Public example · Synthetic data
Trade analysis example: when one trade carries the profit
Read a TradingView CSV analysis report using 24 synthetic trades. Examine profit, drawdown, concentration and added costs, then analyze your own trade history.
These are not market or customer results. We calculated an invented trade history with the OptiNod CSV analysis engine. This is neither a strategy execution backtest nor a forward record.
Remove one trade and the conclusion changes
- Total P&L
- +139
- Largest winning trade (#13)
- +180
- P&L without the largest winner
- −41
Excluding the largest winner leaves a loss. This is a sensitivity calculation for concentration, not an improved strategy or a rerun with different trading rules.
Cumulative closed P&L
Profit and loss are added at each exit. This input contains no open-equity path or intratrade drawdown.
Overall metrics
- Closed positions
- 24
- Win rate
- 50%
- Profit factor (PF)
- 1.62
- Maximum closed-equity drawdown
- 60
All amounts are hypothetical currency units. Initial capital is 10,000, each entry is 1,000, and the input assumes zero fees and slippage.
What remains after added costs?
Costs are added to both entry and exit notionals. One bp is 0.01%. This does not reconstruct actual fills, funding or liquidity gaps.
| Added cost per side | Total P&L |
|---|---|
| 0 bp | +139 |
| 5 bp | +114.93 |
| 10 bp | +90.86 |
| 20 bp | +42.72 |
What this cannot establish
A synthetic sample of 24 positions cannot establish a strategy’s validity or future return. You still need market data, other periods, realistic costs and separate forward observation. This example does not reproduce RSI/MACD parameter comparisons or strategy optimization.
The 24 evidence trades
| Trade | Exit date (UTC) | P&L | Cumulative P&L |
|---|---|---|---|
| 1 | 2024-01-01 | −20 | −20 |
| 2 | 2024-01-04 | +15 | −5 |
| 3 | 2024-01-07 | −18 | −23 |
| 4 | 2024-01-10 | +22 | −1 |
| 5 | 2024-01-13 | −16 | −17 |
| 6 | 2024-01-16 | +18 | +1 |
| 7 | 2024-01-19 | −24 | −23 |
| 8 | 2024-01-22 | +20 | −3 |
| 9 | 2024-01-25 | −15 | −18 |
| 10 | 2024-01-28 | +14 | −4 |
| 11 | 2024-01-31 | −12 | −16 |
| 12 | 2024-02-03 | +16 | 0 |
| 13 | 2024-02-06 | +180 | +180 |
| 14 | 2024-02-09 | −30 | +150 |
| 15 | 2024-02-12 | −25 | +125 |
| 16 | 2024-02-15 | +20 | +145 |
| 17 | 2024-02-18 | −18 | +127 |
| 18 | 2024-02-21 | +12 | +139 |
| 19 | 2024-02-24 | −15 | +124 |
| 20 | 2024-02-27 | +18 | +142 |
| 21 | 2024-03-01 | −22 | +120 |
| 22 | 2024-03-04 | +15 | +135 |
| 23 | 2024-03-07 | −10 | +125 |
| 24 | 2024-03-10 | +14 | +139 |
Sample ID / result revision: trade-analysis-concentration / 38cd3d534b1878b9
What should you check in your own data?
Choose a TradingView List of Trades CSV or an MT5 report; no sign-in is needed to analyze it. Check whether a few trades drive the result and how much survives added costs, then test one change at a time.