2026-06-01T16:03:16Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/336072026-02-03T11:11:30Zcom_10630_2254col_10630_37953
RIUMA. Repositorio Institucional de la Universidad de Málaga
author
Alaminos Aguilera, David
author
Salas-Compás, María Belén
author
Fernández-Gámez, Manuel Ángel
2024-09-27T08:57:52Z
2024-09-27T08:57:52Z
2023
Alaminos, D., Salas, M.B. & Fernández-Gámez, M.A. High-Frequency Trading in Bond Returns: A Comparison Across Alternative Methods and Fixed-Income Markets. Comput Econ (2023). https://doi.org/10.1007/s10614-023-10502-3
https://hdl.handle.net/10630/33607
https://doi.org/10.1007/s10614-023-10502-3
A properly performing and efficient bond market is widely considered important for the smooth functioning of trading systems in general. An important feature of the bond market for investors is its liquidity. High-frequency trading employs sophisticated algorithms to explore numerous markets, such as fixed-income markets. In this trading, transactions are processed more quickly, and the volume of trades rises significantly, improving liquidity in the bond market. This paper presents a comparison of neural networks, fuzzy logic, and quantum methodologies for predicting bond price movements through a high-frequency strategy in advanced and emerging countries. Our results indicate that, of the selected methods, QGA, DRCNN and DLNN-GA can correctly interpret the expected bond future price direction and rate changes satisfactorily, while QFuzzy tend to perform worse in forecasting the future direction of bond prices. Our work has a large potential impact on the possible directions of the strategy of algorithmic trading for investors and stakeholders in fixed-income markets and all methodologies proposed in this study could be great options policy to explore other financial markets.
eng
Beneficios
Redes neuronales (Informática)
Lógica difusa
High-Frequency Trading in Bond Returns: A Comparison Across Alternative Methods and Fixed-Income Markets
journal article
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URL
https://riuma.uma.es/bitstreams/7f4080ef-9acf-4c4a-9365-adaa76f71474/download
File
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5815686157eef05ffe012cb1d4849e1e
2822556
application/pdf
12.High-Frequency Trading in Bond Returns.pdf