Implementation of the vanilla Deep Hedging engine

Tutorials about Quantitative Finance in Python and QuantLib: Pricing, xVAs, Hedging, Portfolio Optimisation, Machine Learning and Deep Learning

This strategy works for every market condition irrespective of the movement

Automatic Options Hedging and Backtesting

Algorithmic Portfolio Hedging. Black-Scholes Pricing for Dynamic Hedges to produce a Dynamic multi-asset Portfolio Hedging with the usage of Options contracts.

KAIST(Korea Advanced Institute of Science and Technology) Financial Engineering( Derivatives) Course Code+@

Hedging unsing Deep Reinforcement Learning and Deep Learning

Samson's MIT Master's Degree Thesis: "Multi-Agent Deep Reinforcement Learning and GAN-Based Market Simulation for Derivatives Pricing and Dynamic Hedging".

Futures-Spot-Arbitrage-Binance-V1

Dynamic delta hedging (DDH) is a trading strategy that involves hedging a non-linear position with linear instruments. Linear instruments include spot, forward, and futures contracts. DDH helps traders manage the Delta or Gamma of a portfolio without monitoring it

Hedging options by using Monte Carlo simulations or real data

Pricing and hedging of HKEX warrants in Python using Black Scholes, Implied Volatility and Delta Hedging. It is connected to HKEX and BOCI data source.

Lending market for AMMs

A Python-based trading bot designed to identify and trade mispriced options using the Schwab API. The bot automatically submits limit orders on options it detects as mispriced, and once the orders are filled, it delta hedges the positions to manage risk.

The main focus of this repository is to analysis the fair price and the risk of the Auto-callable Reverse Convertible issued by Credit Suisse AG on 24/10/2017

“On an Even Keel”: Silver Risk, Trade Finance, and Hedging Strategies around the Turn of the Twentieth Century

Quantitative Finance Library & Option Trading Tool

A portfolio generator developed by QuantYantriki for the QSTH 2022 - a quantum hackathon organized by the Quantum Ecosystems and Technology Council of India (QETCI). It utilizes quantum annealing and quantum approximate optimization algorithms using a feedback-based metaheuristic that incorporates classical optimization tools to improve solutions.

How to hedge any positive linear gamma instrument using a “Gamma transform”