POC: aggressive short-mode momentum strategy on 2022 crypto bear. +87% / Calmar 5.64
Proof of concept / experiment: A GEM regression model but shorting biggest loosers instead of going long on winners. Tuned for bear markets.
Experimental setup as below:
- May 1 – Dec 31, 2022 data (BTC already down ~50% from ATH, Luna gone, 3AC gone, FTX about to be gone)
- 11 Binance USD-M perpetuals -- 4 extreme fallers (SOL, AVAX, ADA, DOT), 4 moderate (BTC, ETH, LINK, MATIC), 3 outperformers (BNB, TRX, XMR)
- $10k starting capital, flat 0.3% round-trip fees, real Binance funding rates applied at 8h cadence.
The models
GEM, sign-flipped for shorts:
- Fit either an exponential or linear regression to each token's recent closes
- Ranks them by the negative momentum, filters by R**2 and a momentum floor
- Goes short on the top N most-negative tokens, weighted by their negative momentum magnitude (tokens ATR over total ATR sum)
- 10-day rebalance cooldown
Results
Best config: lin-n1-w15 (linear, single token, 15-day window), +87.2% total return, -27.4% max drawdown, Calmar 5.64.
Long-only bear specialist from a previous post: Calmar 4.60.
But: baseline naive equal-weight short, never rebalanced: +57.7% return, -16.4% DD, Calmar 5.92
The -27% DD was one event: an ADA short squeeze, Oct 18 - 28 2022. The model entered at 100% weight on a clean 15-day downtrend, ADA bounced
Findings
The risk signals that would have flagged the squeeze, starting with funding-rate inversion, is obviously not in the OHLCV data, so the model cannot anticipate short squeezes.
Full write-up, charts, notebooks for repro: