AI Trading Strategy Prompt Template: Turn Instructions into Testable Rules

A useful AI trading strategy prompt describes observable decisions and how to handle uncertainty. “Find profitable trades” leaves the entry, invalidation, size, and stopping behavior undefined.

Write a versioned instruction before testing and keep risk controls in the product's actual settings. A sentence asking the model to be conservative is not equivalent to an enforced execution limit.

Separate mandate, strategy, and reporting

The mandate identifies the account, allowed instruments, and hard constraints. The strategy describes the conditions for considering and managing a trade. Reporting explains what evidence and uncertainty the assistant should show.

Keeping those sections distinct makes a later review easier. If a trade violates a symbol limit, that is a different failure from a permitted trade with weak reasoning or a broker-rejected order.

For broker inputs, use the actual contract specification. MetaQuotes documents the relevant tick, volume, and order properties in its symbol reference. A prompt should not invent those values from a familiar ticker name.

Copy a bounded research template

The following template is a structure to complete, not a profitable trading strategy:

Account and symbols: use only the specifically selected account and approved instruments. State the account and resolved symbol before analysis.

Data: use the named timeframe and source. Identify the latest completed candle. If data is stale, missing, or inconsistent, wait and explain the gap.

Setup: consider an entry only when the predefined observable condition occurs. State the condition and the evidence rather than substituting a confidence label.

Invalidation: identify the price or event that defeats the thesis. Show entry, stop, first target, and the assumptions behind size.

Management: follow the written exit and cancellation rules. Do not widen risk or force an entry to meet a profit goal.

Review: distinguish proposed actions, broker acknowledgements, and actual fills. Record no-trade decisions and unresolved information.

Replace vague placeholders with measurable conditions before evaluating outcomes. A template that still says predefined condition is not ready to be scored as a finished strategy.

Define the no-trade branch

Specify what happens when signals conflict, costs invalidate the payoff, the minimum volume exceeds the budget, or the broker connection is unavailable. A good instruction allows the assistant to say it cannot verify a setup.

Do not require a minimum number of trades regardless of conditions. That changes the objective from applying the rule to producing activity.

A no-trade record should identify the missing condition or violated limit. Save it with the same timestamp discipline used for executed ideas so a later review can assess the complete decision process.

Put hard limits in TickerAI's settings

Eligible Auto Trading sessions use configured limits for allowed symbols, position count, per-trade risk, minimum reward-to-risk, drawdown, and other session controls. The engine and tools enforce relevant restrictions separately from the model's explanation.

The strategy text does not authorize raising those limits. Broker acceptance and actual fills still require their own checks, and prompt language does not guarantee an exact loss amount.

Read the demo setup guide and goal-accounting details before treating a session objective as a promise or automatic liquidation rule.

Change guidance deliberately

TickerAI lets the user send guidance during a running session. The current implementation carries recent guidance into subsequent ticks and allows it to influence behavior without raising hard constraints.

That context is bounded, so do not assume every message remains verbatim in the model's working view indefinitely. Consolidate standing instructions clearly and inspect the transcript and actual actions after a change.

A material change to entry or exit rules creates a new strategy version for performance review. Do not mix pre-change and post-change outcomes as though one unchanged rule generated all trades.

Evaluate adherence before celebrating returns

Suppose a hypothetical demo test logs ten qualifying decisions, of which eight follow the written rule and two deviate. The observed adherence rate is 80%. That is a process statistic, not the strategy's win rate or evidence of future profit.

Use the trading journal to preserve versions and walk-forward testing principles to plan later evaluation. A precise prompt makes behavior testable; it does not remove market uncertainty or establish a trading edge.