1 citations · 2 across the 9 of their papers we have counts for
10 papers
When the Rules Change: Adaptive Signal Extraction via Kalman Filtering and Markov-Switching Regimes
Sungwoo Kang
Most empirical microstructure research assumes that order flow--return parameters are constant, yet these relationships shift substantially across market regimes. Combining adaptiv…
The Physics of Price Discovery: Deconvolving Information, Volatility, and the Critical Breakdown of Signal during Retail Herding
Sungwoo Kang
How information transmits through prices -- and why this transmission breaks down -- remains poorly understood. We combine regularized deconvolution with Hawkes process analysis to…
Learning Structural Hardness for Combinatorial Auctions: Instance-Dependent Algorithm Selection via Graph Neural Networks
Sungwoo Kang
The Winner Determination Problem (WDP) in combinatorial auctions is NP-hard, and no existing method reliably predicts which instances will defeat fast greedy heuristics. The ML-for…
Multi-Task Learning for Metal Alloy Property Prediction: An Empirical Study of Negative Transfer and Mitigation Strategies
Sungwoo Kang
Multi-task learning (MTL) in materials science relies on the assumption that physically related properties share learnable representations. We challenge this assumption using a 54,…
The Limits of Complexity: Why Feature Engineering Beats Deep Learning in Investor Flow Prediction
Sungwoo Kang
The application of machine learning to financial prediction has accelerated dramatically, yet the conditions under which complex models outperform simple alternatives remain poorly…
Sources and Nonlinearity of High Volume Return Premium: An Empirical Study on the Differential Effects of Investor Identity versus Trading Intensity (2020-2024)
Sungwoo Kang
Chae and Kang (2019, \textit{Pacific-Basin Finance Journal}) documented a puzzling Low Volume Return Premium (LVRP) in Korea -- contradicting global High Volume Return Premium (HVR…
Optimal Signal Extraction from Order Flow: A Matched Filter Perspective on Normalization and Market Microstructure
Sungwoo Kang
We establish a general matched filter principle for order flow normalization: optimal normalization must match the scaling behaviour of the signal-generating process. For capacity-…
Modern Deep Learning Approaches for Cricket Shot Classification: A Comprehensive Baseline Study
Sungwoo Kang
Cricket shot classification from video sequences remains a challenging problem in sports video analysis, requiring effective modeling of both spatial and temporal features. This pa…
Coarse-grained graph architectures for all-atom force predictions
Sungwoo Kang, Jinwoong Chae
We introduce a machine-learning framework termed coarse-grained all-atom force field (CGAA-FF), which incorporates coarse-grained message passing within an all-atom force field usi…
Stock Price Prediction Using Triple Barrier Labeling and Raw OHLCV Data: Evidence from Korean Markets
Sungwoo Kang
This paper demonstrates that deep learning models trained on raw OHLCV (open-high-low-close-volume) data can achieve comparable performance to traditional machine learning (ML) mod…