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71 lines
1.8 KiB
Plaintext
71 lines
1.8 KiB
Plaintext
---
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title: Welcome, and an algorithm
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date: 2015-11-19
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last_update:
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date: 2015-12-05
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slug: 2015/11/welcome
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authors: [bspeice]
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tags: [trading]
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---
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import Notebook from './_notebook.md'
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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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<!-- truncate -->
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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](https://en.wikipedia.org/wiki/Sharpe_ratio)
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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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<table>
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<tr>
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<td>Max Return</td>
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<td>74.1%</td>
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</tr>
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<tr>
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<td>Min Return</td>
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<td>-97.4%</td>
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</tr>
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<tr>
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<td>Average Return</td>
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<td>-.1%</td>
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</tr>
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<tr>
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<td>Std Dev of Returns</td>
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<td>19.6%</td>
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</tr>
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</table>
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---
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<Notebook/> |