Python code for a trading strategy based on time value performed in the SSE 50ETF option market.
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Updated
Mar 30, 2022 - Python
Python code for a trading strategy based on time value performed in the SSE 50ETF option market.
A package to learn optimal hedges by a deep feed forward neural network, to minimise the terminal error
Solutions for hedging strategy, Automated Market Making strategy and Exotic Options Pricing made as a part of Goldman Sachs India Hackathon 2025.
Automate your crypto trading with AutoHedge, an AI-driven hedge fund using swarm intelligence for autonomous market analysis, risk management, and execution on Solana.
Black–Scholes powered Python framework for options trading — featuring volatility forecasting, market microstructure analysis, and backtesting tools for building and deploying advanced trading strategies.
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
Calibrate the SABR stochastic volatility model to SPX implied volatility surfaces and benchmark smile-aware delta-hedging strategies against the Black–Scholes baseline.
CLI & Python library to calculate sports bet hedging scenarios — guaranteed profit regardless of outcome
Does the covariance estimator change out-of-sample hedging of SOFR swap risk? Not for the hedge, no estimator beats the equal-weighted sample consistently. It matters for the risk forecast, EWMA removes the overstated unhedged risk and shrinkage overstates hedged risk 2.5 to 4 times.
A Data-Driven Decision Support System to optimize industrial energy procurement and mitigate tail risks in the Spanish electricity market (Spot/Futures hedging). Developed for the Advanced Business Analytics course (42578) at DTU.
Solutions for hedging strategy, Automated Market Making strategy and Exotic Options Pricing made as a part of Goldman Sachs India Hackathon 2025
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