Elder Triple Screen
Combines a trend filter (MACD + long EMA), a pullback filter (Force Index proxy), and a breakout trigger. Long-only implementation aligned with daily data.
At a glance
What the backtest shows
- Beat buy-and-hold on 3 of 10 markets by annual return over 5 years.
- Had a smaller maximum drawdown than buy-and-hold on 10 of 10 markets.
- Best market by Sharpe ratio: SPY (Sharpe 0.00, CAGR 0.0%).
- Weakest market: ETH-USD (Sharpe 0.00, CAGR 0.0%).
- Few or no trades in the window on SPY, GLD, USO, EURUSD=X, DBC, SLV, DBA, UNG, BTC-USD, ETH-USD — treat those rows as a sign the rules rarely triggered, not as an edge.
Equity curve
Score and risk profile
Not ranked in this window: the strategy was in the market less than 5% of the time.
How it held up in sell-offs (SPY)
| Period | Strategy | Buy & hold |
|---|---|---|
| Q4 2018 sell-off | 0.0% | -19.2% |
| COVID crash (Feb–Mar 2020) | 0.0% | -33.7% |
| 2022 bear market | 0.0% | -24.5% |
| Market above its 200-day average (annualized) · 81% | 0.0% | +12.5% |
| Market below its 200-day average (annualized) · 19% | 0.0% | +19.8% |
Sell-off dates follow the US stock market. Above/below the 200-day average uses the previous day's position, so there is no look-ahead.
Out-of-sample check (SPY)
| Check | Value |
|---|---|
| Chosen parameters on their 3-year training windows (average Sharpe) | 0.00 |
| Same parameters in the following 6 months, when traded (Sharpe) | 0.00 |
| Default parameters over the same months (Sharpe) | 0.00 |
| Parameter re-selections / changes | 28 / 0 |
| Parameter settings with a positive Sharpe (full history) | 0 of 9 |
| Sharpe across settings: worst / median / best | 0.00 / 0.00 / 0.00 |
Out-of-sample periods start on 2013-01-04. Training-window figures are flattered by picking the best of 9 settings; the out-of-sample figure is what the strategy actually earned. A large drop, or a result that depends on one setting, points to overfitting. How walk-forward testing works.
Results by market (5 years)
| Market | CAGR | Buy & hold CAGR | Sharpe | Max drawdown | Buy & hold max DD | Volatility | Arena Score |
|---|---|---|---|---|---|---|---|
| SPYSPDR S&P 500 | 0.0% | 11.6% | 0.00 | 0.0% | -24.5% | 0.0% | — |
| GLDSPDR Gold Shares | 0.0% | 16.4% | 0.00 | 0.0% | -28.3% | 0.0% | — |
| USOUnited States Oil Fund | 0.0% | 20.2% | 0.00 | 0.0% | -36.2% | 0.0% | — |
| EURUSD=XEUR/USD | 0.0% | -0.7% | 0.00 | 0.0% | -17.2% | 0.0% | — |
| DBCInvesco DB Commodity Index | 0.0% | 10.8% | 0.00 | 0.0% | -27.3% | 0.0% | — |
| SLViShares Silver Trust | 0.0% | 15.2% | 0.00 | 0.0% | -57.8% | 0.0% | — |
| DBAInvesco DB Agriculture | 0.0% | 8.8% | 0.00 | 0.0% | -15.9% | 0.0% | — |
| UNGUnited States Natural Gas | 0.0% | -30.7% | 0.00 | 0.0% | -93.3% | 0.0% | — |
| BTC-USDBitcoin | 0.0% | 2.6% | 0.00 | 0.0% | -75.9% | 0.0% | — |
| ETH-USDEthereum | 0.0% | -15.1% | 0.00 | 0.0% | -79.0% | 0.0% | — |
Strategy metrics use daily returns without trading costs. Buy-and-hold figures are for the same market and window. Rows are sorted by Sharpe ratio.
SPY across time windows
Rules
Entry
Trend up AND Force Index < 0 AND close > recent high
Exit
Trend filter turns down
Indicators
MACD histogram for trend filter Force Index proxy = close.diff() Entry breakout = recent high
Inputs
MACD_Fast = 12 MACD_Slow = 26 MACD_Signal = 9 EMA_Long = 50 Force_EMA = 13 Entry_Lookback = 20
Position sizing
Fixed 100% allocation
Risk controls
Requires pullback before breakout entry
Strategy evidence
- BTC-USD · Inspect evidence 2026-11-10
- DBA · Inspect evidence 2026-11-10
- DBC · Inspect evidence 2026-11-10
- ETH-USD · Inspect evidence 2026-11-10
- EURUSD=X · Inspect evidence 2026-11-10
- GLD · Inspect evidence 2026-11-10
- SLV · Inspect evidence 2026-11-10
- SPY · Inspect evidence 2026-11-10
- UNG · Inspect evidence 2026-11-10
- USO · Inspect evidence 2026-11-10
Only available, validated bundles appear below. Missing evidence is not a passing validation result.
Evidence coverage
10 / 10 declared strategy–market pairs validated
Notes
- Force Index uses price-change proxy (no volume)
- Simplified long-only version
Related strategies
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Backtests are historical simulations on daily data and do not include commissions or slippage. They do not guarantee future results and are not investment advice. See the methodology for how every strategy is tested.