• news sentiment propagation in financial networks (US Equity)
• a deep learning framework for asset pricing with heterogeneous data sources (news and technical factors) (Chinese Equity)
• lead-lag detection and network clustering for nonlinear multivariate time series (US equity)
• cross-asset models (CAM) for learning stock interactions; high-dimensional setting (Chinese Equity)
• times series price and limit order book simulation with GANs (US/EU Equity)
• factor models for limit order flow, conditional order flow imbalance, cross-impact/network effects (nowcasting, forecasting) (US Equity)
• analysis of option volume for predicting spot market returns (US Options/Equity)
• analysis and modelling of client order flow in limit order markets
• graph-based asset pricing; fundamentals and trade flow data (US Equity)
• microstructure and network effects in cryptocurrency markets (top 14 most liquid crypto exchanges)
• clustering and change-point detection in time series and correlation networks
• dimensionality reduction and cross-impact for fundamentals data for short/medium term forecasts
• determinants of cancellation behaviour in limit order books
• classification and modelling of non-bank financial institutions via SEC filings
• probabilistic forecasting with GANs
• forecasting volatility and co-volatility via neural networks
• co-jumping behaviour in financial time series networks

Publications and preprints (finance related)

1. Marcos Tapia Costa, Mihai Cucuringu, Guy Nason, Higher-Order Dynamic Network Linear Models for Covariance Forecasting, SSRN, [BibTeX] (2025)
2. Zichuan Guo, Mihai Cucuringu, Alexander Shestopaloff, Generalized Factor Neural Network Model for High-dimensional Regression, SSRN, [BibTeX] (2025)
3. Jakob Albers, Mihai Cucuringu, Sam Howison, Alexander Shestopaloff, To Make, or to Take, That Is the Question: Impact of LOB Mechanics on Natural Trading Strategies, SSRN, [BibTeX] (2024)
4. Emmanuel Djanga, Mihai Cucuringu, Chao Zhang, Cryptocurrency Volatility Forecasting with Applications in Trading, SSRN, [BibTeX] (2024)
5. Nail Khelifa, Jerome Allier, Mihai Cucuringu, Cluster-driven Hierarchical Representation of Large Asset Universes for Optimal Portfolio Construction, ICAIF 2024, Association for Computing Machinery, New York, NY, USA (2024), Best Paper Honorary Mention, [BibTeX] (2024)
6. Kang Li, Mihai Cucuringu, Leandro Sánchez-Betancourt, Timon Willi, Mixtures of Experts for Scaling up Neural Networks in Order Execution, ICAIF 2024, Association for Computing Machinery, New York, NY, USA (2024), [BibTeX] (2024)
7. Anastasia Mantziou, Kerstin Hotte, Mihai Cucuringu, Gesine Reinert, GDP nowcasting with large-scale inter-industry payment data in real time - A network approach, arXiv, [BibTeX] (2024)
8. Nikolas Michael, Mihai Cucuringu, Sam Howison, A GCN-LSTM Approach For ES-Mini And VX Futures Forecasting, SSRN [BibTeX] (2024)
9. Brendan Martin, Francesco Sanna Passino, Mihai Cucuringu, Alessandra Luati, NIRVAR: Network Informed Restricted Vector Autoregression, arXiv, [Code (GitHub)] [BibTeX] (2024)
10. Daniel Cunha Oliveira, Yutong Lu, Xi Lin, Mihai Cucuringu, Andre Fujita, Causality-Inspired Models for Financial Time Series Forecasting, arXiv, [BibTeX] (2024)
11. Chang Luo, Tiejun Ma, Mihai Cucuringu, Spatial-Temporal Stock Movement Prediction and Portfolio Selection based on the Semantic Company Relationship Graph, SSRN [BibTeX] (2024)
12. Jakob Albers, Mihai Cucuringu, Sam Howison, Alexander Shestopaloff, The Good, the Bad, and Latency: Exploratory Trading on Bybit and Binance, SSRN [BibTeX] (2024)
13. Nikolas Michael, Mihai Cucuringu, Sam Howison, Options-driven Volatility Forecasting, SSRN (2024)
14. Álvaro Cartea, Mihai Cucuringu, Mark Jennings, Chao Zhang, A Similarity-based Approach to Covariance Forecasting, SSRN (2023)
15. Álvaro Cartea, Mihai Cucuringu, Qi Jin, Detecting Lead-Lag Relationships in Stock Returns and Portfolio Strategies, SSRN [BibTeX] (2023)
16. Emmanuel Djanga, Mihai Cucuringu, and Chao Zhang, Cryptocurrency volatility forecasting using commonality in intraday volatility, ICAIF 2023, Association for Computing Machinery, New York, NY, USA (2023)
17. Bogdan Sitaru, Anisoara Calinescu, Mihai Cucuringu, Order Flow Decomposition for Price Impact Analysis in Equity Limit Order Books, ICAIF 2023, Association for Computing Machinery, New York, NY, USA, SSRN, (2023)
18. Yichi Zhang, Mihai Cucuringu, Alexander Y. Shestopaloff, Stefan Zohren, Dynamic Time Warping for Lead-Lag Relationships in Lagged Multi-Factor Models, ICAIF 2023, Association for Computing Machinery, New York, NY, USA, SSRN, (2023)
19. Álvaro Cartea, Mihai Cucuringu, Qi Jin, Correlation Matrix Clustering for Statistical Arbitrage Portfolios, ICAIF 2023, Association for Computing Machinery, New York, NY, USA, SSRN [BibTeX] (2023)
20. Edward Turner, Mihai Cucuringu, Graph Denoising Networks: A Deep Learning Framework for Equity Portfolio Construction, ICAIF 2023, Association for Computing Machinery, New York, NY, USA, 193--201 [BibTeX] (2023)
21. Danni Shi, Jan-Peter Calliess, Mihai Cucuringu Multireference Alignment for Lead-Lag Detection in Multivariate Time Series and Equity Trading, ICAIF 2023, Association for Computing Machinery, New York, NY, USA, SSRN, (2023)
22. Rama Cont, Mihai Cucuringu, Jonathan Kochems, Felix Prenzel, Limit Order Book Simulation with Generative Adversarial Networks, SSRN [BibTeX] (2023)
23. Anastasia Mantziou, Mihai Cucuringu, Victor Meirinhos, Gesine Reinert, The GNAR-edge model: A network autoregressive model for networks with time-varying edge weights, Journal of Complex Networks, Volume 11, Issue 6 arXiv, [BibTeX] (2023)
24. Deborah Miori, Mihai Cucuringu, DeFi: Modeling and Forecasting Trading Volume on Uniswap v3 Liquidity Pools, SSRN (2023)
25. Yichi Zhang, Mihai Cucuringu, Alexander Y. Shestopaloff, Stefan Zohren, Robust Detection of Lead-Lag Relationships in Lagged Multi-Factor Models (SSRN), (arXiv) (2023)
26. Nikolas Michael, Mihai Cucuringu, Sam Howison, OFTER: An Online Pipeline for Time Series Forecasting, SSRN (2023)
27. Chao Zhang, Xingyue Pu, Mihai Cucuringu, Xiaowen Dong, Forecasting Realized Volatility with Spillover Effects: Perspectives from Graph Neural Networks, SSRN, to appear in International Journal of Forecasting (2023)
28. Yutong Lu, Gesine Reinert, Mihai Cucuringu, Co-trading networks for modeling dynamic interdependency structures and estimating high-dimensional covariances in US equity markets, SSRN, (arXiv) (2023)
29. Milena Vuletić, Felix Prenzel, Mihai Cucuringu, Fin-GAN: Forecasting and Classifying Financial Time Series via Generative Adversarial Networks, SSRN, Quantitative Finance, [code FinGAN], [BibTeX] (2024)
30. Deborah Miori, Mihai Cucuringu, Clustering Uniswap v3 traders from their activity on multiple liquidity pools, via novel graph embeddings, Digital Finance 6, 113--143, SSRN, [BibTeX] (2024)
31. Qiong Wu, Jian Li, Zhenming Liu, Yanhua Li, Mihai Cucuringu, Symphony in the Latent Space: Provably Integrating High-dimensional Techniques with Non-linear Machine Learning Models, Proceedings of the AAAI Conference on Artificial Intelligence 2023, [BibTeX] (2022)
32. Chao Zhang, Xingyue Pu, Mihai Cucuringu, Xiaowen Dong, Graph-based Methods for Forecasting Realized Covariances, Journal of Financial Econometrics, nbae026, SSRN, [BibTeX] (2024)
33. Yutong Lu, Gesine Reinert, Mihai Cucuringu, Trade Co-occurrence,Trade Flow Decomposition, and Conditional Order Imbalance in Equity Markets, (arXiv), Quantitative Finance, 24(6), 779--809, [BibTeX] (2024)
34. Deborah Miori, Mihai Cucuringu, Returns-Driven Macro Regimes and Characteristic Lead-Lag Behaviour between Asset Classes, (arXiv) ICAIF (2022)
35. Felix Prenzel, Rama Cont, Mihai Cucuringu, Jonathan Kochems, Dynamic Calibration of Order Flow Models with Generative Adversarial Networks, ICAIF '22: 3rd ACM International Conference on AI in Finance, November 2022, pages 446--453 (Best Paper Award) (2022)
36. Deborah Miori, Mihai Cucuringu, Securities and Exchange Commission Form 13F Holdings Report: statistical investigation of trading imbalances and profitability analysis, Journal of Investment Strategies, Volume 12, Number 4 (arXiv) (2023)
37. Deborah Sulem, Henry Kenlay, Mihai Cucuringu, Xiaowen Dong, Graph similarity learning for change-point detection in dynamic networks, Machine Learning 2023, (arXiv) [BibTeX] (2023)
38. Rama Cont, Mihai Cucuringu, Chao Zhang, Renyuan Xu, Tail-GAN: Nonparametric Scenario Generation for Tail Risk Estimation (arXiv), SSRN, [Code (GitHub)] (2022)
39. Chao Zhang, Yihuang Zhang, Mihai Cucuringu, Zhongmin Qian, Volatility forecasting with machine learning and intraday commonality, to appear in Journal of Financial Econometrics (2022)
40. Nikolas Michael, Mihai Cucuringu, Sam Howison, Option Volume Imbalance as a predictor for equity market returns, arXiv 2201.09319 (2022)
41. Rama Cont, Mihai Cucuringu, Chao Zhang, Cross-impact of order flow imbalance in equity markets Quantitative Finance, 0: 1-21 (2023)
42. Stefanos Bennett, Mihai Cucuringu and Gesine Reinert, Lead-lag detection and network clustering for multivariate time series with an application to the US equity market, Machine Learning 111, 4497-4538 (2022); [BibTeX] (2022). Workshop version: KDD Workshop on mining and learning from time series (2021) KDD MiLeTs (2021)
43. Rama Cont, Mihai Cucuringu, Vacslav Glukhov, Felix Prenzel, Analysis and modeling of client order flow in limit order markets, Quantitative Finance, 23:2, 187-205, [BibTeX] (2023)
44. Chao Zhang, Zihao Zhang, Mihai Cucuringu, Stefan Zohren, A Universal End-to-End Approach to Portfolio Optimization via Deep Learning, arXiv 2111.09170 (2021)
45. J. Albers, M. Cucuringu, S. Howison, A. Y. Shestopaloff, Fragmentation, Price Formation, and Cross-Impact in Bitcoin Markets, Applied Mathematical Finance, 28:5, 395-448, (arXiv), [BibTex] (2021)
46. Qiong Wu, Christopher G. Brinton, Zheng Zhang, Andrea Pizzoferrato, Zhenming Liu, Mihai Cucuringu, Equity2Vec: End-to-end Deep Learning Framework for Cross-sectional Asset Pricing, International Conference on AI in Finance (ICAIF 2021), [BibTex] (2021)

© 2023 Mihai Cucuringu