|
no
experience
|
1
products
|
0
demo versions
|
|
0
jobs
|
0
signals
|
0
subscribers
|
Founder
at
Davinci-lab
Davinci-lab is an independent research and development lab focused on quantitative finance, algorithmic trading, artificial intelligence and advanced market analytics.
We design and develop QBrain, a growing family of trading tools, applications and intelligent systems for MetaTrader 5 and other financial platforms.
QBrain products are built to support traders across the full decision and execution workflow, including:
• Market intelligence and regime detection
• Gold and XAU market analytics
• Quantitative signal discovery
• Algorithmic and systematic trading
• Expert Advisors and automated trading systems
• Indicators and market scanners
• Risk and execution management tools
• Strategy analysis and robustness testing
• AI-assisted quantitative research
• Portfolio and multi-asset analytics
Our development approach combines quantitative research, software engineering and systematic validation.
Rather than relying on isolated indicators or black-box trading claims, Davinci-lab focuses on building reusable technologies that can be tested, measured and progressively improved.
QBrain — Research. Intelligence. Automation.
We design and develop QBrain, a growing family of trading tools, applications and intelligent systems for MetaTrader 5 and other financial platforms.
QBrain products are built to support traders across the full decision and execution workflow, including:
• Market intelligence and regime detection
• Gold and XAU market analytics
• Quantitative signal discovery
• Algorithmic and systematic trading
• Expert Advisors and automated trading systems
• Indicators and market scanners
• Risk and execution management tools
• Strategy analysis and robustness testing
• AI-assisted quantitative research
• Portfolio and multi-asset analytics
Our development approach combines quantitative research, software engineering and systematic validation.
Rather than relying on isolated indicators or black-box trading claims, Davinci-lab focuses on building reusable technologies that can be tested, measured and progressively improved.
QBrain — Research. Intelligence. Automation.
Friends
Add friends via their profile or user search and you will be able to see if they are online
Nesrine Emilie Darragi
Published code QBrain Execution Friction Monitor
Quantitative MT5 indicator measuring execution friction relative to ATR using spread, commission and slippage assumptions.
1
Nesrine Emilie Darragi
QBrain Research Note #001 — A Signal Is Not an Edge
A recurring mistake in algorithmic trading is to confuse a detectable market signal with a tradable edge.
A signal may exhibit statistical structure and still be economically useless once execution is taken into account.
For a systematic strategy, the relevant quantity is not simply the gross expected return:
Net Edge = Gross Edge − Spread − Commission − Slippage − Execution Friction
This distinction becomes particularly important in short-horizon trading, where transaction costs can represent a significant fraction of the expected price movement.
At Davinci-lab, our QBrain research workflow therefore separates three questions:
1. Does a signal exist?
Is the observed relationship statistically distinguishable from noise?
2. Is the signal robust?
Does it survive different periods, parameters, market regimes and out-of-sample testing?
3. Is the signal economically tradable?
Does the expected advantage remain positive after realistic execution costs?
A high win rate alone does not answer any of these questions.
Nor does a profitable backtest automatically demonstrate a persistent edge.
QBrain is being developed around this evidence-first philosophy: research, measurement, falsification and only then automation.
Our current research focus includes Gold market microstructure, market regimes, execution friction and systematic signal discovery.
Davinci-lab develops the technology. QBrain delivers the tools.
QBrain — Research. Validate. Automate.
A recurring mistake in algorithmic trading is to confuse a detectable market signal with a tradable edge.
A signal may exhibit statistical structure and still be economically useless once execution is taken into account.
For a systematic strategy, the relevant quantity is not simply the gross expected return:
Net Edge = Gross Edge − Spread − Commission − Slippage − Execution Friction
This distinction becomes particularly important in short-horizon trading, where transaction costs can represent a significant fraction of the expected price movement.
At Davinci-lab, our QBrain research workflow therefore separates three questions:
1. Does a signal exist?
Is the observed relationship statistically distinguishable from noise?
2. Is the signal robust?
Does it survive different periods, parameters, market regimes and out-of-sample testing?
3. Is the signal economically tradable?
Does the expected advantage remain positive after realistic execution costs?
A high win rate alone does not answer any of these questions.
Nor does a profitable backtest automatically demonstrate a persistent edge.
QBrain is being developed around this evidence-first philosophy: research, measurement, falsification and only then automation.
Our current research focus includes Gold market microstructure, market regimes, execution friction and systematic signal discovery.
Davinci-lab develops the technology. QBrain delivers the tools.
QBrain — Research. Validate. Automate.
Nesrine Emilie Darragi
Published product
QBrain Strategy Auditor helps users identify incomplete or weak evidence before drawing conclusions from closed MetaTrader 5 outcomes. The utility is designed for strategy review. It does not open, modify, or close trades. It does not predict returns and does not certify a strategy. Main functions - Reads closed terminal account history in a selected date range or a normalized CSV placed in the MT5 file sandbox. - Checks whether the available evidence is sufficient for analysis. - Displays key