Indicators
A small collection of custom TradingView indicators built under The Traders’ Light. These tools are currently in beta and will evolve as the systems get refined. They are designed to support execution and decision-making — not to replace it.
The Toolkit is the "all-in-one" overlay I use for fast context: VWAPs, Daily Open, EMA structure, EMA 50/200 cross, vector candles, and a compact trend dashboard across multiple timeframes.
- VWAP suite: session VWAP + optional weekly/monthly VWAP
- Daily Open: clean daily open line (session aware)
- Macro trend: EMA 50/200 as the primary bias
- Micro alignment: front-run EMAs 25/50/75 (hidden by default)
- Cross markers: optional EMA 50/200 cross markers
- Vector candles: highlights abnormal participation / expansion candles
- Dashboard: current TF + 30m + 4h (trend / phase / micro)
⚠️ Beta note: defaults will keep the chart clean (50/200 visible; micro EMAs hidden). Dashboard colors/labels are still being refined.
Inspired by tools like Cipher B / VuManChu, but with a specific focus: filtering out the noise and emphasizing high-amplitude moves. The goal is to highlight moments that matter — extreme zones, clean crosses, and context-based divergences.
- Extreme-zone bias: WT2 moves above +60 / below -60
- Cross logic: bullish/bearish alignment conditions
- Divergences: validated between confirmed events with minimum separation
- Extra layers: integrated flow (MFI-style) + rescaled stochastic view
⚠️ Beta note: thresholds and divergence rules are still being tuned to reduce false positives.
A compact viewer that stacks four smoothed stochastics to quickly identify full alignment conditions. It’s meant as a timing / condition tool — especially when combined with structure and context.
- 4 stochastics: 9-3, 14-3, 40-4, 60-10
- Alignment: all > 80 (bearish) or all < 20 (bullish)
- Visual aid: background shading when alignment is complete
- Alerts: webhook-ready conditions for automation workflows
⚠️ Beta note: the viewer is stable, but the “when to act” rules depend on your broader context model.