DOC: Features

_sources/index.txt

@@ -1,4 +1,8 @@
 .. include:: welcome.rst
+|
+|
+Table of Contents
+-----------------
 
 .. toctree::
    :maxdepth: 1

_sources/welcome.txt

@@ -6,4 +6,17 @@ Catalyst empowers users to share and curate data and build profitable,
 data-driven investment strategies.
 
 Features
-========
+========
+
+-  Ease of use: Catalyst tries to get out of your way so that you can 
+   focus on algorithm development. See examples provided.
+-  Support for several of the top crypto-exchanges by trading volume.
+-  Input of historical pricing data of all crypto-assets by exchange, 
+   with daily and minute resolution.
+-  Backtesting and live-trading functionality, with a seamless transition
+   between the two modes.
+-  Output of performance statistics are based on Pandas DataFrames to 
+   integrate nicely into the existing PyData eco-system.
+-  Statistic and machine learning libraries like matplotlib, scipy, 
+   statsmodels, and sklearn support development, analysis, and 
+   visualization of state-of-the-art trading systems.

index.html

@@ -137,11 +137,32 @@ Catalyst empowers users to share and curate data and build profitable,
 data-driven investment strategies.</p>
 <div class="section" id="features">
 <h1>Features<a class="headerlink" href="#features" title="Permalink to this headline">¶</a></h1>
+<ul class="simple">
+<li>Ease of use: Catalyst tries to get out of your way so that you can
+focus on algorithm development. See examples provided.</li>
+<li>Support for several of the top crypto-exchanges by trading volume.</li>
+<li>Input of historical pricing data of all crypto-assets by exchange,
+with daily and minute resolution.</li>
+<li>Backtesting and live-trading functionality, with a seamless transition
+between the two modes.</li>
+<li>Output of performance statistics are based on Pandas DataFrames to
+integrate nicely into the existing PyData eco-system.</li>
+<li>Statistic and machine learning libraries like matplotlib, scipy,
+statsmodels, and sklearn support development, analysis, and
+visualization of state-of-the-art trading systems.</li>
+</ul>
+<div class="line-block">
+<div class="line"><br /></div>
+<div class="line"><br /></div>
+</div>
+<div class="section" id="table-of-contents">
+<h2>Table of Contents<a class="headerlink" href="#table-of-contents" title="Permalink to this headline">¶</a></h2>
 <div class="toctree-wrapper compound">
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="install.html">Install</a></li>
 </ul>
 </div>
+</div>
 </div>
 
 

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welcome.html

@@ -136,6 +136,20 @@ Catalyst empowers users to share and curate data and build profitable,
 data-driven investment strategies.</p>
 <div class="section" id="features">
 <h1>Features<a class="headerlink" href="#features" title="Permalink to this headline">¶</a></h1>
+<ul class="simple">
+<li>Ease of use: Catalyst tries to get out of your way so that you can
+focus on algorithm development. See examples provided.</li>
+<li>Support for several of the top crypto-exchanges by trading volume.</li>
+<li>Input of historical pricing data of all crypto-assets by exchange,
+with daily and minute resolution.</li>
+<li>Backtesting and live-trading functionality, with a seamless transition
+between the two modes.</li>
+<li>Output of performance statistics are based on Pandas DataFrames to
+integrate nicely into the existing PyData eco-system.</li>
+<li>Statistic and machine learning libraries like matplotlib, scipy,
+statsmodels, and sklearn support development, analysis, and
+visualization of state-of-the-art trading systems.</li>
+</ul>
 </div>