Code for the paper Volatility is (mostly) path-dependent

MATLAB code accompanying the paper Bennedsen (2020): "Semiparametric estimation and inference on the fractal index of Gaussian and conditionally Gaussian time series data”, 2020. Econometric Review…

Backtesting Global Growth-at-Risk Replication Files

Some files are currently optimized and will be uploaded again

Quantum Computing for Finance

A machine learning tool that implements the class of state-dependent Hawkes processes.

Python implementation of pricing analytics and Monte Carlo simulations for stochastic volatility models including log-normal SV model, Heston

[FT and FFT] Option pricing with the SINC approach: experiments under the rough Heston model

Mathematica code

Monotonic Networks – 1997, Sill

Expected Shortfall Backtesting

Estimation of realized quantities

Implements risk measures for (financial) networks, such as DebtRank, Impact Susceptibility, Impact Diffusion and Impact Fluidity.

Code for estimation of Large Dynamic Networks

A Point Process Toolbox Based on PyTorch

Code to compute Panel Quantile Regression for Returns (PQR) introduced in Baruník, J. and Čech, F., 2020. Measurement of common risks in tails: A panel quantile regression model for financial retur…

SABR model Python implementation

Code that replicates the Bayesian Compressed Vector Autoregressive (BCVAR) model in Koop, G., Korobilis, D. and Pettenuzzo, D. (2019). “Bayesian Compressed Vector Autoregressions”, Journal of Econo…

Quant Option Pricing - Exotic/Vanilla: Barrier, Asian, European, American, Parisian, Lookback, Cliquet, Variance Swap, Swing, Forward Starting, Step, Fader

Import public NYC taxi and for-hire vehicle (Uber, Lyft) trip data into a PostgreSQL or ClickHouse database

Trying to apply Angiuli et. al's reinforcement learning algorithm for solving both mean field game and mean field control problems from their paper "Reinforcement Learning for Mean Field Games, wit…

Using rough volatility https://tpq.io/p/rough_volatility_with_python.html

code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

A simple and extensible library to create Bayesian Neural Network layers on PyTorch.

A series of Jupyter notebooks with Chinese comment that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

量化宏观及julia应用

An R package for symbolic and numerical computations on scalar and multivariate systems of stochastic differential equations (SDEs). It provides users with a wide range of tools to simulate, estima…