MACD + RSI Filter · Strategy evidence
Inspect the inputs, parameters and accounting behind a published result.
Downloads
Downloads load and verify compressed objects only when selected. Negative weights represent short exposure; no code is executed in your browser.
1. Download a complete bundle
Download the Python tool above and run this command. It checks shared objects and creates replay.zip; no repository clone is needed.
python e0543584b55263609cc8fd38cd032cb8432af6c2b48da3f53599e6e68c922f59.py https://quantarenas.com/data/evidence/runs/d82626e922a2473eb5544abead028bf1cf9374b2fe4ca2515f99b41be44ee8b6/manifest.json --bundle replay.zip2. Replay the arithmetic
Extract replay.zip and run from its folder with Python. This verifies recorded weights, contributions and equity using only the standard library; it does not recalculate strategy decisions.
python scripts/replay_evidence.py data/evidence/runs/d82626e922a2473eb5544abead028bf1cf9374b2fe4ca2515f99b41be44ee8b6/manifest.json3. Obtain and compare inputs
In the extracted bundle, use the recorded Python version and install the pinned dependencies. This command downloads provider inputs privately and reports inputHashMatches. Only a matching hash supports exact recomputation; revised provider data may not match. You may instead supply an original matching snapshot as private-input.json.
python -m pip install -r requirements-lock.txt
python scripts/recompute_evidence.py data/evidence/runs/d82626e922a2473eb5544abead028bf1cf9374b2fe4ca2515f99b41be44ee8b6/manifest.json --fetch-input private-input.json4. Recompute the original strategy
With the exact original input snapshot and recorded dependencies, run the archived strategy and walk-forward selection. Original provider inputs are not public. Revised downloads fail the input-hash match and cannot establish exact reproduction.
python scripts/recompute_evidence.py data/evidence/runs/d82626e922a2473eb5544abead028bf1cf9374b2fe4ca2515f99b41be44ee8b6/manifest.json --input private-input.jsonAccounting assumptions
Each day's return uses the preceding day's target allocation. The new target is decided at the current close. This is a synthetic close-based model, not a measured execution price.
- Cash residual
- 1 - sum(weights); residual may exceed one or be negative for shorts/leverage.
- Decision
- Target weights use bars through close t; previous targets earn (t-1,t].
- Trading costs (bp)
- 0
- Execution assumption
- Synthetic daily target allocations, not broker orders or fills; financing/borrow costs omitted.
- Synthetic rebalance turnover
- Sum(abs(target[t] - target[t-1]*(1+assetReturn[t])/(1+grossReturn[t]))); one-way risky notional at close t after returns, divided by pre-trade equity.
- Return interval
- Sum of previous target weight times each asset close-to-close return; cash return is zero.
- Target weight change
- Sum(abs(target[t] - target[t-1])); changes in rule targets only.
- Walk-forward transition
- Candidate retains its own hypothetical state; first test return uses previous published target.
Parameters used
{
"active": {
"macd_fast": 12,
"macd_signal": 9,
"macd_slow": 26,
"rsi_extreme": 80,
"rsi_overbought": 70,
"rsi_oversold": 30,
"rsi_period": 17
},
"defaults": {
"macd_fast": 12,
"macd_signal": 9,
"macd_slow": 26,
"rsi_extreme": 80,
"rsi_overbought": 70,
"rsi_oversold": 30,
"rsi_period": 14
}
}Walk-forward selections
Default/pre-walk-forward history is not out-of-sample evidence. Each fold records its training and test boundaries; the selected candidate retains its own hypothetical state.
1 · 2017-09-17T00:00:00 → 2018-03-17T00:00:00
{
"config": {
"macd_fast": 10,
"macd_signal": 9,
"macd_slow": 26,
"rsi_extreme": 80,
"rsi_overbought": 70,
"rsi_oversold": 30,
"rsi_period": 14
},
"isSharpe": 1.2242343868508374,
"run": 3,
"testEnd": "2018-03-17T00:00:00",
"testStart": "2017-09-17T00:00:00",
"trainEnd": "2017-09-16T00:00:00",
"trainStart": "2014-09-17T00:00:00"
}2 · 2018-03-18T00:00:00 → 2018-09-18T00:00:00
{
"config": {
"macd_fast": 14,
"macd_signal": 9,
"macd_slow": 26,
"rsi_extreme": 80,
"rsi_overbought": 70,
"rsi_oversold": 30,
"rsi_period": 11
},
"isSharpe": 1.3463929593036479,
"run": 2,
"testEnd": "2018-09-18T00:00:00",
"testStart": "2018-03-18T00:00:00",
"trainEnd": "2018-03-17T00:00:00",
"trainStart": "2015-03-18T00:00:00"
}3 · 2018-09-19T00:00:00 → 2019-03-19T00:00:00
{
"config": {
"macd_fast": 14,
"macd_signal": 9,
"macd_slow": 26,
"rsi_extreme": 80,
"rsi_overbought": 70,
"rsi_oversold": 30,
"rsi_period": 11
},
"isSharpe": 1.3612058473774784,
"run": 2,
"testEnd": "2019-03-19T00:00:00",
"testStart": "2018-09-19T00:00:00",
"trainEnd": "2018-09-18T00:00:00",
"trainStart": "2015-09-19T00:00:00"
}4 · 2019-03-20T00:00:00 → 2019-09-20T00:00:00
{
"config": {
"macd_fast": 10,
"macd_signal": 9,
"macd_slow": 26,
"rsi_extreme": 80,
"rsi_overbought": 70,
"rsi_oversold": 30,
"rsi_period": 17
},
"isSharpe": 1.10004303890981,
"run": 6,
"testEnd": "2019-09-20T00:00:00",
"testStart": "2019-03-20T00:00:00",
"trainEnd": "2019-03-19T00:00:00",
"trainStart": "2016-03-20T00:00:00"
}5 · 2019-09-21T00:00:00 → 2020-03-21T00:00:00
{
"config": {
"macd_fast": 10,
"macd_signal": 9,
"macd_slow": 26,
"rsi_extreme": 80,
"rsi_overbought": 70,
"rsi_oversold": 30,
"rsi_period": 17
},
"isSharpe": 1.1720302008514336,
"run": 6,
"testEnd": "2020-03-21T00:00:00",
"testStart": "2019-09-21T00:00:00",
"trainEnd": "2019-09-20T00:00:00",
"trainStart": "2016-09-21T00:00:00"
}6 · 2020-03-22T00:00:00 → 2020-09-22T00:00:00
{
"config": {
"macd_fast": 12,
"macd_signal": 9,
"macd_slow": 26,
"rsi_extreme": 80,
"rsi_overbought": 70,
"rsi_oversold": 30,
"rsi_period": 17
},
"isSharpe": 0.9714318745968109,
"run": 7,
"testEnd": "2020-09-22T00:00:00",
"testStart": "2020-03-22T00:00:00",
"trainEnd": "2020-03-21T00:00:00",
"trainStart": "2017-03-22T00:00:00"
}7 · 2020-09-23T00:00:00 → 2021-03-23T00:00:00
{
"config": {
"macd_fast": 12,
"macd_signal": 9,
"macd_slow": 26,
"rsi_extreme": 80,
"rsi_overbought": 70,
"rsi_oversold": 30,
"rsi_period": 17
},
"isSharpe": 0.8087587707949843,
"run": 7,
"testEnd": "2021-03-23T00:00:00",
"testStart": "2020-09-23T00:00:00",
"trainEnd": "2020-09-22T00:00:00",
"trainStart": "2017-09-23T00:00:00"
}8 · 2021-03-24T00:00:00 → 2021-09-24T00:00:00
{
"config": {
"macd_fast": 12,
"macd_signal": 9,
"macd_slow": 26,
"rsi_extreme": 80,
"rsi_overbought": 70,
"rsi_oversold": 30,
"rsi_period": 17
},
"isSharpe": 0.9239513286607918,
"run": 7,
"testEnd": "2021-09-24T00:00:00",
"testStart": "2021-03-24T00:00:00",
"trainEnd": "2021-03-23T00:00:00",
"trainStart": "2018-03-24T00:00:00"
}9 · 2021-09-25T00:00:00 → 2022-03-25T00:00:00
{
"config": {
"macd_fast": 12,
"macd_signal": 9,
"macd_slow": 26,
"rsi_extreme": 80,
"rsi_overbought": 70,
"rsi_oversold": 30,
"rsi_period": 17
},
"isSharpe": 0.5019940326916701,
"run": 7,
"testEnd": "2022-03-25T00:00:00",
"testStart": "2021-09-25T00:00:00",
"trainEnd": "2021-09-24T00:00:00",
"trainStart": "2018-09-25T00:00:00"
}10 · 2022-03-26T00:00:00 → 2022-09-26T00:00:00
{
"config": {
"macd_fast": 12,
"macd_signal": 9,
"macd_slow": 26,
"rsi_extreme": 80,
"rsi_overbought": 70,
"rsi_oversold": 30,
"rsi_period": 17
},
"isSharpe": 0.656244862736253,
"run": 7,
"testEnd": "2022-09-26T00:00:00",
"testStart": "2022-03-26T00:00:00",
"trainEnd": "2022-03-25T00:00:00",
"trainStart": "2019-03-26T00:00:00"
}11 · 2022-09-27T00:00:00 → 2023-03-27T00:00:00
{
"config": {
"macd_fast": 12,
"macd_signal": 9,
"macd_slow": 26,
"rsi_extreme": 80,
"rsi_overbought": 70,
"rsi_oversold": 30,
"rsi_period": 17
},
"isSharpe": 0.3607351950517596,
"run": 7,
"testEnd": "2023-03-27T00:00:00",
"testStart": "2022-09-27T00:00:00",
"trainEnd": "2022-09-26T00:00:00",
"trainStart": "2019-09-27T00:00:00"
}12 · 2023-03-28T00:00:00 → 2023-09-28T00:00:00
{
"config": {
"macd_fast": 12,
"macd_signal": 9,
"macd_slow": 26,
"rsi_extreme": 80,
"rsi_overbought": 70,
"rsi_oversold": 30,
"rsi_period": 17
},
"isSharpe": 0.36275638801590687,
"run": 7,
"testEnd": "2023-09-28T00:00:00",
"testStart": "2023-03-28T00:00:00",
"trainEnd": "2023-03-27T00:00:00",
"trainStart": "2020-03-28T00:00:00"
}13 · 2023-09-29T00:00:00 → 2024-03-29T00:00:00
{
"config": {
"macd_fast": 10,
"macd_signal": 9,
"macd_slow": 26,
"rsi_extreme": 80,
"rsi_overbought": 70,
"rsi_oversold": 30,
"rsi_period": 11
},
"isSharpe": -0.2716020926386639,
"run": 0,
"testEnd": "2024-03-29T00:00:00",
"testStart": "2023-09-29T00:00:00",
"trainEnd": "2023-09-28T00:00:00",
"trainStart": "2020-09-29T00:00:00"
}14 · 2024-03-30T00:00:00 → 2024-09-30T00:00:00
{
"config": {
"macd_fast": 10,
"macd_signal": 9,
"macd_slow": 26,
"rsi_extreme": 80,
"rsi_overbought": 70,
"rsi_oversold": 30,
"rsi_period": 11
},
"isSharpe": -0.2256317913344639,
"run": 0,
"testEnd": "2024-09-30T00:00:00",
"testStart": "2024-03-30T00:00:00",
"trainEnd": "2024-03-29T00:00:00",
"trainStart": "2021-03-30T00:00:00"
}15 · 2024-10-01T00:00:00 → 2025-04-01T00:00:00
{
"config": {
"macd_fast": 12,
"macd_signal": 9,
"macd_slow": 26,
"rsi_extreme": 80,
"rsi_overbought": 70,
"rsi_oversold": 30,
"rsi_period": 11
},
"isSharpe": 0.4286466287492968,
"run": 1,
"testEnd": "2025-04-01T00:00:00",
"testStart": "2024-10-01T00:00:00",
"trainEnd": "2024-09-30T00:00:00",
"trainStart": "2021-10-01T00:00:00"
}16 · 2025-04-02T00:00:00 → 2025-10-02T00:00:00
{
"config": {
"macd_fast": 14,
"macd_signal": 9,
"macd_slow": 26,
"rsi_extreme": 80,
"rsi_overbought": 70,
"rsi_oversold": 30,
"rsi_period": 11
},
"isSharpe": 0.2534589137616181,
"run": 2,
"testEnd": "2025-10-02T00:00:00",
"testStart": "2025-04-02T00:00:00",
"trainEnd": "2025-04-01T00:00:00",
"trainStart": "2022-04-02T00:00:00"
}17 · 2025-10-03T00:00:00 → 2026-04-03T00:00:00
{
"config": {
"macd_fast": 14,
"macd_signal": 9,
"macd_slow": 26,
"rsi_extreme": 80,
"rsi_overbought": 70,
"rsi_oversold": 30,
"rsi_period": 11
},
"isSharpe": 0.6686312116168871,
"run": 2,
"testEnd": "2026-04-03T00:00:00",
"testStart": "2025-10-03T00:00:00",
"trainEnd": "2025-10-02T00:00:00",
"trainStart": "2022-10-03T00:00:00"
}18 · 2026-04-04T00:00:00 → 2026-10-04T00:00:00
{
"config": {
"macd_fast": 12,
"macd_signal": 9,
"macd_slow": 26,
"rsi_extreme": 80,
"rsi_overbought": 70,
"rsi_oversold": 30,
"rsi_period": 11
},
"isSharpe": 0.4838994160978805,
"run": 1,
"testEnd": "2026-10-04T00:00:00",
"testStart": "2026-04-04T00:00:00",
"trainEnd": "2026-04-03T00:00:00",
"trainStart": "2023-04-04T00:00:00"
}19 · 2026-10-05T00:00:00 → 2026-11-10T00:00:00
{
"config": {
"macd_fast": 12,
"macd_signal": 9,
"macd_slow": 26,
"rsi_extreme": 80,
"rsi_overbought": 70,
"rsi_oversold": 30,
"rsi_period": 17
},
"isSharpe": 0.38859793965529743,
"run": 7,
"testEnd": "2026-11-10T00:00:00",
"testStart": "2026-10-05T00:00:00",
"trainEnd": "2026-10-04T00:00:00",
"trainStart": "2023-10-05T00:00:00"
}Run summary
| Price observations | 4438 |
|---|---|
| Ending equity | 5.96796 |
| Total return | 496.80% |
| Days with target changes | 226 |
| Cumulative target change | 22600.00% |
| Cumulative synthetic rebalance turnover | 22600.00% |
| Target gross exposure | 0.00% |
| Target net exposure | 0.00% |
| Target cash residual | 100.00% |
| Effective gross exposure | 0.00% |
| Effective net exposure | 0.00% |
| Effective cash residual | 100.00% |
Latest asset weights
| Market | Target | Effective |
|---|---|---|
| BTC-USD | 0.00% | 0.00% |
Target change measures changes in rule weights. Synthetic rebalance turnover also accounts for weight drift after returns; even unchanged targets can require rebalancing. Cash is the signed residual after net exposure.
Accounting changes on identical inputs
{
"changedReturnDays": 0,
"correctedTerminalEquity": 5.967960292131686,
"legacyTerminalEquity": 5.967960292131686,
"maximumDailyReturnDelta": 0.0,
"model": "coherent-lagged-target-v2",
"terminalEquityDelta": 0.0
}Full run identity and technical record
{
"inputHash": "5b3c8b854be76fa4b63c345c5aed9398c52122fb629845e8ed9de94de74eecd0",
"ruleVersion": null,
"sameInputAccountingCorrection": {
"changedReturnDays": 0,
"correctedTerminalEquity": 5.967960292131686,
"legacyTerminalEquity": 5.967960292131686,
"maximumDailyReturnDelta": 0.0,
"model": "coherent-lagged-target-v2",
"terminalEquityDelta": 0.0
},
"sourceHashes": {
"scripts/build_data.py": "e3dcc988d80a46f7f5a24396bb4ffcac240da8e1249de18a5a282eacccc52320",
"scripts/enrich_metrics.py": "05611fa9c6de11c261f631cdd8a3314212e7c567f24878a396d057d88752051c",
"scripts/evidence_v2.py": "c4c6523dbbb9513464dca25150f42cbaac7cbfd71bd8afdc855659b2c763d72e",
"scripts/performance_io.py": "42282ff10697ceb56dc7ca2edf79538c2e1e8344da8e6d69ceac4d16ba5c668a",
"scripts/recompute_evidence.py": "a7f59004cb7c356940ee3748439024cd83cac434acb90c0bead2ae19f81be127",
"scripts/replay_evidence.py": "4e04d937c19b9040da6dc9c3c80ac22181b45ffba0131f3a63a4def95865fad6",
"scripts/requirements.txt": "7424048072a2cf3d8c3b4e4f37a5b36c1e7ff3732d893c43295d17d85c5f97d1",
"scripts/strategies/macd_rsi_filter.py": "9be44bc0d8805b686530d29c62fef30aaccbda1fd905894a345257dc4fef9010",
"scripts/strategy_evidence.py": "a3a93d62a84298470af3eb8e7d74e9f0ca0d29cf672d1d2d5449b41904e3d58c"
},
"runId": "d82626e922a2473eb5544abead028bf1cf9374b2fe4ca2515f99b41be44ee8b6",
"generatedAt": "2026-11-11T10:55:31.449953+00:00",
"executionModel": {
"cash": "1 - sum(weights); residual may exceed one or be negative for shorts/leverage.",
"decision": "Target weights use bars through close t; previous targets earn (t-1,t].",
"feesBasisPoints": 0,
"fills": "Synthetic daily target allocations, not broker orders or fills; financing/borrow costs omitted.",
"id": "synthetic-daily-target-v3",
"rebalanceTurnover": "Sum(abs(target[t] - target[t-1]*(1+assetReturn[t])/(1+grossReturn[t]))); one-way risky notional at close t after returns, divided by pre-trade equity.",
"return": "Sum of previous target weight times each asset close-to-close return; cash return is zero.",
"targetChange": "Sum(abs(target[t] - target[t-1])); changes in rule targets only.",
"wfo": "Candidate retains its own hypothetical state; first test return uses previous published target."
}
}