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@@ -402,7 +402,6 @@ A curated list of insanely awesome libraries, packages and resources for Quants
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- [IndicatorTS](https://github.com/cinar/indicatorts) - Indicator is a TypeScript module providing various stock technical analysis indicators, strategies, and a backtest framework for trading.
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- [ccxt](https://github.com/ccxt/ccxt) - A JavaScript / Python / PHP cryptocurrency trading API with support for more than 100 bitcoin/altcoin exchanges.
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- [PENDAX](https://github.com/CompendiumFi/PENDAX-SDK) - Javascript SDK for Trading/Data API and Websockets for FTX, FTXUS, OKX, Bybit, & More.
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- [Mida](https://github.com/Reiryoku-Technologies/Mida) - The open-source and cross-platform trading framework (https://www.mida.org/).
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### Data Visualization
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@@ -515,3 +514,4 @@ A curated list of insanely awesome libraries, packages and resources for Quants
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- [financialnoob-misc](https://github.com/financialnoob/misc) - Codes from @financialnoob's posts
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- [MesoSim Options Trading Strategy Library](https://github.com/deltaray-io/strategy-library) - Free and public Options Trading strategy library for MesoSim.
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- [Quant-Finance-With-Python-Code](https://github.com/lingyixu/Quant-Finance-With-Python-Code) - Repo for code examples in Quantitative Finance with Python by Chris Kelliher
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- [QuantFinanceTraining](https://github.com/JoaoJungblut/QuantFinanceTraining) - This repository contains codes that were executed during my training in the CQF (Certificate in Quantitative Finance). The codes are organized by class, facilitating navigation and reference.
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<li><a href="https://github.com/financialnoob/misc">financialnoob-misc</a> - Codes from <span class="citation" data-cites="financialnoob">@financialnoob</span>’s posts</li>
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<li><a href="https://github.com/deltaray-io/strategy-library">MesoSim Options Trading Strategy Library</a> - Free and public Options Trading strategy library for MesoSim.</li>
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<li><a href="https://github.com/lingyixu/Quant-Finance-With-Python-Code">Quant-Finance-With-Python-Code</a> - Repo for code examples in Quantitative Finance with Python by Chris Kelliher</li>
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<li><a href="https://github.com/JoaoJungblut/QuantFinanceTraining">QuantFinanceTraining</a> - This repository contains codes that were executed during my training in the CQF (Certificate in Quantitative Finance). The codes are organized by class, facilitating navigation and reference.</li>
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</ul>
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"href": "index.html#reproducing-works-training-books",
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"title": "Awesome Quant",
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"section": "Reproducing Works, Training & Books",
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"text": "Reproducing Works, Training & Books\n\nDerman Papers - Notebooks that replicate original quantitative finance papers from Emanuel Derman.\nML-Quant - Top Quant resources like ArXiv (sanity), SSRN, RePec, Journals, Podcasts, Videos, and Blogs.\nvolatility-trading - A complete set of volatility estimators based on Euan Sinclair’s Volatility Trading.\nquant - Quantitative Finance and Algorithmic Trading exhaust; mostly ipython notebooks based on Quantopian, Zipline, or Pandas.\nfecon235 - Open source project for software tools in financial economics. Many jupyter notebook to verify theoretical ideas and practical methods interactively.\nQuantitative-Notebooks - Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy\nQuantEcon - Lecture series on economics, finance, econometrics and data science; QuantEcon.py, QuantEcon.jl, notebooks\nFinanceHub - Resources for Quantitative Finance\nPython_Option_Pricing - An libary to price financial options written in Python. Includes: Black Scholes, Black 76, Implied Volatility, American, European, Asian, Spread Options.\npython-training - J.P. Morgan’s Python training for business analysts and traders.\nStock_Analysis_For_Quant - Different Types of Stock Analysis in Excel, Matlab, Power BI, Python, R, and Tableau.\nalgorithmic-trading-with-python - Source code for Algorithmic Trading with Python (2020) by Chris Conlan.\nMEDIUM_NoteBook - Repository containing notebooks of cerlymarco’s posts on Medium.\nQuantFinance - Training materials in quantitative finance.\nIPythonScripts - Tutorials about Quantitative Finance in Python and QuantLib: Pricing, xVAs, Hedging, Portfolio Optimisation, Machine Learning and Deep Learning.\nComputational-Finance-Course - Materials for the course of Computational Finance.\nMachine-Learning-for-Asset-Managers - Implementation of code snippets, exercises and application to live data from Machine Learning for Asset Managers (Elements in Quantitative Finance) written by Prof. Marcos López de Prado.\nPython-for-Finance-Cookbook - Python for Finance Cookbook, published by Packt.\nmodelos_vol_derivativos - “Modelos de Volatilidade para Derivativos” book’s Jupyter notebooks\nNMOF - Functions, examples and data from the first and the second edition of “Numerical Methods and Optimization in Finance” by M. Gilli, D. Maringer and E. Schumann (2019, ISBN:978-0128150658).\npy4fi2nd - Jupyter Notebooks and code for Python for Finance (2nd ed., O’Reilly) by Yves Hilpisch.\naiif - Jupyter Notebooks and code for the book Artificial Intelligence in Finance (O’Reilly) by Yves Hilpisch.\npy4at - Jupyter Notebooks and code for the book Python for Algorithmic Trading (O’Reilly) by Yves Hilpisch.\ndawp - Jupyter Notebooks and code for Derivatives Analytics with Python (Wiley Finance) by Yves Hilpisch.\ndx - DX Analytics | Financial and Derivatives Analytics with Python.\nQuantFinanceBook - Quantitative Finance book.\nrough_bergomi - A Python implementation of the rough Bergomi model.\nfrh-fx - A python implementation of the fast-reversion Heston model of Mechkov for FX purposes.\nValue Investing Studies - A collection of data analysis studies that examine the performance and characteristics of value investing over long periods of time.\nMachine Learning Asset Management - Machine Learning in Asset Management (by @firmai).\nDeep Learning Machine Learning Stock - Deep Learning and Machine Learning stocks represent a promising long-term or short-term opportunity for investors and traders.\nTechnical Analysis and Feature Engineering - Feature Engineering and Feature Importance of Machine Learning in Financial Market.\nDifferential Machine Learning and Axes that matter by Brian Huge and Antoine Savine - Implement, demonstrate, reproduce and extend the results of the Risk articles ‘Differential Machine Learning’ (2020) and ‘PCA with a Difference’ (2021) by Huge and Savine, and cover implementation details left out from the papers.\nsystematictradingexamples - Examples of code related to book Systematic Trading and blog\npysystemtrade_examples - Examples using pysystemtrade for Robert Carver’s blog.\nML_Finance_Codes - Machine Learning in Finance: From Theory to Practice Book\nHands-On Machine Learning for Algorithmic Trading - Hands-On Machine Learning for Algorithmic Trading, published by Packt\nfinancialnoob-misc - Codes from @financialnoob’s posts\nMesoSim Options Trading Strategy Library - Free and public Options Trading strategy library for MesoSim.\nQuant-Finance-With-Python-Code - Repo for code examples in Quantitative Finance with Python by Chris Kelliher"
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"text": "Reproducing Works, Training & Books\n\nDerman Papers - Notebooks that replicate original quantitative finance papers from Emanuel Derman.\nML-Quant - Top Quant resources like ArXiv (sanity), SSRN, RePec, Journals, Podcasts, Videos, and Blogs.\nvolatility-trading - A complete set of volatility estimators based on Euan Sinclair’s Volatility Trading.\nquant - Quantitative Finance and Algorithmic Trading exhaust; mostly ipython notebooks based on Quantopian, Zipline, or Pandas.\nfecon235 - Open source project for software tools in financial economics. Many jupyter notebook to verify theoretical ideas and practical methods interactively.\nQuantitative-Notebooks - Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy\nQuantEcon - Lecture series on economics, finance, econometrics and data science; QuantEcon.py, QuantEcon.jl, notebooks\nFinanceHub - Resources for Quantitative Finance\nPython_Option_Pricing - An libary to price financial options written in Python. Includes: Black Scholes, Black 76, Implied Volatility, American, European, Asian, Spread Options.\npython-training - J.P. Morgan’s Python training for business analysts and traders.\nStock_Analysis_For_Quant - Different Types of Stock Analysis in Excel, Matlab, Power BI, Python, R, and Tableau.\nalgorithmic-trading-with-python - Source code for Algorithmic Trading with Python (2020) by Chris Conlan.\nMEDIUM_NoteBook - Repository containing notebooks of cerlymarco’s posts on Medium.\nQuantFinance - Training materials in quantitative finance.\nIPythonScripts - Tutorials about Quantitative Finance in Python and QuantLib: Pricing, xVAs, Hedging, Portfolio Optimisation, Machine Learning and Deep Learning.\nComputational-Finance-Course - Materials for the course of Computational Finance.\nMachine-Learning-for-Asset-Managers - Implementation of code snippets, exercises and application to live data from Machine Learning for Asset Managers (Elements in Quantitative Finance) written by Prof. Marcos López de Prado.\nPython-for-Finance-Cookbook - Python for Finance Cookbook, published by Packt.\nmodelos_vol_derivativos - “Modelos de Volatilidade para Derivativos” book’s Jupyter notebooks\nNMOF - Functions, examples and data from the first and the second edition of “Numerical Methods and Optimization in Finance” by M. Gilli, D. Maringer and E. Schumann (2019, ISBN:978-0128150658).\npy4fi2nd - Jupyter Notebooks and code for Python for Finance (2nd ed., O’Reilly) by Yves Hilpisch.\naiif - Jupyter Notebooks and code for the book Artificial Intelligence in Finance (O’Reilly) by Yves Hilpisch.\npy4at - Jupyter Notebooks and code for the book Python for Algorithmic Trading (O’Reilly) by Yves Hilpisch.\ndawp - Jupyter Notebooks and code for Derivatives Analytics with Python (Wiley Finance) by Yves Hilpisch.\ndx - DX Analytics | Financial and Derivatives Analytics with Python.\nQuantFinanceBook - Quantitative Finance book.\nrough_bergomi - A Python implementation of the rough Bergomi model.\nfrh-fx - A python implementation of the fast-reversion Heston model of Mechkov for FX purposes.\nValue Investing Studies - A collection of data analysis studies that examine the performance and characteristics of value investing over long periods of time.\nMachine Learning Asset Management - Machine Learning in Asset Management (by @firmai).\nDeep Learning Machine Learning Stock - Deep Learning and Machine Learning stocks represent a promising long-term or short-term opportunity for investors and traders.\nTechnical Analysis and Feature Engineering - Feature Engineering and Feature Importance of Machine Learning in Financial Market.\nDifferential Machine Learning and Axes that matter by Brian Huge and Antoine Savine - Implement, demonstrate, reproduce and extend the results of the Risk articles ‘Differential Machine Learning’ (2020) and ‘PCA with a Difference’ (2021) by Huge and Savine, and cover implementation details left out from the papers.\nsystematictradingexamples - Examples of code related to book Systematic Trading and blog\npysystemtrade_examples - Examples using pysystemtrade for Robert Carver’s blog.\nML_Finance_Codes - Machine Learning in Finance: From Theory to Practice Book\nHands-On Machine Learning for Algorithmic Trading - Hands-On Machine Learning for Algorithmic Trading, published by Packt\nfinancialnoob-misc - Codes from @financialnoob’s posts\nMesoSim Options Trading Strategy Library - Free and public Options Trading strategy library for MesoSim.\nQuant-Finance-With-Python-Code - Repo for code examples in Quantitative Finance with Python by Chris Kelliher\nQuantFinanceTraining - This repository contains codes that were executed during my training in the CQF (Certificate in Quantitative Finance). The codes are organized by class, facilitating navigation and reference."
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},
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{
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"objectID": "projects.html",
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@@ -501,3 +501,4 @@ A curated list of insanely awesome libraries, packages and resources for Quants
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- [financialnoob-misc](https://github.com/financialnoob/misc) - Codes from @financialnoob's posts
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- [MesoSim Options Trading Strategy Library](https://github.com/deltaray-io/strategy-library) - Free and public Options Trading strategy library for MesoSim.
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- [Quant-Finance-With-Python-Code](https://github.com/lingyixu/Quant-Finance-With-Python-Code) - Repo for code examples in Quantitative Finance with Python by Chris Kelliher
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- [QuantFinanceTraining](https://github.com/JoaoJungblut/QuantFinanceTraining) - This repository contains codes that were executed during my training in the CQF (Certificate in Quantitative Finance). The codes are organized by class, facilitating navigation and reference.
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@@ -168,7 +168,7 @@ iexfinance,Python > Data Sources,2021-01-02,https://github.com/addisonlynch/iexf
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pyEX,Python > Data Sources,2023-09-11,https://github.com/timkpaine/pyEX,"Python interface to IEX with emphasis on pandas, support for streaming data, premium data, points data (economic, rates, commodities), and technical indicators.",True,False,timkpaine/pyEX
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alpaca-trade-api,Python > Data Sources,2023-09-11,https://github.com/alpacahq/alpaca-trade-api-python,Python interface for retrieving real-time and historical prices from Alpaca API as well as trade execution.,True,False,alpacahq/alpaca-trade-api-python
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metatrader5,Python > Data Sources,,https://pypi.org/project/MetaTrader5/,API Connector to MetaTrader 5 Terminal,False,False,
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akshare,Python > Data Sources,2023-12-05,https://github.com/jindaxiang/akshare,"AkShare is an elegant and simple financial data interface library for Python, built for human beings! <https://akshare.readthedocs.io>",True,False,jindaxiang/akshare
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akshare,Python > Data Sources,2023-12-06,https://github.com/jindaxiang/akshare,"AkShare is an elegant and simple financial data interface library for Python, built for human beings! <https://akshare.readthedocs.io>",True,False,jindaxiang/akshare
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yahooquery,Python > Data Sources,2023-10-28,https://github.com/dpguthrie/yahooquery,Python interface for retrieving data through unofficial Yahoo Finance API.,True,False,dpguthrie/yahooquery
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investpy,Python > Data Sources,2022-10-02,https://github.com/alvarobartt/investpy,Financial Data Extraction from Investing.com with Python! <https://investpy.readthedocs.io/>,True,False,alvarobartt/investpy
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yliveticker,Python > Data Sources,2021-04-29,https://github.com/yahoofinancelive/yliveticker,Live stream of market data from Yahoo Finance websocket.,True,False,yahoofinancelive/yliveticker
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@@ -375,3 +375,4 @@ Hands-On Machine Learning for Algorithmic Trading,"Reproducing Works, Training &
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financialnoob-misc,"Reproducing Works, Training & Books",2023-06-06,https://github.com/financialnoob/misc,Codes from @financialnoob's posts,True,False,financialnoob/misc
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MesoSim Options Trading Strategy Library,"Reproducing Works, Training & Books",2023-11-24,https://github.com/deltaray-io/strategy-library,Free and public Options Trading strategy library for MesoSim. ,True,False,deltaray-io/strategy-library
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Quant-Finance-With-Python-Code,"Reproducing Works, Training & Books",2023-11-16,https://github.com/lingyixu/Quant-Finance-With-Python-Code,Repo for code examples in Quantitative Finance with Python by Chris Kelliher,True,False,lingyixu/Quant-Finance-With-Python-Code
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QuantFinanceTraining,"Reproducing Works, Training & Books",2023-11-24,https://github.com/JoaoJungblut/QuantFinanceTraining,"This repository contains codes that were executed during my training in the CQF (Certificate in Quantitative Finance). The codes are organized by class, facilitating navigation and reference.",True,False,JoaoJungblut/QuantFinanceTraining
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