https://github.com/rbeeli/short-term_momentum_strategy

Short-term momentum trading strategy implemented for the lecture "Systematic risk premia strategies traded at hedge funds" at University of Zurich, FS 2018.
https://github.com/rbeeli/short-term_momentum_strategy

fund hedge momentum reversal strategy trading

Last synced: 6 months ago
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Short-term momentum trading strategy implemented for the lecture "Systematic risk premia strategies traded at hedge funds" at University of Zurich, FS 2018.

• Host: GitHub
• URL: https://github.com/rbeeli/short-term_momentum_strategy
• Owner: rbeeli
• Created: 2018-11-13T14:09:02.000Z (almost 7 years ago)
• Default Branch: master
• Last Pushed: 2022-03-23T01:45:56.000Z (over 3 years ago)
• Last Synced: 2025-04-17T10:27:41.177Z (6 months ago)
• Topics: fund, hedge, momentum, reversal, strategy, trading
• Language: R
• Size: 94.7 MB
• Stars: 41
• Watchers: 2
• Forks: 12
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Short-term Momentum trading strategy

Short-term momentum trading strategy implemented for the lecture "Systematic risk premia strategies traded at hedge funds" at University of Zurich, FS 2018.

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## Overview

* Implementation in R

* In accordance to paper [Short-term Momentum (Medhat, Schmeling 2021)](https://academic.oup.com/rfs/article-abstract/35/3/1480/6286969):

    + Monthly pricing data from the Center for Research in Security Prices (CRSP)

    + Sample starts in July, 1963 and ends in December, 2016

    + All common shares traded on NYSE, AMEX, and Nasdaq 

Measure short-term momentum using the return over the previous month: 𝑀𝑂𝑀_(𝑖,𝑡) = 𝑟_(𝑖,𝑡−1)

    + Measure short-term turnover using previous month volume and number of shares outstanding data: 𝑇𝑂_(𝑖,𝑡) = 𝑉𝑂𝐿_(𝑖,𝑡−1) / 𝑆𝐻𝑅𝑂𝑈𝑇_(𝑖,𝑡−1)

    + Portfolios are value-weighted by market capitalization and rebalanced at the end of each month

## Results

![Main findings (excess returns)](./results/main_findings_table.png)

![Cumulative performance of strategies](./results/strategies_performance.png)