Vwap Cross (Trend)

Buys when price closes above the 20-bar volume-weighted average price — trading above what the average participant paid — and sells when it closes back below.

How It Works

1. Compute the volume-weighted average price over the last 20 bars: each bar's typical price weighted by the volume traded on it.
2. Buy when the close crosses above VWAP — price has moved above what the average participant recently paid, so buyers are now willing to pay up.
3. Sell when the close crosses back below it. Compared with a plain moving-average cross, VWAP is pulled toward the prices where real trading happened, so quiet drifting bars move it far less.

Worked example. Most of the last 20 bars traded near 102 on heavy volume, with a few thin bars down at 100, putting VWAP around 101.7. A close at 102.4 crosses above it and the strategy buys; the trade is closed weeks later when price slips back beneath the rising VWAP.

The Math Behind The Indicators

Everything runs on closing prices of the traded timeframe: P is a close, P_t today's close, and N counts bars — one bar is one candle of that timeframe, so 20 bars on a 1h chart is 20 hours.

Volume-Weighted Average Price (VWAP)

The average price actually paid, rather than the average price printed: every bar's typical price is weighted by the volume traded there, so busy bars pull it and quiet ones barely register. That makes it a benchmark of what participants collectively paid — price above VWAP means the market is now bid above the crowd's cost basis. Crypto never closes, so there is no daily session to anchor the sum to; this uses a rolling 20-bar window, which keeps the same meaning on every timeframe.

\[\mathrm{VWAP}_N = \dfrac{\sum_{i=1}^{N} TP_i \cdot V_i}{\sum_{i=1}^{N} V_i}, \quad TP = \dfrac{H + L + P}{3}\]

Example: Three bars trade at typical prices 100, 102 and 101 on volumes 10, 90 and 10. The plain average is 101, but the volume-weighted one is (100·10 + 102·90 + 101·10) / 110 ≈ 101.7 — pulled toward 102, where nearly all the trading actually happened.

Example Chart

Real Data36/ 100Composite score

Metrics Per Trade

Final Metrics

Scores

Resampled Data39/ 100Composite score

Metrics Per Trade

Final Metrics

Scores