Trading journal software: what to track vs. your backtest report
A trading journal records what really happened in your account: fills, size, fees, reasons and screenshots. A backtest report records what the rules did on history. A systematic trader needs both, and the value comes from comparing them.
By Soren Huang · Published · updated · Editorial policy
Contents
- What should trading journal software record?
- How is a trading journal different from a backtest report?
- How do you compare live trades with backtest expectations?
- How do you review periodic performance and drawdown?
- Free or paid trading journal software: what should you look for?
- Frequently asked questions
- References
What should trading journal software record?
Trading journal software should record each live trade's entry and exit time and price, the size, the fees, the reason for the trade and a chart screenshot. For a systematic trader, the journal shows what actually happened in your account. The backtest report shows what the rules did on history. Comparing the two shows whether live trading matches the test.
A trading journal is a record of every trade you actually placed, with enough detail to explain later why it made or lost money. A bank statement tells you the balance changed. A journal tells you why. For a systematic trader, the most useful extra field is the price the strategy expected, next to the price you got. A journal helps most when trades come from a fixed process, such as a strategy imported into MultiCharts or exported to NinjaTrader.
| Field | What to record | Why it helps |
|---|---|---|
| Strategy and version | The strategy name and the exact parameter set that produced the signal | You can match the trade to the correct backtest, even after the strategy changes |
| Instrument | Symbol and contract month | Roll dates and contract months explain some odd fills |
| Direction and size | Long or short, number of contracts | Results per contract are only comparable if the size is known |
| Signal price and time | The price and bar at which the strategy decided to trade | This is the price your backtest assumed |
| Entry fill | The actual fill price and time | The gap to the signal price is your real slippage |
| Exit signal and exit fill | The same two prices for the exit | Exits often slip more than entries, especially stop exits |
| Fees | Commission plus exchange and clearing fees, per round trip | Small per trade, large per year |
| Reason or deviation | "Signal followed", "manual override", "missed signal" and a short note | Shows whether you traded the system or your own opinion |
| Screenshot | The chart at entry and at exit, with the strategy's marks visible | Lets you check later that the signal really appeared on the chart |
| Incidents | Platform disconnects, data feed problems, news at the time | Separates execution problems from strategy problems |
Slippage is the difference between the price your strategy expected and the price you actually received. You can calculate it per side in ticks:
Slippage in ticks = (fill price − signal price) ÷ tick size
Here, fill price is the price you got, signal price is the price the strategy used, and tick size is the smallest price step of the contract. For a buy, a positive number means you paid more than expected. For a sell, flip the sign so that a worse fill is also positive. Record this number for every entry and every exit.
How is a trading journal different from a backtest report?
A backtest report tells you how the rules behaved over many years of history. A journal tells you how your real trading behaved over the weeks and months you actually traded. Think of the backtest as the route plan for a long drive, and the journal as the driving log: the plan says the trip should take six hours, and the log shows where the traffic and the wrong turns were.
A backtest report is a summary of a strategy's simulated trades on historical data, usually with an equity curve, drawdown, a trade list and statistics. In AlphaPrime (Valynox), the Performance Report shows equity, drawdown, trades, periodic performance and long and short analysis for a tested strategy.
| Question | Backtest report | Trading journal |
|---|---|---|
| How did the rules perform across trending, ranging and volatile years? | Yes | No, it covers only the period you traded |
| How deep can a drawdown plausibly get? | Yes, from the history | Only the drawdowns you have lived through |
| What did execution really cost? | Only what you assumed | Yes, from real fills |
| Did I follow the rules? | No | Yes, from the deviation field |
| Did the platform and data behave? | No | Yes, from the incident notes |
How do you compare live trades with backtest expectations?
Compare execution first and performance later, because execution problems show up after a few trades, while performance needs many trades to mean anything. Run these steps from the top:
- Rerun the backtest over the live period. Use the same data, session settings and costs, and the same dates you traded live. Now each live trade should have a backtest twin.
- Count the trades. Missing or extra live trades usually point to a data difference, a session setting or a manual override. Check the deviation field.
- Compare signal prices. If live and backtest signals come at different prices, the bar data or the session settings differ. Fix this before anything else.
- Compare fills. Average your slippage per side from the journal and compare it with the slippage the backtest assumed.
- Compare the average trade after costs. Expectancy is the average amount a trade makes or loses over many trades. Calculate it from your journal with the win rate and expectancy calculator and put it next to the backtest figure.
- Decide with rules set in advance. Write down before going live what gap in slippage or trade count will make you stop and investigate.
Hypothetical example
A strategy trades a contract where one tick is worth $10. The backtest assumed 1 tick of slippage per side and $10 commission per round trip, and showed an average trade of $50 after costs. After 40 live trades, the journal shows an average trade of $25. The slippage column shows an average of 2.5 ticks per side, which is $50 per round trip instead of the assumed $20. That extra $30 more than covers the $25 gap: with the assumed slippage, the live average would be about $55, close to the backtest. The rules behave as tested, but execution costs more. The next step is to rerun the backtest with 2.5 ticks per side and check whether the average trade is still several times the round-trip cost.
This is why the signal-price field matters so much. Without it, you would only see "$25 instead of $50" and might blame the strategy. For more on how costs eat a small edge, see trading costs in backtests and the average trade. Feeding the slippage you log back into AlphaPrime's backtesting fees and slippage makes the next test start from what your fills actually cost.
Expect live results to come in somewhat below the backtest even when execution matches. When many variants are tested and the best is kept, its backtest result tends to be inflated. Harvey and Liu (2015) propose discounting backtested Sharpe ratios for exactly this reason.
How do you review periodic performance and drawdown?
Review on a fixed schedule and compare each period with the same period type in the backtest, not with your hopes. Drawdown is the fall of account equity from its previous highest point to a later low. You can measure it from your journal's equity series with the drawdown calculator, which also shows how long recovery took.
- Weekly: check execution. Look for missed signals, manual overrides, slippage outliers and platform incidents.
- Monthly: record the net result, the number of trades and the current drawdown. Compare them with the spread of monthly results in the backtest. A losing month is normal if the backtest also had losing months of similar size.
- Quarterly or after a set number of trades: compare live expectancy, win rate and average win and loss with the backtest, and check long and short trades separately.
- At any time: if the live drawdown passes the level you wrote down in advance, stop adding risk and run the comparison steps above.
A single backtest gives one maximum drawdown, but a different order of the same trades would give a different one. Reshuffling your trades gives a range of plausible drawdowns, which is a better yardstick for a live drawdown. See Monte Carlo simulation in Excel for a drawdown range for a method you can run on journal or backtest trades.
Free or paid trading journal software: what should you look for?
The best trading journal is the one you keep complete, so choose by how easily it captures the fields above, not by price. Free options include a spreadsheet, the trade export from your broker or platform, and free tiers of dedicated journal apps. Paid tools usually add automatic import, more reports and storage for screenshots. Check these points before you choose:
| Check | Why it matters for a systematic trader |
|---|---|
| Imports fills from your broker or platform | Manual entry of every fill leads to gaps and typing errors |
| Supports futures point values and contract months | Profit per contract is wrong if the multiplier is wrong |
| Has a fees field per trade | You need net results to compare with a backtest that includes costs |
| Lets you add custom fields, such as signal price | Slippage cannot be calculated without the expected price |
| Tags trades by strategy and version | Several strategies in one account must be reviewed separately |
| Attaches screenshots | Visual proof that the signal appeared where the rules say |
| Handles time zones consistently | Fill times must line up with the backtest's bar times |
| Exports all your data | You can rebuild the analysis in a spreadsheet or move to another tool |
A spreadsheet covers every row in this table if you are willing to paste in your platform's trade export each day. Many systematic traders start that way, because the custom columns for signal price and strategy version are easy to add.
What this means if you use AlphaPrime: the Performance Report gives you the backtest side of the comparison, so keep your journal in the same units and periods. Store each strategy in the Strategy databank and write its name and version into every journal entry, so each live trade points back to the exact rules that produced it.
Frequently asked questions
Is there free trading journal software?
Yes. A spreadsheet, your broker's or platform's trade export, and the free tiers of dedicated journal apps can all serve as a journal. What matters is that it stores fees, the signal price, the strategy version and screenshots, and that you can export your data.
What is the best trading journal for futures traders?
The best trading journal is the one you keep complete for every trade. For futures, check that it handles point values and contract months, records fees per trade, and lets you add custom fields such as the signal price. Automatic import from your platform makes it much easier to stay complete.
Do I need a trading journal if my strategy is fully automated?
Yes. Automation removes manual decisions but not slippage, missed orders, platform disconnects or data problems. The journal is where you see these, and it is the only way to check that live trading matches the backtest.
How many live trades do I need before comparing them with the backtest?
Execution can be checked from the first trades: slippage, missed signals and trade count. Profit and loss need many more trades, because a short sample can look good or bad by chance. Decide in advance how many trades you will wait for before judging performance.
What is the difference between a trading journal and a backtest report?
A backtest report shows how a strategy's rules performed on years of historical data with assumed costs. A trading journal shows the trades you actually placed, with real fills, fees and notes. The backtest sets the expectation and the journal checks it.
References
- Harvey, C. R., & Liu, Y. (2015). Backtesting. The Journal of Portfolio Management, 42(1), 13–28.