World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
41
Citations
10115
World Ranking
1868
National Ranking
106

Research.com Recognitions

  • 2003 - Fellow of the American Statistical Association (ASA)

Overview

Wai Keung Li is affiliated with the University of Hong Kong in China and has contributed extensively to the fields of economics, econometrics, and finance, with additional work in mathematics. Their research primarily centers on financial risk and volatility modeling, as well as statistical and Bayesian methods applied to economics and finance.

Li's recent publications cover a variety of topics within these fields. Notable papers include:

  • Hybrid quantile estimation for asymmetric power GARCH models, 2020, Journal of Econometrics
  • Variable screening for survival data in the presence of heterogeneous censoring, 2020, Scandinavian Journal of Statistics
  • Evaluation methods for portfolio management, 2020, Applied Stochastic Models in Business and Industry
  • Time series models for realized covariance matrices based on the matrix-F distribution, 2020, Statistica Sinica
  • An empirical evaluation of large dynamic covariance models in portfolio value-at-risk estimation, 2020, The Journal of Risk Model Validation

The frequent co-authors collaborating with Li include:

  • Philip L. H. Yu
  • Ke Zhu
  • Keith Law
  • Feiyu Jiang
  • Guochang Wang

Li's work has appeared repeatedly in prominent academic venues such as:

  • Statistica Sinica
  • Journal of Econometrics
  • Scandinavian Journal of Statistics
  • Applied Stochastic Models in Business and Industry
  • Journal of Time Series Analysis

The main fields of study for Li comprise:

  • Economics, Econometrics and Finance
  • Mathematics

Within these areas, the scientist's subfields include:

  • Finance
  • Statistics and Probability
  • General Economics, Econometrics and Finance
  • Economics and Econometrics
  • Artificial Intelligence

Research topics frequently addressed in Li's work include:

  • Financial Risk and Volatility Modeling
  • Monetary Policy and Economic Impact
  • Statistical Methods and Inference
  • Statistical Methods and Bayesian Inference
  • Financial Markets and Investment Strategies
  • Market Dynamics and Volatility
  • Bayesian Methods and Mixture Models

Li was recognized as a Fellow of the American Statistical Association in 2003.

Best Publications

  • DIAGNOSTIC CHECKING ARMA TIME SERIES MODELS USING SQUARED‐RESIDUAL AUTOCORRELATIONS

    A. I. McLeod;Wai Keung Li

  • An adaptive estimation of dimension reduction space

    Yingcun Xia;Yingcun Xia;Howell Tong;Howell Tong;Wai Keung Li;Li-Xing Zhu;Li-Xing Zhu

  • On a mixture autoregressive model

    Chun Shan Wong;Wai Keung Li

  • Recent Theoretical Results for Time Series Models with GARCH Errors

    W. K. Li;Shiqing Ling;Michael McAleer

  • On Fractionally Integrated Autoregressive Moving-Average Time Series Models with Conditional Heteroscedasticity

    Shiqing Ling;W. K. Li

  • On a double‐threshold autoregressive heteroscedastic time series model

    C. W. Li;Wai Keung Li

  • Distribution of the Residual Autocorrelations in Multivariate Arma Time Series Models

    Unknown

  • On the squared residual autocorrelations in non-linear time series with conditional heteroskedasticity

    Wai Keung Li;T. K. Mak

  • A Stochastic Volatility Model With Markov Switching

    Mike K. P. So;K. Lam;Wai Keung Li

  • Fractional time series modelling

    W. K. Li;A. I. Mcleod

  • Diagnostic Checks in Time Series

    Wai Keung Li

  • On a mixture autoregressive conditional heteroscedastic model

    Chun Shan Wong;Wai Keung Li

  • On Single-Index Coefficient Regression Models

    Yingcun Xia;W. K. Li

  • Time series models based on generalized linear models: some further results.

    Wai Keung Li

  • A threshold stochastic volatility model

    Mike K. P. So;Wai Keung Li;K. Lam

  • On extended partially linear single-index models

    Yingcun Xia;Howell Tong;Wai Keung Li

  • Limiting distributions of maximum likelihood estimators for unstable autoregressive moving-average time series with general autoregressive heteroscedastic errors

    Shiqing Ling;Wai Keung Li

  • Diagnostic checking of nonlinear multivariate time series with multivariate ARCH errors

    Shiqing Ling;Wai Keung Li

  • On a logistic mixture autoregressive model

    C. S. Wong;W. K. Li

  • ON THE ESTIMATION AND TESTING OF FUNCTIONAL-COEFFICIENT LINEAR MODELS

    Yingcun Xia;Wai Keung Li

  • A Survey of Recent Theoretical Results for Time Series Models with GARCH Errors

    W. K. Li;Shiqing Ling;Michael McAleer

Frequent Co-Authors

Shiqing Ling
Shiqing Ling Hong Kong University of Science and Technology
Howell Tong
Howell Tong London School of Economics and Political Science
Wai-Ki Ching
Wai-Ki Ching University of Hong Kong
Tak Kuen Siu
Tak Kuen Siu Macquarie University
Michael McAleer
Michael McAleer Erasmus University Rotterdam
Richard A. Davis
Richard A. Davis Columbia University
Lixing Zhu
Lixing Zhu Beijing Normal University
Bellie Sivakumar
Bellie Sivakumar Indian Institute of Technology Bombay
Paul K.S. Lam
Paul K.S. Lam Hong Kong Metropolitan University
Joseph H.W. Lee
Joseph H.W. Lee Hong Kong Polytechnic University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Studying Mathematics in the USA opens doors not only to traditional math-related careers but also to diverse fields such as business and marketing. Many students leverage their analytical skills by pursuing an MBA, often opting for the fastest online MBA to quickly enhance their qualifications while continuing to work. These accelerated programs minimize time commitment without compromising quality.

For those interested in blending quantitative skills with strategic business knowledge, a masters degree in marketing can be an excellent choice. Such degrees are often available online at affordable rates, offering strong earning potential post-graduation.

Considerations like program duration matter greatly. Students looking to complete their studies efficiently might explore 1 year MBA programs in USA, which deliver comprehensive business education in a condensed timeline. This option suits those eager to advance their careers swiftly.

Additionally, many programs today facilitate credit mobility. If you've started coursework elsewhere, it's worth investigating if you “ can you transfer credits into an MBA program ”, as this can save both time and money, making career progression smoother.

Best Scientists Citing Wai Keung Li

Trending Scientists

Recently Published Articles