Hypotheses
DeFi Liquidity-Normalization Spread Across Hyperliquid and Bybit
Test whether temporary deterioration in an asset's own trading liquidity predicts subsequent relative recovery. Use synchronized 4-HOUR OHLCV bars for a fixed four-token DeFi basket: AAVE and UNI on Hyperliquid, CRV…
Hypothesis
Test whether temporary deterioration in an asset's own trading liquidity predicts subsequent relative recovery. Use synchronized 4-HOUR OHLCV bars for a fixed four-token DeFi basket: AAVE and UNI on Hyperliquid, CRV and SUSHI on Bybit. Buy the token with the greatest normalized illiquidity and short the token with the least, only after the former's liquidity begins improving. This is a multi-day liquidity-normalization experiment. Inspiration: [Market Microstructure Analytics](https://www.tradingview.com/script/34R4Mh5W-Market-Microstructure-Analytics/), consulted in the local library, supplies the Amihud proxy; no source code is copied. [Zhang and Li's cryptocurrency liquidity research](https://doi.org/10.1002/ijfe.2431) documents a cross-sectional liquidity–return relationship, but does not establish this proposed timing rule. Execute market orders at completed signal-bar closes, with one net position per selected instrument and platform-matched intrabar protective stops.
Backtest and paper results are hypothetical. Trading involves risk of loss.