Momentum Strategies

Crypto is all about momentum

Momentum strategies

Economic intuition

Crypto markets exhibit momentum due to:

• Narrative-driven capital flows: Retail FOMO creates self-reinforcing buying pressure

• Trend-following systematic funds: Algo-traders and quant funds add fuel to trends

• Liquidation cascades: Forced selling/buying creates trend persistence

• Positive feedback: Price increases → media coverage → more buyers → price increases

Signal calculation

$$Momentum_{t} = \frac{\text{EMA}_{fast}(t) - \text{EMA}_{slow}(t)}{\sigma_t}$$

Where:

• $EMA_{fast}(t)$is fast exponential moving average (e.g., 5-day)

• $EMA_{slow}(t)$is slow exponential moving average (e.g., 60-day)

• $\sigma_t$ is realized volatility at time t

Momentum variations

We will support two distinct variations of this signal to capture different timeframe effects:

Fast momentum (5-day vs 30-day):

• Purpose: Captures short-term trend continuation (several weeks moves)

• Best for: High-volatility tokens with strong directional moves (HYPE, small caps)

• Turnover: ~40 trades/year

• Risk: Whipsaws in choppy markets, high turnover costs

Slow momentum (10-day vs 60-day):

• Purpose: Core momentum signal for portfolio (monthly trends)

• Best for: BTC, ETH, large-cap tokens

• Turnover: ~20 trades/year

• Risk: Moderate - catches most major trends without excessive churn

Volatility calculation

$$\sigma_t = \sqrt{\text{EMA}_{20}\left[(P_t - P_{t-1})^2\right]}$$

This exponentially-weighted volatility gives more weight to recent market conditions. Why 20 days? It balances responsiveness with stability. We use this volatility calculation throughout out entire framework.