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A trading signal is not an order, and an order request is not a fill. To find why a bot appears to ignore a signal, log each transition—from market data and strategy evaluation through filters, submission, broker response, and final order state—as a separate, timestamped event. The title’s 41-day account is a personal anecdote; it should not be read as a verified incident report or a statistic about trading bots generally.
What “ignored a signal” can mean
The phrase can describe failures at very different points. A market event may never reach the strategy; the strategy may not evaluate the relevant condition; a candidate signal may be suppressed by a rule; an order may fail to submit; or a submitted order may be rejected, canceled, expire, or remain unfilled. Without records at each boundary, those cases can look identical: no trade appeared.
Separate the stages in your records. AKQuant’s strategy documentation describes distinct strategy, order, trade, and rejection callbacks, including on_order, on_trade, and on_reject. That separation is useful even if your system uses a different framework: it prevents a signal event from being mistaken for proof of an order or execution. AKQuant Strategy Guide
Trace one missing opportunity from input to outcome
Choose a specific event with an expected symbol and approximate event time. Search chronologically, following a correlation ID where one exists. The goal is to identify the last confirmed transition and the first missing or failed one—not to assume that a missing order means the strategy malfunctioned.
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- Confirm the input. Was the relevant market event received, and was it fresh enough for the strategy to use? Check feed or receiver records before looking only at orders.
- Confirm evaluation. Did the strategy process the relevant symbol and condition? Record the event time and, where useful, the inputs or rule version involved.
- Confirm candidate generation. Was a signal emitted? Record its direction and a signal identifier if the implementation provides one.
- Check decision gates. Did risk, position, session, cooldown, duplicate, or quality checks allow the candidate? These are examples, not a universal list. Log the actual gate and a specific reason whenever a candidate is suppressed.
- Check order intent and submission. Was an order created and sent? Preserve the client order ID and broker order ID when available.
- Check the broker lifecycle. Find the acknowledgment and subsequent fill, rejection, cancellation, or expiry. A submission record alone does not establish execution.
- Check downstream handling. If the broker recorded an event, verify that callbacks, queue consumers, and reporting stages processed it successfully.
A candidate that is intentionally filtered should leave a decision record, not merely an absence of an order. Otherwise, an operator cannot distinguish an expected suppression from a failure before submission.
What to put in the event trail
Use structured, machine-readable records so that related events can be searched and compared reliably. A practical starting schema is below; it is an implementation recommendation, not a universal standard.
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| Field | What it helps establish |
|---|---|
event_time_utc |
When the event occurred according to the system clock. |
event_type and phase |
Whether the record is input, evaluation, signal, gate decision, submission, broker update, or another transition. |
strategy_id and symbol |
Which strategy and instrument the event concerns. |
signal_id |
Which candidate signal later decisions or orders relate to, if the system assigns one. |
decision and reason |
Whether a candidate was allowed or suppressed, and the specific rule or cause. |
client_order_id and order_id |
How an order intent maps to an exchange or broker order once identifiers are available. |
| Broker status or error | Whether the order was acknowledged, filled, rejected, canceled, expired, or returned an error. |
In asynchronous systems, preserve both event time and receipt or processing time. A delay between them can otherwise be mistaken for a missing event. AKQuant documents context such as phase, strategy, symbol, event time, and order identifiers as part of its callback and logging guidance. AKQuant Strategy Guide
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Keep records after the process stops
Console output is useful during a live session, but it is not a dependable post-mortem trail if it is noisy, rotated away, or lost when a process restarts. Persist the order lifecycle separately so that submissions and later updates can be reconstructed.
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AKQuant documents a JSON order-audit stream for events such as submit, update, fill, cancel, and reject. Its live operations guide also recommends explicitly configuring logging and combining strategy-side order and trade records with gateway and execution warnings. The guide describes a separately persisted INFO-level order audit stream while keeping console output less noisy. AKQuant Live Trading Systems and Operations
AKQuant documents sensitive-field masking as enabled by default in that framework. Verify masking, storage access, and retention settings in your own deployment rather than assuming another system has the same defaults. The cited documentation does not establish a universal retention period or legal requirement.
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If the bot receives signals by webhook
Start at the receiver. If there is no receipt record, investigate the source alert, endpoint, and transport path before debugging order placement. If receipt exists but processing failed, follow the event into validation, risk checks, and order submission.
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Check whether market data was lost upstream
If input events are missing or delayed, inspect the feed and queue boundary as well as the strategy. OpenFNO’s data documentation lists queue-depth metrics and counts for ticks dropped, not stored, or rejected. These are useful examples of upstream observability, but their existence does not show that a particular bot has a data-loss problem. OpenFNO Data Module
Turn the first missing transition into an alert
Once the trail identifies the first absent or failed transition, add an alert aimed at that specific failure mode—for example, repeated feed drops, signal candidates without a decision record, or submitted orders without a later broker update. A process heartbeat only shows that a process is alive; it does not prove that data reached the strategy or that an order reached a terminal broker state. The alert should monitor the boundary that failed, not just the process.
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