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A lost connection does not tell you what your broker did with your orders, and it does not close your position. Those are two separate facts, and mixing them up is how a short outage turns into a hanging position. A “brake layer” is a control layer that sits between your strategy and your broker. It stops new orders when the connection looks unhealthy, pulls resting orders where the venue allows it, and refuses to resume until it has checked what the venue thinks is true.
This article sets out what that layer has to do, what venue-documented controls do and don’t cover (Kraken and Cboe are the documented examples), and how to test it. It describes design patterns and official guidance. It is not a trading recommendation, and it makes no claim about any particular outage or tool’s results.
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What actually happens to orders and positions when your bot disconnects
It depends on the venue and the API. Nothing is universal.
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- Open positions are not closed by any of the controls documented in the sources reviewed. Kraken’s timer cancels client orders. Cboe’s port controls cancel open orders or quotes and can block new ones. Neither is documented as a position-liquidation feature.
- Your local picture of orders and fills goes stale the moment the link drops. Fills can arrive while you can’t see them.
So a bot that reconnects and trusts its own memory can place orders against a state that no longer exists. That is the core failure the brake layer is for.
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Three states the layer must track separately
Keep these apart in code and in your head:
- Connection health: are heartbeats, market data and order acknowledgments arriving on time?
- Venue-acknowledged resting orders: what the broker says is live right now, not what you sent.
- Actual account positions: what the account holds, including partial fills that happened while you were blind.
This three-way split is an engineering recommendation inferred from the gap between a client-side timer and venue-side order state. The sources don’t prescribe a specific retail architecture.
What venue-side controls document today
Kraken: cancel on disconnect (dead man’s switch)
Kraken’s WebSocket API documents cancelAllOrdersAfter, described as a “Dead Man’s Switch.” Its documentation says: “The client has to keep sending new requests to push back the trigger time, or deactivate the mechanism by specifying a timeout of 0.” If the timer lapses, client orders are canceled.
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- Recommended values: a 60-second timeout, refreshed every 15 to 30 seconds. These are Kraken’s documented recommendations, not a general standard.
- Maintenance warning: Kraken says to disable the timer before scheduled matching-engine maintenance, because orders may be canceled when the engine comes back.
- Scope: orders only. Do not describe it as closing a position.
Cboe: port-level cancel and kill switch
Cboe’s Titanium U.S. Secure Web API specification describes port controls to cancel open orders/quotes, or to start a kill switch that cancels and blocks new orders. It notes that blocking does not persist across trading segments or dates, and it describes restrictions on resetting. I could not open that specification when preparing this article, so confirm current parameters and reset behavior in Cboe’s own documentation before relying on them.
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| Question | Kraken dead man’s switch | Cboe port controls |
|---|---|---|
| Trigger | Missed timer refresh | Explicit control action (cancel or kill switch) |
| Affects | Client’s open orders | Open orders/quotes; kill switch also blocks new orders |
| Closes positions? | Not documented | Not documented |
| Runs where | Venue-side, armed by the client | Venue/port-side, invoked by the user |
| Reset / maintenance | Disable before scheduled maintenance; refresh again after | Block doesn’t persist across segments/dates; reset restrictions apply (verify current text) |
These two examples don’t amount to a feature comparison across brokers. Run the same five questions (trigger, effect, location, reset, verification) against your own broker’s documentation.
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What the brake layer should do
1. Define “unhealthy” explicitly
Pick measurable signals: a missed heartbeat, no market data for N seconds, order acknowledgments exceeding a delay threshold, an expired API session, or a failed state query. Write the thresholds down. A vague “looks broken” rule gets argued with at the worst moment.
2. Stop generating orders first
The cheapest, most reliable action is the one fully under your control: halt new order creation the instant health fails. Everything else depends on a connection that may not exist.
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3. Use venue-side protection where it exists
If your venue offers a timer like Kraken’s, arm it so the venue acts even when your process is dead. A client-side cancel loop cannot run if the client has lost the network or crashed. Where only manual or port-level controls exist, document who triggers them and how.
4. Treat cancel and close as different actions
Canceling resting instructions does not reduce an existing position. If your concern is a hanging position, decide in advance, per broker, per instrument and per account, what a position-reducing action is, who is allowed to trigger it, and whether the bot may do it alone. Many setups sensibly make that a human decision with an alert, since an automated flatten during a data outage can itself trade on bad information.
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5. Reconcile before resuming
- Keep order generation halted after the connection returns.
- Query authoritative venue state: open orders, recent fills, positions, balances or margin.
- Compare with local state and resolve differences in the venue’s favor.
- Confirm any timer or block is in the state you expect (a dead man’s switch may have fired; a kill switch may still be active).
- Only then re-enable the strategy, preferably with a human confirmation after any non-trivial mismatch.
6. Handle cancel rejections
A cancel request can fail or be acknowledged late. The layer needs a retry policy, an escalation path (alert, manual intervention) and a rule that unresolved order state keeps the strategy halted.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Scenarios to test before trusting it
List these as test cases and run them in a paper or sandbox environment where the venue offers one. Only state that a test passed if you actually ran it.
- Network dropped mid-order, then restored
- Delayed or missing acknowledgments
- API session expiry
- Scheduled exchange maintenance, including the dead man’s switch firing on return
- Restart with stale local state
- Partial fills while disconnected
- Cancel requests rejected
FINRA’s algorithmic-trading overview lists pre-production testing and validation, and review after deployment or change, among practices firms can use. It also notes: “A reasonable supervision and control program may not prevent every possible failure.” Good controls reduce exposure. They don’t remove it.
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- United States: SEC Rule 15c3-5 applies to broker-dealers with market access. Under it, they must maintain controls reasonably designed to prevent orders exceeding preset credit or capital thresholds and orders that appear erroneous, review those controls regularly, and make an annual CEO certification. Staff FAQ guidance describes direct and exclusive control requirements, with limited circumstances for written allocation of some controls. It is not automatically a rule for an individual’s personal script, and it doesn’t require an individual to use any particular kill switch. FINRA’s overview is likewise addressed to member firms.
- United Kingdom: the FCA Handbook’s MAR 7A.3 covers firms engaged in algorithmic trading within its scope. It calls for effective systems and controls, resilient and adequately capacitated systems, trading thresholds and limits, prevention of erroneous orders, and testing and monitoring. MAR 7A.3.3 states: “A firm must have in place effective business continuity arrangements to deal with any failure of its trading systems.” The page shows a last-updated date of 1 January 2021, so check the current Handbook text.
Individual traders can still borrow the structure of these rules: thresholds, tested systems, monitoring and a continuity plan.
What hardware does and doesn’t solve
Backup internet, a router failover or a UPS can reduce some local failures. None of them guarantees broker connectivity, venue availability, correct order-state reconciliation or position liquidation. They sit alongside the software layer, not in place of it.
Quick Recap
A pre-flight checklist
- Do you know, from your broker’s documentation, what happens to resting orders on disconnect?
- Is any venue-side timer armed, with a refresh interval comfortably inside the timeout?
- Is that timer disabled or handled around scheduled maintenance?
- Does the bot halt new orders on its own health signals?
- Is there a written, per-instrument plan for reducing a position, and a named person who triggers it?
- Does reconnect force a full state query before trading resumes?
- Have you run the failure scenarios above, and do alerts reach you off the trading machine?
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