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

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

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.

Black–Scholes powered Python framework for options trading — featuring volatility forecasting, market microstructure analysis, and backtesting tools for building and deploying advanced trading strategies.

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.

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

Delta hedging of European options in the Black-Scholes framework, with transaction costs and different rebalancing frequencies

In this Repository you will find projects, exercises and bibliography related to Risk Hedging Strategies.

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.

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.

Efficient Delta Hedging with Transaction Costs

A package to learn optimal hedges by a deep feed forward neural network, to minimise the terminal error

Delta Hedging strategy on European Option

A comparison of commonly used assets to hedge against US inflation.

This repository implements Differential Machine Learning (DML) for pricing European options using the Heston model and introduces Differential Principal Component Analysis (Diff-PCA) to enhance computational efficiency.

This project implements a multi-asset portfolio optimisation and risk management framework using historical equity data. Classical mean–variance optimisation, Monte Carlo simulation, and Value at Risk are used to analyse portfolio behaviour under unconstrained short selling and noisy return estimates.