Key research areas

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금융시계열의 비정규성 분석

Non-Gaussian Analysis

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네트워크 분석

Network Analysis

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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
Maximizing the risk-adjusted return of classification model-based investments

Jaewon Yang & Woojin Chang

Applied Soft Computing

2026

Forecasting realized volatility using deep learning quantile function

Jungyoon Song, Hyunju Lee, Jongu Lee & Woojin Chang

Applied Soft Computing

2025

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