site updated

index.qmd

@@ -59,7 +59,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants
 - [lppls](https://github.com/Boulder-Investment-Technologies/lppls) - A Python module for fitting the [Log-Periodic Power Law Singularity (LPPLS)](https://en.wikipedia.org/wiki/Didier_Sornette#The_JLS_and_LPPLS_models) model.
 
 ### Trading & Backtesting
-
+- [Investing algorithm framework](https://github.com/coding-kitties/investing-algorithm-framework) - Framework for developing, backtesting, and deploying automated trading algorithms.
 - [QSTrader](https://github.com/mhallsmoore/qstrader) - QSTrader backtesting simulation engine.
 - [Blankly](https://github.com/Blankly-Finance/Blankly) - Fully integrated backtesting, paper trading, and live deployment.
 - [TA-Lib](https://github.com/mrjbq7/ta-lib) - Python wrapper for TA-Lib (<http://ta-lib.org/>).
@@ -127,6 +127,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants
 - [PyBroker](https://github.com/edtechre/pybroker) - Algorithmic Trading with Machine Learning.
 - [OctoBot Script](https://github.com/Drakkar-Software/OctoBot-Script) - A quant framework to create cryptocurrencies strategies - from backtesting to optimisation to livetrading.
 - [hftbacktest](https://github.com/nkaz001/hftbacktest) - A high-frequency trading and market-making backtesting tool accounts for limit orders, queue positions, and latencies, utilizing full tick data for trades and order books.
+- [vnpy](https://github.com/vnpy/vnpy) - VeighNa is a Python-based open source quantitative trading system development framework.
 
 ### Risk Analysis
 
@@ -148,6 +149,10 @@ A curated list of insanely awesome libraries, packages and resources for Quants
 - [alphalens](https://github.com/quantopian/alphalens) - Performance analysis of predictive alpha factors.
 - [Spectre](https://github.com/Heerozh/spectre) - GPU-accelerated Factors analysis library and Backtester
 
+### Quant Research Environment
+
+- [Jupyter Quant](https://github.com/gnzsnz/jupyter-quant) - A dockerized Jupyter quant research environment with preloaded tools for quant analysis, statsmodels, pymc, arch, py_vollib, zipline-reloaded, PyPortfolioOpt, etc.
+
 ### Time Series
 
 - [ARCH](https://github.com/bashtage/arch) - ARCH models in Python.
@@ -384,7 +389,6 @@ A curated list of insanely awesome libraries, packages and resources for Quants
 - [IndicatorTS](https://github.com/cinar/indicatorts) - Indicator is a TypeScript module providing various stock technical analysis indicators, strategies, and a backtest framework for trading.
 - [ccxt](https://github.com/ccxt/ccxt) - A JavaScript / Python / PHP cryptocurrency trading API with support for more than 100 bitcoin/altcoin exchanges.
 - [PENDAX](https://github.com/CompendiumFi/PENDAX-SDK) - Javascript SDK for Trading/Data API and Websockets for FTX, FTXUS, OKX, Bybit, & More.
-- [Mida](https://github.com/Reiryoku-Technologies/Mida) - The open-source and cross-platform trading framework (https://www.mida.org/).
 
 ### Data Visualization
 
@@ -438,6 +442,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants
   - [ta-lib](https://github.com/TA-Lib/ta-lib)
 - [Portfolio Optimizer](https://portfoliooptimizer.io/) - Portfolio Optimizer is a Web API for portfolio analysis and optimization.
 
+
 ## CSharp
 
 - [QuantConnect](https://github.com/QuantConnect/Lean) - Lean Engine is an open-source fully managed C# algorithmic trading engine built for desktop and cloud usage.