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Statistical arbitrage in the US equities market

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Cited by:

  1. Boming Ning & Prakash Chakraborty & Kiseop Lee, 2023. "Optimal Entry and Exit with Signature in Statistical Arbitrage," Papers 2309.16008, arXiv.org, revised Mar 2024.
  2. Endres, Sylvia & Stübinger, Johannes, 2017. "Optimal trading strategies for Lévy-driven Ornstein-Uhlenbeck processes," FAU Discussion Papers in Economics 17/2017, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
  3. Khizar Qureshi & Tauhid Zaman, 2024. "Pairs Trading Using a Novel Graphical Matching Approach," Papers 2403.07998, arXiv.org.
  4. Ahmet G�nc�, 2015. "Statistical arbitrage in the Black-Scholes framework," Quantitative Finance, Taylor & Francis Journals, vol. 15(9), pages 1489-1499, September.
  5. Johannes Stübinger & Lucas Schneider, 2019. "Statistical Arbitrage with Mean-Reverting Overnight Price Gaps on High-Frequency Data of the S&P 500," JRFM, MDPI, vol. 12(2), pages 1-19, April.
  6. Christian Rein & Ludger Rüschendorf & Thorsten Schmidt, 2021. "Generalized statistical arbitrage concepts and related gain strategies," Mathematical Finance, Wiley Blackwell, vol. 31(2), pages 563-594, April.
  7. Gao, Xing & Ladley, Daniel, 2022. "Statistical arbitrage and risk contagion," Journal of Economic Dynamics and Control, Elsevier, vol. 144(C).
  8. Zheng, Li & Sun, Yuying & Wang, Shouyang, 2024. "A novel interval-based hybrid framework for crude oil price forecasting and trading," Energy Economics, Elsevier, vol. 130(C).
  9. Jorge Guijarro-Ordonez & Markus Pelger & Greg Zanotti, 2021. "Deep Learning Statistical Arbitrage," Papers 2106.04028, arXiv.org, revised Oct 2022.
  10. Muhammad Asif Khan & Masood Ahmed & József Popp & Judit Oláh, 2020. "US Policy Uncertainty and Stock Market Nexus Revisited through Dynamic ARDL Simulation and Threshold Modelling," Mathematics, MDPI, vol. 8(11), pages 1-20, November.
  11. Flori, Andrea & Regoli, Daniele, 2021. "Revealing Pairs-trading opportunities with long short-term memory networks," European Journal of Operational Research, Elsevier, vol. 295(2), pages 772-791.
  12. Kanjamapornkul, K. & Pinčák, Richard & Bartoš, Erik, 2016. "The study of Thai stock market across the 2008 financial crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 117-133.
  13. Krauss, Christopher & Do, Xuan Anh & Huck, Nicolas, 2017. "Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500," European Journal of Operational Research, Elsevier, vol. 259(2), pages 689-702.
  14. Kiseop Lee & Tim Leung & Boming Ning, 2023. "A Diversification Framework for Multiple Pairs Trading Strategies," Risks, MDPI, vol. 11(5), pages 1-18, May.
  15. Chen, Qi-an & Hu, Qingyu & Yang, Hu & Qi, Kai, 2022. "A kind of new time-weighted nonnegative lasso index-tracking model and its application," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
  16. Yerkin Kitapbayev & Tim Leung, 2017. "Optimal mean-reverting spread trading: nonlinear integral equation approach," Annals of Finance, Springer, vol. 13(2), pages 181-203, May.
  17. Raanju R. Sundararajan & Wagner Barreto‐Souza, 2023. "Student‐t stochastic volatility model with composite likelihood EM‐algorithm," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(1), pages 125-147, January.
  18. Xiang, Yun & He, Jiaxuan, 2022. "Pairs trading and asset pricing," Pacific-Basin Finance Journal, Elsevier, vol. 72(C).
  19. Marianna Brunetti & Roberta De Luca, 2023. "Pre-selection in cointegration-based pairs trading," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(5), pages 1611-1640, December.
  20. Ahmet Göncü & Erdinc Akyildirim, 2017. "Statistical Arbitrage In The Multi-Asset Black–Scholes Economy," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 12(01), pages 1-18, March.
  21. Focardi, Sergio M. & Fabozzi, Frank J. & Mitov, Ivan K., 2016. "A new approach to statistical arbitrage: Strategies based on dynamic factor models of prices and their performance," Journal of Banking & Finance, Elsevier, vol. 65(C), pages 134-155.
  22. Marco Avellaneda & Brian Healy & Andrew Papanicolaou & George Papanicolaou, 2020. "PCA for Implied Volatility Surfaces," Papers 2002.00085, arXiv.org.
  23. Matthew Clegg & Christopher Krauss, 2018. "Pairs trading with partial cointegration," Quantitative Finance, Taylor & Francis Journals, vol. 18(1), pages 121-138, January.
  24. José Cerda & Nicolás Rojas-Morales & Marcel C. Minutolo & Werner Kristjanpoller, 2022. "High Frequency and Dynamic Pairs Trading with Ant Colony Optimization," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 1251-1275, March.
  25. Huck, Nicolas, 2019. "Large data sets and machine learning: Applications to statistical arbitrage," European Journal of Operational Research, Elsevier, vol. 278(1), pages 330-342.
  26. Claudio Barbieri & Mattia Guerini & Mauro Napoletano, 2021. "The anatomy of government bond yields synchronization in the Eurozone," SciencePo Working papers Main hal-03373853, HAL.
  27. Isabel Figuerola‐Ferretti & Ioannis Paraskevopoulos & Tao Tang, 2018. "Pairs‐trading and spread persistence in the European stock market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(9), pages 998-1023, September.
  28. Stübinger, Johannes & Walter, Dominik & Knoll, Julian, 2017. "Financial market predictions with Factorization Machines: Trading the opening hour based on overnight social media data," FAU Discussion Papers in Economics 19/2017, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
  29. Natalie Packham, 2023. "Risk factor aggregation and stress testing," Papers 2310.04511, arXiv.org.
  30. Tim Leung & Kevin W. Lu, 2023. "Monte Carlo Simulation for Trading Under a L\'evy-Driven Mean-Reverting Framework," Papers 2309.05512, arXiv.org, revised Jan 2024.
  31. Ziping Zhao & Rui Zhou & Zhongju Wang & Daniel P. Palomar, 2018. "Optimal Portfolio Design for Statistical Arbitrage in Finance," Papers 1803.02974, arXiv.org.
  32. Law, K.F. & Li, W.K. & Yu, Philip L.H., 2018. "A single-stage approach for cointegration-based pairs trading," Finance Research Letters, Elsevier, vol. 26(C), pages 177-184.
  33. Schnaubelt, Matthias & Fischer, Thomas G. & Krauss, Christopher, 2018. "Separating the signal from the noise - financial machine learning for Twitter," FAU Discussion Papers in Economics 14/2018, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
  34. Ziping Zhao & Daniel P. Palomar, 2017. "Mean-Reverting Portfolio Design with Budget Constraint," Papers 1701.05016, arXiv.org.
  35. Johannes St binger & Jens Bredthauer, 2017. "Statistical Arbitrage Pairs Trading with High-frequency Data," International Journal of Economics and Financial Issues, Econjournals, vol. 7(4), pages 650-662.
  36. Jim Gatheral, 2023. "Marco Avellaneda: Mathematician and trader," Mathematical Finance, Wiley Blackwell, vol. 33(1), pages 16-18, January.
  37. Erdinc Akyildirim & Ahmet Goncu & Alper Hekimoglu & Duc Khuong Nguyen & Ahmet Sensoy, 2023. "Statistical arbitrage: factor investing approach," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(4), pages 1295-1331, December.
  38. Rama Cont & Mihai Cucuringu & Renyuan Xu & Chao Zhang, 2022. "Tail-GAN: Learning to Simulate Tail Risk Scenarios," Papers 2203.01664, arXiv.org, revised Mar 2023.
  39. Ahmet Göncü & Erdinc Akyildirim, 2016. "A stochastic model for commodity pairs trading," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1843-1857, December.
  40. Marianna Brunetti & Roberta De Luca, 2023. "Pairs trading in the index options market," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 13(1), pages 145-173, March.
  41. Guglielmo Maria Caporale & Luis Gil-Alana & Alex Plastun, 2017. "Searching for Inefficiencies in Exchange Rate Dynamics," Computational Economics, Springer;Society for Computational Economics, vol. 49(3), pages 405-432, March.
  42. Knoll, Julian & Stübinger, Johannes & Grottke, Michael, 2017. "Exploiting social media with higher-order Factorization Machines: Statistical arbitrage on high-frequency data of the S&P 500," FAU Discussion Papers in Economics 13/2017, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
  43. Krauss, Christopher, 2015. "Statistical arbitrage pairs trading strategies: Review and outlook," FAU Discussion Papers in Economics 09/2015, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
  44. Sangmin Lee & Andrew Papanicolaou, 2016. "Pairs Trading Of Two Assets With Uncertainty In Co-Integration'S Level Of Mean Reversion," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 19(08), pages 1-36, December.
  45. Marco Avellaneda, 2019. "Hierarchical PCA and Applications to Portfolio Management," Papers 1910.02310, arXiv.org.
  46. Staer, Arsenio & Sottile, Pedro, 2018. "Equivalent volume and comovement," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 143-157.
  47. Deshen Wang, 2017. "Adjustable Robust Singular Value Decomposition: Design, Analysis and Application to Finance," Data, MDPI, vol. 2(3), pages 1-15, August.
  48. Bo Liu & Lo-Bin Chang & Hélyette Geman, 2017. "Intraday pairs trading strategies on high frequency data: the case of oil companies," Quantitative Finance, Taylor & Francis Journals, vol. 17(1), pages 87-100, January.
  49. Firoozye, Nikan & Tan, Vincent & Zohren, Stefan, 2023. "Canonical portfolios: Optimal asset and signal combination," Journal of Banking & Finance, Elsevier, vol. 154(C).
  50. Anna Ananova & Rama Cont & Renyuan Xu, 2020. "Model-free Analysis of Dynamic Trading Strategies," Papers 2011.02870, arXiv.org, revised Aug 2023.
  51. Stübinger, Johannes & Endres, Sylvia, 2017. "Pairs trading with a mean-reverting jump-diffusion model on high-frequency data," FAU Discussion Papers in Economics 10/2017, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
  52. Bahman Angoshtari, 2016. "On the Market-Neutrality of Optimal Pairs-Trading Strategies," Papers 1608.08268, arXiv.org.
  53. Hengxu Lin & Dong Zhou & Weiqing Liu & Jiang Bian, 2021. "Deep Risk Model: A Deep Learning Solution for Mining Latent Risk Factors to Improve Covariance Matrix Estimation," Papers 2107.05201, arXiv.org, revised Oct 2021.
  54. Vladimír Holý & Michal Černý, 2022. "Bertram’s pairs trading strategy with bounded risk," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(2), pages 667-682, June.
  55. Andrew Papanicolaou & Hao Fu & Prashanth Krishnamurthy & Farshad Khorrami, 2023. "A Deep Neural Network Algorithm for Linear-Quadratic Portfolio Optimization with MGARCH and Small Transaction Costs," Papers 2301.10869, arXiv.org, revised Feb 2023.
  56. Fischer, Thomas & Krauss, Christopher, 2018. "Deep learning with long short-term memory networks for financial market predictions," European Journal of Operational Research, Elsevier, vol. 270(2), pages 654-669.
  57. Yerkin Kitapbayev & Tim Leung, 2018. "Mean Reversion Trading With Sequential Deadlines And Transaction Costs," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(01), pages 1-22, February.
  58. Jeff Stephenson & Bruce Vanstone & Tobias Hahn, 2021. "A Unifying Model for Statistical Arbitrage: Model Assumptions and Empirical Failure," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 943-964, December.
  59. João Frois Caldeira & Gulherme Valle Moura, 2013. "Selection of a Portfolio of Pairs Based on Cointegration: A Statistical Arbitrage Strategy," Brazilian Review of Finance, Brazilian Society of Finance, vol. 11(1), pages 49-80.
  60. Bruno Breyer Caldas & João Frois Caldeira & Guilherme Vale Moura, 2016. "Is Pairs Trading Performance Sensitive To The Methodologies?: A Comparison," Anais do XLII Encontro Nacional de Economia [Proceedings of the 42nd Brazilian Economics Meeting] 130, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
  61. Schnaubelt, Matthias & Fischer, Thomas G. & Krauss, Christopher, 2020. "Separating the signal from the noise – Financial machine learning for Twitter," Journal of Economic Dynamics and Control, Elsevier, vol. 114(C).
  62. Trent Spears & Stefan Zohren & Stephen Roberts, 2023. "On statistical arbitrage under a conditional factor model of equity returns," Papers 2309.02205, arXiv.org.
  63. Viviana Fanelli & Claudio Fontana & Francesco Rotondi, 2023. "A hidden Markov model for statistical arbitrage in international crude oil futures markets," Papers 2309.00875, arXiv.org.
  64. Raymond C. W. Leung & Yu-Man Tam, 2021. "Statistical Arbitrage Risk Premium by Machine Learning," Papers 2103.09987, arXiv.org.
  65. Paul Bilokon & David Finkelstein, 2021. "Iterated and exponentially weighted moving principal component analysis," Papers 2108.13072, arXiv.org.
  66. Shen, Keren & Yao, Jianfeng & Li, Wai Keung, 2019. "On a spiked model for large volatility matrix estimation from noisy high-frequency data," Computational Statistics & Data Analysis, Elsevier, vol. 131(C), pages 207-221.
  67. Pushpendu Ghosh & Ariel Neufeld & Jajati Keshari Sahoo, 2020. "Forecasting directional movements of stock prices for intraday trading using LSTM and random forests," Papers 2004.10178, arXiv.org, revised Jun 2021.
  68. Gianna Figá-Talamanca & Sergio Focardi & Marco Patacca, 2021. "Common dynamic factors for cryptocurrencies and multiple pair-trading statistical arbitrages," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 863-882, December.
  69. Alexander Lipton & Marcos Lopez de Prado, 2020. "A closed-form solution for optimal mean-reverting trading strategies," Papers 2003.10502, arXiv.org.
  70. Jiahe Lin & George Michailidis, 2019. "Approximate Factor Models with Strongly Correlated Idiosyncratic Errors," Papers 1912.04123, arXiv.org.
  71. Charles-Albert Lehalle & Eyal Neuman, 2019. "Incorporating signals into optimal trading," Finance and Stochastics, Springer, vol. 23(2), pages 275-311, April.
  72. Paul Bilokon & Burak Gunduz, 2023. "C++ Design Patterns for Low-latency Applications Including High-frequency Trading," Papers 2309.04259, arXiv.org.
  73. Wang, Xi & Bao, Si & Chen, Jingchao, 2017. "High-frequency stock linkage and multi-dimensional stationary processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 70-83.
  74. Jordan Mann & J. Nathan Kutz, 2016. "Dynamic mode decomposition for financial trading strategies," Quantitative Finance, Taylor & Francis Journals, vol. 16(11), pages 1643-1655, November.
  75. Ivan Letteri & Giuseppe Della Penna & Giovanni De Gasperis & Abeer Dyoub, 2022. "DNN-ForwardTesting: A New Trading Strategy Validation using Statistical Timeseries Analysis and Deep Neural Networks," Papers 2210.11532, arXiv.org.
  76. Endres, Sylvia & Stübinger, Johannes, 2018. "A flexible regime switching model with pairs trading application to the S&P 500 high-frequency stock returns," FAU Discussion Papers in Economics 07/2018, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
  77. Clegg, Matthew & Krauss, Christopher, 2016. "Pairs trading with partial cointegration," FAU Discussion Papers in Economics 05/2016, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
  78. Jorge Guijarro-Ordonez, 2019. "High-dimensional statistical arbitrage with factor models and stochastic control," Papers 1901.09309, arXiv.org, revised Jun 2021.
  79. Charalampos Stasinakis & Georgios Sermpinis & Ioannis Psaradellis & Thanos Verousis, 2016. "Krill-Herd Support Vector Regression and heterogeneous autoregressive leverage: evidence from forecasting and trading commodities," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1901-1915, December.
  80. J. C. Arismendi-Zambrano & T. Ramos-Almeida & J. C. Reboredo & M. A. Rivera-Castro, 2020. "Identifying Statistical Arbitrage in Interest Rate Markets: A Genetic Algorithm Approach," Economics Department Working Paper Series n305-20.pdf, Department of Economics, National University of Ireland - Maynooth.
  81. Tim Leung & Xin Li, 2015. "Optimal Mean Reversion Trading With Transaction Costs And Stop-Loss Exit," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 18(03), pages 1-31.
  82. Soumyadip Sarkar, 2023. "Harnessing Deep Q-Learning for Enhanced Statistical Arbitrage in High-Frequency Trading: A Comprehensive Exploration," Papers 2311.10718, arXiv.org.
  83. Sant'Anna, Leonardo Riegel & de Oliveira, Alan Delgado & Filomena, Tiago Pascoal & Caldeira, João Frois, 2020. "Solving the index tracking problem based on a convex reformulation for cointegration," Finance Research Letters, Elsevier, vol. 37(C).
  84. Sabino da Silva, Fernando A.B. & Ziegelmann, Flavio A. & Caldeira, João F., 2023. "A pairs trading strategy based on mixed copulas," The Quarterly Review of Economics and Finance, Elsevier, vol. 87(C), pages 16-34.
  85. Han, Chulwoo & He, Zhaodong & Toh, Alenson Jun Wei, 2023. "Pairs trading via unsupervised learning," European Journal of Operational Research, Elsevier, vol. 307(2), pages 929-947.
  86. Jonathan A. Batten & Cetin Ciner & Brian M. Lucey & Peter G. Szilagyi, 2013. "The structure of gold and silver spread returns," Quantitative Finance, Taylor & Francis Journals, vol. 13(4), pages 561-570, March.
  87. Boming Ning & Kiseop Lee, 2024. "Advanced Statistical Arbitrage with Reinforcement Learning," Papers 2403.12180, arXiv.org.
  88. Ariel Neufeld & Julian Sester & Daiying Yin, 2022. "Detecting data-driven robust statistical arbitrage strategies with deep neural networks," Papers 2203.03179, arXiv.org, revised Feb 2024.
  89. E. Boguslavskaya & M. Boguslavsky & D. Muravey, 2020. "Trading multiple mean reversion," Papers 2009.09816, arXiv.org.
  90. P. S. Lintilhac & A. Tourin, 2017. "Model-based pairs trading in the bitcoin markets," Quantitative Finance, Taylor & Francis Journals, vol. 17(5), pages 703-716, May.
  91. Fischer, Thomas & Krauss, Christopher, 2017. "Deep learning with long short-term memory networks for financial market predictions," FAU Discussion Papers in Economics 11/2017, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
  92. Ghosh, Pushpendu & Neufeld, Ariel & Sahoo, Jajati Keshari, 2022. "Forecasting directional movements of stock prices for intraday trading using LSTM and random forests," Finance Research Letters, Elsevier, vol. 46(PA).
  93. Karen Balladares & José Pedro Ramos-Requena & Juan Evangelista Trinidad-Segovia & Miguel Angel Sánchez-Granero, 2021. "Statistical Arbitrage in Emerging Markets: A Global Test of Efficiency," Mathematics, MDPI, vol. 9(2), pages 1-20, January.
  94. Lucas Schneider & Johannes Stübinger, 2020. "Dispersion Trading Based on the Explanatory Power of S&P 500 Stock Returns," Mathematics, MDPI, vol. 8(9), pages 1-22, September.
  95. Sant’Anna, Leonardo Riegel & Caldeira, João Frois & Filomena, Tiago Pascoal, 2020. "Lasso-based index tracking and statistical arbitrage long-short strategies," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
  96. Rama Cont & Mihai Cucuringu & Chao Zhang, 2021. "Cross-Impact of Order Flow Imbalance in Equity Markets," Papers 2112.13213, arXiv.org, revised Jun 2023.
  97. Kasper Johansson & Thomas Schmelzer & Stephen Boyd, 2024. "Finding Moving-Band Statistical Arbitrages via Convex-Concave Optimization," Papers 2402.08108, arXiv.org.
  98. Dat Thanh Tran & Juho Kanniainen & Moncef Gabbouj & Alexandros Iosifidis, 2021. "Bilinear Input Normalization for Neural Networks in Financial Forecasting," Papers 2109.00983, arXiv.org.
  99. Choi, Jungjun & Yang, Xiye, 2022. "Asymptotic properties of correlation-based principal component analysis," Journal of Econometrics, Elsevier, vol. 229(1), pages 1-18.
  100. Ha, Youngmin & Zhang, Hai, 2020. "Algorithmic trading for online portfolio selection under limited market liquidity," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1033-1051.
  101. Zhengqin Zeng & Chi-Guhn Lee, 2014. "Pairs trading: optimal thresholds and profitability," Quantitative Finance, Taylor & Francis Journals, vol. 14(11), pages 1881-1893, November.
  102. Roy Cerqueti & Viviana Fanelli, 2021. "Long memory and crude oil’s price predictability," Annals of Operations Research, Springer, vol. 299(1), pages 895-906, April.
  103. Stübinger, Johannes & Mangold, Benedikt & Krauss, Christopher, 2016. "Statistical arbitrage with vine copulas," FAU Discussion Papers in Economics 11/2016, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
  104. Stübinger, Johannes, 2018. "Statistical arbitrage with optimal causal paths on high-frequencydata of the S&P 500," FAU Discussion Papers in Economics 01/2018, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
  105. Ahmet Göncü & Erdinç Akyıldırım, 2016. "Statistical Arbitrage with Pairs Trading," International Review of Finance, International Review of Finance Ltd., vol. 16(2), pages 307-319, June.
  106. Vladim'ir Hol'y & Petra Tomanov'a, 2018. "Estimation of Ornstein-Uhlenbeck Process Using Ultra-High-Frequency Data with Application to Intraday Pairs Trading Strategy," Papers 1811.09312, arXiv.org, revised Jul 2022.
  107. Sergey Nasekin & Wolfgang Karl Hardle, 2020. "Model-driven statistical arbitrage on LETF option markets," Papers 2009.09713, arXiv.org.
  108. Schnaubelt, Matthias & Seifert, Oleg, 2020. "Valuation ratios, surprises, uncertainty or sentiment: How does financial machine learning predict returns from earnings announcements?," FAU Discussion Papers in Economics 04/2020, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
  109. Elisabeth Leoff & Leonie Ruderer & Jörn Sass, 2022. "Signal-to-noise matrix and model reduction in continuous-time hidden Markov models," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 95(2), pages 327-359, April.
  110. Jifei Wang & Lingjing Wang, 2019. "Residual Switching Network for Portfolio Optimization," Papers 1910.07564, arXiv.org.
  111. Fernando Caneo & Werner Kristjanpoller, 2021. "Improving statistical arbitrage investment strategy: Evidence from Latin American stock markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4424-4440, July.
  112. T. N. Li & A. Papanicolaou, 2019. "Statistical Arbitrage for Multiple Co-Integrated Stocks," Papers 1908.02164, arXiv.org, revised Feb 2022.
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