Cost Basis & ROI

Overview

Compute a wallet’s cost basis (average entry price), current position value, and profit/loss scenarios for Polymarket markets. This workflow uses trade history to calculate precise financial metrics.

Prerequisites

polymarket CLI installed
A wallet address with trade history
The market’s current price (from markets get or clob price-history)

Workflow

Fetch wallet trades

Retrieve the full trade history:

polymarket -o json data trades <WALLET_ADDRESS> --limit 500

Example:

polymarket -o json data trades 0x9876543210abcdef9876543210abcdef98765432 --limit 500 > trades.json

Each trade object contains:

{
  "id": "trade_12345",
  "condition_id": "0x0f49db97f71c68b1e42a6d16e3de93d85dbf7d4148e3f018eb79e88554be9f75",
  "side": "BUY",
  "size": "1000",
  "price": "0.64",
  "timestamp": 1709856000
}

Filter to target market

Isolate trades for the market you’re analyzing:

import json

with open("trades.json") as f:
    all_trades = json.load(f)

target_condition = "0x0f49db97f71c68b1e42a6d16e3de93d85dbf7d4148e3f018eb79e88554be9f75"
market_trades = [t for t in all_trades if t["condition_id"] == target_condition]

Calculate total cost and shares

Sum across all BUY trades:

buys = [t for t in market_trades if t["side"] == "BUY"]

total_cost = sum(
    float(trade["size"]) * float(trade["price"])
    for trade in buys
)

total_shares = sum(float(trade["size"]) for trade in buys)

Example calculation:

Trade	Size	Price	Cost
1	500	0.60	300
2	300	0.65	195
3	200	0.70	140
Total	1000	—	635

total_cost = 635.00
total_shares = 1000

Compute average entry price

Divide total cost by total shares:

avg_price = total_cost / total_shares if total_shares > 0 else 0

Continuing the example:

avg_price = 635 / 1000 = 0.635  # 63.5%

This is your cost basis per share.

Account for SELL trades

If the wallet has sold shares, subtract from the position:

sells = [t for t in market_trades if t["side"] == "SELL"]

shares_sold = sum(float(trade["size"]) for trade in sells)
shares_held = total_shares - shares_sold

Cost basis remains the same (it’s the average entry price across all BUYs). Only the position size changes.

Get current market price

Fetch the latest price:

polymarket -o json markets get <market-slug>

Extract the current price from the output (e.g., 0.28 for 28%).

Calculate current value

Multiply shares held by the current price:

current_price = 0.28  # From market data
current_value = shares_held * current_price

Example:

shares_held = 1000
current_price = 0.28
current_value = 1000 * 0.28 = 280.00

Compute unrealized P&L

Compare current value to cost basis:

unrealized_pnl = current_value - total_cost
unrealized_pnl_pct = (unrealized_pnl / total_cost) * 100 if total_cost > 0 else 0

Example:

unrealized_pnl = 280 - 635 = -355.00  # Down $355
unrealized_pnl_pct = (-355 / 635) * 100 = -55.9%

Calculate win payout scenarios

If the outcome resolves in favor of the wallet’s position, each share pays out $1.00:

win_payout = shares_held * 1.00
win_pnl = win_payout - total_cost
roi_if_win = (win_pnl / total_cost) * 100 if total_cost > 0 else 0

Example:

win_payout = 1000 * 1.00 = 1000.00
win_pnl = 1000 - 635 = 365.00
roi_if_win = (365 / 635) * 100 = 57.5%

This assumes the wallet holds YES shares and YES resolves. If they hold NO shares, the payout occurs if NO resolves.

Example: Full Cost Basis Calculation

Let’s walk through a complete example.

Input Data

Wallet: 0x9876543210abcdef9876543210abcdef98765432 Trades (filtered to one market):

Trade ID	Side	Size	Price	Cost
1	BUY	500	0.60	300
2	BUY	300	0.65	195
3	BUY	200	0.70	140
4	SELL	100	0.68	(68)

Current market price: 0.28 (28%)

Calculations

# BUY trades
total_cost = 300 + 195 + 140 = 635.00
total_shares = 500 + 300 + 200 = 1000
avg_price = 635 / 1000 = 0.635  # 63.5%

# SELL trades
shares_sold = 100
shares_held = 1000 - 100 = 900

# Current position
current_price = 0.28
current_value = 900 * 0.28 = 252.00

# Unrealized P&L
unrealized_pnl = 252 - 635 = -383.00  # Down $383
unrealized_pnl_pct = (-383 / 635) * 100 = -60.3%

# Win scenario (if YES resolves)
win_payout = 900 * 1.00 = 900.00
win_pnl = 900 - 635 = 265.00  # Profit $265
roi_if_win = (265 / 635) * 100 = 41.7%

Summary

Metric	Value
Total Cost	$635.00
Shares Held	900
Avg Entry Price	$0.635 (63.5%)
Current Price	$0.28 (28%)
Current Value	$252.00
Unrealized P&L	-$383.00 (-60.3%)
Win Payout	$900.00
Win P&L	+$265.00 (+41.7%)

Key Formulas

Total Cost

Σ (size × price) for BUY trades

Total Shares

Σ size for BUY trades

Average Entry Price

total_cost / total_shares

Shares Held

total_shares - Σ size for SELL trades

Current Value

shares_held × current_price

Unrealized P&L

current_value - total_cost

Win Payout

shares_held × 1.00

ROI if Win

(win_payout - total_cost) / total_cost × 100

Tips

Use high --limit for active traders: A wallet with hundreds of trades needs --limit 1000 or pagination to capture full history.

Distinguish YES vs NO positions: Filter trades by outcome_index if available, or cross-reference with holder data to know which side the wallet is on.

Track realized P&L from SELL trades: Multiply each SELL by (sell_price - avg_price) to compute profit/loss on exited shares.

realized_pnl = sum(
    float(t["size"]) * (float(t["price"]) - avg_price)
    for t in sells
)

Caveats

Cost basis assumes FIFO (first-in, first-out). If the wallet uses a different accounting method (LIFO, specific lot), adjust accordingly.

Fees are not included in trade data. Polymarket charges a small fee on each trade. True cost basis is slightly higher than the sum of size × price.

Market resolution is binary: Shares pay

1.00 if the outcome resolves in your favor, or

0.00 otherwise. There is no partial payout.

Current price may be stale. Always re-fetch market data before calculating current value. Prices update with each trade.

Example Code: Python Script

import json
import sys

def compute_cost_basis(trades, condition_id, current_price):
    # Filter to target market
    market_trades = [t for t in trades if t["condition_id"] == condition_id]
    
    # Separate BUY and SELL
    buys = [t for t in market_trades if t["side"] == "BUY"]
    sells = [t for t in market_trades if t["side"] == "SELL"]
    
    # Total cost and shares
    total_cost = sum(float(t["size"]) * float(t["price"]) for t in buys)
    total_shares = sum(float(t["size"]) for t in buys)
    avg_price = total_cost / total_shares if total_shares > 0 else 0
    
    # Shares held
    shares_sold = sum(float(t["size"]) for t in sells)
    shares_held = total_shares - shares_sold
    
    # Current value
    current_value = shares_held * current_price
    
    # Unrealized P&L
    unrealized_pnl = current_value - total_cost
    unrealized_pnl_pct = (unrealized_pnl / total_cost * 100) if total_cost > 0 else 0
    
    # Win scenario
    win_payout = shares_held * 1.00
    win_pnl = win_payout - total_cost
    roi_if_win = (win_pnl / total_cost * 100) if total_cost > 0 else 0
    
    return {
        "total_cost": total_cost,
        "total_shares": total_shares,
        "avg_price": avg_price,
        "shares_held": shares_held,
        "current_price": current_price,
        "current_value": current_value,
        "unrealized_pnl": unrealized_pnl,
        "unrealized_pnl_pct": unrealized_pnl_pct,
        "win_payout": win_payout,
        "win_pnl": win_pnl,
        "roi_if_win": roi_if_win,
    }

if __name__ == "__main__":
    # Load trades from JSON file
    with open("trades.json") as f:
        trades = json.load(f)
    
    condition_id = "0x0f49db97f71c68b1e42a6d16e3de93d85dbf7d4148e3f018eb79e88554be9f75"
    current_price = 0.28  # Update with real-time price
    
    result = compute_cost_basis(trades, condition_id, current_price)
    
    print(f"Total Cost: ${result['total_cost']:.2f}")
    print(f"Shares Held: {result['shares_held']:.0f}")
    print(f"Avg Entry Price: ${result['avg_price']:.4f} ({result['avg_price']*100:.2f}%)")
    print(f"Current Price: ${result['current_price']:.4f} ({result['current_price']*100:.2f}%)")
    print(f"Current Value: ${result['current_value']:.2f}")
    print(f"Unrealized P&L: ${result['unrealized_pnl']:.2f} ({result['unrealized_pnl_pct']:.2f}%)")
    print(f"Win Payout: ${result['win_payout']:.2f}")
    print(f"Win P&L: ${result['win_pnl']:.2f} ({result['roi_if_win']:.2f}%)")

Next Steps

After computing cost basis:

Monitor the position: Re-run the analysis periodically as the market price changes
Compare to other holders: Use Holder Analysis to see how this wallet ranks
Generate a price chart: Visualize market movement with Charts

Get Started

Core Commands

Workflows

Reference

Examples

Overview

Prerequisites

Workflow

Example: Full Cost Basis Calculation

Input Data

Calculations

Summary

Key Formulas

Total Cost

Total Shares

Average Entry Price

Shares Held

Current Value

Unrealized P&L

Win Payout

ROI if Win

Tips

Caveats

Example Code: Python Script

Next Steps

Build docs developers (and LLMs) love

Get Started

Core Commands

Workflows

Reference

Examples

​Overview

​Prerequisites

​Workflow

​Example: Full Cost Basis Calculation

​Input Data

​Calculations

​Summary

​Key Formulas

Total Cost

Total Shares

Average Entry Price

Shares Held

Current Value

Unrealized P&L

Win Payout

ROI if Win

​Tips

​Caveats

​Example Code: Python Script

​Next Steps

Build docs developers (and LLMs) love

Overview

Prerequisites

Workflow

Example: Full Cost Basis Calculation

Input Data

Calculations

Summary

Key Formulas

Tips

Caveats

Example Code: Python Script

Next Steps