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ORCID3rd ICAIF 2022: New York, NY, USA
- Daniele Magazzeni, Senthil Kumar, Rahul Savani, Renyuan Xu, Carmine Ventre, Blanka Horvath, Ruimeng Hu, Tucker Balch, Francesca Toni:
3rd ACM International Conference on AI in Finance, ICAIF 2022, New York, NY, USA, November 2-4, 2022. ACM 2022, ISBN 978-1-4503-9376-8
Blockchain
- Christopher Felder, Johannes Seemüller:
Intelligent Inventory Management for Cryptocurrency Brokers. 1-8 - Zhou Fan, Francisco J. Marmolejo Cossío, Ben Altschuler, He Sun, Xintong Wang, David C. Parkes:
Differential Liquidity Provision in Uniswap v3 and Implications for Contract Design✱. 9-17 - Christina Ovezik, Aggelos Kiayias:
Decentralization Analysis of Pooling Behavior in Cardano Proof of Stake. 18-26 - Pin Ni
, Qiao Yuan, Raad Khraishi, Ramin Okhrati, Aldo Lipani, Francesca Medda:
Eigenvector-based Graph Neural Network Embeddings and Trust Rating Prediction in Bitcoin Networks. 27-35
Causality
- Wei Zhang, Brian Barr, John Paisley:
An Interpretable Deep Classifier for Counterfactual Generation. 36-43 - Wei Zhang, Brian Barr, John Paisley:
Understanding Counterfactual Generation using Maximum Mean Discrepancy. 44-52
Deep Learning
- Anastasios Petropoulos, Vasilis Siakoulis, Konstantinos P. Panousis, Loukas Papadoulas, Sotirios Chatzis:
A Deep Learning Approach for Dynamic Balance Sheet Stress Testing. 53-61 - Yichen Feng, Ming Min, Jean-Pierre Fouque:
Deep Learning for Systemic Risk Measures. 62-69 - Dangxing Chen, Weicheng Ye:
Monotonic Neural Additive Models: Pursuing Regulated Machine Learning Models for Credit Scoring. 70-78 - Tuna Tuncer, Uygar Kaya, Emre Sefer, Onur Alacam, Tugcan Hoser:
Asset Price and Direction Prediction via Deep 2D Transformer and Convolutional Neural Networks. 79-86 - Dimitrios Vamvourellis, Máté Tóth, Dhruv Desai, Dhagash Mehta, Stefano Pasquali:
Learning Mutual Fund Categorization using Natural Language Processing. 87-95 - Andrew Alden, Carmine Ventre, Blanka Horvath, Gordon Lee:
Model-Agnostic Pricing of Exotic Derivatives Using Signatures. 96-104
Federated Learning
- Marco Schreyer, Timur Sattarov, Damian Borth:
Federated and Privacy-Preserving Learning of Accounting Data in Financial Statement Audits. 105-113 - David Byrd, Vaikkunth Mugunthan, Antigoni Polychroniadou, Tucker Balch:
Collusion Resistant Federated Learning with Oblivious Distributed Differential Privacy. 114-122
Fraud
- Anubha Pandey, Alekhya Bhatraju, Shiv Markam, Deepak Bhatt:
Adversarial Fraud Generation for Improved Detection. 123-129 - Mário Cardoso, Pedro Saleiro, Pedro Bizarro:
LaundroGraph: Self-Supervised Graph Representation Learning for Anti-Money Laundering. 130-138 - David Byrd:
Learning Not to Spoof. 139-147 - Awanish Kumar, Soumyadeep Ghosh, Janu Verma:
Guided Self-Training based Semi-Supervised Learning for Fraud Detection. 148-155
Graph Neural Networks
- Qinkai Chen, Christian-Yann Robert:
Multivariate Realized Volatility Forecasting with Graph Neural Network. 156-164 - Yue Leng, Evangelia D. Skiani, William Peak, Ewan Mackie, Fuyuan Li, Thwisha Charvi, Jennifer Law, Kieran Daly:
Customer-Category Interest Model: A Graph-Based Collaborative Filtering Model with Applications in Finance. 165-173
Interpretability
- Ricardo Müller, Marco Schreyer, Timur Sattarov, Damian Borth:
RESHAPE: Explaining Accounting Anomalies in Financial Statement Audits by enhancing SHapley Additive exPlanations. 174-182 - Shubhi Asthana, Ruchi Mahindru:
Mapping of Financial Services datasets using Human-in-the-Loop. 183-191 - Sahar Mazloom, Antigoni Polychroniadou, Tucker Balch:
Addressing Extreme Market Responses Using Secure Aggregation. 192-198
Market Making
- Bingyan Han:
Can maker-taker fees prevent algorithmic cooperation in market making? 199-206 - Jacobo Roa-Vicens, Yao Lei Xu, Ricardo Silva, Danilo P. Mandic:
Graph and tensor-train recurrent neural networks for high-dimensional models of limit order books. 207-213 - Joseph Jerome, Gregory Palmer, Rahul Savani:
Market Making with Scaled Beta Policies. 214-222 - Guhyuk Chung, Munki Chung, Yongjae Lee, Woo Chang Kim:
Market Making under Order Stacking Framework: A Deep Reinforcement Learning Approach. 223-231
Mechanism Design
- Kshama Dwarakanath, Svitlana Vyetrenko, Tucker Balch:
Equitable Marketplace Mechanism Design. 232-239 - Ji Qi, Carmine Ventre:
Incentivising Market Making in Financial Markets. 240-248
Portfolio Selection
- Eric Luxenberg, Stephen P. Boyd, Misha van Beek, Wen Cao, Mykel J. Kochenderfer:
Strategic Asset Allocation with Illiquid Alternatives. 249-256 - Yiming Peng, Vadim Linetsky:
Portfolio Selection: A Statistical Learning Approach. 257-263 - Tina Ruiwen Wang, Jithin Pradeep, Jerry Zikun Chen:
Objective Driven Portfolio Construction Using Reinforcement Learning. 264-272 - Ziyin Liu, Kentaro Minami, Kentaro Imajo:
Theoretically Motivated Data Augmentation and Regularization for Portfolio Construction. 273-281
Prediction
- Ajim Uddin, Xinyuan Tao, Chia-Ching Chou, Dantong Yu:
Machine Learning for Earnings Prediction: A Nonlinear Tensor Approach for Data Integration and Completion. 282-290 - Dan Zhou, Ajim Uddin, Zuofeng Shang, Cheickna Sylla, Dantong Yu:
Core Matrix Regression and Prediction with Regularization. 291-299 - Enguerrand Horel, Kay Giesecke:
Computationally Efficient Feature Significance and Importance for Predictive Models. 300-307 - Dan Zhou, Ajim Uddin, Xinyuan Tao, Zuofeng Shang, Dantong Yu:
Temporal Bipartite Graph Neural Networks for Bond Prediction. 308-316 - Alexandre Boulenger, Davide Liu, George Philippe Farajalla:
Sequential Banking Products Recommendation and User Profiling in One Go. 317-324
Reinforcement Learning
- Raad Khraishi, Ramin Okhrati:
Offline Deep Reinforcement Learning for Dynamic Pricing of Consumer Credit. 325-333 - Jingwei Ji, Renyuan Xu, Ruihao Zhu:
Risk-Aware Linear Bandits with Application in Smart Order Routing. 334-342 - Chunli Liu, Carmine Ventre, Maria Polukarov:
Synthetic Data Augmentation for Deep Reinforcement Learning in Financial Trading. 343-351 - Martino Bernasconi, Stefano Martino, Edoardo Vittori, Francesco Trovò, Marcello Restelli:
Dark-Pool Smart Order Routing: a Combinatorial Multi-armed Bandit Approach. 352-360 - Phillip Murray, Ben Wood, Hans Buehler, Magnus Wiese, Mikko Pakkanen:
Deep Hedging: Continuous Reinforcement Learning for Hedging of General Portfolios across Multiple Risk Aversions. 361-368 - Jimin Lin, Andrea Angiuli, Nils Detering, Jean-Pierre Fouque, Mathieu Laurière:
Reinforcement Learning for Intra-and-Inter-Bank Borrowing and Lending Mean Field Control Game. 369-376 - Yilie Huang, Yanwei Jia, Xun Yu Zhou:
Achieving Mean-Variance Efficiency by Continuous-Time Reinforcement Learning. 377-385 - Di Chen, Yada Zhu, Miao Liu, Jianbo Li:
Cost-Efficient Reinforcement Learning for Optimal Trade Execution on Dynamic Market Environment. 386-393 - Antonio Riva, Lorenzo Bisi, Pierre Liotet, Luca Sabbioni, Edoardo Vittori, Marco Pinciroli, Michele Trapletti, Marcello Restelli:
Addressing Non-Stationarity in FX Trading with Online Model Selection of Offline RL Experts. 394-402
Similarity
- Kevin Huynh, Gregor Lenhard:
Asymmetric Autoencoders for Factor-Based Covariance Matrix Estimation. 403-410 - Jerinsh Jeyapaulraj, Dhruv Desai, Dhagash Mehta, Peter Chu, Stefano Pasquali, Philip Sommer:
Supervised similarity learning for corporate bonds using Random Forest proximities. 411-419 - Gaurav Oberoi, Pranav Poduval, Karamjit Singh, Sangam Verma, Pranay Gupta:
CaPE: Category Preserving Embeddings for Similarity-Search in Financial Graphs. 420-427
Simulation and Calibration
- Andrea Coletta, Aymeric Moulin, Svitlana Vyetrenko, Tucker Balch:
Learning to simulate realistic limit order book markets from data as a World Agent. 428-436 - Yuanlu Bai, Henry Lam, Tucker Balch, Svitlana Vyetrenko:
Efficient Calibration of Multi-Agent Simulation Models from Output Series with Bayesian Optimization. 437-445 - Felix Prenzel, Rama Cont, Mihai Cucuringu, Jonathan Kochems:
Dynamic Calibration of Order Flow Models with Generative Adversarial Networks. 446-453
Time Series
- Gabriel Francisco Borrageiro, Nick Firoozye, Paolo Barucca:
Sequential asset ranking in nonstationary time series. 454-462 - Yuanrong Wang, Tomaso Aste:
Network Filtering of Spatial-temporal GNN for Multivariate Time-series Prediction. 463-470 - Yanqing Ma, Carmine Ventre, Maria Polukarov:
Denoised Labels for Financial Time Series Data via Self-Supervised Learning. 471-479 - Shibal Ibrahim, Wenyu Chen, Yada Zhu, Pin-Yu Chen, Yang Zhang, Rahul Mazumder:
Knowledge Graph Guided Simultaneous Forecasting and Network Learning for Multivariate Financial Time Series. 480-488 - Yousef El-Laham, Svitlana Vyetrenko:
StyleTime: Style Transfer for Synthetic Time Series Generation. 489-496 - Kshama Dwarakanath, Danial Dervovic, Peyman Tavallali, Svitlana Vyetrenko, Tucker Balch:
Optimal Stopping with Gaussian Processes. 497-505 - Mohsen Ghassemi, Niccolò Dalmasso, Simran Lamba, Vamsi K. Potluru, Tucker Balch, Sameena Shah, Manuela Veloso:
Online Learning for Mixture of Multivariate Hawkes Processes. 506-513
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