Scalable, event-driven, deep-learning-friendly backtesting library
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Updated
Aug 28, 2021 - Python
Scalable, event-driven, deep-learning-friendly backtesting library
Tutorials about Quantitative Finance in Python and QuantLib: Pricing, xVAs, Hedging, Portfolio Optimisation, Machine Learning and Deep Learning
Markowitzify will implement a variety of portfolio and stock/cryptocurrency analysis methods to optimize portfolios or trading strategies. The two primary classes are "portfolio" and "stonks."
高性能并行、事件驱动量化回测框架 high performance backtest,factor investing, portfiolio analysis
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
A Quantity calculator which suggests you best position size following your Risk Management.
An advanced platform for quantitative trading strategies, including AI-driven price prediction models and user management systems. Emulating institutional-grade practices like Citadel, it facilitates the development, training, and deployment of machine learning models for precise market forecasting.
Part of my master's thesis, this repository showcases my foray into quantitative research, reflecting my analytical prowess through complex data manipulation and advanced statistical strategies, harnessed to distill actionable insights in the realm of financial markets.
My thesis 🏅
Base indicators and forecasting models for statistics and quantitive analysis
The ModFin project aims to provide users with the necessary tools for modeling and analyzing individual assets and portfolios.
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