Merge branch 'master' into master

README.md

@@ -14,6 +14,8 @@ A curated list of insanely awesome libraries, packages and resources for Quants
 - [Haskell](#haskell)
 - [Scala](#scala)
 - [Ruby](#ruby)
+- [Elixir/Erlang](#elixirerlang)
+- [Golang](#golang)
 - [CSharp](#csharp)
 - [Frameworks](#frameworks) - frameworks that support different languages
 - [Reproducing Works](#reproducing-works) - repositories that reproduce books and papers results or implement examples
@@ -43,6 +45,14 @@ A curated list of insanely awesome libraries, packages and resources for Quants
 - [hasura/base-python-dash](https://platform.hasura.io/hub/projects/hasura/base-python-dash) - Hasura quickstart to deploy Dash framework. Written on top of Flask, Plotly.js, and React.js, Dash is ideal for building data visualization apps with highly custom user interfaces in pure Python.
 - [hasura/base-python-bokeh](https://platform.hasura.io/hub/projects/hasura/base-python-bokeh) - Hasura quickstart to visualize data with bokeh library.
 - [pysabr](https://github.com/ynouri/pysabr) - SABR model Python implementation.
+- [FinancePy](https://github.com/domokane/FinancePy) - A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives.
+- [FinancePy-Examples](https://github.com/domokane/FinancePy-Examples) - Examples of how to use FinancePy
+- [gs-quant](https://github.com/goldmansachs/gs-quant) - Python toolkit for quantitative finance
+
+### Indicators
+- [pandas_talib](https://github.com/femtotrader/pandas_talib) - A Python Pandas implementation of technical analysis indicators.
+- [finta](https://github.com/peerchemist/finta) - Common financial technical analysis indicators implemented in Pandas.
+- [Tulipy](https://github.com/cirla/tulipy) - Financial Technical Analysis Indicator Library (Python bindings for [tulipindicators]( https://github.com/TulipCharts/tulipindicators))
 
 ### Trading & Backtesting
 
@@ -58,18 +68,33 @@ A curated list of insanely awesome libraries, packages and resources for Quants
 - [pybacktest](https://github.com/ematvey/pybacktest) - Vectorized backtesting framework in Python / pandas, designed to make your backtesting easier.
 - [pyalgotrade](https://github.com/gbeced/pyalgotrade) - Python Algorithmic Trading Library.
 - [tradingWithPython](https://pypi.org/project/tradingWithPython/) - A collection of functions and classes for Quantitative trading.
-- [pandas_talib](https://github.com/femtotrader/pandas_talib) - A Python Pandas implementation of technical analysis indicators.
+- [Pandas TA](https://github.com/twopirllc/pandas-ta) - Pandas TA is an easy to use Python 3 Pandas Extension with 115+ Indicators. Easily build Custom Strategies.
+- [ta](https://github.com/bukosabino/ta) - Technical Analysis Library using Pandas (Python)
 - [algobroker](https://github.com/joequant/algobroker) - This is an execution engine for algo trading.
 - [pysentosa](https://pypi.org/project/pysentosa/) - Python API for sentosa trading system.
 - [finmarketpy](https://github.com/cuemacro/finmarketpy) - Python library for backtesting trading strategies and analyzing financial markets.
 - [binary-martingale](https://github.com/metaperl/binary-martingale) - Computer program to automatically trade binary options martingale style.
 - [fooltrader](https://github.com/foolcage/fooltrader) - the project using big-data technology to provide an uniform way to analyze the whole market.
+- [zvt](https://github.com/zvtvz/zvt) - the project using sql,pandas to provide an uniform and extendable way to record data,computing factors,select securites, backtesting,realtime trading and it could show all of them in clearly charts in realtime.
 - [pylivetrader](https://github.com/alpacahq/pylivetrader) - zipline-compatible live trading library.
 - [pipeline-live](https://github.com/alpacahq/pipeline-live) - zipline's pipeline capability with IEX for live trading.
 - [zipline-extensions](https://github.com/quantrocket-llc/zipline-extensions) - Zipline extensions and adapters for QuantRocket.
 - [moonshot](https://github.com/quantrocket-llc/moonshot) - Vectorized backtester and trading engine for QuantRocket based on Pandas.
 - [PyPortfolioOpt](https://github.com/robertmartin8/PyPortfolioOpt) - Financial portfolio optimisation in python, including classical efficient frontier and advanced methods.
+- [riskparity.py](https://github.com/dppalomar/riskparity.py) - fast and scalable design of risk parity portfolios with TensorFlow 2.0
 - [mlfinlab](https://github.com/hudson-and-thames/mlfinlab) - Implementations regarding "Advances in Financial Machine Learning" by Marcos Lopez de Prado. (Feature Engineering, Financial Data Structures, Meta-Labeling)
+- [pyqstrat](https://github.com/abbass2/pyqstrat) - A fast, extensible, transparent python library for backtesting quantitative strategies.
+- [NowTrade](https://github.com/edouardpoitras/NowTrade) - Python library for backtesting technical/mechanical strategies in the stock and currency markets.
+- [pinkfish](https://github.com/fja05680/pinkfish) - A backtester and spreadsheet library for security analysis.
+- [aat](https://github.com/timkpaine/aat) - Async Algorithmic Trading Engine
+- [Backtesting.py](https://kernc.github.io/backtesting.py/) - Backtest trading strategies in Python
+- [catalyst](https://github.com/enigmampc/catalyst) - An Algorithmic Trading Library for Crypto-Assets in Python
+- [quantstats](https://github.com/ranaroussi/quantstats) - Portfolio analytics for quants, written in Python
+- [qtpylib](https://github.com/ranaroussi/qtpylib) - QTPyLib, Pythonic Algorithmic Trading <http://qtpylib.io> 
+- [Quantdom](https://github.com/constverum/Quantdom) - Python-based framework for backtesting trading strategies & analyzing financial markets [GUI :neckbeard:]
+- [freqtrade](https://github.com/freqtrade/freqtrade) - Free, open source crypto trading bot
+- [algorithmic-trading-with-python](https://github.com/chrisconlan/algorithmic-trading-with-python) - Free `pandas` and `scikit-learn` resources for trading simulation, backtesting, and machine learning on financial data.
+- [DeepDow](https://github.com/jankrepl/deepdow) - Portfolio optimization with deep learning
 - [Qlib](https://github.com/microsoft/qlib) -  An AI-oriented Quantitative Investment Platform by Microsoft. Full ML pipeline of data processing, model training, back-testing; and covers the entire chain of quantitative investment: alpha seeking, risk modeling, portfolio optimization, and order execution.
 
 ### Risk Analysis
@@ -85,6 +110,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants
 ### Factor Analysis
 
 - [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
 
 ### Time Series
 
@@ -133,8 +159,15 @@ A curated list of insanely awesome libraries, packages and resources for Quants
 - [pytdx](https://github.com/rainx/pytdx) - Python Interface for retrieving chinese stock realtime quote data from TongDaXin Nodes.
 - [pdblp](https://github.com/matthewgilbert/pdblp) - A simple interface to integrate pandas and the Bloomberg Open API.
 - [tiingo](https://github.com/hydrosquall/tiingo-python) - Python interface for daily composite prices/OHLC/Volume + Real-time News Feeds, powered by the Tiingo Data Platform.
-- [IEX](https://github.com/addisonlynch/iexfinance) - Python Interface for retrieving real-time and historical prices and equities data from The Investor's Exchange.
+- [iexfinance](https://github.com/addisonlynch/iexfinance) - Python Interface for retrieving real-time and historical prices and equities data from The Investor's Exchange.
+- [pyEX](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.
 - [alpaca-trade-api](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.
+- [metatrader5](https://pypi.org/project/MetaTrader5/) - API Connector to MetaTrader 5 Terminal
+- [akshare](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>
+- [yahooquery](https://github.com/dpguthrie/yahooquery) - Python interface for retrieving data through unofficial Yahoo Finance API.
+- [investpy](https://github.com/alvarobartt/investpy) - Financial Data Extraction from Investing.com with Python! <https://investpy.readthedocs.io/>
+- [yliveticker](https://github.com/yahoofinancelive/yliveticker) - Live stream of market data from Yahoo Finance websocket.
+- [bbgbridge](https://github.com/ran404/bbgbridge) - Easy to use Bloomberg Desktop API wrapper for Python.
 
 ### Excel Integration
 
@@ -148,6 +181,11 @@ A curated list of insanely awesome libraries, packages and resources for Quants
 - [expy](http://www.bnikolic.co.uk/expy/expy.html) - The ExPy add-in allows easy use of Python directly from within an Microsoft Excel spreadsheet, both to execute arbitrary code and to define new Excel functions.
 - [pyxll](https://www.pyxll.com) - PyXLL is an Excel add-in that enables you to extend Excel using nothing but Python code.
 
+### Visualization
+
+- [D-Tale](https://github.com/man-group/dtale) - Visualizer for pandas dataframes and xarray datasets.
+- [mplfinance](https://github.com/matplotlib/mplfinance) - matplotlib utilities for the visualization, and visual analysis, of financial data.
+
 ## R
 
 ### Numerical Libraries & Data Structures
@@ -261,6 +299,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants
 
 ## Java
 
+- [Strata](http://strata.opengamma.io/) - Modern open-source analytics and market risk library designed and written in Java.
 - [JQuantLib](http://www.jquantlib.org) - JQuantLib is a free, open-source, comprehensive framework for quantitative finance, written in 100% Java.
 - [finmath.net](http://finmath.net) - Java library with algorithms and methodologies related to mathematical finance.
 - [quantcomponents](https://github.com/lsgro/quantcomponents) - Free Java components for Quantitative Finance and Algorithmic Trading.
@@ -284,6 +323,15 @@ A curated list of insanely awesome libraries, packages and resources for Quants
 ## Ruby
 
 - [Jiji](https://github.com/unageanu/jiji2) - Open Source Forex algorithmic trading framework using OANDA REST API.
+-
+## Elixir/Erlang
+
+- [Tai](https://github.com/fremantle-capital/tai) - Open Source composable, real time, market data and trade execution toolkit.
+- [Workbench](https://github.com/fremantle-industries/workbench) - From Idea to Execution - Manage your trading operation across a globally distributed cluster
+
+## Golang
+
+- [Kelp](https://github.com/stellar/kelp) - Kelp is an open-source Golang algorithmic cryptocurrency trading bot that runs on centralized exchanges and Stellar DEX (command-line usage and desktop GUI).
 
 ## Frameworks
 
@@ -307,3 +355,4 @@ A curated list of insanely awesome libraries, packages and resources for Quants
 - [volatility-trading](https://github.com/jasonstrimpel/volatility-trading) - A complete set of volatility estimators based on Euan Sinclair's Volatility Trading.
 - [quant](https://github.com/paulperry/quant) - Quantitative Finance and Algorithmic Trading exhaust; mostly ipython notebooks based on Quantopian, Zipline, or Pandas.
 - [fecon235](https://github.com/rsvp/fecon235) - Open source project for software tools in financial economics. Many jupyter notebook to verify theoretical ideas and practical methods interactively.
+- [Quantitative-Notebooks](https://github.com/LongOnly/Quantitative-Notebooks) - Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy