Summary of Trading Bots Activity Overnight

The overnight monitoring period from the attached log file shows a fleet of three trading bots (bot_cl_crack_spread_arbitrage, bot_mbt_halving_call_ladder, and bot_mnq_ai_semiconductor) that experienced significant operational issues preventing any trade execution. The AI watchdog system (Minimax-M2.7-FW) continuously monitored the fleet and provided diagnostic recommendations throughout the period.

• All three bots were connected and running

• No entry/exit orders placed in 374-389 minutes initially

• All three bots flagged for AI diagnosis due to inactivity

Problem Identified:

• No spread data published (spread field = null)

• Execution timeframe (5 minutes) vs signal timeframe (60 minutes) created a 1:12 ratio instead of the recommended 1:6

• No trades executed in 620+ minutes of operation

Root Cause:
The bot is designed to exploit geopolitical crack spreads between crude oil and refined products, but it’s only receiving single-leg CLV6 price data without the required spread information. Without spread data, the arbitrage logic cannot evaluate whether entry conditions are met.

Recommended Fix:

• Implement an internal spread calculator using best bid/ask of the two legs

• Lower the entry threshold to react to price-level changes

• Align execution timeframe to approximately 10 minutes (1/6 of 60-minute signal)

Status: Regeneration recommended - YES

Problem Identified:

• Data feed stale at 132 seconds (significantly exceeding the 5-second threshold)

• No options market data available (option_quote_count = 0)

• IV at 100th percentile (extremely high) but realized volatility at only 0.25th percentile

• Zero bid-ask spread (bid = ask = price)

• No trades executed in 635+ minutes of operation

Root Cause:
The bot is designed to execute a call ladder strategy around Bitcoin halving events, relying on live options market data to calculate Greeks and trigger entries. However, the options market for MBTU6 appears to be either non-existent or extremely illiquid, preventing the bot from constructing the ladder or generating any signals.

Recommended Fix:

• Add a data-freshness monitor that forces a gateway reconnect if tick age exceeds 5 seconds

• Switch to a more actively quoted options series or replace with futures-based halving trigger

• Increase lookback bars to capture enough history for the ladder calculation

Status: Regeneration recommended - YES

Problem Identified:

• Execution timeframe (5 minutes) too long relative to signal timeframe (15 minutes) - ratio 1:3 instead of recommended 1:6

• Insufficient lookback period (20 bars) for reliable signal detection

• Extremely low proxy_vix readings (0.72-2.06) indicating ultra-low volatility environment

• No signals generated (signal_reason = NONE)

• No trades executed in 619+ minutes of operation

Root Cause:
The bot is designed to capture AI-driven semiconductor disruptions on the Micro Nasdaq-100 futures using momentum-based signals. However, the current low-volatility environment and insufficient historical data (20 bars) prevent the strategy from generating actionable signals. The lookback period may be too short for the AI semiconductor theme to develop meaningful trends.

Recommended Fix:

• Reduce execution timeframe to approximately 2.5 minutes (1/6 of 15-minute signal)

• Increase lookback bars to at least 40-50 bars for more reliable indicator calculations

• Add a volatility filter requiring proxy_vix ≥ 2.0 before allowing entries

Status: Regeneration recommended - YES

• No 2:1 win/loss rule breaches - All bots had zero trades, so no losses or wins recorded

• No circuit breakers tripped - No automatic stoppages triggered

• Primary risk: Opportunity cost from non-productive capital deployment and potential for unexpected clustering of orders if conditions suddenly align

All bots had unknown win rates, making it impossible to compute meaningful Kelly fractions. The AI recommended:

• Sizing down to minimum contract counts (1 contract per bot)

• Pausing any size increases until at least 30 trades are collected to establish reliable win-rate estimates

1. Spread data missing for CLV6 - preventing crack spread arbitrage logic

2. Stale data feed for MBTU6 - 132 seconds vs 5-second threshold

3. No options market data for MBTU6 - option_quote_count = 0

4. Ultra-low volatility across all bots - proxy_vix consistently below 2.0

• CLV6: 1:12 ratio (should be 1:6)

• MNQQ6: 1:3 ratio (should be 1:6)

• MBTU6: Execution timeframe not specified, requiring verification

1. bot_cl_crack_spread_arbitrage: Implement spread calculation logic, widen entry thresholds, align execution to 10 minutes

2. bot_mbt_halving_call_ladder: Add data-freshness monitors, ensure live options feed or switch to futures

3. bot_mnq_ai_semiconductor: Increase lookback to 40+ bars, reduce execution to 2.5 minutes, add volatility filter

• All bots should have explicit daily and weekly loss limits defined

• Data age thresholds should be enforced (max 5 seconds)

• Volatility filters should be implemented to prevent trading in unfavorable conditions

• Position sizing should remain at minimum until win rate data is collected

By the end of the monitoring period (04:51 UTC), all three bots remained idle with no trades executed. The AI watchdog system continued to monitor and recommend parameter adjustments. The fleet required:

1. Immediate reconnection of market data feeds

2. Parameter updates to align timeframes and entry thresholds

3. Instrument changes where market conditions are unsuitable

4. Implementation of proper risk controls before resuming operations

The primary conclusion was that the bots were not failing due to technical issues but rather due to market conditions and configuration mismatches that prevented signal generation. Resolving data quality issues and adjusting strategy parameters should enable the fleet to become productive once market conditions improve.