Indicator — Xhmaster Formula
// Plotting plotshape(strong_buy, title="Strong Buy", location=location.belowbar, style=shape.triangleup, size=size.small, color=color.new(color.green, 0)) plotshape(strong_sell, title="Strong Sell", location=location.abovebar, style=shape.triangledown, size=size.small, color=color.new(color.red, 0))
// Signal Logic strong_buy = trend_up and nmo > 70 and close > upper_env strong_sell = trend_down and nmo < 30 and close < lower_env
// Trend Direction trend_up = close > atl trend_down = close < atl
[ Upper\ Envelope = EMA_20 + (ATR_10 \times 1.5) ] [ Lower\ Envelope = EMA_20 - (ATR_10 \times 1.5) ] Xhmaster Formula Indicator
The Xhmaster scans for hidden and regular divergences between the NMO and price action, flagging them as "exhaustion" warnings. 3. Volatility Envelope (Keltner Hybrid) The final filter compares the current close to a volatility-adjusted band:
In the crowded landscape of technical analysis, most indicators are derivatives of the same few mathematical concepts: moving averages, standard deviations, and RSI calculations. The Xhmaster Formula Indicator stands apart. Designed for traders who need confluence without clutter, this indicator synthesizes trend direction, momentum divergence, and volatility contraction into a single, color-coded signal system.
//@version=6 indicator("Xhmaster Formula Indicator", overlay=true) // Parameters length = input.int(22, "ATR Length") multiplier_base = input.float(1.5, "Base Multiplier") The Xhmaster Formula Indicator stands apart
[ Signal = \fracNMO + 36 \times 100 ]
A signal is considered "valid" only if price closes outside the envelope for two consecutive bars. This eliminates the majority of whipsaws. The Xhmaster outputs three states:
[ NMO = \frac(Close - Close_t-14) - \mu_14\sigma_14 ] This eliminates the majority of whipsaws
// Adaptive Trend Line atr_val = ta.atr(length) rsi_val = ta.rsi(close, 14) dynamic_mult = multiplier_base + (rsi_val / 100) atl = (high + low + close) / 3 - (atr_val * dynamic_mult)
// Normalized Momentum Oscillator (NMO) period_mom = 14 price_change = close - close[period_mom] mean_change = ta.sma(price_change, period_mom) std_change = ta.stdev(price_change, period_mom) nmo_raw = (price_change - mean_change) / std_change nmo = (nmo_raw + 3) / 6 * 100
