Optimal Market-Neutral Multivariate Pair Trading on the Cryptocurrency Platform

Hongshen Yang () and Avinash Malik
Additional contact information
Hongshen Yang: Department of ECSE, Faculty of Engineering, The University of Auckland, Auckland CBD, Auckland 1010, New Zealand
Avinash Malik: Department of ECSE, Faculty of Engineering, The University of Auckland, Auckland CBD, Auckland 1010, New Zealand

IJFS, 2024, vol. 12, issue 3, 1-24

Abstract: This research proposes a novel arbitrage approach in multivariate pair trading, termed the Optimal Trading Technique (OTT). We present a method for selectively forming a “bucket” of fiat currencies anchored to cryptocurrency for monitoring and exploiting trading opportunities simultaneously. To address quantitative conflicts from multiple trading signals, a novel bi-objective convex optimization formulation is designed to balance investor preferences between profitability and risk tolerance. We understand that cryptocurrencies carry significant financial risks. Therefore this process includes tunable parameters such as volatility penalties and action thresholds. In experiments conducted in the cryptocurrency market from 2020 to 2022, which encompassed a vigorous bull run followed by a bear run, the OTT achieved an annualized profit of 15.49%. Additionally, supplementary experiments detailed in the appendix extend the applicability of OTT to other major cryptocurrencies in the post-COVID period, validating the model’s robustness and effectiveness in various market conditions. The arbitrage operation offers a new perspective on trading, without requiring external shorting or holding the intermediate during the arbitrage period. As a note of caution, this study acknowledges the high-risk nature of cryptocurrency investments, which can be subject to significant volatility and potential loss.

Keywords: pair trading; multivariate; quantitative trading; cryptocurrency market (search for similar items in EconPapers)
JEL-codes: F2 F3 F41 F42 G1 G2 G3 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7072/12/3/77/pdf (application/pdf)
https://www.mdpi.com/2227-7072/12/3/77/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijfss:v:12:y:2024:i:3:p:77-:d:1453239

Access Statistics for this article

IJFS is currently edited by Ms. Hannah Lu

More articles in IJFS from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().