QuantSignals FST
QuantSignals FST is a supervised AI trading agent that turns QS Research signals into account-aware, risk-governed brokerage execution with order preview, approval, monitored execution, and a reviewable session record.
QuantSignals FST is finance software teams evaluate for education & research. Use this page to review pricing, integration signals, and the best alternatives before you commit.
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Quick Overview
Best for: Education & Research
What it does
Finance software for decision-makers comparing workflow fit and alternatives.
Best fit
Education & Research
Pricing snapshot
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QuantSignals FST is a supervised AI trading agent designed to carry time-stamped QS Research signals into a bounded brokerage workflow. It screens opportunities, reads supporting and conflicting evidence, checks portfolio fit, calculates a risk budget, previews orders, follows account approval policies, monitors resulting positions, and records session activity. FST's purpose is to make decision and execution processes more consistent, observable, and accountable while keeping hard controls (account eligibility, risk limits, broker capabilities, approval and reconciliation) outside the language model. It is available for evaluation via QS paper trading and runs across QS web, desktop and CLI surfaces, iOS, and Android.
QuantSignals FST is a supervised AI trading agent that connects QS Research to risk-governed brokerage execution across web, desktop, CLI, iOS, and Android.
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Claim this listing for $29Key Features
Supervised AI trading agent
FST interprets QS Research signals and forms an explicit thesis and policy decision while remaining supervised by account and risk controls.
Signal screening and evidence reading
Screens the configured universe, reads time-stamped supporting and conflicting evidence from QS Research, and narrates the market and thesis state.
Account-aware decisions
Every order is constrained by the selected account's certified broker capabilities, risk policy, approval settings, and reconciliation requirements.
Risk budgeting and policy enforcement
Agent checks portfolio fit and calculates bounded exposure, rejecting plans that violate account or risk rules.
Order preview and approval workflow
Orders are previewed, follow the configured approval policy, and route to the exact account for approval before execution.
Monitored execution and session recording
FST monitors positions (price, thesis, stop, target, market state) and records the session for review, reconciliation, and learning.
Multi-surface availability
Runs across the QS web app, desktop and CLI surfaces, iOS, and Android.
Paper trading evaluation
New users can observe complete session behavior using QS paper trading before connecting an eligible live account.
Pricing
Current pricing details are not available from the vendor source.
Use Cases
Research-to-execution workflows
Translate QS Research signals and time-stamped evidence into actionable, account-aware trade plans enforced by risk and broker constraints.
Supervised automated sessions
Run automated sessions inside preconfigured boundaries while retaining approval and hard limits to maintain supervision and control.
Paper testing and evaluation
Evaluate agent behavior, approval flows, and execution monitoring using QS paper trading before moving to an eligible live brokerage account.
Integrations
QS Research
Supplies time-stamped signals and supporting evidence that FST turns into an explicit thesis and policy decision.
QS Brokerage
Owns account capabilities, risk enforcement, execution, reconciliation, and the authoritative order record used by FST.
Benefits
Limitations
Frequently Asked Questions
What is QuantSignals FST?
Is FST fully autonomous?
Does FST guarantee profits?
Can I test FST without a live brokerage account?
Where does FST run?
Getting Started
- 1 Step 1: Choose a destination — select QS paper trading or an eligible live account whose capabilities have been verified for the requested operation.
- 2 Step 2: Start a supervised session — configure the universe and start FST so it can screen opportunities and read QS signal evidence.
- 3 Step 3: Review previews and approvals — examine the agent's order previews, follow the configured approval policy, and approve or reject as required.
- 4 Step 4: Monitor and park — allow FST to monitor positions, apply stops/targets, and park or exit positions under policy; review the session record for reconciliation and learning.
Support
docs
Product guide and installation instructions available at https://quantsignals.xyz/fst
installation
Install FST 2.0 for desktop CLI and mobile via the product guide page linked above.
API
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