송재욱

전체 60건 중 1번부터 10번까지의 결과를 표시합니다.

2026

Conference

Physics Informed Realized Volatility Forecasting

Conference

Beyond HAR: Realized Volatility Forecasting with Heterogeneous Attention Mechanism

Article

Probabilistic forecasting of high-frequency realized cryptocurrency volatility via CEEMDAN-integrated autoregressive recurrent neural network

Article

Learning standardized noise for risk-neutral option pricing via Generative Adversarial Networks

Article

From vision to value: Stock chart image-driven factors and their pricing power

Article

HGAIT: heterogeneous graph attention with inverted transformers for correlation-aware stock return prediction

2025

Conference

PRISM-VQ: Fusing Financial Priors and Vector-Quantized Latent Factors for Dynamic Cross-Sectional Stock Prediction

Article

Random Forests for Feature Selection: Concepts and Applications in Asset Management

Conference

Probabilistic Forecasting of High-Frequency Crypto Volatility via Decomposition-Integrated Recurrent Neural Networks

Conference

FPQ-VAE: A Dynamic Factor Model Fusing Financial Priors and Vector-Quantized Factors for Stock Rank Prediction

상세 보기

송재욱

자료유형

발행연도

키워드

언어

Physics Informed Realized Volatility Forecasting

Beyond HAR: Realized Volatility Forecasting with Heterogeneous Attention Mechanism

Probabilistic forecasting of high-frequency realized cryptocurrency volatility via CEEMDAN-integrated autoregressive recurrent neural network

Learning standardized noise for risk-neutral option pricing via Generative Adversarial Networks

From vision to value: Stock chart image-driven factors and their pricing power

HGAIT: heterogeneous graph attention with inverted transformers for correlation-aware stock return prediction

PRISM-VQ: Fusing Financial Priors and Vector-Quantized Latent Factors for Dynamic Cross-Sectional Stock Prediction

Random Forests for Feature Selection: Concepts and Applications in Asset Management

Probabilistic Forecasting of High-Frequency Crypto Volatility via Decomposition-Integrated Recurrent Neural Networks

FPQ-VAE: A Dynamic Factor Model Fusing Financial Priors and Vector-Quantized Factors for Stock Rank Prediction