Pyth Network (PYTH) 4-Hour Trend Following Relative Strength Momentum Rotation
Algorithmic 4-Hour Trend Following Relative Strength Momentum Rotation strategy for Pyth Network (PYTH). Calibrated for 3 to 14 days with Multi-day trend structure, volume profile nodes, and funding rate bias. Paper trade on live Binance data.
4-Hour Trend Following Calibration & Execution Dynamics
Expected duration from algorithmic entry trigger to defensive target exit.
Multi-day trend structure, volume profile nodes, and funding rate bias
Core systematic swing trend captures with highest signal-to-noise ratio
Mathematical Engine & Formula
RS = (AssetPrice_t / AssetPrice_{t-30}) / (BTCPrice_t / BTCPrice_{t-30})Entry Condition: Asset 30-day relative strength exceeds 1.20 and daily volume ranks in the top quartile of Binance spot pairs.
Exit Condition: Rotate capital into stablecoins or BTC when 7-day relative momentum decelerates below parity (1.00).
Execution & Cost Transparency (4H)
Most backtests fabricate impossible returns by assuming zero fees and zero slippage. Zengtrade factors realistic market realities into every paper trade on Pyth Network:
- Spot Friction: Rebalancing costs apply during sector rotations. Maintain disciplined trade frequency.
- Risk Guidance: Size positions according to ATR volatility to ensure stop loss does not exceed 1.5% account equity.
- 35 bps Friction Model: Exchange taker fee (10 bps) + maker fee (10 bps) + dynamic slippage buffer (15 bps).
Authored & Verified by Zengtrade Quantitative Research: Every model parameter for Pyth Network (PYTH) on 4-Hour Trend Following is calibrated on historical Binance spot tick archives with a 35 bps round-trip friction model. Zengtrade operates under a strict non-custodial, paper-first mandate: we never hold client deposits, never charge commissions on trading volume, and never fabricate hypothetical return curves. Forward-test evidence must be established before live deployment. Read our Regime Engine Methodology and Risk Disclosures.