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60 lines
1.9 KiB
Markdown
60 lines
1.9 KiB
Markdown
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Title: Welcome, and an algorithm
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Date: 2015-11-19
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Tags: introduction, trading
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Modified: 2015-12-05
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Category: Blog
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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
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I'm working on!
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To start things off, Columbia has been hosting a trading competition that
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myself and another partner are competing in. I'm including a notebook of the
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algorithm that we're using, just to give a simple overview of a miniature
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algorithm.
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The competition is scored in 3 areas:
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- Total return
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- [Sharpe ratio](1)
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- Maximum drawdown
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Our algorithm uses a basic momentum strategy: in the given list of potential
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portfolios, pick the stocks that have been performing well in the past 30
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days. Then, optimize for return subject to the drawdown being below a specific
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level. We didn't include the Sharpe ratio as a constraint, mostly because
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we were a bit late entering the competition.
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I'll be updating this post with the results of our algorithm as they come along!
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---
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**UPDATE 12/5/2015**: Now that the competition has ended, I wanted to update
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how the algorithm performed. Unfortunately, it didn't do very well. I'm planning
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to make some tweaks over the coming weeks, and do another forward test in January.
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- After week 1: Down .1%
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- After week 2: Down 1.4%
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- After week 3: Flat
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And some statistics for all teams participating in the competition:
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|--------------------|--------|
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| Max Return | 74.1% |
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| Min Return | -97.4% |
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| Average Return | -.1% |
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| Std Dev of Returns | 19.6% |
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---
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{% notebook 2015-11-14-welcome.ipynb %}
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<script type="text/x-mathjax-config">
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MathJax.Hub.Config({tex2jax: {inlineMath: [['$','$'], ['\(','\)']]}});
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</script>
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<script async src='https://cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-AMS_CHTML'></script>
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[1]: https://en.wikipedia.org/wiki/Sharpe_ratio
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