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Chong Huang

Chong Huang

· Associate Professor

University of California, Irvine · Finance

Active 2002–2026

h-index34
Citations5.1k
Papers293124 last 5y
Funding

Academic metrics are sourced from OpenAlex and public funding records; values may differ from Google Scholar.

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About

Chong Huang joined The Paul Merage School of Business at UC Irvine in July 2012 as an Assistant Professor of Finance. His research interests include learning in financial markets, corporate finance, and financial crises. He received his PhD in Economics from the University of Pennsylvania, a Master's degree in Economics from the Chinese University of Hong Kong, and a Bachelor's degree in Finance from Peking University. Prior to his current position, he has developed expertise in understanding financial market behaviors and corporate financial strategies through his academic training and research.

Research topics

  • Computer Science
  • Geography
  • Environmental science
  • Remote sensing
  • Materials science
  • Geology
  • Agroforestry
  • Statistics
  • Forestry
  • Mathematics

Selected publications

  • Fragility of Financial Markets

    Annual Review of Financial Economics · 2025-04-22 · 3 citations

    articleOpen access

    Fragility of financial markets arises when market prices exhibit amplified reaction to underlying shocks, either fundamental or nonfundamental. The history of financial markets features many examples of such episodes, market-wide or asset-specific, which have generally been of great concern. Using a canonical framework of trading in financial markets, we provide an overview of forces generating fragility. These forces include learning by investors from the price as they make trading decisions an…

  • Individual tree detection from aerial RGB images using transfer learning semantic segmentation and simulated illumination template matching in the Yellow River Delta

    Science of Remote Sensing · 2025-10-17 · 1 citations

    articleOpen access

    Efficient and accurate detection of individual trees automatically in the Yellow River Delta Provincial Germplasm In-situ Conservation Area (YRD-PGICA) can acquire data such as the location, quantity, and distribution of trees to facilitate tree species protection tasks. However, the existence of a large number of vegetation with similar spectral characteristics to tree crowns, the diverse density of wild trees, and the relatively limited image data in the study area pose challenges to the indiv…

  • A Major Geomagnetic Storm in 2024 October Linked to Sympathetic CME--Prominence Eruptions

    arXiv (Cornell University) · 2026-04-08

    preprintOpen access

    Improving predictions of the geomagnetic impact of coronal mass ejections (CMEs) requires understanding how solar source properties relate to in-situ measurements at Earth. However, major geomagnetic storms frequently arise from interacting CMEs, complicating the link back to their solar origins. We analyze a CME interaction event that caused a major geomagnetic storm in 2024 October 10-11 (D$_{st}$ $\sim$-333 nT). Multiviewpoint observations reveal that the storm was related to a sympathetic er…

  • A Major Geomagnetic Storm in 2024 October Linked to Sympathetic Coronal Mass Ejection–Prominence Eruptions

    The Astrophysical Journal Letters · 2026-04-24

    articleOpen access

    Abstract Improving predictions of the geomagnetic impact of coronal mass ejections (CMEs) requires understanding how solar source properties relate to in situ measurements at Earth. However, major geomagnetic storms frequently arise from interacting CMEs, complicating the link back to their solar origins. We analyze a CME interaction event that caused a major geomagnetic storm in 2024 October 10–11 ( D st ∼ −333 nT). Multiviewpoint observations reveal that the storm was related to a sympathetic…

  • An Inexact Copula-Based Stochastic Fractional Programming Model for Planning Emergency Evacuation at Nuclear Power Plant Sites

    Journal of Environmental Informatics · 2025-01-01

    article1st authorCorresponding

    In this study, an inexact copula-based stochastic fractional model (ICSFP) approach is developed for supporting emergency evacuation management in response to nuclear power plant accidents. Based on an integration interval mathematical programming (IPP), fractional programming (FP) and joint chance-constraint programming (JCCP), ICSFP can systematically reflect various complexities in emergency evacuation systems such as multiple uncertainties and controversial targets. Specifically, the copula…

Frequent coauthors

  • Qingsheng Liu

    Yunnan Agricultural University

    253 shared
  • Gaohuan Liu

    222 shared
  • He Li

    137 shared
  • Fenzhen Su

    Chinese Academy of Sciences

    46 shared
  • Chenchen Zhang

    Chinese Academy of Sciences

    37 shared
  • Xudong Guan

    Chinese Academy of Sciences

    31 shared
  • Bowei Yu

    Shanghai Ninth People's Hospital

    28 shared
  • Chunsheng Wu

    Xi'an Jiaotong University

    27 shared

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