Research Operating System
The governed workflow connecting hypothesis, evidence, validation, engineering and deployment.
One annual membership brings together the QTL research framework, published strategy research, source code, historical backtest evidence, AI-assisted workflows, market intelligence and deployment resources developed across the QTL research programme.
Built from roughly two years of accumulated research and development — organised into one connected environment designed to help you investigate, test, understand and ultimately implement systematic trading ideas.
Annual access · Cancel future renewal through the billing portal
Billed £997 GBP every 12 months, recurring until cancelled. Cancel any time — access runs to the end of your paid year.
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Research and educational content only. Trading involves risk. Historical and simulated results do not guarantee future performance.
This is not access to a single strategy, book or course. QTL connects research, AI, code, backtesting, validation, publishing and deployment inside one governed workflow.
Instead of starting with an empty notebook, members enter an established research environment containing the workflows, publications, prompts, strategy work and deployment resources developed through the QTL programme.
The governed workflow connecting hypothesis, evidence, validation, engineering and deployment.
104 structured prompts supporting research, coding, challenge, validation and controlled deployment.
A structured route through AI-assisted quantitative research, Python, backtesting, validation and implementation.
Operational research artefacts, working practices and supporting material for real research activity.
A controlled pathway from research parity toward production implementation.
Dedicated prompts and deployment guidance designed to help translate a researched and backtested system toward live MT5 implementation.
FlipBB and OS1 demonstrate the type of evidence-led strategy research published through the QTL process.
Members receive more than performance headlines: the research context, backtest evidence, methodology, implementation notes and supporting source code are provided where applicable.
Historical research simulation
Treasury-ledger historical backtest
Historical and simulated results are research outputs only. Past performance is not a reliable indicator of future results.
Membership begins with the current archive. It does not end there.
The QTL publishing programme targets one new fully backtested strategy research dossier each month, alongside current market research, strategy updates, publication revisions and member resources.
Structured current market intelligence, regime context and research observations.
Your central member workspace for intelligence, publications, strategy monitoring and research access.
The growing archive of published QTL strategy research, supporting evidence and updates.
The publishing programme targets one new fully backtested strategy research dossier each month.
Ongoing research observations and updates sit alongside the original published research.
New market research, publication revisions, downloads and member resources as the programme develops.
As the programme develops, active members gain access to new strategy research and subsequent updates released during their membership.
ChatGPT and other LLMs can explain concepts, generate and debug Python, interrogate performance results and translate plain-English research questions into structured quantitative workflows.
AI lowers the technical barrier. It does not lower the research standard.
QTL includes dedicated deployment material and prompts designed to help members work through the transition from researched strategy logic toward a controlled live MT5 implementation.
QTL research is built around explicit hypotheses, reproducible analysis, validation controls and documented limitations. Members see the research process rather than receiving an unexplained signal or performance headline.
Access the Research Terminal, member publications, FlipBB and OS1 research, source code, backtest evidence, governed AI prompts, Daily Quant Brief, deployment guidance and future research released during your active membership.
Research and educational content only. Historical or simulated results are not reliable indicators of future performance.