Finding attractive technical patterns in cryptocurrency markets

By Sungjoo Ha, B. Moon. 2018

25 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Information Systems, Marketing

How researchers see this paper

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

In Economics and Econometrics

1. Alexander Deinert
2. Thomas G. Fischer
3. Christopher Krauss
4. David Martínez-Rego
5. Carmine Ventre
6. Leslie Kanthan
7. Lingbo Li
8. Fan Wu

In Information Systems

1. David Martínez-Rego
2. Carmine Ventre
3. Leslie Kanthan
4. Lingbo Li
5. Christopher Krauss
6. Fan Wu
7. Fan Fang
8. H. Kong

In Marketing

1. Christopher Krauss
2. Thomas G. Fischer

Citations in the corpus

• Statistical Arbitrage in Cryptocurrency Markets (2019, background): “Recently, Ha and Moon (2018) use genetic programming to detect profitable technical trading patterns for cryptocurrencies, and find that their system performs better than a buy-and-hold strategy.”
• Cryptocurrency trading: a comprehensive survey (2020, background): “[107] investigated using genetic programming (GP) to find attractive technical patterns in the cryptocurrency market.”