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2018-01-16 20:13:50 -05:00

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<h1 class="header-title">Welcome, and an algorithm</h1>
<p class="header-date"> <a href="/author/bradlee-speice.html">Bradlee Speice</a>, Thu 19 November 2015, Sat 05 December 2015, <a href="/category/blog.html">Blog</a></p>
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<a href="/tag/introduction.html">introduction</a>, <a href="/tag/trading.html">trading</a> </p>
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<p>Hello! Glad to meet you. I'm currently a student at Columbia University
studying Financial Engineering, and want to give an overview of the projects
I'm working on!</p>
<p>To start things off, Columbia has been hosting a trading competition that
myself and another partner are competing in. I'm including a notebook of the
algorithm that we're using, just to give a simple overview of a miniature
algorithm.</p>
<p>The competition is scored in 3 areas:</p>
<ul>
<li>Total return</li>
<li><a href="1">Sharpe ratio</a></li>
<li>Maximum drawdown</li>
</ul>
<p>Our algorithm uses a basic momentum strategy: in the given list of potential
portfolios, pick the stocks that have been performing well in the past 30
days. Then, optimize for return subject to the drawdown being below a specific
level. We didn't include the Sharpe ratio as a constraint, mostly because
we were a bit late entering the competition.</p>
<p>I'll be updating this post with the results of our algorithm as they come along!</p>
<hr>
<p><strong>UPDATE 12/5/2015</strong>: Now that the competition has ended, I wanted to update
how the algorithm performed. Unfortunately, it didn't do very well. I'm planning
to make some tweaks over the coming weeks, and do another forward test in January.</p>
<ul>
<li>After week 1: Down .1%</li>
<li>After week 2: Down 1.4%</li>
<li>After week 3: Flat</li>
</ul>
<p>And some statistics for all teams participating in the competition:</p>
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<td>Max Return</td>
<td>74.1%</td>
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<td>Min Return</td>
<td>-97.4%</td>
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<td>Average Return</td>
<td>-.1%</td>
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<td>Std Dev of Returns</td>
<td>19.6%</td>
</tr>
</tbody>
</table>
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<p>{% notebook 2015-11-14-welcome.ipynb %}</p>
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