FT Quant Studio

SaaS interface for modern quantitative finance

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Python for Finance SaaS

Model scenarios with institutional-grade clarity.

Capture volatility, alpha, beta and risk-adjusted returns from robust Python-based engines, wrapped in a high-end fintech interface.

ƒModel Inputs

Scenario configuration

Configure the time horizon, symbol and risk-free rate powering the Python-for-Finance models.

(decimal)

Validate new custom inputs by extending the schema in FinanceInputForm.

Snapshot

Current scenario

Results refresh live as you refine instruments, horizons or risk-free assumptions.

Engine status

Idle · Ready

Integration

Swap mock logic for live models via useFinancialRatios.

Final portfolio value

$1,000,000

∑

Mark-to-market value at the end of the horizon.

Total return

32.0%

∑

Cumulative performance over the full period.

Volatility

22.0%

∑

Annualised standard deviation of returns.

Sharpe ratio

1.40

∑

Risk-adjusted performance vs risk-free rate.

Alpha

4.0%

∑

Excess return beyond systematic market risk.

Beta

1.10

∑

Sensitivity of the strategy to broad market moves.