Trades

The Trade endpoint returns the fill history for an account — every executed order that resulted in a position change. Use this to analyze your strategy’s trading activity, calculate performance metrics, or build a trade journal.

Trades vs. Orders

• Orders are instructions to buy or sell (may be pending, partially filled, filled, or canceled)
• Trades (also called “fills”) are the actual executions — completed transactions where contracts changed hands

An order with status 2 (Filled) will have a corresponding trade. Pending and canceled orders do not generate trades.

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POST Trade/search

Get the trade/fill history for an account. Returns all trades executed during the current session.

URL: POST /api/sim/Trade/search

Authentication: Bearer token required.

Request body

{
  "accountId": 12345,
  "startTimestamp": "2025-01-15T00:00:00Z",
  "endTimestamp": "2025-01-16T00:00:00Z"
}

Field	Type	Required	Description
accountId	number	Yes	Account ID
startTimestamp	string	No	Only return fills at or after this time
endTimestamp	string	No	Only return fills at or before this time

Response

Returns up to 500 fills, newest first.

{
  "success": true,
  "errorCode": 0,
  "errorMessage": null,
  "trades": [
    {
      "id": 2,
      "accountId": 12345,
      "contractId": "CON.F.US.ENQ.H25",
      "creationTimestamp": "2025-01-15T14:45:12.000Z",
      "price": 21518.50,
      "profitAndLoss": null,
      "fees": 1.24,
      "side": 1,
      "size": 1,
      "voided": false,
      "orderId": 1000000043
    },
    {
      "id": 1,
      "accountId": 12345,
      "contractId": "CON.F.US.ENQ.H25",
      "creationTimestamp": "2025-01-15T14:30:05.000Z",
      "price": 21503.25,
      "profitAndLoss": null,
      "fees": 1.24,
      "side": 0,
      "size": 1,
      "voided": false,
      "orderId": 1000000042
    }
  ]
}

Field	Type	Description
trades	array	List of trade/fill objects, newest first
trades[].id	number	Trade index within the response
trades[].accountId	number	Account ID
trades[].contractId	string	Contract ID
trades[].creationTimestamp	string	ISO 8601 timestamp of the fill
trades[].price	number	Execution price
trades[].profitAndLoss	null	Always null — fills are half-turns; compute round-trip P&L yourself
trades[].fees	number	Commission/fees charged on the fill
trades[].side	number	0 = Buy, 1 = Sell
trades[].size	number	Number of contracts filled
trades[].voided	boolean	Always false
trades[].orderId	number	The order ID that generated this trade

Example

Python

result = api("Trade/search", {"accountId": ACCOUNT_ID})

if result["success"]:
    trades = result.get("trades", [])
    print(f"Total trades: {len(trades)}")

    for trade in trades:
        side = "BUY" if trade["side"] == 0 else "SELL"
        print(f"  {trade['creationTimestamp']} — {side} {trade['size']} @ {trade['price']}")

cURL

curl -X POST https://api.test-max.com/api/sim/Trade/search \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_TOKEN" \
  -d '{"accountId": 12345}'

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Calculating performance from trades

You can compute key performance metrics directly from the trade history:

Total P&L

This FIFO example supports long and short positions, partial exits, and reversals. Use a complete fill history starting from a flat position, for one contract, with TICK_VALUE and TICK_SIZE set for that contract. Trade/search returns at most 500 fills: a truncated response or a timestamp filter that omits entries cannot produce reliable P&L. For a full run, use the final account balance from Replay/end minus the starting balance for net realized P&L after positions are flattened, assuming no other balance adjustments.

from collections import deque

result = api("Trade/search", {"accountId": ACCOUNT_ID})
if not result["success"]:
    raise RuntimeError(result.get("errorMessage"))
trades = sorted(result.get("trades", []), key=lambda t: t["creationTimestamp"])
entries = deque()
round_trips = []
gross_pnl = 0.0
fees = sum(trade["fees"] for trade in trades)

for trade in trades:
    direction = 1 if trade["side"] == 0 else -1
    remaining = trade["size"]
    while remaining and entries and entries[0]["direction"] != direction:
        entry = entries[0]
        quantity = min(remaining, entry["remaining"])
        pnl = (trade["price"] - entry["price"]) * entry["direction"] * quantity * TICK_VALUE / TICK_SIZE
        gross_pnl += pnl
        round_trips.append(pnl)
        remaining -= quantity
        entry["remaining"] -= quantity
        if entry["remaining"] == 0:
            entries.popleft()
    if remaining:
        entries.append({"direction": direction, "price": trade["price"], "remaining": remaining})

net_pnl = gross_pnl - fees
print(f"Gross realized P&L: ${gross_pnl:,.2f}")
print(f"Fill fees: ${fees:,.2f}")
print(f"Net realized P&L after all fill fees: ${net_pnl:,.2f}")

Gross realized P&L excludes fees. Net realized P&L subtracts all returned fill fees, including fees on any still-open entries; neither value includes unrealized P&L on those entries. When all positions are closed, net P&L includes both entry and exit fees.

Win rate of matched exit portions

Reuse round_trips from the FIFO example above. Each matched exit portion counts once, so scaling out can produce several results for one position. This is a gross win rate before fees, rather than the app’s closed-position win rate.

wins = sum(pnl > 0 for pnl in round_trips)
losses = sum(pnl < 0 for pnl in round_trips)
total_trades = wins + losses
win_rate = (wins / total_trades * 100) if total_trades > 0 else 0
print(f"Gross win rate of matched exit portions: {win_rate:.1f}% ({wins}W / {losses}L)")

Trade count and frequency

from datetime import datetime

trades = sorted(result.get("trades", []), key=lambda t: t["creationTimestamp"])
if len(trades) >= 2:
    first = datetime.fromisoformat(trades[0]["creationTimestamp"].replace("Z", "+00:00"))
    last = datetime.fromisoformat(trades[-1]["creationTimestamp"].replace("Z", "+00:00"))
    duration = last - first
    print(f"Session duration: {duration}")
    print(f"Trades: {len(trades)} over {duration}")

Tip

For strategy development, use Trade/search at the end of a backtest to evaluate performance before adjusting parameters. The Replay/end endpoint also returns the final account snapshot (balance and equity).

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Usage notes

• Trades are returned newest first (up to 500). Sort by creationTimestamp if you need chronological order.
• Each fill is a separate trade object, even if the order was partially filled across multiple prices.
• The trade list is scoped to the current replay session. Starting a new session resets the trade history.
• Use Trade/search after calling Replay/end to get the complete trade log for a session. Replay/end returns only the final account snapshot (balance and equity), while Trade/search gives you the individual fill details.