Getting a result is one thing. Knowing what it proves is another.
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.
Two predictions right out of three. One account loses.
The prices and predictions are made up for this exercise. They are not Quantic Eagle trades or results.
Same predictions. Why does one account gain and the other lose?
Here we compare two settings of the same trading system: a program that reads price predictions and calculates purchases, sales and an account balance. The predictions stay the same. Only the amount used for the third purchase changes.
All three predictions say the price will rise; the third is marked as more convincing. One setting always buys €1,000 worth. The other uses €2,000 for that third prediction. Both accounts start with a simulated €10,000; the trades happen one after another and each costs €2, including the sale.
The vertical axis zooms in on differences of a few dozen euros. The starting account balance is €10,000.
€1,000 every time€10,004Result after costs: +€4
Variable amount for the third purchase€9,984Result after costs: −€16
The price rises in 2 out of 3 cases, with both settings.
What happens if you change only that amount?
Keep predictions, prices and costs fixed. Choose the amount for the third purchase in the second test and watch its closing balance change.
Follow the money in the third purchase
The price falls from 100 to 98: a 2% loss. With €1,000 invested, you lose €20 plus €2 in costs. With €2,000 invested, you lose €40 plus the same €2 in costs. The first two trades made €26 after costs. That is why one account finishes €4 up and the other €16 down.
“The model was right twice out of three” leaves out exactly this difference. When comparing versions of your system, check how much each buys. Otherwise, you may attribute a change to the model when it arose after the prediction.
Two paths can finish at the same level after exposing capital to very different losses.
Path A
Path B
Same starting pointSame endpoint
Path B falls much further from its peak. Its final rise still leaves it below that peak. Looking only at where the two paths finish would miss this difference.
Depth
How far does it fall from its peak?
Duration
How long does it stay below that peak?
Recovery
Does it regain the peak within the period observed?
02 / Testing the assumptions
What happens when conditions change?
Illustration · invented data
A promising result may depend on low costs or execution that is hard to achieve. Those assumptions need testing too.
Reference assumptions
Higher costs
Less favourable execution
Shared starting conditionsChanged conditions
In the final part of this example, higher costs or less favourable execution reduce the gain and can turn it into a loss. These are invented scenarios, not forecasts or results from our systems.
Costs
Does the result hold up under less favourable assumptions?
Execution
Are the prices, timing and liquidity realistic?
Context
What changes in a different period?
Brand film · 49 seconds
Our capital. We answer for every decision.
Four checks to make sense of your test.
What change do you want to try?
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.
Had that information arrived yet?
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.
What is left after the costs?
A simulation can look promising until you include fees and less favourable purchase prices. Run the numbers again before drawing a conclusion.
What do you really need to repeat?
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.
Changed the rule? Keep the previous version too.
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.
Keep the decisions the program made at the time.
Save the past rerun with the new rule separately.
From now on, record which version you are using.
The prices and predictions are made up for this exercise. They are not Quantic Eagle trades or results.
IN PREPARATION · FREE RESOURCES AVAILABLE NOW
Turn your trading idea into a system you can test.
Before Capital is the practical fieldbook we are preparing for readers who already work with data and statistics. It takes you through choosing data, building tests and comparing versions of your system. The free cases are available now: follow the calculations and try the questions for yourself.
A practical note on how information becomes price, why competition compresses opportunity and why systematic research is ultimately a test of what survives beyond the historical sample.
Clarity is part of the operating discipline. Quantic Eagle is built to deploy its own capital and to keep research, execution and governance inside a controlled perimeter.
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A proprietary systematic investment company.
Operates exclusively with company capital
Develops and operates quantitative investment infrastructure
Conducts research, selection and operations internally
May engage selectively on corporate and strategic matters
Is not
A public investment proposition.
Does not accept or manage third-party capital
Does not offer investment advice or accept client mandates
Does not sell signals, models, trading execution software or execution access
Does not publish operational secrets or account-level data
Is not authorised to manage third-party investment capital or provide regulated investment services to clients, and does not offer those services.
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Understanding roles and relationships between owners
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