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ORCID4th ICAIF 2023: Brooklyn, NY, USA
- 4th ACM International Conference on AI in Finance, ICAIF 2023, Brooklyn, NY, USA, November 27-29, 2023. ACM 2023
- Seyoung Kim
, Joohwan Hong, Yongjae Lee:
A GANs-Based Approach for Stock Price Anomaly Detection and Investment Risk Management. 1-9 - Haochen Li, Maria Polukarov, Carmine Ventre:
Detecting Financial Market Manipulation with Statistical Physics Tools. 1 - Fadi Hamad, Shinpei Nakamura-Sakai, Saheed Obitayo, Vamsi K. Potluru:
A supervised generative optimization approach for tabular data. 10-18 - Masanori Hirano, Kentaro Minami, Kentaro Imajo:
Adversarial Deep Hedging: Learning to Hedge without Price Process Modeling. 19-26 - Andrea Coletta, Joseph Jerome, Rahul Savani, Svitlana Vyetrenko:
Conditional Generators for Limit Order Book Environments: Explainability, Challenges, and Robustness. 27-35 - He Sun, Zhun Deng, Hui Chen, David C. Parkes:
Decision-Aware Conditional GANs for Time Series Data. 36-45 - Namid R. Stillman, Rory Baggott, Justin Lyon, Jianfei Zhang, Dingqiu Zhu, Tao Chen, Perukrishnen Vytelingum:
Deep Calibration of Market Simulations using Neural Density Estimators and Embedding Networks. 46-54 - Zikai Wei, Bo Dai, Dahua Lin:
E2EAI: End-to-End Deep Learning Framework for Active Investing. 55-63 - Timur Sattarov, Marco Schreyer, Damian Borth:
FinDiff: Diffusion Models for Financial Tabular Data Generation. 64-72 - Zhen Zeng, William Watson, Nicole Cho, Saba Rahimi, Shayleen Reynolds, Tucker Balch, Manuela Veloso:
FlowMind: Automatic Workflow Generation with LLMs. 73-81 - Zhen Zeng, Rachneet Kaur, Suchetha Siddagangappa, Tucker Balch, Manuela Veloso:
From Pixels to Predictions: Spectrogram and Vision Transformer for Better Time Series Forecasting. 82-90 - Peer Nagy, Sascha Frey, Silvia Sapora, Kang Li, Anisoara Calinescu, Stefan Zohren, Jakob N. Foerster:
Generative AI for End-to-End Limit Order Book Modelling: A Token-Level Autoregressive Generative Model of Message Flow Using a Deep State Space Network. 91-99 - Kausik Lakkaraju, Sara E. Jones, Sai Krishna Revanth Vuruma, Vishal Pallagani, Bharath C. Muppasani, Biplav Srivastava:
LLMs for Financial Advisement: A Fairness and Efficacy Study in Personal Decision Making. 100-107 - Zhiyu Cao, Zihan Chen, Prerna Mishra, Hamed Amini, Zachary Feinstein:
Modeling Inverse Demand Function with Explainable Dual Neural Networks. 108-115 - Betul Seyhan, Emre Sefer:
NFT Primary Sale Price and Secondary Sale Prediction via Deep Learning. 116-123 - Anh Tong, Thanh Nguyen-Tang, Dongeun Lee, Toan M. Tran, Jaesik Choi:
SigFormer: Signature Transformers for Deep Hedging. 124-132 - Ricardo Ribeiro Pereira, Jacopo Bono, João Tiago Ascensão, David Aparício, Pedro Ribeiro, Pedro Bizarro:
The GANfather: Controllable generation of malicious activity to improve defence systems. 133-140 - Piotr Skalski, David Sutton, Stuart Burrell, Iker Perez, Jason Wong:
Towards a Foundation Purchasing Model: Pretrained Generative Autoregression on Transaction Sequences. 141-149 - Francois Buet-Golfouse, Islam Utyagulov, Parth Pahwa, Peter Hill:
Turbo-Charging Deep Learning Methods for Partial Differential Equations. 150-158 - Ruslan Tepelyan, Achintya Gopal:
Generative Machine Learning for Multivariate Equity Returns. 159-166 - Shibal Ibrahim, Max Tell, Rahul Mazumder:
Dyn-GWN: Time-Series Forecasting using Time-varying Graphs with Applications to Finance and Traffic Prediction. 167-175 - Jacopo Bono, Ahmad Naser Eddin, David Aparício, Hugo Ferreira, João Tiago Ascensão, Pedro Ribeiro, Pedro Bizarro:
From random-walks to graph-sprints: a low-latency node embedding framework on continuous-time dynamic graphs. 176-184 - Soumava Ghosh, Ravi Anand, Tanmoy Bhowmik, Siddhanth Chandrashekhar:
GoSage: Heterogeneous Graph Neural Network Using Hierarchical Attention for Collusion Fraud Detection. 185-192 - Edward Turner, Mihai Cucuringu:
Graph Denoising Networks: A Deep Learning Framework for Equity Portfolio Construction. 193-201 - Pritam Kumar Nath, Govind Waghmare, Nikhil Tumbde, Nitish Kumar, Siddhartha Asthana:
Learning Temporal Representations of Bipartite Financial Graphs. 202-209 - Lingxiao Zhao, Maria Polukarov, Carmine Ventre:
Liquidity and Solvency Risks in Financial Networks. 210-218 - Shuaicheng Zhang, Yada Zhu, Dawei Zhou:
TGEditor: Task-Guided Graph Editing for Augmenting Temporal Financial Transaction Networks. 219-226 - Hamed Amini, Zhongyuan Cao, Agnès Sulem:
The Default Cascade Process in Stochastic Financial Networks. 227-234 - Siqi Jiang, Ajim Uddin, Zhi Wei, Dantong Yu:
The Network of Mutual Funds: A Dynamic Heterogeneous Graph Neural Network for Estimating Mutual Funds Performance. 235-243 - Ana Clara Teixeira, Hamed Yazdanpanah, Aline Pezente, Mohammad M. Ghassemi:
Bayesian Networks Improve Out-of-Distribution Calibration for Agribusiness Delinquency Risk Assessment. 244-252 - Nelson Vadori:
Calibration of Derivative Pricing Models: a Multi-Agent Reinforcement Learning Perspective. 253-260 - Roberto Daluiso, Marco Pinciroli, Michele Trapletti, Edoardo Vittori:
CVA Hedging with Reinforcement Learning. 261-269 - Kang Gao, Stephen Weston, Perukrishnen Vytelingum, Namid R. Stillman, Wayne Luk, Ce Guo:
Deeper Hedging: A New Agent-based Model for Effective Deep Hedging. 270-278 - Xueying Ding, Nikita Seleznev, Senthil Kumar, C. Bayan Bruss, Leman Akoglu:
From Detection to Action: a Human-in-the-loop Toolkit for Anomaly Reasoning and Management. 279-287 - Joel Dyer, Arnau Quera-Bofarull, Ayush Chopra, J. Doyne Farmer, Anisoara Calinescu, Michael J. Wooldridge:
Gradient-Assisted Calibration for Financial Agent-Based Models. 288-296 - Anubha Pandey, Himanshu Chaudhary, Alekhya Bhatraju, Deepak Bhatt, Maneet Singh:
Improving the Robustness of Financial Models through Identification of the Minimal Vulnerable Feature Set. 297-304 - Aldo Glielmo, Marco Favorito, Debmallya Chanda, Domenico Delli Gatti:
Reinforcement Learning for Combining Search Methods in the Calibration of Economic ABMs. 305-313 - Jesse S. Ghashti, John R. J. Thompson:
The complexity of financial wellness: examining survey patterns via kernel metric learning and clustering of mixed-type data. 314-322 - Jinan Zou, Yanxi Liu, Yuankai Qi, Haiyao Cao, Lingqiao Liu, Javen Qinfeng Shi:
A Generative Approach for Comprehensive Financial Event Extraction at the Document Level. 323-330 - Zixuan Yuan, Yada Zhu, Wei Zhang, Hui Xiong:
Earnings Call Analysis Using a Sparse Attention Based Encoder and Multi-Source Counterfactual Augmentation. 331-339 - Ana Clara Teixeira, Vaishali Marar, Hamed Yazdanpanah, Aline Pezente, Mohammad M. Ghassemi:
Enhancing Credit Risk Reports Generation using LLMs: An Integration of Bayesian Networks and Labeled Guide Prompting. 340-348 - Boyu Zhang, Hongyang Yang, Tianyu Zhou, Ali Babar, Xiao-Yang Liu:
Enhancing Financial Sentiment Analysis via Retrieval Augmented Large Language Models. 349-356 - Sandro Gössi, Ziwei Chen, Wonseong Kim, Bernhard Bermeitinger, Siegfried Handschuh:
FinBERT-FOMC: Fine-Tuned FinBERT Model with Sentiment Focus Method for Enhancing Sentiment Analysis of FOMC Minutes. 357-364 - Jiseon Yun, Jae Eui Sohn, Sunghyon Kyeong:
Fine-Tuning Pretrained Language Models to Enhance Dialogue Summarization in Customer Service Centers. 365-373 - Yinheng Li, Shaofei Wang, Han Ding, Hang Chen:
Large Language Models in Finance: A Survey. 374-382 - Seonmi Kim, Seyoung Kim, Yejin Kim, Junpyo Park, Seongjin Kim, Moolkyeol Kim, Chang Hwan Sung, Joohwan Hong, Yongjae Lee:
LLMs Analyzing the Analysts: Do BERT and GPT Extract More Value from Financial Analyst Reports? 383-391 - Lefteris Loukas, Ilias Stogiannidis, Odysseas Diamantopoulos, Prodromos Malakasiotis, Stavros Vassos:
Making LLMs Worth Every Penny: Resource-Limited Text Classification in Banking. 392-400 - Andy Chung, Kumiko Tanaka-Ishii:
Predictability of Post-Earnings Announcement Drift with Textual and Contextual Factors of Earnings Calls. 401-408 - Dan Zhou, Ajim Uddin, Zuofeng Shang, Cheickna Sylla, Xinyuan Tao, Dantong Yu:
A Fast Non-Linear Coupled Tensor Completion Algorithm for Financial Data Integration and Imputation. 409-417 - Xin Du, Kai Moriyama, Kumiko Tanaka-Ishii:
Co-Training Realized Volatility Prediction Model with Neural Distributional Transformation. 418-426 - Omkar Nabar, Gautam Shroff:
Conservative Predictions on Noisy Financial Data. 427-435 - Emmanuel Djanga, Mihai Cucuringu, Chao Zhang:
Cryptocurrency volatility forecasting using commonality in intraday volatility. 436-444 - Wenyu Chen, Riade Benbaki, Yada Zhu, Rahul Mazumder:
Dynamic Covariance Estimation under Structural Assumptions via a Joint Optimization Approach. 445-453 - Yichi Zhang, Mihai Cucuringu, Alexander Y. Shestopaloff, Stefan Zohren:
Dynamic Time Warping for Lead-Lag Relationship Detection in Lagged Multi-Factor Models. 454-462 - Niccolò Dalmasso, Renbo Zhao, Mohsen Ghassemi, Vamsi K. Potluru, Tucker Balch, Manuela Veloso:
Efficient Event Series Data Modeling via First-Order Constrained Optimization. 463-471 - Defu Cao, Yixiang Zheng, Parisa Hassanzadeh, Simran Lamba, Xiaomo Liu, Yan Liu:
Large Scale Financial Time Series Forecasting with Multi-faceted Model. 472-480 - Francois Buet-Golfouse, Nicholas William David Martin:
Lifting Volterra Diffusions via Kernel Decomposition. 481-489 - Andy Chung, Kumiko Tanaka-Ishii:
Modeling Momentum Spillover with Economic Links Discovered from Financial Documents. 490-497 - Tom Bamford, Andrea Coletta, Elizabeth Fons, Sriram Gopalakrishnan, Svitlana Vyetrenko, Tucker Balch, Manuela Veloso:
Multi-Modal Financial Time-Series Retrieval Through Latent Space Projections. 498-506 - Danni Shi, Jan-Peter Calliess, Mihai Cucuringu:
Multireference Alignment for Lead-Lag Detection in Multivariate Time Series and Equity Trading. 507-515 - Uras Varolgunes, Dan Zhou, Dantong Yu, Ajim Uddin:
NMTucker: Non-linear Matryoshka Tucker Decomposition for Financial Time Series Imputation. 516-523 - Giuseppe Masi, Matteo Prata, Michele Conti, Novella Bartolini, Svitlana Vyetrenko:
On Correlated Stock Market Time Series Generation. 524-532 - Yoontae Hwang, Junhyeong Lee, Daham Kim, Seunghwan Noh, Joohwan Hong, Yongjae Lee:
SimStock : Representation Model for Stock Similarities. 533-540 - Martin Magris, Alexandros Iosifidis:
Variational Inference for GARCH-family Models. 541-548 - Domingo Ramírez, José-Manuel Peña, Fernando Suárez, Omar Larré, Arturo Cifuentes:
A Machine Learning Plus-Features Based Approach for Optimal Asset Allocation. 549-556 - Qi Jin, Mihai Cucuringu, Álvaro Cartea:
Correlation Matrix Clustering for Statistical Arbitrage Portfolios. 557-564 - Marcus Jun Rong Foo, Nixie S. Lesmana, Chi Seng Pun:
DRL Trading with CPT Actor and Truncated Quantile Critics. 574-582 - Sascha Yves Frey, Kang Li, Peer Nagy, Silvia Sapora, Christopher Lu, Stefan Zohren, Jakob N. Foerster, Anisoara Calinescu:
JAX-LOB: A GPU-Accelerated limit order book simulator to unlock large scale reinforcement learning for trading. 583-591 - Megan Shearer, Gabriel Rauterberg, Michael P. Wellman:
Learning to Manipulate a Financial Benchmark. 592-600 - Ruihua Ruan:
Liquidity takers behavior representation through a contrastive learning approach. 601-609 - Jingyi Gu, Wenlu Du, A M. Muntasir Rahman, Guiling Wang:
Margin Trader: A Reinforcement Learning Framework for Portfolio Management with Margin and Constraints. 610-618 - Joseph Jerome, Leandro Sánchez-Betancourt, Rahul Savani, Martin Herdegen:
Mbt-gym: Reinforcement learning for model-based limit order book trading. 619-627 - Abhinav Prasad, Prakash Arunachalam, Ali Motamedi, Ranjeeta Bhattacharya, Beibei Liu, Hays McCormick, Shengzhe Xu, Nikhil Muralidhar, Naren Ramakrishnan:
ML-Assisted Optimization of Securities Lending. 628-636 - Bogdan Sitaru, Anisoara Calinescu, Mihai Cucuringu:
Order Flow Decomposition for Price Impact Analysis in Equity Limit Order Books. 637-645 - David Ricardo Montalvan Hernandez, Cassio de Campos:
Portfolio Optimization via Credal Probabilistic Circuits. 646-654 - Dhruv Desai, Ashmita Dhiman, Tushar Sharma, Deepika Sharma, Dhagash Mehta, Stefano Pasquali:
Quantifying Outlierness of Funds from their Categories using Supervised Similarity. 655-663 - Ziyi Wang, Carmine Ventre, Maria Polukarov:
Robust Market Making: To Quote, or not To Quote. 664-672 - Parisa Hassanzadeh, Eleonora Kreacic, Sihan Zeng, Yuchen Xiao, Sumitra Ganesh:
Sequential Fair Resource Allocation under a Markov Decision Process Framework. 673-680 - Yuanrong Wang, Antonio Briola, Tomaso Aste:
Topological Portfolio Selection and Optimization. 681-688
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