Pairs-trading System using Quantum-inspired Combinatorial Optimization Accelerator for Optimal Path Search in Market Graphs (2307.05923v1)
Abstract: Pairs-trading is a trading strategy that involves matching a long position with a short position in two stocks aiming at market-neutral profits. While a typical pairs-trading system monitors the prices of two statistically correlated stocks for detecting a temporary divergence, monitoring and analyzing the prices of more stocks would potentially lead to finding more trading opportunities. Here we report a stock pairs-trading system that finds trading opportunities for any two stocks in an $N$-stock universe using a combinatorial optimization accelerator based on a quantum-inspired algorithm called simulated bifurcation. The trading opportunities are detected through solving an optimal path search problem in an $N$-node directed graph with edge weights corresponding to the products of instantaneous price differences and statistical correlation factors between two stocks. The accelerator is one of Ising machines and operates consecutively to find multiple opportunities in a market situation with avoiding duplicate detections by a tabu search technique. It has been demonstrated in the Tokyo Stock Exchange that the FPGA (field-programmable gate array)-based trading system has a sufficiently low latency (33 $\mu$s for $N$=15 or 210 pairs) to execute the pairs-trading strategy based on optimal path search in market graphs.
- W. F. Sharpe, G. J. Alexander, J. V. Bailey, “Investments (4th edition),” Prentice Hall, Englewood Cliffs, N.J. 1990.
- A. Shleifer, R. W. Vishny, “The limits of arbitrage,” The Journal of finance 52, pp. 35–55, 1997. [Online]. Available: https://doi.org/10.1111/j.1540-6261.1997.tb03807.x
- D. Gromb, D. Vayanos, “Limits of arbitrage,” Annual Review of Financial Economics 2, pp. 251–275, 2010. [Online]. Available: https://doi.org/10.1146/annurev-financial-073009-104107
- D. Rösch, “The impact of arbitrage on market liquidity,” Journal of Financial Economics 142, pp. 195–213, 2021. [Online]. Available: https://doi.org/10.1016/j.jfineco.2021.04.034
- E. Gatev, W. N. Goetzmann, K. G. Rouwenhorst, “Pairs trading: Performance of a relative-value arbitrage rule,” The Review of Financial Studies 19, pp. 797–827, 2006. [Online]. Available: https://doi.org/10.1093/rfs/hhj020
- C. Krauss, “Statistical arbitrage pairs trading strategies: Review and outlook,” Journal of Economic Surveys 31, pp. 513–545, 2017. [Online]. Available: https://doi.org/10.1111/joes.12153
- A. Flori, D. Regoli, “Revealing pairs-trading opportunities with long short-term memory network,” European Journal of Operational Research 295, pp. 772–791, 2021. [Online]. Available: https://doi.org/10.1016/j.ejor.2021.03.009
- S. Butenko, “Maximum independent set and related problems, with applications,” Ph.D. dissertation, the Industrial and Systems Engineering Department, University of Florida, 2003. [Online]. Available: https://ufdcimages.uflib.ufl.edu/UF/E0/00/10/11/ 00001/butenko_s.pdf
- V. Boginski, S. Butenko, P. M. Pardalos, “Network-based Techniques in the Analysis of the Stock Market,” in Supply Chain and Finance, eds. P. M. Pardalos, A. Migdalas, G. Baourakis, World Scientific, pp. 1–14, 2004. [Online]. Available: https://doi.org/10.1142/9789812562586_0001
- M. Marzec, “Portfolio optimization: Applications in quantum computing,” in Handbook of High-Frequency Trading and Modeling in Finance eds. I. Florescu, M. C. Mariani, H. E. Stanley, F. G. Viens, Wiley Online Library, pp. 73–106, 2016. [Online]. Available: https://doi.org/10.1002/9781118593486.ch4
- A. Lucas, “Ising formulations of many NP problems,” Frontiers in physics 2, 5, 2014. [Online]. Available: https://doi.org/10.3389/fphy.2014.00005
- H. Goto, K. Tatsumura, A. R. Dixon, “Combinatorial optimization by simulating adiabatic bifurcations in nonlinear Hamiltonian systems,” Science Advances 5, eaav2372, 2019. [Online]. Available: https://doi.org/10.1126/sciadv.aav2372
- K. Tatsumura, A. R. Dixon, H. Goto, “FPGA-Based Simulated Bifurcation Machine,” Proc. of IEEE International Conference on Field Programmable Logic and Applications (FPL), pp. 59–66, 2019. [Online]. Available: https://doi.org/10.1109/FPL.2019.00019
- H. Goto, K. Endo, M. Suzuki, Y. Sakai, T. Kanao, Y. Hamakawa, R. Hidaka, M. Yamasaki, K. Tatsumura, “High-performance combinatorial optimization based on classical mechanics,” Science Advances 7, eabe7953, 2021. [Online]. Available: https://doi.org//10.1126/sciadv.abe7953
- K. Tatsumura, M. Yamasaki, H. Goto, “Scaling out Ising machines using a multi-chip architecture for simulated bifurcation,” Nature Electronics 4, pp. 208–217, 2021. [Online]. Available: https://doi.org/10.1038/s41928-021-00546-4
- T. Kanao, H. Goto, “Simulated bifurcation for higher-order cost functions,” Applied Physics Express 16, 014501, 2023. [Online]. Available: https://doi.org/10.35848/1882-0786/acaba9
- M. W. Johnson, M. H. S. Amin, S. Gildert, T. Lanting, F. Hamze, N. Dickson, R. Harris, A. J. Berkley, J. Johansson, P. Bunyk, E. M. Chapple, C. Enderud, J. P. Hilton, K. Karimi, E. Ladizinsky, N. Ladizinsky, T. Oh, I. Perminov, C. Rich, M. C. Thom, E. Tolkacheva, C. J. S. Truncik, S. Uchaikin, J. Wang, B. Wilson, G. Rose, “Quantum annealing with manufactured spins,” Nature 473, pp. 194–198 (2011). [Online]. Available: https://doi.org/10.1038/nature10012
- A. D. King, J. Raymond, T. Lanting, R. Harris, A. Zucca, F. Altomare, A. J. Berkley, K. Boothby, S. Ejtemaee, C. Enderud, E. Hoskinson, S. Huang, E. Ladizinsky, A. J. R. MacDonald, G. Marsden, R. Molavi, T. Oh, G. Poulin-Lamarre, M. Reis, C. Rich, Y. Sato, N. Tsai, M. Volkmann, J. D. Whittaker, J. Yao, A. W. Sandvik, M. H. Amin, “Quantum critical dynamics in a 5,000-qubit programmable spin glass,” Nature 617, pp. 61–-66 (2023). [Online]. Available: https://doi.org/10.1038/s41586-023-05867-2
- T. Honjo, T. Sonobe, K. Inaba, T. Inagaki, T. Ikuta, Y. Yamada, T. Kazama, K. Enbutsu, T. Umeki, R. Kasahara, K. Kawarabayashi, H. Takesue, “100,000-spin coherent ising machine,” Science Advances 7, eabh095 (2021). [Online]. Available: https://doi.org/10.1126/sciadv.abh0952
- D. Pierangeli, G. Marcucci, C. Conti, “Large-Scale Photonic Ising Machine by Spatial Light Modulation,” Physical Review Letters 122, 213902 (2019). [Online]. Available: https://doi.org/10.1103/PhysRevLett.122.213902
- F. Cai, S. Kumar, T. V. Vaerenbergh, X. Sheng, R. Liu, C. Li, Z. Liu, M. Foltin, S. Yu, Q. Xia, J. J. Yang, R. Beausoleil, W. D. Lu, J. P. Strachan, “Power-efficient combinatorial optimization using intrinsic noise in memristor Hopfield neural networks,” Nature Electronics 3, pp. 409–418, 2020. [Online]. Available: https://doi.org/10.1038/s41928-020-0436-6
- N. A. Aadit, A. Grimaldi, M. Carpentieri, L. Theogarajan, J. M. Martinis, G. Finocchio, K. Camsari, “Massively parallel probabilistic computing with sparse Ising machines,” Nature Electronics 5, pp. 460–468, 2022. [Online]. Available: https://doi.org/10.1038/s41928-022-00774-2
- W. Moy, I. Ahmed, P. Chiu, J. Moy, S. S. Sapatnekar, C. H. Kim, “A 1,968-node coupled ring oscillator circuit for combinatorial optimization problem solving,” Nature Electronics 5, pp. 310–317, 2022. [Online]. Available: https://doi.org/10.1038/s41928-022-00749-3
- A. Sharma, R. Afoakwa, Z. Ignjatovic, M. Huang, “Increasing Ising machine capacity with multi-chip architectures,” Proc. of Annual International Symposium on Computer Architecture (ISCA), pp. 508–521, 2022. [Online]. Available: https://doi.org/10.1145/3470496.3527414
- T. Takemoto, M. Hayashi, C. Yoshimura, M. Yamaoka, “A 2×\times×30k-Spin Multi-Chip Scalable Annealing Processor Based on a Processing-In-Memory Approach for Solving Large-Scale Combinatorial Optimization Problems,” IEEE Journal of Solid-State Circuits 55, pp. 145–156, 2019. [Online]. Available: https://doi.org/10.1109/JSSC.2019.2949230
- K. Kawamura, J. Yu, D. Okonogi, S. Jimbo, G. Inoue, A. Hyodo, Á. L. García-Anas, K. Ando, B. H. Fukushima-Kimura, R. Yasudo, T. Van Chu, M. Motomura, “Amorphica: 4-replica 512 fully connected spin 336MHz metamorphic annealer with programmable optimization strategy and compressed-spin-transfer multi-chip extension,” Proc. of IEEE International Solid-State Circuits Conference (ISSCC), pp. 42–43, 2023. [Online]. Available: https://doi.org/10.1109/ISSCC42615.2023.10067504
- S. Matsubara, M. Takatsu, T. Miyazawa, T. Shibasaki, Y. Watanabe, K. Takemoto, H. Tamura, “Digital annealer for high-speed solving of combinatorial optimization problems and its applications,” Proc. of Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 667–672, 2020. [Online]. Available: https://doi.org/10.1109/ASP-DAC47756.2020.9045100
- H. M. Waidyasooriya, M. Hariyama, “Highly-parallel FPGA accelerator for simulated quantum annealing,” IEEE Transactions on Emerging Topics in Computing 9, pp. 2019–2029, 2021. [Online]. Available: https://doi.org/10.1109/TETC.2019.2957177
- T. Okuyama, T. Sonobe, K. Kawarabayashi, M. Yamaoka, “Binary optimization by momentum annealing,” Physical Review E 100, 012111, 2019. [Online]. Available: https://doi.org/10.1103/PhysRevE.100.012111
- F. Barahona, “On the computational complexity of Ising spin glass models,” Journal of Physics A: Mathematical and General 15, pp. 3241–-3253, 1982. [Online]. Available: https://doi.org/10.1088/0305-4470/15/10/028
- S. Yoo, H. Kim, J. Kim, S. Park, J.-Y. Kim, J. Oh, “LightTrader: A Standalone High-Frequency Trading System with Deep Learning Inference Accelerators and Proactive Scheduler,” IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 1017–1030, 2023. [Online]. Available: https://doi.org/10.1109/HPCA56546.2023.10070930
- M. Fil, L. Kristoufek, “Pairs trading in cryptocurrency markets,” IEEE Access 8, pp. 172644–172651, 2020. [Online]. Available: https://doi.org/10.1109/ACCESS.2020.3024619
- B. Huang, Y. Huan, L. D. Xu, L. Zheng, Z. Zou, “Automated trading systems statistical and machine learning methods and hardware implementation: a survey,” Enterprise Information Systems 13, pp. 132–144, 2019. [Online]. Available: https://doi.org/10.1080/17517575.2018.1493145
- S. Denholm, H. Inoue, T. Takenaka, T. Becker, W. Luk, “Network-level FPGA acceleration of low latency market data feed arbitration,” IEICE Transactions on Information and Systemss E98-D, pp. 288–297, 2015. [Online]. Available: https://doi.org/10.1587/transinf.2014RCP0011
- C. Leber, B. Geib, H. Litz, “High frequency trading acceleration using FPGAs,” Proc. of IEEE International Conference on Field Programmable Logic and Applications (FPL), pp. 317–322, 2011. [Online]. Available: https://doi.org/10.1109/FPL.2011.64
- L. Malceniece, K. Malcenieks, T. J. Putniņš, Tālis, “High frequency trading and comovement in financial markets,” Journal of Financial Economics 134, pp. 381–399, 2019. [Online]. Available: https://doi.org/10.1016/j.jfineco.2018.02.015
- J. Brogaard, T. Hendershott, R. Riordan, “High-Frequency Trading and Price Discovery,” The Review of Financial Studies 27, pp. .2267-2306, 2014. [Online]. Available: https://doi.org/10.1093/rfs/hhu032
- S. Spyrou, “Herding in financial markets: a review of the literature,” Review of Behavioral Finance,5, pp. 175–194, 2013. [Online]. Available: https://doi.org/10.1108/RBF-02-2013-0009
- K. Tatsumura, R. Hidaka, M. Yamasaki, Y. Sakai, H. Goto, “A Currency Arbitrage Machine based on the Simulated Bifurcation Algorithm for Ultrafast Detection of Optimal Opportunity,” Proc. of IEEE International Symposium on Circuits and Systems (ISCAS), pp. 1–5, 2020. [Online]. Available: https://doi.org/10.1109/ISCAS45731.2020.9181114
- H. Goto, “Bifurcation-based adiabatic quantum computation with a nonlinear oscillator network,” Scientific Reports 6, 21686, 2016. [Online]. Available: https://doi.org/10.1038/srep21686
- H. Sakoe, S. Chiba, “Dynamic programming algorithm optimization for spoken word recognition,” IEEE Transactions on Acoustics, Speech, and Signal Processing 26, pp. 43–49, 1978. [Online]. Available: https://doi.org/10.1109/TASSP.1978.1163055
- G. Marsaglia, “Xorshift RNGs,” Journal of Statistical software 8, pp. 1–6, 2003. [Online]. Available: https://doi.org/10.18637/jss.v008.i14
- W. F. Sharpe, “Mutual fund performance,” The Journal of Business 39, pp. 119–138, 1966. [Online]. Available: https://www.jstor.org/stable/2351741
- D. K. Backus, A. W. Gregory, C. I. Telmer, “Accounting for forward rates in markets for foreign currency,” The Journal of Finance 48, pp. 1887–1908, 1993. [Online]. Available: https://doi.org/10.1111/j.1540-6261.1993.tb05132.x