TradrisAI Insights

What TradrisAI Is (And What It Is Not)

TradrisAI is not a chatbot. It does not generate generic trading tips or motivational quotes. It is structured behavioral intelligence derived from YOUR trading data — your actual trades, your journal entries, your position sizes, and your exit decisions.

Every insight you see in TradrisAI is calculated directly from the trades you have logged in your portfolio. If you have not logged enough trades, the insight simply does not appear. There is no filler, no hallucination, and no guessing.

TradrisAI answers one question: What does my own data say about how I trade?

It does this through 10 rule-based insights organized into three categories:

• Strategy — Which of your approaches actually works best?
• Discipline — Are you following your own rules?
• Behavior — What unconscious patterns show up in your trading?

All calculations are deterministic SQL and math. No large language model is involved in generating these insights, which means the numbers are reproducible, auditable, and grounded in reality.

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Where to Find TradrisAI

TradrisAI lives inside the Journal page. On desktop, it occupies the right-hand pane alongside your journal timeline. On mobile, it appears below the journal entries.

The pane has two tabs:

• Trade Patterns — The 10 rule-based insights described in this guide
• Mindset — AI-powered journal analysis (separate from Trade Patterns)

This guide covers the Trade Patterns tab.

On mobile, the TradrisAI pane appears below the journal entries.

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Severity Color Coding

Every insight card has a colored left border that tells you at a glance whether the finding is positive, neutral, or requires attention.

Each card is expandable. Tap or click to reveal the recommendation and supporting detail numbers.

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The 10 Insights

Insight 1: Most Profitable Strategy

Category: Strategy

What it shows: Which of your named strategies has the highest average R-multiple across closed trades. If you use three strategies — say Breakout, Mean Reversion, and Momentum — this insight tells you which one is actually making you money (measured in R, not raw P&L).

How it is calculated:

1. Filters to closed trades that have a strategy assigned
2. Groups trades by strategy
3. For each strategy, calculates average R-multiple: R = realizedPnl / riskAmount
4. Ranks strategies by average R and shows the top 3

Severity coding:

What to do with this:

• If one strategy clearly outperforms, lean into it. Allocate more of your trading time and capital to what your data says works.
• If your best strategy is barely breaking even (neutral), look at the detail breakdown. Are there enough trades for a meaningful sample? Is one bad trade dragging the average down?
• If the top strategy is negative (amber), something is fundamentally off. Review whether you are executing the strategy correctly or whether market conditions have shifted.

Insight 2: Discipline vs Performance Correlation

Category: Discipline

What it shows: Whether your disciplined trades actually perform better than your undisciplined ones. "Disciplined" means a trade has a discipline score of 70 or above (roughly 7+ journal entries across the trade lifecycle).

How it is calculated:

1. Filters to closed trades with a calculable R-multiple
2. Splits trades into two groups:
   • Disciplined: discipline score >= 70
   • Undisciplined: discipline score < 70
3. Calculates average R-multiple for each group
4. Compares the difference

Severity coding:

Why this matters:

This is perhaps the most powerful insight in TradrisAI. It uses YOUR data to answer the question every trader asks: "Does discipline actually pay off?" If the answer is yes (green), you have concrete, personalized proof that journaling and following your process leads to better results. That is not a generic motivational claim — it is a fact derived from your own trading history.

What to do with this:

• Green: Use this as motivation. When you feel tempted to skip journaling or deviate from your plan, remember that your own data proves discipline pays.
• Neutral: You may not have enough data yet, or your discipline level is inconsistent. Focus on increasing the number of trades with 7+ journal entries.
• Amber: This is rare but worth investigating. Are you journaling trades that are already going well (creating a false correlation)? Or are there other factors at play?

Insight 3: Discipline Trend

Category: Discipline

What it shows: Whether you are becoming more or less disciplined over time. It compares your most recent 10 closed trades against the 10 before that.

How it is calculated:

1. Takes all closed trades, sorted by exit date (most recent first)
2. Calculates average discipline score for trades 1-10 (recent)
3. Calculates average discipline score for trades 11-20 (previous)
4. Compares the difference

Severity coding:

What to do with this:

• Green (improving): Great momentum. Whatever routine change you made is working — keep doing it.
• Neutral (steady): Consistency is good. Try adding more detail to your journals to push the score higher.
• Amber (declining): Something changed. Did you get busy? Did you stop journaling entry and exit notes? Try journaling before and after each trade to get back on track.

Insight 4: Early Exit Detection

Category: Behavior

What it shows: What percentage of your winning trades you exited before reaching even half of your target price. This measures a common behavioral bias: cutting winners short.

How it is calculated:

1. Filters to closed, profitable trades that have entry price, exit price, and target price set
2. For each trade, calculates the exit ratio:
   • LONG: (exitPrice - entryPrice) / (targetPrice - entryPrice)
   • SHORT: (entryPrice - exitPrice) / (entryPrice - targetPrice)
3. Counts trades where the exit ratio is below 0.50 (exited before reaching 50% of target)
4. Calculates the percentage

Severity coding:

Why this matters:

"Let your winners run" is one of the oldest rules in trading, and one of the hardest to follow. Fear of giving back gains, boredom, or the urge to lock in a profit all push traders to exit early. This insight quantifies exactly how often you do it.

What to do with this:

• Green: You are letting winners run. Your exit discipline is solid.
• Neutral: Consider setting price alerts at 50% of your target so you have a checkpoint rather than an impulse exit.
• Amber: You are consistently leaving money on the table. Try moving your stop loss to breakeven instead of closing the trade. That way you protect your capital while giving the trade room to reach the target.

Insight 5: Risk Escalation After Wins

Category: Behavior

What it shows: Whether you tend to increase your position size after a winning trade. Overconfidence after wins is one of the most common and destructive behavioral patterns in trading.

How it is calculated:

1. Takes all closed trades in chronological order
2. Identifies trades that immediately follow a winning trade
3. Compares the average position size (quantity) of post-win trades against the overall baseline average position size
4. Calculates the escalation percentage

Severity coding:

Why this matters:

After a win, it feels natural to "press the advantage." But increasing position size based on recent results rather than your risk plan is a form of overconfidence bias. A streak of wins does not change the probability of the next trade. This insight catches the pattern before it catches you.

What to do with this:

• Green: Your sizing discipline is solid. You are not letting wins inflate your risk.
• Neutral: Minor size creep detected. Worth keeping an eye on. Consider logging your reasoning for position size in your journal.
• Amber: You are materially increasing risk after wins. Consider using fixed position sizing rules (e.g., always risk 1% of capital per trade) regardless of recent results.

Insight 6: Risk Utilization

Category: Behavior

What it shows: How much of your total allowed risk capacity is currently being used. If you have configured risk management settings (risk per trade and maximum parallel trades), this insight shows what percentage of that capacity is occupied by your current open positions.

How it is calculated:

1. Max risk exposure = maximum parallel trades x risk per trade
2. Utilization = current risk exposure / max risk exposure x 100

Severity coding:

What to do with this:

• Green: Comfortable capacity remaining. You can consider new positions without exceeding your risk plan.
• Neutral: Approaching your limit. Monitor your open positions before adding new exposure.
• Amber: Consider closing or hedging positions before adding new ones.

Note: This insight only appears if you have configured risk management settings in your portfolio.

Insight 7: Parallel Exposure Behavior

Category: Behavior

What it shows: How your trade performance varies depending on the number of positions you manage simultaneously. Some traders perform best when focused on a single trade; others thrive with multiple concurrent positions.

How it is calculated:

1. Takes the last 50 closed trades with entry and exit dates
2. For each trade, counts how many other trades were active at the time of entry
3. Groups trades into buckets: 1 trade, 2 trades, or 3+ trades active
4. Calculates average R-multiple for each bucket
5. Identifies which bucket has the best and worst performance

Severity coding:

This insight only surfaces when the difference between best and worst buckets is at least 0.3R (otherwise the signal is too weak).

What to do with this:

• If you perform best with 1 trade active: focus. Resist the urge to open multiple positions. Quality over quantity.
• If you perform best with 2 or 3+ trades active: you may benefit from diversified exposure. Your sweet spot is managing multiple positions simultaneously.

Insight 8: Position Sizing Consistency

Category: Behavior

What it shows: Whether your actual position sizes are consistent with your configured risk settings. If you say you risk 1% per trade, do your trades actually reflect that?

How it is calculated:

1. Takes the last 20 closed trades with a risk amount
2. Calculates each trade's risk as a percentage of total capital
3. Measures the standard deviation of risk percentages
4. Checks how many trades fall within +/- 1% of your configured risk level

Severity coding:

What to do with this:

• Green: Your sizing is consistent with your plan. This supports disciplined risk management.
• Neutral/Amber: Your sizing varies significantly from trade to trade. Use a position size calculator or fixed percentage rule to standardize.

Note: Requires risk management settings to be configured.

Insight 9: Stop Loss Discipline

Category: Discipline

What it shows: Two things: (1) how often you set stop losses on your trades, and (2) when you do set them, whether you actually honor them or exit beyond your stop.

How it is calculated:

1. Counts closed trades with and without a stop loss price set
2. For losing trades that had a stop loss, checks whether the exit price was worse than the stop loss (with a 2% tolerance for slippage):
   • LONG: exit below 98% of stop loss = breached
   • SHORT: exit above 102% of stop loss = breached

Severity coding:

What to do with this:

• Green: Strong stop loss discipline. Your detail view will also show whether you honored those stops on losing trades.
• Neutral/Amber: Many of your trades have no stop loss. Setting a stop loss on every trade defines your maximum risk upfront and removes the emotional decision of "when to get out" during a drawdown.

Insight 10: Worst Trade vs Risk Appetite

Category: Behavior

What it shows: Whether your single worst loss stayed within your configured risk appetite, or whether it blew past your limit.

How it is calculated:

1. Finds the trade with the most negative realized P&L (includes both closed and partially closed trades)
2. Calculates that loss as a percentage of total capital
3. Compares against your configured risk appetite percentage

Severity coding:

What to do with this:

• Green: Your worst-case loss stayed within your plan. That is the mark of a disciplined risk manager.
• Amber: Your largest loss exceeded what you said you were willing to risk. Consider tighter stop losses or smaller position sizes to prevent this from happening again.

Note: Requires risk management settings to be configured.

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Minimum Data Requirements

Each insight requires a certain number of trades before it can generate a meaningful result. If you do not have enough data, the insight simply does not appear — no filler, no guessing.

Practical guidance: If you are just getting started, focus on logging trades with complete data: entry price, exit price, target price, stop loss, risk amount, and a strategy name. The more fields you fill in, the more insights TradrisAI can generate for you.

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How Insights Are Refreshed

Trade Pattern insights load automatically when you open the Journal page. You can also manually refresh by clicking the refresh icon in the TradrisAI pane header.

Insights are calculated on demand from your current trade data. There is no caching or delay — what you see reflects the latest state of your portfolio.

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Understanding the Insight Card

Each insight card follows the same structure:

Collapsed view:

CATEGORY — Main message summarizing the finding. (chevron to expand)

(Left border color indicates severity: green, gray, or amber)

Expanded view:

CATEGORY — Main message summarizing the finding. (chevron to collapse)

Recommendation: What to do about this finding.

Detail	Value
Detail label	Detail value
Detail label	Detail value
Detail label	Detail value

• Category label (top): Strategy, Discipline, or Behavior
• Main message: The key finding in plain language
• Recommendation (expanded): What to do about it
• Details (expanded): The supporting numbers behind the insight

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Key Concepts

R-Multiple: A normalized measure of trade performance. R = realized profit or loss divided by the amount you risked. A trade that makes 2x what you risked is +2R. A trade that loses exactly what you risked is -1R. Using R (instead of raw rupees) lets you compare trades of different sizes on equal footing.

Discipline Score: A score from 0 to 100 based on how many journal entries a trade has. Each journal entry adds 10 points, capped at 100 (10 entries). A trade with a score of 70+ (7 or more journal entries) is considered "disciplined."

Risk Amount: The amount of money you are willing to lose on a trade if it hits your stop loss. This is set when you log the trade. TradrisAI uses this field heavily — trades without a risk amount cannot contribute to R-multiple calculations.

Risk Settings: Your portfolio-level risk configuration: total capital, risk per trade, and maximum parallel open trades. Insights 6, 8, and 10 require these settings to be configured. You can set them in Portfolio > Risk Management.

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Tips for Getting the Most Out of TradrisAI

1. Fill in all trade fields. Entry price, exit price, target price, stop loss, risk amount, strategy, and direction. Missing fields mean missing insights.

2. Assign a strategy to every trade. Without a strategy name, Insight 1 (Most Profitable Strategy) cannot include that trade.

3. Journal consistently. The discipline score is based on journal entry count. Aim for at least 7 entries per trade: pre-entry analysis, entry note, one or more updates during the trade, and an exit review.

4. Configure risk management settings. Three of the ten insights (Risk Utilization, Position Sizing Consistency, Worst Trade vs Appetite) require your risk settings to be configured.

5. Close your trades. Most insights only look at closed trades. If you have many active positions that never get closed out in Tradris, the insights will not reflect your full picture.

6. Check back after every 5-10 trades. Insights become more meaningful as your sample size grows. After 20 closed trades, all insights should be active.