default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCID4th ICAIF 2024: Brooklyn, NY, USA
- Proceedings of the 5th ACM International Conference on AI in Finance, ICAIF 2024, Brooklyn, NY, USA, November 14-17, 2024. ACM 2024, ISBN 979-8-4007-1081-0
Asset Allocation, Robustness, and Risk
- Szymon Kubiak
, Tillman Weyde, Oleksandr Galkin, Daniel Philps, Ram Gopal:
Denoising Diffusion Probabilistic Model for Realistic Financial Correlation Matrices. 1-9 - Hongda Shen, Eren Kurshan:
Generational Knowledge Transfer for Model Robustness & Agility: Label Augmentation for Time-Sensitive Financial Services Applications. 10-18 - Carlo Nicolini, Monisha Gopalan, Bruno Lepri, Jacopo Staiano:
Hopfield networks for asset allocation. 19-26 - Edward Stevinson, Alessio Lomuscio:
Reducing Return Volatility in Neural Network-Based Asset Allocation via Formal Verification and Certified Training. 27-35
Fairness, Explainability and Other
- Anne M. Tumlin, Diego Manzanas Lopez, Preston Robinette, Yuying Zhao, Tyler Derr, Taylor T. Johnson:
FairNNV: The Neural Network Verification Tool For Certifying Fairness. 36-44 - Guanchao Feng, Dhruv Desai, Stefano Pasquali, Dhagash Mehta:
Open Set Recognition for Random Forest. 45-53 - Elizabeth Fons, Rachneet Kaur, Zhen Zeng, Soham Palande, Tucker Balch, Svitlana Vyetrenko, Manuela Veloso:
TADACap: Time-series Adaptive Domain-Aware Captioning. 54-62 - Dangxing Chen, Jingfeng Chen, Weicheng Ye:
Why Groups Matter: Necessity of Group Structures in Attributions. 63-71
Generative models
- Zhuohan Wang, Carmine Ventre:
A Financial Time Series Denoiser Based on Diffusion Models. 72-80 - Juraj Zelman, Martin Stefanik, Moritz Weiss, Josef Teichmann:
Adversarial Inverse Reinforcement Learning for Market Making. 81-89 - Ruma Roy, Darshika Tiwari, Anubha Pandey:
FraudDiffuse: Diffusion-aided Synthetic Fraud Augmentation for Improved Fraud Detection. 90-98 - Achintya Gopal:
NeuralFactors: A Novel Factor Learning Approach to Generative Modeling of Equities. 99-107
Generative models and data-driven simulation
- Shojiro Tsutsui, Michihiro Karino, Kenichi Kuroki, Aya Fukumoto, Yusuke Hamano, Kenji Sobata, Temma Saito, Tatsunori Kawamoto, Taku Odashima, Tsuyoshi Kato, Yosuke Motohashi:
A Case Study on Enhancing Inquiry Response in a Non-Life Insurance Company Using Generative AI. 108-116 - Chris Mascioli, Anri Gu, Yongzhao Wang, Mithun Chakraborty, Michael P. Wellman:
A Financial Market Simulation Environment for Trading Agents Using Deep Reinforcement Learning. 117-125 - Sohyeon Kwon, Yongjae Lee:
Can GANs Learn the Stylized Facts of Financial Time Series? 126-133 - Giorgos Iacovides, Thanos Konstantinidis, Mingxue Xu, Danilo P. Mandic:
FinLlama: LLM-Based Financial Sentiment Analysis for Algorithmic Trading. 134-141 - Jeevesh Natarajan, Wayne Wang, Yaqiao Jiang, Zeqi Zhang, Huanhui Ye, Lingxi Kuang:
Generative-CNN for Pattern Recognition in Finance. 142-149 - Alexander Michael Rusnak, Stéphane Daul:
Macroeconomic Conditioned Synthetic Financial Markets. 150-158 - Simone Brusatin, Tommaso Padoan, Andrea Coletta, Domenico Delli Gatti, Aldo Glielmo:
Simulating the Economic Impact of Rationality through Reinforcement Learning and Agent-Based Modelling. 159-167 - Kshama Dwarakanath, Jialin Dong, Svitlana Vyetrenko:
Tax Credits and Household Behavior: The Roles of Myopic Decision-Making and Liquidity in a Simulated Economy. 168-176
Graph theory and Clustering
- Nail Khelifa, Jérôme Allier, Mihai Cucuringu:
Cluster-driven Hierarchical Representation of Large Asset Universes for Optimal Portfolio Construction. 177-185 - John R. J. Thompson, Matt Davison:
Functional Mixed-type Clustering of Investors' Daily Returns During a Market Shock Change-point and Recovery. 186-194 - Kiwhan Song, Mohamed Ali Dhraief, Muhua Xu, Locke Cai, Xuhao Chen, Arvind Mithal, Jie Chen:
Identifying Money Laundering Subgraphs on the Blockchain. 195-203 - Cheng-Wei Lin, Yu-Pao Tu, Chuan-Ju Wang:
Time-aware Graph Attention Networks for Multiperiod Default Prediction. 204-212
Graphs, Clustering, and Spoofing
- Nathalia M. Castellanos, Sebastian Frank, Dhruv Desai, Stefano Pasquali, Dhagash Mehta:
Can an unsupervised clustering algorithm reproduce a categorization system? 213-221 - Jovan Blanusa, Maximo Cravero Baraja, Andreea Anghel, Luc von Niederhäusern, Erik R. Altman, Haris Pozidis, Kubilay Atasu:
Graph Feature Preprocessor: Real-time Subgraph-based Feature Extraction for Financial Crime Detection. 222-230 - Ashraf Ghiye, Baptiste Barreau, Laurent Carlier, Michalis Vazirgiannis:
Rolling Forward: Enhancing LightGCN with Causal Graph Convolution for Credit Bond Recommendation. 231-238 - Anri Gu, Yongzhao Wang, Chris Mascioli, Mithun Chakraborty, Rahul Savani, Theodore L. Turocy, Michael P. Wellman:
The Effect of Liquidity on the Spoofability of Financial Markets. 239-247
Large Language Models and Counterfactual Explanations
- Jingyi Gu, Junyi Ye, Guiling Wang, Wenpeng Yin:
Adaptive and Explainable Margin Trading via Large Language Models on Portfolio Management. 248-256 - Yupeng Cao, Zhi Chen, Qingyun Pei, Nathan Lee, K. P. Subbalakshmi, Papa Momar Ndiaye:
ECC Analyzer: Extracting Trading Signal from Earnings Conference Calls using Large Language Model for Stock Volatility Prediction. 257-265 - Kuldeep Singh, Simerjot Kaur, Charese Smiley:
FinQAPT: Empowering Financial Decisions with End-to-End LLM-driven Question Answering Pipeline. 266-273 - Emmanouil Panagiotou, Manuel Heurich, Tim Landgraf, Eirini Ntoutsi:
TABCF: Counterfactual Explanations for Tabular Data Using a Transformer-Based VAE. 274-282
LLMs and Graphs
- Sander Noels, Jorne De Blaere, Tijl De Bie:
A Dutch Financial Large Language Model. 283-291 - Junhong Lin, Xiaojie Guo, Yada Zhu, Samuel Mitchell, Erik Altman, Julian Shun:
FraudGT: A Simple, Effective, and Efficient Graph Transformer for Financial Fraud Detection. 292-300 - Varad Srivastava:
Lending an Ear: How LLMs Hear Your Banking Intentions. 301-309 - Fengbin Zhu, Ziyang Liu, Fuli Feng, Chao Wang, Moxin Li, Tat-Seng Chua:
TAT-LLM: A Specialized Language Model for Discrete Reasoning over Financial Tabular and Textual Data. 310-318
Pricing, Hedging, and Fraud
- Konrad Mueller, Amira Akkari, Lukas Gonon, Ben Wood:
Fast Deep Hedging with Second-Order Optimization. 319-327 - Anubha Pandey:
Retrieval Augmented Fraud Detection. 328-335 - Aadhithya Ashok Naarayan, Panos Parpas:
Stable Multilevel Deep Neural Networks for Option Pricing and xVAs Using Forward-Backward Stochastic Differential Equations. 336-343
Reinforcement learning
- Max M. Camilleri, Josef Bajada, Vincent Vella:
Adaptive Risk-Based Control in Financial Trading. 344-352 - Magdalene Hui Qi Lim, Nixie S. Lesmana, Chi Seng Pun:
Autoregressive DRL with Learned Intrinsic Rewards for Portfolio Optimisation. 353-360 - Arishi Orra, Aryan Bhambu, Himanshu Choudhary, Manoj Thakur:
Dynamic Reinforced Ensemble using Bayesian Optimization for Stock Trading. 361-369 - Parvin Malekzadeh, Zissis Poulos, Jacky Chen, Zeyu Wang, Konstantinos N. Plataniotis:
EX-DRL: Hedging Against Heavy Losses with EXtreme Distributional Reinforcement Learning. 370-378
Time Series and Networks
- Rian Dolphin, Barry Smyth, Ruihai Dong:
Contrastive Learning of Asset Embeddings from Financial Time Series. 379-387 - Jingyi Gu, Junyi Ye, Ajim Uddin, Guiling Wang:
DySTAGE: Dynamic Graph Representation Learning for Asset Pricing via Spatio-Temporal Attention and Graph Encodings. 388-396 - Dragos Gorduza, Yaxuan Kong, Xiaowen Dong, Stefan Zohren:
Extracting Alpha from Financial Analyst Networks. 397-405 - Álvaro Ibrain, Verónica Hernández, Luis Peinado:
Unveiling Recurring Financial Patterns: Novel unsupervised filtering algorithms for enhanced forecasting. 406-418
Poster Session
- Kassiani Papasotiriou, Srijan Sood, Shayleen Reynolds, Tucker Balch:
AI in Investment Analysis: LLMs for Equity Stock Ratings. 419-427 - Shengyuan Lin, Keyi Wang, Xiao-Yang Liu:
Analyzing Cascading Outbreak of GameStop Event: A Practical Approach Using Network Analysis and Large Language Models. 428-436 - Ziyi Wang, Carmine Ventre, Maria Polukarov:
ARL-Based Multi-Action Market Making with Hawkes Processes and Variable Volatility. 437-444 - Dmitriy Nuriyev, Songyun Duan, Lingjie Yi:
Augmenting Equity Factor Investing with Global Macro Regimes. 445-452 - Andreas Sideras, Konstantinos Bougiatiotis, Elias Zavitsanos, Georgios Paliouras, George A. Vouros:
Bankruptcy Prediction: Data Augmentation, LLMs and the Need for Auditor's Opinion. 453-460 - Timur Mudarisov, Radu Valentin State, Zsófia Kräussl, Alexander Yakubov, Tatiana Petrova:
Cross-Sector Market Regime Forecasting with LLM-Augmented News Analysis. 461-468 - Felix Tian, Ajay Byadgi, Daniel S. Kim, Daochen Zha, Matt White, Kairong Xiao, Xiao-Yang Liu:
Customized FinGPT Search Agents Using Foundation Models. 469-477 - Alessio Brini, Giacomo Domeniconi, Ali Fathi:
Data-driven Derivative Hedging with Quadratic Variation Penalty. 478-486 - Wee Ling Tan, Stephen Roberts, Stefan Zohren:
Deep Learning for Options Trading: An End-To-End Approach. 487-495 - Xintong Wang, David M. Pennock, David M. Rothschild, Nikhil R. Devanur:
Designing Expressive and Liquid Financial Options Markets via Linear Programming and Automated Market Making. 496-503 - Andrei-Bogdan Balcau, Leandro Sánchez-Betancourt, Stefan Sarkadi, Carmine Ventre:
Detecting Collective Liquidity Taking Distributions. 504-512 - Jing Xu, Yung-Cheng Hsu, William Biscarri:
Dynamic Pricing in Securities Lending Market: Application in Revenue Optimization for an Agent Lender Portfolio. 513-520 - Joshua Rosaler, Dhruv Desai, Bhaskarjit Sarmah, Dimitrios Vamvourellis, Deran Onay, Stefano Pasquali, Dhagash Mehta:
Enhanced Local Explainability and Trust Scores with Random Forest Proximities. 521-529 - Sorouralsadat Fatemi, Yuheng Hu:
Enhancing Financial Question Answering with a Multi-Agent Reflection Framework. 530-537 - Xuewen Han, Neng Wang, Shangkun Che, Hongyang Yang, Kunpeng Zhang, Sean Xin Xu:
Enhancing Investment Analysis: Optimizing AI-Agent Collaboration in Financial Research. 538-546 - Changshuo Liu, Canyao Liu:
Entity-based Financial Tabular Data Synthesis with Diffusion Models. 547-554 - Parameswaran Kamalaruban, Yulu Pi, Stuart Burrell, Eleanor Drage, Piotr Skalski, Jason Wong, David Sutton:
Evaluating Fairness in Transaction Fraud Models: Fairness Metrics, Bias Audits, and Challenges. 555-563 - Yingjie Niu, Lanxin Lu, Rian Dolphin, Valerio Potì, Ruihai Dong:
Evaluating Financial Relational Graphs: Interpretation Before Prediction. 564-572 - Xiaohui Victor Li, Francesco Sanna Passino:
FinDKG: Dynamic Knowledge Graphs with Large Language Models for Detecting Global Trends in Financial Markets. 573-581 - Sorouralsadat Fatemi, Yuheng Hu:
FinVision: A Multi-Agent Framework for Stock Market Prediction. 582-590 - Nicole Cho, Nishan Srishankar, Lucas Cecchi, William Watson:
FISHNET: Financial Intelligence from Sub-querying, Harmonizing, Neural-Conditioning, Expert Swarms, and Task Planning. 591-599 - Zeda Xu, John Liechty, Sebastian Benthall, Nicholas Skar-Gislinge, Christopher McComb:
GARCH-Informed Neural Networks for Volatility Prediction in Financial Markets. 600-607 - Bhaskarjit Sarmah, Dhagash Mehta, Benika Hall, Rohan Rao, Sunil Patel, Stefano Pasquali:
HybridRAG: Integrating Knowledge Graphs and Vector Retrieval Augmented Generation for Efficient Information Extraction. 608-616 - Marco Schreyer, Timur Sattarov, Alexander Sim, Kesheng Wu:
Imb-FinDiff: Conditional Diffusion Models for Class Imbalance Synthesis of Financial Tabular Data. 617-625 - Wonseong Kim, Jan Frederic Spörer, Choong Lyol Lee, Siegfried Handschuh:
Is Small Really Beautiful for Central Bank Communication? Evaluating Language Models for Finance: Llama-3-70B, GPT-4, FinBERT-FOMC, FinBERT, and VADER. 626-633 - Preetha Saha, Jasmine Lyu, Dhruv Desai, Rishab Chauhan, Jerinsh Jeyapaulraj, Peter Chu, Philip Sommer, Dhagash Mehta:
Machine Learning-based Relative Valuation of Municipal Bonds. 634-642 - Yongzhao Wang, Rahul Savani, Anri Gu, Chris Mascioli, Theodore L. Turocy, Michael P. Wellman:
Market Making with Learned Beta Policies. 643-651 - Jiayu Shi, Siu Hin Tang, Chao Zhou:
Market-Making and Hedging with Market Impact using Deep Reinforcement Learning. 652-659 - Ashkan Golgoon, Khashayar Filom, Arjun Ravi Kannan:
Mechanistic interpretability of large language models with applications to the financial services industry. 660-668 - Kang Li, Mihai Cucuringu, Leandro Sánchez-Betancourt, Timon Willi:
Mixtures of Experts for Scaling up Neural Networks in Order Execution. 669-676 - Hajar Emami-Gohari, Xuan-Hong Dang, Syed Yousaf Shah, Petros Zerfos:
Modality-aware Transformer for Financial Time series Forecasting. 677-685 - Jingxiang Tang, Nixie S. Lesmana, Chi Seng Pun:
Navigating the Difficulty of Achieving Global Optimality under Variance-Induced Time Inconsistency. 686-694 - Jimin Lin, Guixin Liu:
Neural Term Structure of Additive Process for Option Pricing. 695-702 - Aniruddha Mukherjee, Rekha Singhal, Gautam Shroff:
Numin: Weighted-Majority Ensembles for Intraday Trading. 703-710 - Zekai Chen, Po-Yu Chen, Francois Buet-Golfouse:
Online Personalizing White-box LLMs Generation with Neural Bandits. 711-718 - Sunmin Kweon, Yonghwan Yim, Seungki Min:
Optimizing Sequential Predictions for Order Execution: a Decision Focused Learning Approach. 719-727 - Mingshu Li, Bhaskarjit Sarmah, Dhruv Desai, Joshua Rosaler, Snigdha Bhagat, Philip Sommer, Dhagash Mehta:
Quantile Regression using Random Forest Proximities. 728-736 - Vanio Slavov Markov, Vladimir Rastunkov, Juan I Adame:
Quantum Generative Models of Mid-Price Movement in Limit Order Books. 737-744 - Eren Kurshan, Dhagash Mehta, Tucker Balch:
AI versus AI in Financial Crimes & Detection: GenAI Crime Waves to Co-Evolutionary AI. 745-751 - Tao Ren, Ruihan Zhou, Jinyang Jiang, Jiafeng Liang, Qinghao Wang, Yijie Peng:
RiskMiner: Discovering Formulaic Alphas via Risk Seeking Monte Carlo Tree Search. 752-760 - Leo Ardon, Benjamin Patrick Evans, Deepeka Garg, Annapoorani Lakshmi Narayanan, Makada Henry-Nickie, Sumitra Ganesh:
Simulate and Optimise: A two-layer mortgage simulator for designing novel mortgage assistance products. 761-769 - Riasat Ali Istiaque, Chi Seng Pun, Yuli Song:
Simulating Asset Prices using Conditional Time-Series GAN. 770-778 - Kaushal Shetty, Santosh Kumar Bojanki, Adwait Ratnaparkhi:
Sovereign Risk Summarization. 779-786 - Junkyu Jang, Taehwan Kim, Sung-Hyuk Park:
Stock Index Forecasting Using an Explainable TAFT Model with Online Data-Driven Social Sentiment Index. 787-794 - Youngbin Lee, Yejin Kim, Javier Sanz-Cruzado, Richard McCreadie, Yongjae Lee:
Stock Recommendations for Individual Investors: A Temporal Graph Network Approach with Mean-Variance Efficient Sampling. 795-803 - Dayananda Herurkar, Federico Raue, Andreas Dengel:
Tab-Distillation: Impacts of Dataset Distillation on Tabular Data For Outlier Detection. 804-812 - Fei Wu, Thomas Thiery, Stefanos Leonardos, Carmine Ventre:
To Compete or Collude: Bidding Incentives in Ethereum Block Building Auctions. 813-821 - Lucas Coelho e Silva, Gustavo de Freitas Fonseca, Paulo André L. De Castro:
Transformers and attention-based networks in quantitative trading: a comprehensive survey. 822-830 - Braulio C. Blanco Lambruschini, Mats Brorsson:
Transforming Unstructured Sensitive Information into Structured Knowledge. 831-838 - Arno Geimer, Beltran Fiz, Radu State:
WallStreetFeds: Client-Specific Tokens as Investment Vehicles in Federated Learning. 839-846 - Kentaro Hoshisashi, Carolyn E. Phelan, Paolo Barucca:
Whack-a-mole Online Learning: Physics-Informed Neural Network for Intraday Implied Volatility Surface. 847-855 - Shijie Han, Haoqiang Kang, Bo Jin, Xiao-Yang Liu, Steve Y. Yang:
XBRL Agent: Leveraging Large Language Models for Financial Report Analysis. 856-864
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
last updated on 2025-12-12 22:52 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
