Automatic Options Hedging and Backtesting
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Updated
Jun 28, 2023 - Julia
Automatic Options Hedging and Backtesting
Delta hedging under SABR model
Futures-Spot-Arbitrage-Binance-V1
Python code for a trading strategy based on time value performed in the SSE 50ETF option market.
Excel/Python application of stochastic methods for financial analysis
Simulating different hedging strategies on Apple's stock option data
A decision model build using probability and stochastic process knowledge to mitigate the revenue loss of a company due to unfavorable fluctuations in international Dollar value
Pricing energy options (focus on German power) with MC and jump-diffusion mean-reversion model, including stochastic volatility, seasonality and regime filtering. Model parameters are calibrated on historical ENTSO-e data.
This project analyzes stock market data, implements option pricing models (Binomial Trees, Black-Scholes-Merton and Monte Carlo Simulation), evaluates hedging strategies and constructs an optimized portfolio. It integrates derivative valuation with portfolio analysis to provide insights into risk management and investment decision-making.
This repository collects models that me and my colleagues developed in practical fulfillment of studyiing exotic option pricing under Black Sholes. Topics covered include Black Sholes option pricing, dynamics of American contingent claims and discrete and continuous time hedging strategies.
Solutions for hedging strategy, Automated Market Making strategy and Exotic Options Pricing made as a part of Goldman Sachs India Hackathon 2025.
A Python-based quantitative finance tool for pricing European options and calculating first and second-order Greeks. Features vectorized NumPy computations and comprehensive risk dashboards for derivatives analysis
In this Repository you will find projects, exercises and bibliography related to Risk Hedging Strategies.
Delta hedging of European options in the Black-Scholes framework, with transaction costs and different rebalancing frequencies
Simulation and analysis of two volatility-based options strategies - Long Straddle and Delta-Gamma Hedged Portfolio - using real SPY options data. Includes Black-Scholes-based computation of option Greeks, portfolio construction, and PnL visualization to evaluate convexity and market regime suitability.
CLI & Python library to calculate sports bet hedging scenarios — guaranteed profit regardless of outcome
QuantHedge-MM implements advanced computational methods for pricing and hedging options in markets with stochastic regime shifts. Built for quants and researchers, it extends Black-Scholes to Markov-modulated models.
Efficient Delta Hedging with Transaction Costs
Calibrate the SABR stochastic volatility model to SPX implied volatility surfaces and benchmark smile-aware delta-hedging strategies against the Black–Scholes baseline.
A package to learn optimal hedges by a deep feed forward neural network, to minimise the terminal error
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