Market Echo Screener [BigBeluga]

The Market Echo Screener is a structured multi-asset dashboard capable of tracking up to 15 symbols simultaneously.
Designed to condense complex market data into an actionable format. Each column represents a specialized calculation, giving traders insight into signals, phases, retests, and volatility — all updated in real time.

For each symbol, it displays a full set of analytics: trend signals, take profit progression, wave structure, equilibrium pulls, volatility-adjusted flows, smart band retests, volatility regimes, and live price context — all condensed into one unified table.

Instead of flipping through multiple charts, traders get an instant overview of market dynamics across an entire watchlist, making it easier to spot alignment and high-probability opportunities.

⬤ Trend Signals

This column is powered by a low-pass digital trend filter that smooths short-term fluctuations and isolates directional momentum.
It produces Buy and Sell signals when price crosses adaptive thresholds relative to the smoothed baseline. Stronger “＋” signals appear when slope acceleration or momentum divergence confirms additional conviction.



• Uses recursive filtering to eliminate noise.
• Signal strength is determined by the magnitude of deviation from the baseline.
• Tracks how many bars back the signal occurred, using a bar-counting algorithm.
• Combines both normal and power signals to reflect phases of market conviction.

⬤ TPs (Take Profits)

The take profit ladder is generated through an adaptive volatility-projection model.
When a signal fires, projected levels are based on volatility-weighted extensions. Each level (TP1–TP6) represents an incrementally wider confidence band, dynamically recalculated with every new bar.



• Uses volatility-normalized ranges for TP distances.
• Level activation is sequential, progressing as price reaches thresholds.
• Reset occurs when opposite signals are detected.
• Higher TPs imply extended momentum runs, while early TP triggers highlight conservative exits.

⬤ ActionWave

The ActionWave column applies a dual-smoothing algorithm combining custom MA stacks and polynomial regression to capture the underlying wave structure.
It identifies macro phases (Bullish ∆ / Bearish ∇) and flags retests when price folds back into the average after expansion.



• Wave slope is calculated using gradient differentials.
• Retests are confirmed within a bar-window threshold (e.g., 20–25 bars).
• Distinguishes continuation from exhaustion by analyzing whether slope remains positive/negative.
• Provides a clean map of trend rhythm without intrabar noise.

⬤ Magnet

The Magnet measure calculates a dynamic equilibrium band around price.
By averaging the midpoints of recent high–low ranges and weighting them by volatility, it defines a “fair zone” where price tends to trend and mean-revert.



• Bullish/Bearish status is derived from price position relative to the equilibrium mean.
• Retests occur when price leaves the zone and then re-enters within a tolerance band.
• Incorporates a mean-reversion index to highlight strength of pull.
• Acts as a gravitational anchor, showing when price is likely to snap back.

⬤ FlowTrend

FlowTrend is calculated using volatility and noise adjusted envelope bands.
It determines the active market flow by testing whether price consistently holds above or below the smoothed envelope. Retests are logged when price touches the envelope and respects trend direction.



• Bands expand/contract based on ATR and rolling variance.
• Flow state = Bullish if closing above upper envelope, Bearish if below.
• Retests validated only if trend slope and band alignment remain intact.
• Helps identify continuation setups by filtering false flips.

⬤ Smart Bands

Smart Bands employ an adaptive trailing stop framework that shifts with volatility and momentum.
Price interaction with these bands is tracked for bullish (∆) or bearish (∇) retests, highlighting whether the current move has revalidated at its volatility boundary.



• Bands derived from trailing volatility-adjusted stops.
• Upward retest fires when price tests support bands during uptrend.
• Downward retest occurs when resistance bands are tapped in downtrend.
• Provides structured “confirmation points” that validate signals.

⬤ Volatility

Volatility is measured via a hybrid standard deviation logic.
First, the standard deviation of closing prices over 10 bars is scaled by a factor, then normalized against its own 20-bar rolling standard deviation. The result is converted into a 0–100 index, producing three regimes:

❄️ Calm (<50): low dispersion, mean-reversion conditions dominate.

⚠️ Elevated (50–70): directional expansion likely, watch for breakout tension.

💥 Explosive (>70): strong dispersion, trend-following setups favored.


• Uses layered smoothing to dampen noise.
• Normalization ensures comparability across different assets.
• Acts as a meta-filter for selecting strategy type (range vs. momentum).

⬤ Price

The price column displays the latest close rounded to the nearest tick size.
It is color-coded by candle bias: green for bullish closes, red for bearish closes.



• Tick normalization ensures clean display across assets with different decimal precision.
• Color-coding gives instant sentiment context.
• Serves as the anchor reference for all other metrics in the row.


The Market Echo Screener is not a simple signal table — it’s a layered analytics framework.
Each column is driven by technical calculations: smoothing filters, volatility projections, equilibrium models, and adaptive band logic. Together, they create a unified lens on multiple assets, allowing traders to rapidly identify alignment, filter out noise, and focus on the clearest opportunities.