deploy: 2ab6db153b

index.html

@@ -213,6 +213,7 @@ ul.task-list li input[type="checkbox"] {
 <li><a href="https://www.numpy.org">numpy</a> - NumPy is the fundamental package for scientific computing with Python.</li>
 <li><a href="https://www.scipy.org">scipy</a> - SciPy (pronounced “Sigh Pie”) is a Python-based ecosystem of open-source software for mathematics, science, and engineering.</li>
 <li><a href="https://pandas.pydata.org">pandas</a> - pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.</li>
+<li><a href="https://docs.pola.rs/">polars</a> - Polars is a blazingly fast DataFrame library for manipulating structured data.</li>
 <li><a href="https://github.com/johnbywater/quantdsl">quantdsl</a> - Domain specific language for quantitative analytics in finance and trading.</li>
 <li><a href="https://docs.python.org/3/library/statistics.html">statistics</a> - Builtin Python library for all basic statistical calculations.</li>
 <li><a href="https://www.sympy.org/">sympy</a> - SymPy is a Python library for symbolic mathematics.</li>
@@ -339,11 +340,14 @@ ul.task-list li input[type="checkbox"] {
 <li><a href="https://github.com/asavinov/intelligent-trading-bot">Intelligent Trading Bot</a> - Automatically generating signals and trading based on machine learning and feature engineering</li>
 <li><a href="https://github.com/enzoampil/fastquant">fastquant</a> - fastquant allows you to easily backtest investment strategies with as few as 3 lines of python code.</li>
 <li><a href="https://github.com/nautechsystems/nautilus_trader">nautilus_trader</a> - A high-performance algorithmic trading platform and event-driven backtester.</li>
+<li><a href="https://github.com/bsdz/yabte">YABTE</a> - Yet Another (Python) BackTesting Engine.</li>
 </ul>
 </section>
 <section id="risk-analysis" class="level3">
 <h3 class="anchored" data-anchor-id="risk-analysis">Risk Analysis</h3>
 <ul>
+<li><a href="https://github.com/auto-differentiation/QuantLib-Risks-Py">QuantLibRisks</a> - Fast risks with QuantLib</li>
+<li><a href="https://github.com/auto-differentiation/xad-py">XAD</a> - Automatic Differentation (AAD) Library</li>
 <li><a href="https://github.com/quantopian/pyfolio">pyfolio</a> - Portfolio and risk analytics in Python.</li>
 <li><a href="https://github.com/quantopian/empyrical">empyrical</a> - Common financial risk and performance metrics.</li>
 <li><a href="https://github.com/rsvp/fecon235">fecon235</a> - Computational tools for financial economics include: Gaussian Mixture model of leptokurtotic risk, adaptive Boltzmann portfolios.</li>
@@ -708,6 +712,8 @@ ul.task-list li input[type="checkbox"] {
 <h2 class="anchored" data-anchor-id="cpp">CPP</h2>
 <ul>
 <li><a href="https://github.com/lballabio/QuantLib">QuantLib</a> - The QuantLib project is aimed at providing a comprehensive software framework for quantitative finance.</li>
+<li><a href="https://github.com/auto-differentiation/QuantLib-Risks-Cpp">QuantLibRisks</a> - Fast risks with QuantLib in C++</li>
+<li><a href="https://github.com/auto-differentiation/xad">XAD</a> - Automatic Differentation (AAD) Library</li>
 <li><a href="https://github.com/rburkholder/trade-frame">TradeFrame</a> - C++ 17 based framework/library (with sample applications) for testing options based automated trading ideas using DTN IQ real time data feed and Interactive Brokers (TWS API) for trade execution. Comes with built-in <a href="https://github.com/rburkholder/trade-frame/tree/master/lib/TFOptions">Option Greeks/IV</a> calculation library.</li>
 </ul>
 </section>
@@ -716,6 +722,8 @@ ul.task-list li input[type="checkbox"] {
 <ul>
 <li><a href="https://github.com/lballabio/QuantLib">QuantLib</a> - The QuantLib project is aimed at providing a comprehensive software framework for quantitative finance.
 <ul>
+<li>QuantLibRisks - Fast risks with QuantLib in <a href="https://pypi.org/project/QuantLib-Risks/">Python</a> and <a href="https://github.com/auto-differentiation/QuantLib-Risks-Cpp">C++</a></li>
+<li>XAD - Automatic Differentiation (AAD) Library in <a href="https://pypi.org/project/xad/">Python</a> and <a href="https://github.com/auto-differentiation/xad/">C++</a></li>
 <li><a href="https://github.com/frgomes/jquantlib">JQuantLib</a> - Java port.</li>
 <li><a href="https://github.com/eddelbuettel/rquantlib">RQuantLib</a> - R port.</li>
 <li><a href="https://www.quantlib.org/quantlibaddin/">QuantLibAddin</a> - Excel support.</li>
@@ -724,7 +732,6 @@ ul.task-list li input[type="checkbox"] {
 <li><a href="https://github.com/enthought/pyql">PyQL</a> - Python port.</li>
 <li><a href="https://github.com/pazzo83/QuantLib.jl">QuantLib.jl</a> - Julia port.</li>
 <li><a href="https://quantlib-python-docs.readthedocs.io/">QuantLib-Python Documentation</a> - Documentation for the Python bindings for the QuantLib library</li>
-<li><a href="https://github.com/auto-differentiation/quantlib-xad">QuantLib with Automatic Differention enabled</a> - Integration of Automatic Differentiation with the QuantLib library</li>
 </ul></li>
 <li><a href="https://ta-lib.org">TA-Lib</a> - perform technical analysis of financial market data.
 <ul>
@@ -732,6 +739,7 @@ ul.task-list li input[type="checkbox"] {
 <li><a href="https://github.com/TA-Lib/ta-lib">ta-lib</a></li>
 </ul></li>
 <li><a href="https://portfoliooptimizer.io/">Portfolio Optimizer</a> - Portfolio Optimizer is a Web API for portfolio analysis and optimization.</li>
+<li>XAD: Automatic Differentation (AAD) Library for <a href="https://pypi.org/project/xad/">Python</a> and <a href="https://github.com/auto-differentiation/xad">C++</a></li>
 </ul>
 </section>
 <section id="csharp" class="level2">
@@ -757,6 +765,7 @@ ul.task-list li input[type="checkbox"] {
 <section id="reproducing-works-training-books" class="level2">
 <h2 class="anchored" data-anchor-id="reproducing-works-training-books">Reproducing Works, Training &amp; Books</h2>
 <ul>
+<li><a href="https://auto-differentiation.github.io/">Auto-Differentiation Website</a> - Background and resources on Automatic Differentiation (AD) / Adjoint Algorithmic Differentitation (AAD).</li>
 <li><a href="https://github.com/MarcosCarreira/DermanPapers">Derman Papers</a> - Notebooks that replicate original quantitative finance papers from Emanuel Derman.</li>
 <li><a href="https://www.ml-quant.com/">ML-Quant</a> - Top Quant resources like ArXiv (sanity), SSRN, RePec, Journals, Podcasts, Videos, and Blogs.</li>
 <li><a href="https://github.com/jasonstrimpel/volatility-trading">volatility-trading</a> - A complete set of volatility estimators based on Euan Sinclair’s Volatility Trading.</li>