May was the bot's second live month, and it was the month the main strategy showed it could pay its way. Its wins slightly outweighed its losses live, paper trading agreed, and the one big problem was easy to trace. Here's the month from the trade log.
At a glance
- The main strategy did most of the work, and did it well enough. It placed 66 of 75 live trades (88%), won 54.5% of them, and its wins slightly outweighed its losses before charges: a profit factor of 1.02.
- Paper trading told the same story. The same strategy on paper won 66% of 278 records with a profit factor of 1.16. Two separate samples pointing the same way is what I look for before I trust anything.
- Its losses were contained and its best win was big. The largest loss on the main strategy was 2.7 average losses. The best win was 9.2.
- A strong start. In the first week of May, 38 live records came in with a profit factor of 1.23, and the main strategy was up 2.8 average losses by Friday.
- The best run was 8 winners in a row.
- One trade explains the gap to break-even. On 25 May a new strategy, on only its third live trade, hit its stop for 13.1 average losses. That one record was bigger than everything the main strategy made all month.
The scorecard
| Live | Paper | |
|---|---|---|
| Trade records | 75 | 832 |
| Trading days with activity | 13 | 19 |
| Strategy variants | 6 | 64 |
| Win rate | 54.7% | 54.9% |
| Payoff ratio (average win ÷ average loss) | 0.58 | 0.53 |
| Profit factor (all wins ÷ all losses) | 0.71 | 0.71 |
| Longest winning streak | 8 in a row | 14 in a row |
| Longest losing streak | 7 in a row | 11 in a row |
| Deepest drawdown (in average losses) | 14.8 | 118.9 |
| Ran to the bot's own exit | 70 of 75 (93.3%) | 825 of 832 (99.2%) |
Live and paper are always kept apart. Paper runs many more ideas, including ones that never go live, so it is the wider and noisier of the two.
Where the result came from
The main strategy placed 66 of the 75 live trades. Results below are in units of the month's average live loss, so a figure of +1.0 means the group made back one average losing trade, before charges.
| Live records | Share | Win rate | Profit factor | Net result (in average losses) | |
|---|---|---|---|---|---|
| Main strategy | 66 | 88% | 54.5% | 1.02 | +0.5 |
| Other live strategies | 9 | 12% | 55.6% | 0.23 | -10.5 |
| All live trading | 75 | 100% | 54.7% | 0.71 | -10.0 |
The single best live record was worth 9.2 average losses and the single worst 13.1.
What worked
The rules did the exiting. 70 of the 75 live records ran to the bot's own exit, and 37 of the 41 winners were closed by the bot's rules, mostly by booking partial profit early. I stayed out of the way far more than I expected to in only the second live month.
Losses on the main strategy were capped. No main-strategy loss was bigger than 2.7 average losses. Its best win was more than three times that size. That lopsided shape is what lets a strategy work with a win rate close to 50%.
Live and paper agreed. The main strategy won 54.5% of its trades live and 66.2% on paper, and it stayed above break-even before charges in both. Paper is a best case, so the live number being lower is expected. What matters is that both sat on the right side of 1.
What held it back
A new strategy went live at full size, too early. A breakout variant went live on 15 May, before it had any paper history at all. It won its first two live trades, which is exactly the kind of start that makes you trust something. Its third, on 25 May, was the month's worst record. The idea hadn't earned that size yet. It's the clearest lesson of the month, and the most expensive one.
The payoff ratio needs to be higher. Across all live trading the average win was 0.58 of the average loss. At a 55% win rate, break-even needs a payoff of about 0.83. Stops were the most common way a live trade ended, at 41% of records.
The margin is thin once charges come in. A profit factor of 1.02 is before brokerage and taxes. After them, the main strategy was close to break-even rather than clearly ahead.
The first week didn't repeat. The main strategy's weekly profit factor went from 1.23 to 0.79 to 0.48 as the month went on, on fewer trades each week.
How trades ended
| How the trade ended | Live | Share of live | Share of paper |
|---|---|---|---|
| Stop-loss | 31 | 41% | 18% |
| Partial profit booked | 24 | 32% | 18% |
| Other rule-based exit | 9 | 12% | 28% |
| Closed by hand | 5 | 7% | 1% |
| Trailing stop | 5 | 7% | 15% |
| Time limit or end of day | 1 | 1% | 2% |
| Target reached | 0 | 0% | 18% |
What I'm watching in June
- Can the main strategy's margin grow enough to clear charges comfortably? A profit factor of 1.02 before charges is a starting point, not a result.
- Payoff ratio above 0.83 at this win rate. That's the number that turns a slight edge into a clear one.
- Small size for anything new until it has a record of its own. In May, one trade proved why.
- Manual exits at five or fewer. May's 70 of 75 is the bar.
- Nothing to report yet on time of day or expiry days. I checked both. Live and paper disagreed, and the samples are small, so there's no pattern worth acting on.
Every scorecard uses the same layout and definitions, explained on the scorecard page. Figures are counts and ratios from the trade log, before brokerage and taxes. For how I read the log, see how I analyse my trading bot's trades.
This scorecard describes my own trading system, for information only. It is not investment advice, and past results say nothing certain about the future. I am not registered with SEBI as an investment adviser or research analyst.