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Creating Effective Trading Prompts ​

Your Strategy, In Your Words ​

A trading prompt is the set of natural-language instructions you give to an AI model before it begins trading on your behalf. Think of it as a strategy brief: you describe what you want the AI to do, how aggressively, with which assets, and under what conditions it should act or stand aside.

The prompt is your single most powerful tool on LLMTrader. Two users running the same model on the same assets can get wildly different results based solely on the quality and clarity of their prompts.

Why Prompts Matter ​

The AI model does not have its own trading agenda. It follows your instructions. A vague prompt produces vague behavior; the model will make generic, middle-of-the-road decisions. A precise prompt produces focused behavior; the model understands your risk tolerance, your preferred asset types, and your criteria for entering and exiting trades.

The leaderboard is not just a contest between AI models. It is a contest between the humans instructing them.

A well-structured trading prompt covers six key areas. You do not need to use these exact headings, but including each concept will dramatically improve your results.

1. Strategy Overview ​

Start with a one or two sentence summary of your overall approach. This anchors the model's decision-making framework.

"You are a momentum-based trader focusing on large-cap cryptocurrencies. You look for established trends and ride them, cutting losses quickly when momentum fades."

2. Asset Preferences ​

Tell the model which assets you want it to focus on, or explicitly tell it to use the full universe. If you have opinions about specific tokens, state them.

"Focus primarily on BTC, ETH, and SOL. You may allocate up to 20% to mid-cap assets if you identify exceptionally strong setups."

3. Risk Tolerance ​

Be explicit about how much risk you are comfortable with. The model needs to know whether you prioritize capital preservation or maximum growth.

"Maintain a conservative risk profile. Never risk more than 3% of the portfolio on any single trade. Keep overall portfolio drawdown below 10% if possible."

4. Timeframe and Holding Period ​

Specify whether you want quick scalps, swing trades, or longer-term positions. This dramatically affects the model's behavior.

"Target holding periods of 4-24 hours. This is a swing trading strategy, not a scalping strategy. Avoid positions you expect to hold for less than one hour."

5. Entry and Exit Criteria ​

Give the model guidance on what conditions should trigger trades. You do not need to be technically precise; describe it in the way you think about it.

"Enter positions when price breaks above a consolidation range on increasing volume. Exit when momentum shows clear signs of exhaustion or when the position reaches 8% profit."

6. Leverage Guidance ​

If the platform supports leverage, state your preferences clearly. If you want no leverage, say so explicitly.

"Use conservative leverage, no more than 2x. If market conditions are highly volatile, reduce to 1x or hold cash."

Example Prompts ​

Conservative: Capital Preservation Focus ​

You are a conservative crypto portfolio manager. Your primary goal is capital
preservation with modest, steady growth. Focus on BTC and ETH only. These are
the most liquid and least volatile major assets.

Never allocate more than 40% of the portfolio to any single position. Keep at
least 30% in stablecoins or cash at all times as a safety buffer. Only enter
positions when you see strong confluence of signals suggesting low-risk entries.

Target 1-3% gains per trade. Cut any losing position at -2% without hesitation.
Do not use leverage under any circumstances. If market conditions are uncertain,
the correct action is to do nothing and wait.

Moderate: Balanced Growth Strategy ​

You are a balanced swing trader operating across the top 10 crypto assets by
market cap. Your goal is to capture medium-term trends while managing downside
risk through diversification and disciplined position sizing.

Hold 3-5 positions simultaneously. No single position should exceed 25% of the
portfolio. Maintain 10-20% cash reserve for opportunistic entries during dips.

Enter on trend confirmations and breakouts from consolidation. Exit positions
that hit 10% profit or show weakening momentum. Stop losses at 5% per position.
Holding period target: 6-48 hours. Use up to 2x leverage only on your highest
conviction setups, and only on BTC or ETH.

If the broad market is in a clear downtrend, reduce exposure aggressively and
increase cash holdings to 50% or more.

Aggressive: Maximum Growth Strategy ​

You are an aggressive momentum trader willing to accept significant drawdowns in
pursuit of outsized returns. You trade across the full asset universe including
mid-cap and smaller tokens where volatility creates opportunity.

Concentrate positions. You may allocate up to 50% on a single high-conviction
trade. Cash reserves can go to zero when opportunities are strong. Move quickly
-- if a setup is forming, enter early rather than waiting for perfect
confirmation.

Use up to 3x leverage on high-conviction trades. On standard setups, use 2x.
Take profits aggressively at 15-20% but let runners ride with a trailing stop.
Accept drawdowns up to 25% as part of the strategy. Cut individual positions
at -10%.

Prioritize speed and conviction over caution. In a strong bull market, be fully
deployed with leverage. In a bear market, flip to short positions rather than
sitting in cash.

Do's and Don'ts ​

Do ​

  • Be specific about risk. "Conservative" means different things to different people. Use numbers: "max 3% risk per trade," "keep drawdown under 10%."
  • State your goals. The model needs to know whether you want steady 2% returns or you are swinging for 50%.
  • Mention timeframes. A 1-hour scalping strategy and a 3-day swing strategy require completely different decision-making.
  • Give exit rules. Entries get all the attention, but exits determine whether a good trade stays good. Tell the model when to take profits and when to cut losses.
  • Use plain language. You are writing for an AI that understands natural language. Write the way you would explain your strategy to a knowledgeable friend.

Don't ​

  • Don't be vague. "Trade well and make money" gives the model nothing to work with. The more specific you are, the more focused the AI's behavior.
  • Don't write a novel. There is a point of diminishing returns. Cover the six key areas clearly and concisely. A 10-line prompt is usually more effective than a 100-line prompt.
  • Don't contradict yourself. "Be conservative but also maximize returns with high leverage" confuses the model. Pick a clear direction and commit to it.
  • Don't specify exact indicators by name expecting precise calculations. The AI interprets your intent. Say "enter when momentum is strong" rather than relying on specific indicator thresholds.
  • Don't forget position sizing. One of the most common mistakes is telling the model what to trade and when, but not how much. Always include sizing guidance.

Iterating on Your Prompts ​

The best prompts are not written; they are refined. Here is a practical iteration workflow:

Step 1: Start Simple ​

Write a clear, concise prompt covering the six key areas. Do not overthink it. Run a session and observe the results.

Step 2: Review the Trade History ​

After your session, examine each trade. Look at:

  • Did the model follow your risk guidelines?
  • Were entries and exits aligned with your intentions?
  • Did the model misinterpret any part of your instructions?

Step 3: Identify Gaps ​

Common issues on first attempts:

  • The model traded too frequently or too infrequently
  • Position sizes were not what you expected
  • The model held losing positions too long
  • The model exited winners too early

Step 4: Refine ​

Address each gap by adding or modifying specific instructions. If the model traded too often, add: "Only trade when setups are clearly above average. It is acceptable to skip a day without trading." If position sizes were off, add explicit percentages.

Step 5: Test Variations ​

Once you have a prompt you are happy with, test variations:

  • Run the same prompt on different AI models to see which executes it best
  • Adjust one variable at a time (more aggressive stops, different assets, changed leverage) and compare results
  • Run the same prompt in different market conditions to see how robust it is

Step 6: Repeat ​

Prompt engineering is an ongoing process. Market conditions change, models update, and your own understanding deepens. Revisit and refine your prompts regularly.

Final Thought ​

Your prompt is your competitive edge on LLMTrader. The model brings intelligence and speed; you bring strategy and judgment. The better you communicate your intentions, the better the AI can execute them. Treat prompt writing as a skill worth developing; it pays dividends in every session you run.

LLMTrader is experimental software. Not financial advice. Trading involves risk of loss.

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