position-sizing

Q: How do I install position-sizing?

Run npx skills add https://github.com/agiprolabs/claude-trading-skills --skill position-sizing in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/position-sizing/ (personal) or .claude/skills/position-sizing/ (project).

by agiprolabsBusiness & Finance

Trade sizing methods including fixed fractional, volatility-adjusted, Kelly criterion, and liquidity-constrained sizing

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/agiprolabs/claude-trading-skills --skill position-sizing

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads position-sizing automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Position Sizing

Position sizing is the single most important risk management decision in trading. Your entry signal determines direction; your position size determines survival. A mediocre strategy with proper sizing will outperform a great strategy with reckless sizing over any meaningful time horizon.

Core principle: Size determines survival, not entries. Two traders with the same signals but different sizing will have wildly different outcomes. The one who sizes conservatively survives drawdowns and compounds capital; the one who oversizes blows up.

Methods Covered

Method	Best For	Key Input
Fixed Fractional	General trading, most recommended	Account risk %
Volatility-Adjusted	Volatile markets, multi-asset	ATR or realized vol
Kelly Criterion	Quantified edge with track record	Win rate + payoff ratio
Liquidity-Constrained	Low-liquidity Solana tokens	Pool depth
Anti-Martingale	Trend-following strategies	Recent P&L streak

1. Fixed Fractional Sizing

The most recommended method for most traders. Risk a fixed percentage of your account on each trade.

Formula

risk_amount = account_value * risk_percentage
price_risk_per_unit = entry_price - stop_loss_price
position_size_units = risk_amount / price_risk_per_unit
position_value = position_size_units * entry_price

Risk Tiers

Tier	Risk Per Trade	Use Case
Conservative	0.5–1%	New strategies, drawdown recovery
Standard	1–2%	Most traders, proven strategies
Aggressive	3–5%	High-conviction setups with strong, measured edge

Example

account = 10_000  # $10,000 or 100 SOL
risk_pct = 0.02   # 2%
entry = 1.50
stop_loss = 1.30

risk_amount = account * risk_pct          # $200
price_risk = entry - stop_loss            # $0.20
position_units = risk_amount / price_risk # 1,000 tokens
position_value = position_units * entry   # $1,500

With this sizing, if the stop loss is hit, you lose exactly 2% of your account regardless of the token's price or volatility.

2. Volatility-Adjusted Sizing

Scale position size inversely with volatility. When volatility is high, take smaller positions; when low, take larger positions. This normalizes the dollar risk across different market conditions.

Formula

adjusted_size = base_size * (target_vol / current_vol)

Where:

target_vol: your desired daily portfolio volatility (e.g., 2%)
current_vol: the token's current daily volatility (from ATR or realized vol)

Using ATR

atr_14 = 0.12          # 14-period ATR
close_price = 1.50
daily_vol_pct = atr_14 / close_price  # 8%

target_daily_vol = account * 0.02      # $200 target daily move
position_size = target_daily_vol / atr_14  # 1,667 units

This automatically reduces exposure in volatile markets and increases it in calm ones.

3. Kelly Criterion

The mathematically optimal fraction of capital to risk, maximizing long-term growth rate. Derived from maximizing expected logarithmic utility.

Formula

f* = (p * b - q) / b

Where:

p = win rate (probability of winning trade)
q = 1 - p (probability of losing trade)
b = average win / average loss (payoff ratio)
f* = optimal fraction of capital to risk

Equivalent form: f* = (p * (b + 1) - 1) / b

Critical Rule: NEVER Use Full Kelly

Full Kelly assumes perfect knowledge of your edge. In practice, edge estimates are noisy. Always use fractional Kelly:

Fraction	Use Case	Notes
0.25x Kelly	Conservative, recommended default	Robust to edge estimation error
0.50x Kelly	Moderate, for well-measured edges	Still significant drawdown risk
1.0x Kelly	Never in practice	Theoretical maximum, catastrophic if edge is overestimated

Example

win_rate = 0.55       # 55% win rate
avg_win = 2.0         # Average win is 2x the average loss
avg_loss = 1.0
payoff_ratio = avg_win / avg_loss  # b = 2.0

kelly = (win_rate * payoff_ratio - (1 - win_rate)) / payoff_ratio
# kelly = (0.55 * 2.0 - 0.45) / 2.0 = 0.325 = 32.5%

quarter_kelly = kelly * 0.25  # 8.1% — use this
half_kelly = kelly * 0.50     # 16.25%

If Kelly is negative, you have no edge. Do not trade.

See references/sizing_formulas.md for the full mathematical derivation.

4. Liquidity-Constrained Sizing

Critical for Solana tokens. Even if your risk model says you can take a large position, the pool may not support it without unacceptable slippage.

Formula (Constant-Product AMM)

slippage ≈ trade_size / pool_liquidity
max_trade = pool_liquidity * max_slippage_pct

Rules of Thumb

Constraint	Guideline
Max single trade	2% of pool liquidity
Max position	5% of pool liquidity
Minimum pool depth	10x your desired position size

Example

pool_sol = 500          # 500 SOL in pool
max_slippage = 0.02     # 2% max slippage

max_trade_sol = pool_sol * max_slippage  # 10 SOL
# For a $150 SOL price, that's $1,500 max per trade

Always check all pools, not just the largest. Aggregate liquidity across Raydium, Orca, and Meteora for the full picture. See the liquidity-analysis skill for pool depth assessment.

5. Anti-Martingale Sizing

Increase size after wins, decrease after losses. This is the opposite of the gambler's fallacy (Martingale). The logic: winning streaks may indicate your strategy is in sync with the market; losing streaks may indicate regime change.

Implementation

def anti_martingale_size(
    base_size: float,
    consecutive_wins: int,
    consecutive_losses: int,
    scale_factor: float = 0.25,
    max_multiplier: float = 2.0,
    min_multiplier: float = 0.5,
) -> float:
    if consecutive_losses > 0:
        multiplier = max(min_multiplier, 1.0 - consecutive_losses * scale_factor)
    elif consecutive_wins > 0:
        multiplier = min(max_multiplier, 1.0 + consecutive_wins * scale_factor)
    else:
        multiplier = 1.0
    return base_size * multiplier

Use conservatively. After 3+ consecutive losses, reducing size by 50% protects capital during drawdowns.

Position Sizing Ladder

Combine all methods and take the most conservative result:

1. Calculate Kelly size          → theoretical max based on edge
2. Calculate fixed fractional    → risk-based size
3. Calculate volatility-adjusted → vol-normalized size
4. Calculate liquidity-constrained max → market-based ceiling
5. Final size = min(all four)    → binding constraint wins

The binding constraint tells you what is limiting your size:

Kelly-bound: your edge is small, size accordingly
Risk-bound: standard risk management is the limit
Volatility-bound: market is too volatile for larger size
Liquidity-bound: pool cannot absorb more without slippage

Account-Level Limits

Individual position sizing is necessary but not sufficient. You also need portfolio-level constraints:

Limit	Guideline	Rationale
Max single position	10% of portfolio	Diversification floor
Max correlated exposure	25% of portfolio	Correlated assets move together
Max total exposure	50–80% of portfolio	Cash reserve for opportunities/margin
Max positions	5–10 concurrent	Attention and management bandwidth

PumpFun / Meme Token Sizing

PumpFun and early-stage meme tokens require special sizing discipline:

Very small positions: 0.1–1 SOL per trade due to extreme risk
Scale with bonding curve fill %: smaller when early (high rug risk), slightly larger when proven (graduated to Raydium)
Never size based on expected return — size based on acceptable total loss
Treat as lottery tickets: expect most to go to zero
Position limit: no more than 5–10% of portfolio across all meme positions combined

# PumpFun sizing example
account_sol = 100
meme_budget = account_sol * 0.05   # 5 SOL total for memes
per_trade = meme_budget / 10       # 0.5 SOL each, 10 shots

Integration with Other Skills

Skill	Integration
`risk-management`	Portfolio-level limits, drawdown rules
`liquidity-analysis`	Pool depth data for liquidity constraints
`kelly-criterion`	Deeper Kelly math, edge estimation
`exit-strategies`	Stop loss placement affects fixed fractional sizing
`volatility-modeling`	Better vol estimates for volatility-adjusted sizing
`slippage-modeling`	Precise slippage estimates for liquidity constraints

Files

References

references/sizing_formulas.md — Mathematical derivations for all sizing methods with worked examples
references/practical_guide.md — Sizing by account size, token type, and common mistakes

Scripts

scripts/size_calculator.py — Calculates position size using all methods, shows binding constraint
scripts/portfolio_sizer.py — Portfolio risk dashboard with per-position risk and available budget

Quick Reference

# Minimal fixed fractional sizing — copy-paste starter
def calc_position_size(
    account: float, risk_pct: float, entry: float, stop: float
) -> float:
    """Return number of units to buy."""
    risk_amount = account * risk_pct
    price_risk = abs(entry - stop)
    if price_risk == 0:
        return 0.0
    return risk_amount / price_risk

FAQ

What does the position-sizing skill do?

Trade sizing methods including fixed fractional, volatility-adjusted, Kelly criterion, and liquidity-constrained sizing

How do I install position-sizing?

Run npx skills add https://github.com/agiprolabs/claude-trading-skills --skill position-sizing in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/position-sizing/ (personal) or .claude/skills/position-sizing/ (project).

Which AI agents can use position-sizing?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is position-sizing safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains position-sizing?

It is published by agiprolabs in agiprolabs/claude-trading-skills. It has 581 recorded installs.

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position-sizing

Install

Install

Describe the task

Review the result

SKILL.md

Position Sizing

Methods Covered

1. Fixed Fractional Sizing

Formula

Risk Tiers

Example

2. Volatility-Adjusted Sizing

Formula

Using ATR

3. Kelly Criterion

Formula

Critical Rule: NEVER Use Full Kelly

Example

4. Liquidity-Constrained Sizing

Formula (Constant-Product AMM)

Rules of Thumb

Example

5. Anti-Martingale Sizing

Implementation

Position Sizing Ladder

Account-Level Limits

PumpFun / Meme Token Sizing

Integration with Other Skills

Files

References

Scripts

Quick Reference

FAQ

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