Risk Management

How Affective State Updates

• After a win: Confidence += f(P&L magnitude), win streak ++, loss streak reset
• After a loss: Confidence -= f(P&L magnitude), loss streak ++, win streak reset
• Drawdown crossing thresholds: Risk appetite auto-reduces at 5%, 10%, 15% drawdown
• Daily review: Confidence recalibrated against actual hit rate

Using Affective State

Check get_agent_state before every trading session:

get_agent_state() → {
  confidence: 0.42,
  drawdown: 8.3%,
  win_streak: 0,
  loss_streak: 3,
  risk_appetite: "low"
}

Action rules:

• risk_appetite == "low" → Reduce position size by 50% or skip marginal setups
• loss_streak >= 3 → Stop trading for the session. Review, don't revenge trade.
• confidence < 0.3 → Paper trade only until confidence recovers
• drawdown > 15% → Hard stop. No new positions until daily review.

Behavioral Risk Indicators

1. Disposition Effect

What: Cutting winners short and holding losers too long. Detection: get_behavioral_analysis → disposition_ratio

• Ratio < 1.0 = Good (holding winners longer than losers)
• Ratio > 1.5 = Problem (losers held 50% longer than winners)
• Ratio > 2.0 = Critical (classic retail trader failure mode)

2. Revenge Trading

What: Increasing position size or trade frequency after losses. Detection: Compare lot sizes and trade count in the N trades after a losing streak vs baseline.

• Lot size > 1.5x baseline after loss = Revenge sizing
• Trade frequency > 2x baseline after loss = Overtrading

3. Overtrading

What: Taking more trades than the strategy generates signals for. Detection: Compare actual trade count vs strategy signal count.

• If strategy generates 3 signals/week but you take 10 trades/week, you're inventing trades.

4. Session Drift

What: Trading outside designated sessions. Detection: Check trade timestamps against strategy's defined trading windows.

• VolBreakout is a London session strategy. Trades at 3am UTC = session drift.

5. Confidence Miscalibration

What: Your confidence doesn't match your actual accuracy. Detection: get_behavioral_analysis → confidence calibration curve.

• If trades rated confidence 0.8 win only 40% of the time, your confidence is miscalibrated.

Position Sizing Rules

TradeMemory's procedural memory tracks position sizing patterns:

Fixed Fractional

Default: Risk X% of equity per trade (typically 0.25-2%).

Position Size = (Equity × Risk%) / (Entry - StopLoss)

Kelly Criterion

Optimal sizing based on historical edge:

Kelly% = WinRate - (LossRate / AvgWin÷AvgLoss)

• Full Kelly is too aggressive for real trading. Use Half Kelly or Quarter Kelly.
• get_behavioral_analysis returns Kelly criterion values per strategy.

Lot Sizing Variance

Procedural memory tracks how consistent your sizing is:

• Low variance = Disciplined execution
• High variance = Emotional sizing (bigger when confident, smaller when scared)
• Target: coefficient of variation < 0.2

Best Practices

Before Every Session

1. Check get_agent_state — is confidence reasonable? Any active streaks?
2. Check drawdown — are you within acceptable limits?
3. Review active trading plans — don't enter trades outside your plans

After Every Trade

1. Record the trade with remember_trade — include honest reflection
2. Did the trade match your strategy rules? If not, why?
3. Was position sizing consistent with your risk rules?

After a Losing Streak (3+ consecutive losses)

1. Stop trading. Not permanently — just for the current session.
2. Run /daily-review — is there a systematic problem or just variance?
3. Check disposition ratio — are you holding losers too long?
4. Reduce position size for the next 5 trades (half the normal size)
5. Only resume full size after 2 consecutive wins at reduced size

After a Winning Streak (5+ consecutive wins)

1. Don't increase size. Winning streaks end. Mean reversion is real.
2. Check if you're cherry-picking easy setups and avoiding harder (but higher EV) ones
3. Review: are the wins from your strategy or from a favorable market regime?

Common Mistakes