Entry
- Long: EMA-50 > EMA-100 AND price > 100-day high (Clenow variant)
- Short: EMA-50 < EMA-100 AND price < 100-day low
- Trend filter: the 200-day MA direction confirms the signal
- Diversified across 50+ futures in 4 asset classes
Exit
- Counter-crossover of EMA-50 vs. 100
- Stop-loss: 3×ATR against entry (Clenow value)
- No fixed profit target — trail
| Name | Typ. value | Description |
|---|---|---|
| fast_ema | 50 | Fast EMA |
| slow_ema | 100 | Slow EMA |
| atr_period | 100 | Volatility measurement |
| risk_factor | 0.002 (20 bp) | Per-trade risk per ATR |
| portfolio_vol_target | 12-15% | Annual volatility of the overall portfolio |
Pros
- Proven over decades of real CTA performance
- Fully automatable
- Crisis-proof: positive correlation to vol spikes
- Clenow documents year-by-year performance for reproducibility
Cons
- Needs capital for broad futures diversification (min. 500k)
- Long drawdown phases (sometimes 2-3 years)
- Hard for retail to implement — futures accounts, margin capacity
- Weaker since 2010 than historically
Core idea
In Following the Trend, Andreas Clenow documents how CTAs (Commodity Trading Advisors) manage billions with the simplest of rules. The central message of his book: the signals are unimportant, the infrastructure is everything.
Concretely: an EMA crossover on its own delivers a marginal edge. Only in combination with
- ATR position sizing (constant risk per trade, vol-neutral)
- portfolio vol targeting (leverage across all positions chosen so that total vol is ~15%/year)
- broad diversification across 50+ uncorrelated futures
- disciplined execution without discretion
does a returns pattern emerge that has carried the CTA industry for decades.
The rules
Signal
- Long setup: EMA-50 > EMA-100 AND price > high of the last 100 days
- Short setup: EMA-50 < EMA-100 AND price < low of the last 100 days
- Exit: crossover back OR 3×ATR stop
Sizing
Per market i:
ATR_i = 100-day ATR
Unit_i = Account × 0.002 / ATR_i
I.e. 20 basis points of the account are risked per ATR unit. In the diversified portfolio, total vol is measured across all open positions and the leverage is adjusted.
Why it works
The trick is not signal quality but:
- Vol scaling makes positions comparable — a 10% move in gold counts as much as a 2% move in eurodollars.
- Diversification across asset classes decorrelates individual false signals — single markets can whipsaw, but not all at the same time.
- Fat-tail exposure: when a market really breaks out (commodity supershock, currency crisis), trend followers ride the entire move. These happen 2-3 times per decade — and they generate the bulk of the returns.
Performance data
Clenow documents year by year 2002-2021 in the second edition. Highlights: - 2008: +20% during the equity crash - 2020: +15% during the Covid crash - 2013-2019: stagnating, a few losing years - Long-term CAGR: ~12-15% at ~15% vol
Relevance for Botty
Botty is not a CTA portfolio, but the signal recipe (EMA-50/100 + breakout confirmation) and ATR sizing are directly transferable. The full Clenow effect, however, needs multi-asset diversification — which would mean expanding Botty to multiple Hyperliquid coins (BTC + ETH + SOL + ...) with a shared vol target. That would be a significant architectural upgrade.