:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Kwon, Sohyeon, Lee, Yongjae
Format:	Preprint
Published:	2024
Subjects:	Computational Finance
Online Access:	https://arxiv.org/abs/2410.09850
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Revisiting Cont's Stylized Facts for Modern Stock Markets
by: Ratliff-Crain, Ethan, et al.
Published: (2023)

International Financial Markets Through 150 Years: Evaluating Stylized Facts
by: Safari, Sara A., et al.
Published: (2025)

Stylized Facts of High-Frequency Bitcoin Time Series
by: Tang, Yaoyue, et al.
Published: (2024)

Temporal Representation Learning for Stock Similarities and Its Applications in Investment Management
by: Hwang, Yoontae, et al.
Published: (2024)

Robust Hedging GANs
by: Limmer, Yannick, et al.
Published: (2023)

Reasoning on Time-Series for Financial Technical Analysis
by: Koa, Kelvin J. L., et al.
Published: (2025)

Cross-Sectional Asset Retrieval via Future-Aligned Soft Contrastive Learning
by: Lee, Hyeongmin, et al.
Published: (2026)

The Statistical Significance of the Inclusion of Graph Neural Networks in the Financial Time Series Forecasting Problem
by: Gregnanin, Marco, et al.
Published: (2026)

Causality-Inspired Models for Financial Time Series Forecasting
by: Oliveira, Daniel Cunha, et al.
Published: (2024)

Transfer Learning in Financial Time Series with Gramian Angular Field
by: Long, Hou-Wan, et al.
Published: (2025)

From Text to Alpha: Can LLMs Track Evolving Signals in Corporate Disclosures?
by: Choi, Chanyeol, et al.
Published: (2025)

CoFinDiff: Controllable Financial Diffusion Model for Time Series Generation
by: Tanaka, Yuki, et al.
Published: (2025)

Temporal Graph Networks for Graph Anomaly Detection in Financial Networks
by: Kim, Yejin, et al.
Published: (2024)

Financial Fine-tuning a Large Time Series Model
by: Fu, Xinghong, et al.
Published: (2024)

Time Series Augmented Generation for Financial Applications
by: Kolonin, Anton, et al.
Published: (2026)

Decision by Supervised Learning with Deep Ensembles: A Practical Framework for Robust Portfolio Optimization
by: Kim, Juhyeong, et al.
Published: (2025)

Mean-Variance Efficient Collaborative Filtering for Stock Recommendation
by: Chung, Munki, et al.
Published: (2023)

Deep Generative Modeling for Financial Time Series with Application in VaR: A Comparative Review
by: Ericson, Lars, et al.
Published: (2024)

Towards Financially Inclusive Credit Products Through Financial Time Series Clustering
by: Bester, Tristan, et al.
Published: (2024)

Decision-informed Neural Networks with Large Language Model Integration for Portfolio Optimization
by: Hwang, Yoontae, et al.
Published: (2025)

Machine Learning Methods for Pricing Financial Derivatives
by: Fan, Lei, et al.
Published: (2024)

Feature Selection with Annealing for Forecasting Financial Time Series
by: Pabuccu, Hakan, et al.
Published: (2023)

Quantitative Financial Modeling for Sri Lankan Markets: Approach Combining NLP, Clustering and Time-Series Forecasting
by: Perera, Linuk
Published: (2025)

FinMultiTime: A Four-Modal Bilingual Dataset for Financial Time-Series Analysis
by: Xu, Wenyan, et al.
Published: (2025)

Same Error, Different Function: The Optimizer as an Implicit Prior in Financial Time Series
by: Cortesi, Federico Vittorio, et al.
Published: (2026)

Predicting Liquidity-Aware Bond Yields using Causal GANs and Deep Reinforcement Learning with LLM Evaluation
by: Walia, Jaskaran Singh, et al.
Published: (2025)

AI-Trader: Benchmarking Autonomous Agents in Real-Time Financial Markets
by: Fan, Tianyu, et al.
Published: (2025)

Multimodal Language Models with Modality-Specific Experts for Financial Forecasting from Interleaved Sequences of Text and Time Series
by: Koval, Ross, et al.
Published: (2025)

Alleviating Non-identifiability: a High-fidelity Calibration Objective for Financial Market Simulation with Multivariate Time Series Data
by: Wang, Chenkai, et al.
Published: (2024)

Stylized Facts and Market Microstructure: An In-Depth Exploration of German Bond Futures Market
by: Bodor, Hamza, et al.
Published: (2024)

Global Neural Networks and The Data Scaling Effect in Financial Time Series Forecasting
by: Liu, Chen, et al.
Published: (2023)

FinCast: A Foundation Model for Financial Time-Series Forecasting
by: Zhu, Zhuohang, et al.
Published: (2025)

FinZero: Launching Multi-modal Financial Time Series Forecast with Large Reasoning Model
by: Wang, Yanlong, et al.
Published: (2025)

Time-Causal VAE: Robust Financial Time Series Generator
by: Acciaio, Beatrice, et al.
Published: (2024)

TWICE: What Advantages Can Low-Resource Domain-Specific Embedding Model Bring? -- A Case Study on Korea Financial Texts
by: Hwang, Yewon, et al.
Published: (2025)

FinTSB: A Comprehensive and Practical Benchmark for Financial Time Series Forecasting
by: Hu, Yifan, et al.
Published: (2025)

Learning Temporal Patterns in Financial Time Series: A Comparative Study of Quantum LSTM and Quantum Reservoir Computing
by: Maheshwari, Danyal, et al.
Published: (2026)

Uncovering Residual Factors in Financial Time Series via PCA and MTP2-constrained Gaussian Graphical Models
by: Watanabe, Koshi, et al.
Published: (2026)

A Generative Adversarial Graph Neural Network for Synthetic Time Series Data
by: Gregnanin, Marco, et al.
Published: (2026)

Fin-Fact: A Benchmark Dataset for Multimodal Financial Fact Checking and Explanation Generation
by: Rangapur, Aman, et al.
Published: (2023)