Xhmaster Formula Indicator -

// 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))

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:

// Trend Direction trend_up = close > atl trend_down = close < atl Xhmaster Formula Indicator

Where μ is the mean of 14-period price changes and σ is the standard deviation. The output is then clamped to a range of -3 to +3 and converted to a percentage:

[ Upper\ Envelope = EMA_20 + (ATR_10 \times 1.5) ] [ Lower\ Envelope = EMA_20 - (ATR_10 \times 1.5) ] The output is then clamped to a range

// 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)

//@version=6 indicator("Xhmaster Formula Indicator", overlay=true) // Parameters length = input.int(22, "ATR Length") multiplier_base = input.float(1.5, "Base Multiplier") // Signal Logic strong_buy = trend_up and nmo

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.

// Signal Logic strong_buy = trend_up and nmo > 70 and close > upper_env strong_sell = trend_down and nmo < 30 and close < lower_env

The gray neutral zone is not noise—it's a warning. Forcing trades during neutral conditions is the #1 cause of drawdowns with this indicator.

// 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