Trading systems research · Our own capital
Quantic Eagle builds trading systems: programs that turn market analysis into decisions about what to buy or sell and how much. We trade only with our own capital; we do not raise or manage other people’s funds. Here we share cases that help you understand and check those decisions.
Invented example · Not Quantic Eagle results
You are running a backtest: simulating a strategy’s buys and sells on past prices. You want to try a filter, an extra rule that skips some buy signals. Does it actually help you choose better trades?
Take every signal from the strategy, without the added filter. Use the same amount for each purchase.
The filter skips 12 trades. Expecting the remaining signals to be more reliable, you also choose to invest twice as much in each. Rerun the test over the same period.
These are separate tests; you are not changing positions that are already open. Both start with a simulated €10,000 account. In the second test you use more of that money per trade, without adding money to the account. At a price of €100, for example, you buy 20 shares instead of 10.
You made €154 more. Was that because of the filter, or because you doubled the trade size? The second test changed both which trades you took and how much you invested in each.
To measure the filter’s effect, rerun the second test with €1,000 purchases. The second button shows this comparison: identical prices and purchase amounts, with only the filter switched on or off.
Accumulated net profit · euros
Each point is a test: with or without the filter, buying €1,000 or €2,000 per trade.
Final net profit · €
A higher point means a larger final profit. A point further left means a smaller maximum drawdown: the account lost less money from a previous balance high. Here we measure the balance after each sale; temporary losses while a position is open are not visible.
Squares: no filter. Circles: filter applied. The number beside each point is the amount invested per trade in that test. The two filled symbols correspond to the comparison selected with the buttons.
You are comparing 48 trades at €1,000 without the filter against 36 at €2,000 with it. Profits are €294 and €448, but this comparison mixes two changes. Choose “Change only the filter” to see both versions buying €1,000 per trade.
Accumulated net profit · euros
Each point is a test: with or without the filter, buying €1,000 or €2,000 per trade.
Final net profit · €
A higher point means a larger final profit. A point further left means a smaller maximum drawdown: the account lost less money from a previous balance high. Here we measure the balance after each sale; temporary losses while a position is open are not visible.
Squares: no filter. Circles: filter applied. The number beside each point is the amount invested per trade in that test. The two filled symbols correspond to the comparison selected with the buttons.
Rerunning the filtered test with €1,000 purchases produces €188, versus €294 for the original strategy. The filter therefore cuts profit by €106 in this example. It also reduces maximum balance drawdown from €88 to €82: €6 less. You can now judge that trade-off; the €448 profit did not establish that the filter increased profit.
This can happen when you try a new strategy version: you add a rule and adjust position sizes too. To find out which change helps, first compare versions with one thing changed at a time.
| Strategy | Amount per trade | Net profit | Maximum balance drawdown |
|---|---|---|---|
| Without filter | €1,000 | +€294 | €88 |
| With filter | €1,000 | +€188 | €82 |
| Without filter | €2,000 | +€684 | €168 |
| With filter | €2,000 | +€448 | €142 |
At €2,000 per trade, you can also compare both strategies: profit is €684 without the filter and €448 with it. The filter therefore reduces profit by €236. Why is that not twice the €106 difference in the €1,000 tests? Doubling the amount doubles gross gains and losses, while the cost stays at €2 per trade. Skipping 12 trades always saves €24 in costs. These are this example’s assumptions, not a general law about filters or AI models.
Maximum balance drawdown is the largest fall from a balance high to a later low. For example, if the balance reaches €10,100 and then falls to €10,000, the drawdown is €100. Here we observe only the starting balance and the balance after each sale; the account could have lost more while shares were still held.
Each test starts with €10,000. Trades are sequential: sell the entire position before opening the next one. Within each test, invest the same amount per trade, without leverage or increasing it as profits accumulate.
Every purchase is made at €100 per share. Sale prices and the 12 skipped trades are already fixed in the invented data. We are not searching for a profitable filter; these choices illustrate how to compare two versions. A completed trade costs €2 in total for buying and selling; a skipped trade has no cost or profit.
Equal amounts per trade do not guarantee equal risk: the filter changes which trades are taken. This example does not evaluate a real AI model or establish future profits. Other costs, differences between expected and actual execution prices, and order execution constraints are excluded.
node QE-COMPARE-02.js
Why compare every combination? NIST/SEMATECH explains experimental design and interactions between changes. It is a methodological reference, not a validation of this example.
QE-COMPARE-02 / 1.0 · 20.09.2026 · Quantic Eagle LTD
01 / Risk along the way
Two paths can finish at the same level after exposing capital to very different losses.
02 / Testing the assumptions
A promising result may depend on low costs or execution that is hard to achieve. Those assumptions need testing too.
Brand film · 49 seconds
If you add a rule to skip some purchases, compare the program with and without that rule. Use the same data so you can see what the change actually did.
Suppose you make a decision on Monday at 10 am. News published at noon could not have helped, even if both entries have Monday’s date in your file.
A simulation can look promising until you include fees and less favourable purchase prices. Run the numbers again before drawing a conclusion.
If you change only the rule for choosing purchases, you may be able to reuse scores you have already calculated and checked. Repeat every test that depends on the new choice, though.
On day 15 you add a rule and run the simulation again from the start of the month. The new chart can help you understand the change. It does not show what the program actually decided during the first fourteen days, when it was still using the old rule.
The prices and predictions are made up for this exercise. They are not Quantic Eagle trades or results.
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