Differentiable SDE solvers with GPU support and efficient sensitivity analysis.
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Updated
May 25, 2024 - Python
Differentiable SDE solvers with GPU support and efficient sensitivity analysis.
Generate realizations of stochastic processes in python.
Quant Option Pricing - Exotic/Vanilla: Barrier, Asian, European, American, Parisian, Lookback, Cliquet, Variance Swap, Swing, Forward Starting, Step, Fader
Option pricing function for the Heston model based on the implementation by Christian Kahl, Peter Jäckel and Roger Lord. Includes Black-Scholes-Merton option pricing and implied volatility estimation. No Financial Toolbox required.
R Code to accompany "A Note on Efficient Fitting of Stochastic Volatility Models"
DRIP Fixed Income is a collection of Java libraries for Instrument/Trading Conventions, Treasury Futures/Options, Funding/Forward/Overnight Curves, Multi-Curve Construction/Valuation, Collateral Valuation and XVA Metric Generation, Calibration and Hedge Attributions, Statistical Curve Construction, Bond RV Metrics, Stochastic Evolution and Optio…
Source code and data for the tutorial: "Getting started with particle Metropolis-Hastings for inference in nonlinear models"
Bayesian optimisation for fast approximate inference in state-space models with intractable likelihoods
Monte Carlo option pricing algorithms for vanilla and exotic options
This is a collection of Stochastic indicators. It's developed in PineScript for the technical analysis platform of TradingView.
Numerical experiments with stochastic differential equations
A list (quite disorganized for now) of papers tackling the Bayesian estimation of Ito processes (and their discrete time version)
An implementation of the Heston model, a stochastic volatility model for options pricing. We compute prices of European call and put options via Monte Carlo simulation, for a variety of strike prices and maturities. We also show that the Heston model captures volatility smiles/smirks/skews.
Quantitative finance and derivative pricing
Bayer, Friz, Gassiat, Martin, Stemper (2017). A regularity structure for finance.
Comparison of different implementations of the same stochastic volatility model (stochvol, JAGS, Stan)
Demonstrates how to price derivatives in a Heston framework, using successive approximations of the invariant distribution of a Markov ergodic diffusion with decreasing time discretization steps. The framework is that of G. Pagès & F. Panloup.
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