Sentiment-Informed Position Sizing

Methodology

Sentiment-informed position sizing integrates qualitative market signals with quantitative risk constraints to dynamically adjust capital allocation in crypto derivative contracts. Analysts derive these inputs from social volume, funding rate divergence, and order book skew to quantify investor bias. This approach moves beyond static exposure models by anchoring trade scale to the prevailing narrative strength before executing orders.