Statistical arbitrage pairs trading strategies: Review and outlook

By Christopher Krauss. 2017

207 citations recorded by the source corpus.

Subfields: Accounting, Economics and Econometrics, Finance

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Accounting

1. Alexander Deinert
2. Thomas G. Fischer
3. Christopher Krauss
4. Nicolas Huck

In Economics and Econometrics

1. Alexander Deinert
2. Thomas G. Fischer
3. Christopher Krauss
4. Xuan Anh Do
5. Nicolas Huck
6. Omer Berat Sezer
7. A. Ozbayoglu
8. M. Ugur Gudelek

In Finance

1. Alexander Deinert
2. Thomas G. Fischer
3. Christopher Krauss
4. Xuan Anh Do
5. Nicolas Huck
6. A. Ozbayoglu
7. Omer Berat Sezer
8. M. Ugur Gudelek

Citations in the corpus

• Statistical Arbitrage in Cryptocurrency Markets (2019, methodology): “Huck (2009, 2010); Krauss et al. (2017); Moritz and Zimmermann (2014); Takeuchi and Lee (2013), who have developed similar methods for U.S. cash equities, but on much lower frequencies (days to months). With the present manuscript, we successfully show that relative-value arbitrage opportunities exi”
• Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500 (2017, background): “Krauss (2015) provides a recent review of more than 90 statistical arbitrage pairs trading strategies, focusing on relative mispricings between two and more securities.”