Key research areas

icon (3)
금융시계열의 비정규성 분석

Non-Gaussian Analysis

icon (2)
네트워크 분석

Network Analysis

icon (9)
다중프랙탈 분석

Multifractal Analysis

Financial Risk Engineering Lab uses mathematics, statistics, and computing technologies to analyze and model the inherent properties of financial markets to study optimal financial investments and financial risk management techniques.

Recent Articles
NQF-RNN: probabilistic forecasting via neural quantile function-based recurrent neural networks

Jungyoon Song, Woojin Chang & Jae Wook Song

Applied Intelligence

2024

Self-attention based deep direct recurrent reinforcement learning with hybrid loss for trading signal generation

Kwak, D., Choi, S., & Chang, W.

Information Sciences, 623, 592-606.

2023

Stock market network based on bi-dimensional histogram and autoencoder

Choi, S., Gwak, D., Song, J. W., & Chang, W.

Intelligent Data Analysis, 26(3), 723-750.

2022

Fractal structure in the S&P500: A correlation-based threshold network approach

Seungmo Ku, Changju Lee, Woojin Chang & Jae Wook Song

Chaos, Solitons & Fractals, 137, 109848

2020

Link prediction in the Granger causality network of the global currency market

Ji Hwan Park, Woojin Chang & Jae Wook Song

Physica A, 553, 124668

2020

Predicting the direction of US stock prices using effective transfer entrophy and machine learning techniques

Sondo Kim, Seungmo Ku, Woojin Chang & Jae Wook Song

IEEE Access, 8, 111660

2020