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< title > Welcome, and an algorithm - Bradlee Speice< / title >
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< a class = "pull-left" href = "/" > < img class = "mr20" src = "/images/logo.svg" alt = "logo" > Bradlee Speice< / a >
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< 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
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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 >
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< hr >
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< 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 >
< table >
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< tr >
< th > < / th >
< th > < / th >
< / tr >
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< tr >
< td > Max Return< / td >
< td > 74.1%< / td >
< / tr >
< tr >
< td > Min Return< / td >
< td > -97.4%< / td >
< / tr >
< tr >
< td > Average Return< / td >
< td > -.1%< / td >
< / tr >
< tr >
< 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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