Paper: arXiv 2405.15461

Authors: Hongshen Yang, Avinash Malik

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.

Complexity vs Empirical Score

  • Math Complexity: 6.5/10
  • Empirical Rigor: 6.0/10 (capped from 7.5: transaction costs only partially modelled; see penalty flags)
  • Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper introduces a novel bi-objective convex optimization approach (OTT) for multivariate pair trading using cryptocurrencies as anchors while maintaining market neutrality in fiat assets. It combines solid mathematical formulation with an empirical backtest spanning both bull and bear market regimes from 2020 to 2022.

Research Flowchart

  flowchart TD
    A[Goal: Market-Neutral Currency Arbitrage on Crypto Platforms] --> B[Data Inputs: Crypto-Fiat Market Data 2020-2022]
    B --> C[Method: Form Multivariate Currency Buckets for Pair Trading]
    C --> D[Process: Bi-Objective Convex Optimization]
    D --> E[Risk Control: Tunable Volatility Penalties & Thresholds]
    E --> F[Execution: Arbitrage without External Shorting]
    F --> G[Outcomes: 15.49% Annualized Profit & Robust Post-COVID Results]

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2 of 164 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.