ITCP ATR BB RSI Stoch Signals

14 jam lalu

This indicator generates BUY/SELL signals when price stretches outside Bollinger Bands during elevated volatility, confirmed by RSI, a Stochastic crossover, and a volume filter. To reduce counter-trend entries, it applies a macro trend filter using the Daily SMA 200: it looks for longs only above the SMA 200 and shorts only below it.

It tends to perform best in Forex, especially on liquid pairs, because market conditions (liquidity, continuous sessions, and relatively stable spreads on major pairs) often suit this confirmation-based approach. That said, it can be adapted to other markets (indices, commodities, or crypto) by tuning parameters such as Bollinger length/deviation, RSI/Stoch thresholds, and ATR settings (multipliers/factors) to fit the asset’s volatility.

It also plots ATR-based stop-loss reference levels (configurable smoothing) and includes webhook-ready alerts with a JSON payload (action, symbol, price, stop_loss, time, and interval) for external automation. The goal is to support rules-based execution and reduce impulsive trades: if conditions don’t align, there’s no signal.

If you manage to improve it, discover better settings, or build a more robust solution inspired by this, I’d really appreciate it if you share it back (even if it’s just feedback or an idea). I’m open to collaborating and iterating together to create stronger versions over time.

14 jam lalu

Nota Keluaran

This indicator generates BUY/SELL signals when price stretches outside Bollinger Bands during elevated volatility, confirmed by RSI, a Stochastic crossover, and a volume filter. To reduce counter-trend entries, it applies a macro trend filter using the Daily SMA 200: it looks for longs only above the SMA 200 and shorts only below it.

It tends to perform best in Forex, especially on liquid pairs, because market conditions (liquidity, continuous sessions, and relatively stable spreads on major pairs) often suit this confirmation-based approach. That said, it can be adapted to other markets (indices, commodities, or crypto) by tuning parameters such as Bollinger length/deviation, RSI/Stoch thresholds, and ATR settings (multipliers/factors) to fit the asset’s volatility.

It also plots ATR-based stop-loss reference levels (configurable smoothing) and includes webhook-ready alerts with a JSON payload (action, symbol, price, stop_loss, time, and interval) for external automation. The goal is to support rules-based execution and reduce impulsive trades: if conditions don’t align, there’s no signal.

If you manage to improve it, discover better settings, or build a more robust solution inspired by this, I’d really appreciate it if you share it back (even if it’s just feedback or an idea). I’m open to collaborating and iterating together to create stronger versions over time.