Frequently asked questions

Data Gateway is in production with 90+ sources and exchanges and more than 640 governed routes.

Backtester Open is available under Apache 2.0 with 50 runnable strategies, 80+ research metrics and local execution.

Backtester PRO adds managed research data and more advanced research workflows around validation, walk-forward analysis and optimisation.

OneBook is currently being tested with an institutional client across portfolio management, IBOR, proposed changes, risk and investment workflows.

Data Gateway provides one maintained access layer across financial, regulatory, macro, derivatives, alternative and crypto data sources.

Teams can access enabled sources through REST, Python SDK or permissioned MCP rather than maintaining a separate integration for every provider.

Public sources can be used under their own terms. Commercial sources use the client's own vendor licences and credentials.

Backtester Open is the Apache 2.0 research engine. It runs locally and includes the core simulation framework, strategies, execution assumptions, metrics and research tooling.

Backtester PRO adds the managed research environment around that engine, including fundamental and research-ready data, advanced walk-forward and optimisation workflows, experiment management and additional tooling for systematic research.

Your strategy logic remains yours.

Yes. OneBook includes portfolio management, IBOR, portfolio construction, risk and research capabilities.

It can provide the portfolio environment directly or integrate with existing OMS, PMS, broker, custodian, administrator, accounting and reporting systems where required.

The scope depends on how the investment team wants to use it.

QuantJourney is public-markets first.

OneBook currently focuses on equities, ETFs and other liquid public-market instruments.

Backtester supports equities, futures and FX, with both weight-based and order-based research workflows.

Data Gateway covers a broader set of domains including equities, fundamentals, macro, rates, derivatives, commodities, regulatory data, prediction markets and crypto.

Complex derivatives lifecycle management, private-asset administration and fund accounting are not core product capabilities today.

Yes.

QuantJourney products can operate independently, provide core investment capabilities directly, or integrate with systems already in place.

A team can use only Data Gateway, only Backtester, only OneBook, or combine them.

Yes.

Integration can use APIs, files and product-specific adapters depending on the system and workflow.

For OneBook deployments, the PMS, OMS, broker, custodian, administrator and other systems in scope are agreed during the workflow review.

Data Gateway exposes consistent REST, Python SDK and MCP interfaces across enabled sources.

Yes.

Private deployment options include dedicated single-tenant cloud, deployment in your own cloud environment and compatible private/on-premise infrastructure.

Data Gateway Private can run as a licensed runtime inside your network.

OneBook can also be deployed in a dedicated environment.

Backtester Open runs locally or on infrastructure controlled by your team.

Yes.

Permissions, portfolio controls, approval flows, research processes and integrations can be configured around the investment workflow.

Where a requested capability fits the broader product, it can become part of the shared product roadmap rather than creating a permanent private fork.

Access is scoped by tenant, identity, role and service.

Data Gateway isolates tenant credentials, sessions, quotas and data access. Dedicated single-tenant environments are available for OneBook and private deployments.

Secrets and vendor credentials are stored in managed secrets infrastructure rather than application code or client-side configuration.

Transport and storage are encrypted, and access and administrative actions are auditable.

Deployment-specific security controls are confirmed during due diligence.

EU-region cloud infrastructure is the default for managed deployments.

For private deployments, the region, network boundary, retention policy, subprocessors and transfer requirements are agreed for the specific deployment.

Where QuantJourney runs inside the client's environment, provider credentials and permitted data can remain inside that network boundary.

Credentials are scoped to the relevant tenant or private deployment.

Data Gateway uses managed secrets storage for provider credentials and platform keys. Vendor keys are not embedded in source code, container images or browser-side configuration.

For Private Data Gateway deployments, vendor credentials can remain inside the client's own environment.

QuantJourney does not pool one customer's commercial data licence for use by another customer.

Platform access and administrative actions are recorded with relevant identity, action, target, timestamp and request context.

Data Gateway responses include provider and request lineage so teams can identify where a result came from and when the request was routed.

OneBook decision records can preserve portfolio state, inputs and relevant source context around investment workflows.

Retention and export requirements are agreed by deployment.

Identity and access are based on explicit users, roles, service identities and scoped permissions.

SSO/OIDC/SAML integration, MFA policy and joiner-mover-leaver requirements depend on the deployment and are confirmed during institutional onboarding.

We do not claim a specific identity-control configuration publicly unless it is implemented and applicable to that deployment.

Managed deployments use encrypted backups, monitoring and defined recovery paths.

Private and OneBook deployments can specify backup frequency, retention, RPO, RTO and recovery-testing requirements during due diligence.

QuantJourney does not publish deployment-specific recovery targets unless they are contractually agreed and supported by current evidence.

Institutional customers can request deployment architecture, data-flow documentation, operating-responsibility boundaries, DPA information and relevant security-control documentation.

Security questionnaires, SLA requirements, data residency, retention, identity controls and incident-notification requirements are handled as part of onboarding.

QuantJourney does not claim third-party certifications or penetration-test status unless they are current and evidenced.

Data Gateway Hosted is currently US$199 per month.

Data Gateway Private is US$999 per month plus a US$999 standard setup fee; infrastructure and third-party data-provider costs are separate.

Backtester Open is free under Apache 2.0. Backtester PRO is a paid research offering with managed data and advanced research workflows.

OneBook Core starts at US$30,000 per year for one book and one primary workflow in a dedicated environment, and scales with books, users, integrations and deployment requirements.

Enterprise and non-standard requirements are scoped separately.

Yes.

For OneBook and larger institutional deployments, the usual starting point is one clearly defined workflow implemented in a controlled or shadow environment.

The scope, success criteria, systems involved and commercial treatment are agreed before the proof of concept starts.

Data Gateway can normally start directly through Hosted or Private deployment without a separate PoC.

Support depends on product and deployment.

Data Gateway Hosted has published standard service targets. Private deployments include connector maintenance, software updates and an agreed operating-responsibility model.

Enterprise and OneBook deployments define support hours, escalation paths, incident notification and applicable service targets contractually.

No SLA is implied where it has not been agreed in writing.

Yes.

The products are designed to work independently.

A team can start with Data Gateway for data access, Backtester for research, or OneBook for portfolio management and risk, then connect additional QuantJourney capabilities later if useful.

There is no requirement to adopt the full platform.

No for Backtester Open.

The open-source engine runs locally or on infrastructure controlled by your team.

Private and institutional research deployments can also be structured around customer-controlled infrastructure where required.

The exact boundary for managed Backtester PRO services depends on which managed data and hosted capabilities are used.

Backtester PRO adds a managed research layer around the open-source engine.

The intended scope includes managed market and fundamental data, advanced walk-forward workflows, optimisation, experiment management, reproducibility tooling and additional research infrastructure that teams would otherwise need to build and maintain themselves.

Backtester Open remains available for teams that only need the local engine.

PRO is designed to include managed research data, including market and fundamental datasets used in systematic and quantamental research.

Dataset coverage, point-in-time characteristics, history and licensing depend on the selected data package and provider rights.

Where third-party licensing applies, those rights remain subject to the underlying provider's terms.

QuantJourney supports research workflows that separate parameter selection from out-of-sample evaluation rather than treating one in-sample backtest as sufficient evidence.

Walk-forward analysis can use rolling or expanding research windows, while optimisation can evaluate parameter sets subject to strategy and portfolio constraints.

The objective is not to find the highest historical Sharpe ratio, but to understand whether a result remains stable outside the period used to select it.

Yes.

Research workflows can preserve the relevant strategy configuration, parameters, execution assumptions, datasets and output metrics associated with a run.

The goal is for another researcher to be able to understand how a result was produced and reproduce the experiment rather than relying on an isolated chart or notebook output.

For Data Gateway, choose Hosted or discuss a Private deployment.

For Backtester, start with the open-source engine or request access to PRO if you need managed data and advanced research workflows.

For OneBook, book a demo and review one investment workflow with the team.

We recommend starting with the smallest useful scope and expanding only where the product removes real operational or research friction.