trades at the close (baseline SACEMS).
  3. Calculate SACEMS portfolio performances during July 2006 through May 2021 for a variation that ranks assets at the open on the last trading day of each month, liquidates SACEMS portfolios at the open and reforms them at the close. This variation is more aggressive in exploiting an overnight return effect than the proposed approach, but is easier to program.

We consider Top 1, equal-weighted (EW) Top 2 and EW Top 3 SACEMS portfolios. We focus on full-sample gross compound annual growth rate, gross annual Sharpe ratio and maximum drawdown based on monthly data for portfolio comparisons. Using dividend-adjusted opening and closing prices for all SACEMS assets during July 2002 through May 2021, we find that: Keep Reading

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