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API Reference

Complete reference for all public classes, functions, and parameters in the quantflow library.

Modules

Data

Clients for fetching market data from external sources. Requires the optional data extra:

pip install quantflow[data]
Module Description
Deribit Crypto options and futures from the Deribit exchange
Financial Modeling Prep Equity prices, profiles, and sector data
FRED US macroeconomic time series from the St. Louis Fed
Federal Reserve Federal Reserve H.15 interest rate data

Options

Option pricing, volatility surface construction, and model calibration.

Module Description
Black-Scholes Black-76 pricing formula and implied volatility inversion
Pricer Model-based option pricer supporting any stochastic process
Volatility Surface Build and serialise implied volatility surfaces from market data
Calibration Calibrate Heston and Heston-jump-diffusion models to a surface
Deep IV Factor Model Neural-network option pricing via the DIVFM architecture

Stochastic Processes

Continuous-time stochastic processes used as underlying models for option pricing and simulation.

Module Description
Wiener Process Geometric Brownian motion (constant volatility)
Heston Model Stochastic volatility with optional jump component (HestonJ)
Jump Diffusion Compound Poisson jump processes
CIR Process Cox-Ingersoll-Ross mean-reverting process
Ornstein-Uhlenbeck Ornstein-Uhlenbeck mean-reverting process
Poisson Process Homogeneous Poisson process
Compound Poisson Poisson arrivals with a jump-size distribution
Doubly Stochastic Poisson Poisson process with stochastic intensity

Technical Analysis

Time series filters and indicators for financial data.

Module Description
EWMA Exponentially weighted moving average
Kalman Filter Kalman filter for state estimation
Supersmoother Ehlers two-pole supersmoother filter
OHLC OHLC bar utilities and resampling
Paths Simulated path containers and statistics

Utilities

Low-level building blocks used throughout the library.

Module Description
Distributions Jump-size distributions (Normal, DoubleExponential)
Marginal 1D Marginal distribution via characteristic function inversion
Bins Histogram binning helpers
Numbers Decimal and float numeric utilities
Types Shared type aliases