Question
How are trading strategies stress-tested on CrashTestYourStrategy?
Methodology gateway: case catalog, failure-mode taxonomy, V2 scoring with a-priori augmentation.
Short answer
Strategies are evaluated against a curated case set of 31 empirical anchors (Lehman 2008, Dotcom 2000, COVID 2020, Luna 2022, etc.) and 32 synthetic stress probes (50 Monte-Carlo replicas each, generated by a Hybrid Field-SME agent-based simulator with per-asset CoT calibration). Each replica is classified ex-post into a failure-mode bucket via operational gating definitions; sparse buckets are augmented from a-priori tags (Phase 18d). The composite robustness score (0-100) is the equal-weight mean across populated FM-buckets with shrinkage. Currently 13 reference strategies are pre-computed in the catalog.
Pre-computed catalog strategies
| Strategy | Asset | Score |
|---|---|---|
| RSI with SMA 200 Trend Filter | SPY | 76 / 100 |
| MACD Signal Line Crossover | SPY | 60 / 100 |
| Supertrend Strategy | SPY | 60 / 100 |
| Bollinger Band Bounce | SPY | 60 / 100 |
| Buy and Hold S&P 500 | SPY | 59 / 100 |
| EMA 12/26 Crossover (BTC) | BTC | 55 / 100 |
| EMA 12/26 Crossover | SPY | 54 / 100 |
| Buy and Hold Bitcoin | BTC | 53 / 100 |
| SMA 200 Trend Following (GOLD) | GOLD | 51 / 100 |
| RSI 30/70 Mean Reversion | SPY | 51 / 100 |
| RSI 30/70 Mean Reversion (BTC) | BTC | 51 / 100 |
| SMA 200 Crossover | SPY | 51 / 100 |
| MACD + RSI Confirmation (BTC) | BTC | 50 / 100 |
For the full taxonomy, see /ontology. For the machine-readable schema, see /interop. The V2 score path is calculate_robustness_score_v2 in robustness_calculator.py.
Related failure-mode definitions
Related questions
Data is sourced from the curated case set: 31 empirical anchors + 32 synthetic stress probes across 9 score buckets, V2 per-FM-bucket scoring with a-priori augmentation. See /methodology.
Programmatic access: POST /api/v1/agent/analyze · GET /api/v1/catalog/query · see /interop.