Main Roadmap

Live Dashboard/Google Sheet Embed for Live Pricing

The user would like to see live pricing data directly within a dashboard or through an embedded Google Sheet to provide a real-time track record.

Live Position Trade Execution Alerts

User Problem: While the strategy is not for day trading, there's a lack of visibility into when initial positions are actually executed within the announced deployment window. This makes it difficult to align personal trades with the portfolio's actual entry points. Proposed Solution: Add a "Last Execution" timestamp and entry price to positions on the Flight Deck. Implement an optional, real-time alert (e.g., email or text message) that notifies members the moment a "BUY" order is executed for a new or scaled position.

Adaptive Trailing Stop Loss System.

We will introduce an Intelligent Trailing Stop Loss feature that dynamically adjusts stop levels based on the indicator's confidence score and momentum state, providing superior risk management compared to traditional fixed-percentage stops. The core innovation lies in its multi-factor adaptation: the stop distance would be calculated as base_atr_multiplier * (2.0 - conf_score) * volatility_factor , creating tighter stops (1.0-1.5x ATR) when confidence is high (>0.7) and wider stops (1.5-2.0x ATR) when confidence is moderate, preventing premature exits during normal market noise. The trailing mechanism would accelerate during strong momentum phases, using trail_speed = mom_up ? 0.02 * (1 + mom_rvfi_score) : 0.01 to quickly lock in profits during powerful moves while maintaining patience during consolidations. The system would feature three distinct modes: Aggressive Mode (activated when conf_score > 0.8 and strong momentum) trails at 0.5x ATR below the highest high, Standard Mode uses the adaptive calculation described above, and Protective Mode (triggered during regime transitions or when risk-off) widens stops to 2.5x ATR to weather increased volatility. Additionally, the stop would incorporate a "ratchet" mechanism that prevents the stop from moving lower in long positions (or higher in shorts) even if confidence temporarily decreases, ensuring profits are protected. The visual implementation would display the stop as a stepped line that changes color based on distance from price (red when <2% away, yellow at 2-4%, gray when >4%), with the current stop level and percentage distance shown in the info table. This feature would integrate seamlessly with the existing signal system, automatically initiating stops on buy/sell signals and clearing them on opposite signals, while providing alerts when price approaches within 1% of the stop level. Feedback submitted Close an hour ago 9 minutes ago a few seconds ago

The exit alert on ETHT issued on the weekend of 28th of September on the peformance trade log.. Exiting at market open price on the monday it opened up at 88 however the exit price on the performance board was at 97.5. This may be a typo executing according to the instuction yielded 11% lower at 88.

Enhanced Mean Reversion Signal System

We will introduce an Advanced Mean Reversion Detection module that generates additional high-probability reversal signals by identifying extreme oversold/overbought conditions through a proprietary multi-factor approach. The system would calculate a composite extremity score using extremity_score = (rsi_component * 0.3 + rvfi_component * 0.3 + price_stretch * 0.4) where each component is normalized to detect deviations from equilibrium. The RSI component would use adaptive thresholds that adjust based on recent volatility, with oversold levels dynamically set between 20-35 and overbought between 65-80 depending on vol_score . The RVFI component would identify extreme readings using percentile ranking over the adaptive lookback period, flagging conditions when RVFI falls below the 10th percentile (oversold) or above the 90th percentile (overbought). The price stretch component would measure deviation from multiple moving averages, calculating stretch_score = weighted_distance / adaptive_atr where weighted_distance combines distances from the 20, 50, and 200-period EMAs with heavier weighting on shorter timeframes. The system would generate "R" (Reversal) signals when extremity_score exceeds 0.8 and momentum shows early signs of exhaustion (declining velocity in the direction of the trend), displayed as distinctive purple triangles above/below price bars. To prevent false signals, the module would require confirmation through a "exhaustion pattern" - three consecutive bars where price makes new extremes but momentum indicators (RVFI score, volume pressure) show divergence. The feature would include an intelligent filtering system that suppresses reversal signals during strong trending markets (when market_trend >= 3 ) and enhances them during choppy conditions, with signal strength indicated by triangle size (larger = higher probability). The info table would add a new "REV" column showing the current extremity score (0-100) with color coding, helping traders identify when mean reversion conditions are building. This enhancement would complement the existing momentum signals, providing a complete trading system that captures both trend-following and mean-reversion opportunities while maintaining the indicator's strategic timeframe focus.

Enhanced position sizing framework based on confidence score.

We will introduce an Adaptive Position Sizing Module that transforms the current basic confidence-based sizing into a sophisticated risk management system. This new feature would calculate position sizes using a multi-tiered approach: first applying a Kelly-criterion inspired formula where base_size = account_risk * math.pow(conf_score / adaptive_threshold, 1.5) to create exponential scaling for high-confidence signals, then adjusting for market conditions with volatility_multiplier = 1.0 / math.sqrt(vol_score) to automatically reduce exposure during volatile periods, and finally incorporating a regime-based modifier that increases position sizes by 20% during strong trending markets (when market_trend >= 2 ) while reducing them by 30% in choppy conditions. The system would also feature a mean reversion boost that adds 15% to position size when price reaches extreme Bollinger Band deviations (|z-score| > 2.0), recognizing high-probability reversal opportunities. Additionally, the module would implement protective mechanisms including a maximum position size cap at 2x base allocation, automatic scaling down when the indicator detects regime transitions (reducing size by 50% temporarily), and integration with the existing risk-on/off system to completely halt new positions when is_risk_on is false. This enhancement would display the calculated position size in the info table with color coding (green for >1.2x, yellow for 0.8-1.2x, gray for <0.8x), making it easy for traders to quickly assess the indicator's conviction level and adjust their actual position sizes accordingly.