GPMv (DMS)
Compute average momentum and correlation-adjusted z_score for all 14 assets. Backtest max drawdown: -14.1%.
Strategy & methodology
Compute average momentum and correlation-adjusted z_score for all 14 assets; Count n_positive risky assets; n_positive_v = n_positive + 1; safety_pct = 2 × (11 - n_positive_v) / 11, clamped to [0, 1]; If n_positive_v >= 6 → top 3 risky…
- Strategy type:
- Tactical asset allocation
- Rebalance frequency:
- Monthly
- Original publication:
- 2022-05-23; results after that are out-of-sample for the original research. All results are backtest simulations.
- Data through:
- Backtest data through 2026-10-01.
Simulated history
Stand-in funds and until when (10)
- VGIT: IEF before Nov 23, 2009
- HYG: VWEHX before Apr 11, 2007
- VPL: EWJ x0.9 before Mar 10, 2005
- VGK: EFA x1.05 before Mar 10, 2005
- TLT: VUSTX before Jul 26, 2002
- SHY: VFISX before Jul 26, 2002
- LQD: PIGIX before Jul 26, 2002
- IWR: IJH before Jul 20, 2001
- IWB: SPY before May 19, 2000
- LQD: VWESX before Jul 26, 2002
Before these dates the backtest uses a stand-in, not the fund itself, so the results over those stretches show how the rules would have behaved, not what the fund returned.
Research data and disclosures
Compute average momentum and correlation-adjusted z_score for all 14 assets. Backtest max drawdown: -14.1%. This is a tactical asset allocation strategy. BestFolio supplies the public rule or approach and backtest context; current signals, allocations, and paid interactive data remain restricted to Pro access. Users review the published signal and place any resulting trades in their own brokerage. Displayed returns remain hypothetical and do not represent a customer's brokerage record. The facts above show how current the data is.
- BestFolio supplies
- The monthly signal email and this strategy page; current signals and email alerts require Pro access.
- Customer action
- Review the published signal and place any required trades in your own brokerage. BestFolio does not execute orders.
- Costs and exclusions
- Backtests are net of a modeled one-way transaction cost (10 bps, scaled up to 3x under stress); taxes, fund-expense drift, or market impact are not modeled. No tax, no slippage beyond the stated cost. Methodology limitations
Published result: Engine drift-until-flip-v1, data version 4e9f0928, published 2026-10-01
Is GPMv (DMS) still working in 2026?
GPMv (DMS) returned 13.01% over the trailing 12 months and 65.66% over 36 months through 2026-10-01, compared with a full-backtest annualized return of 10.36%. Its full-backtest maximum drawdown was -14.13%. The full sample contains 9862 daily NAV observations from 1987-12-31. These are model results, not investor account returns or a promise. As of 2026-10-01 it is -7.53% below its high-water mark of 2026-02-27, 7 months ago, and its longest run below a previous high was 2.2 years. Recent returns do not establish that the strategy will keep working.
| Period | Return | CAGR | Max drawdown | Observations | Dates |
|---|---|---|---|---|---|
| Trailing 12 months | 13.01% | Not annualized | -13.32% | 252 | 2025-10-01 to 2026-10-01 |
| Trailing 36 months | 65.66% | Not annualized | -13.32% | 754 | 2023-09-29 to 2026-10-01 |
| Full backtest | 4465.72% | 10.36% | -14.13% | 9862 | 1987-12-31 to 2026-10-01 |
Last verified
Common questions about these results
Are these live investor returns?
No. These are the latest model NAV results from the published backtest. A recent date alone does not make a result an independently observed live record. Investor costs, taxes and execution can differ.
Why can a strategy lag for a year?
A tactical model can hold defensive assets during a rally or change positions during reversals. A short window can differ substantially from its full history. Compare cumulative returns over matching dates and inspect drawdowns as well.
How long has it spent below a previous high?
Its last high-water mark was 2026-02-27, 7 months before 2026-10-01, and it is -7.53% below that level now. The longest run below a previous high in the full backtest was 2.2 years. Recovering from a drawdown can take years, and a strong trailing return does not mean a past high has been regained.
Where can I check the signals behind these results?
The Signals tab on this page lists each dated model decision for the selected variant; for Pro strategies they are visible to Pro members. The methodology page explains the backtest assumptions.
GPMv (DMS) at a glance
GPMv (DMS) is a tactical asset allocation (TAA) strategy by Randy Harris (DMS variant of Keller & Keuning's GPM) across US Equity, Tech, Mid-Cap, Pacific, rebalanced monthly. Backtested 1987-12-31 to 2026-10-01 (38.8 years): 10.4% CAGR, 1.26 Sharpe, -14.1% max drawdown, 8.6% volatility.
- Type
- Tactical (TAA)
- Author
- Randy Harris (DMS variant of Keller & Keuning's GPM)
- Rebalancing
- Monthly
- Risk
- Moderate
- Period
- 1987-12-31 to 2026-10-01
- CAGR
- 10.4%
- Sharpe
- 1.26
- Max Drawdown
- -14.1%
- Volatility
- 8.6%
GPMv (DMS) — Tactical Asset Allocation Strategy
GPMv is Randy Harris's DMS adaptation of GPM by Keuning & Keller. It uses correlation-adjusted momentum z-scores across 11 risky and 3 safe assets. The key GPMv modification is n_positive_v = n_positive + 1, allowing quicker re-entry into risky assets after sell-offs. The safety fraction scales linearly with market breadth.
GPMv (DMS): frequently asked questions
- What is GPMv (DMS)?
- Randy Harris's variant of Generalized Protective Momentum (GPM), the breadth-and-correlation crash-protection strategy created by Wouter Keller and Jan Willem Keuning. Correlation-based selection across 11 risky assets with a modified re-entry formula for quicker equity exposure after drawdowns; top 3 by score, with the safety fraction scaling to market breadth. Monthly rebalancing.
- Who created the GPMv (DMS) strategy?
- GPMv (DMS) was developed by Randy Harris (DMS variant of Keller & Keuning's GPM). It is based on Keuning, J.W. & Keller, W.J. (2016). Generalized Protective Momentum (GPM).
- What is the historical return and maximum drawdown of GPMv (DMS)?
- Backtested from 1987-12-31 to 2026-10-01, GPMv (DMS) returned 10.4% CAGR with a -14.1% maximum drawdown and a Sharpe ratio of 1.26. Past performance does not guarantee future results.
- How often is GPMv (DMS) rebalanced?
- GPMv (DMS) is rebalanced monthly. BestFolio publishes the updated allocation signal each period.
- Is GPMv (DMS) a tactical asset allocation strategy?
- Yes. GPMv (DMS) is a tactical asset allocation (TAA) strategy: it adjusts its holdings based on market signals each period rather than holding a fixed allocation.
Backtest Performance (1987-12-31 to 2026-10-01)
| Metric | GPMv (DMS) |
|---|---|
| CAGR | 10.4% |
| Max Drawdown | -14.1% |
| Sharpe | 1.26 |
| Sortino | 2.36 |
| Volatility | 8.6% |
| Calmar | 0.73 |
| Total Return | 4465.7% |
| Backtest Period | 38.8 years |
Every rebalance fills at the signal-day close, net of modeled transaction costs. Followers trade at the next open; the delayed-close line in the Rebalance Frequency Sensitivity card shows the effect of trading one session later. Execution assumption
Strategy Details
- Type
- Tactical (TAA)
- Rebalancing
- monthly
- Risk Level
- moderate
- Variants
- 1
- Author
- Randy Harris (DMS variant of Keller & Keuning's GPM)
- Source
- Keuning, J.W. & Keller, W.J. (2016). Generalized Protective Momentum (GPM)
Asset Classes
- US Equity
- Tech
- Mid-Cap
- Pacific
- Europe
- Gold
- Commodities
- REITs
- High Yield Bonds
- Corporate Bonds
- Long-Term Treasuries
- Short-Term Treasuries
Categories
Further reading
New to this approach? Read what tactical asset allocation is and how it works.
Holding GPMv (DMS) alongside another strategy? Use the free portfolio overlap calculator to see how much of the two portfolios actually differs.
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