Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
169 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Optimal Settings for Cryptocurrency Trading Pairs (2210.10971v3)

Published 20 Oct 2022 in q-fin.TR, cs.AI, and math.OC

Abstract: The goal of cryptocurrencies is decentralization. In principle, all currencies have equal status. Unlike traditional stock markets, there is no default currency of denomination (fiat), thus the trading pairs can be set freely. However, it is impractical to set up a trading market between every two currencies. In order to control management costs and ensure sufficient liquidity, we must give priority to covering those large-volume trading pairs and ensure that all coins are reachable. We note that this is an optimization problem. Its particularity lies in: 1) the trading volume between most (>99.5%) possible trading pairs cannot be directly observed. 2) It satisfies the connectivity constraint, that is, all currencies are guaranteed to be tradable. To solve this problem, we use a two-stage process: 1) Fill in missing values based on a regularized, truncated eigenvalue decomposition, where the regularization term is used to control what extent missing values should be limited to zero. 2) Search for the optimal trading pairs, based on a branch and bound process, with heuristic search and pruning strategies. The experimental results show that: 1) If the number of denominated coins is not limited, we will get a more decentralized trading pair settings, which advocates the establishment of trading pairs directly between large currency pairs. 2) There is a certain room for optimization in all exchanges. The setting of inappropriate trading pairs is mainly caused by subjectively setting small coins to quote, or failing to track emerging big coins in time. 3) Too few trading pairs will lead to low coverage; too many trading pairs will need to be adjusted with markets frequently. Exchanges should consider striking an appropriate balance between them.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (16)
  1. A trust region method based on interior point techniques for nonlinear programming. Mathematical programming, 89(1):149–185, 2000.
  2. Michael X. Cohen. A tutorial on generalized eigendecomposition for source separation in multichannel electrophysiology. 2021.
  3. How comparable are origin-destination matrices estimated from automatic fare collection, origin-destination surveys and household travel survey? an empirical investigation in lyon. Transportation Research Part A: Policy and Practice, 138:267–282, 2020.
  4. Ascertaining price formation in cryptocurrency markets with machine learning. The European Journal of Finance, pages 1–23, 2021.
  5. Cryptocurrency trading: a comprehensive survey. Financial Innovation, 8(1):1–59, 2022.
  6. A data-driven approach for origin–destination matrix construction from cellular network signalling data: a case study of lyon region (france). Transportation, 48:1671–1702, 2021.
  7. Pairs trading in cryptocurrency markets. IEEE Access, 8:172644–172651, 2020.
  8. A data driven method for od matrix estimation. Transportation Research Part C: Emerging Technologies, 113:38–56, 2020.
  9. Satoshi Nakamoto. Bitcoin: A peer-to-peer electronic cash system. 2008.
  10. Solving limit analysis problems: an interior-point method. Communications in numerical methods in engineering, 21(11):631–642, 2005.
  11. Introducing hurst exponent in pair trading. Physica A: statistical mechanics and its applications, 488:39–45, 2017.
  12. Some notes on the formation of a pair in pairs trading. Mathematics, 8(3):348, 2020.
  13. A practical approach to assignment-free dynamic origin–destination matrix estimation problem. Transportation Research Part C: Emerging Technologies, 134:103477, 2022.
  14. A comprehensive review of branch-and-bound algorithms: Guidelines and directions for further research on the flowshop scheduling problem. Expert Systems with Applications, 158:113556, 2020.
  15. Daniel Davis Wood. Ethereum: A secure decentralised generalised transaction ledger. 2014.
  16. Research on regional traffic and economic linkage based on accessibility and gravity model–taking hengyang, china as an example. IOP Conference Series: Earth and Environmental Science, 510, 2020.

Summary

We haven't generated a summary for this paper yet.