Momentum and trend following trading strategies for currencies revisited : combining academia and industry

By Janick Rohrbach, Silvan Suremann, Joerg Osterrieder. 2017

15 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance, Management Science and Operations Research

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. Bryan Lim
2. Stephen J. Roberts
3. B. Moon
4. Stefan Zohren
5. Weiwei Jiang

In Finance

1. Bryan Lim
2. Stephen J. Roberts
3. B. Moon
4. Stefan Zohren

In Management Science and Operations Research

1. Stefan Zohren
2. Bryan Lim
3. Stephen J. Roberts
4. B. Moon
5. Sungjoo Ha
6. Weiwei Jiang

Citations in the corpus

• Enhancing Time-Series Momentum Strategies Using Deep Neural Networks (2019, background): “More sophisticated trading rules are proposed in [4] and [37], taking volatility-normalised moving average convergence divergence (MACD) indicators”
• Finding attractive technical patterns in cryptocurrency markets (2018, background): “…Byung-Ro Moon moon@snu.ac.kr 1 School of Computer Science and Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 151-744, Korea Rohrbach et al. [21] adopts a more modular technique and focuses on a specific technical indicator that captures the momentum of the current market.”