Rui Fan

About

Dr. Fan's research interest lies in the analysis of nonstationary and long-memory time series data that can be applied in many areas in finance, including financial markets prediction, financial systemic risk, portfolio investment, and risk management. Specifically, her research has been focused on developing statistical methods that can be used to deal with nonstationary issues when conducting statistical inference or making predictions. Her work in this context is directed towards:

1. Identification of informative economic and financial predictors of market returns. A new inference approach, MBB-IVXQR, is proposed in one of her recent papers to test for the significance of both nonstationary and stationary predictors. Different from the widely used filtration methods such as first-differencing, the IVX-filtration can maintain the maximum amount of information in a nonstationary data stream during the process of filtration. In the simulated experiments, it has been shown that the proposed method can effectively reduce more than 50% of the inference errors of the conventional methods.

2. Prediction of rare events in the financial markets. Her research also focuses on time series quantile regression and its application in finance. Quantile regression (QR) is a powerful statistical method that can be used to identify heterogeneous relationships between economic variables. In finance, it can be applied to identify useful information to predict the bad/good time in the market. With an understanding of the properties of the financial time series data, she has proposed several statistical methods to apply the quantile regression method to analyze the rare events in the financial markets.

3. Applying machine learning techniques to the analysis of high-dimensional, nonstationary time series data. Some of her recent work focuses on dealing with high-dimensional time series data when some time series are stationary, some are nonstationary, and some are cointegrated. Dr. Fan proposes to use the adaptive lasso method for selecting mixed-root predictors in an increasing-dimension framework, and prove its validity and efficiency. She also provides sufficient evidence from the analysis of financial markets to show that this method can greatly reduce the forecasting errors relative to conventional statistical methods.

Education & Training
  • Ph.D.   Economics, University of Illinois at Urbana-Champaign, 2018.
  • M.S.     Statistics, University of Illinois at Urbana-Champaign, 2015.
  • M.A.    Economics, Xiamen University, 2011.
  • B.A.     Economics, Sichuan University, 2008.

Research

Primary Research Focus
Econometric Theory, Financial Econometrics, Financial Systemic Risk
Other Focus Areas

Forecasting and Modeling, High Dimensional Data Analysis, Causal Inference

Teaching

  • Applied Econometrics (Graduate and Undergraduate), Fall 2018 – ECON 6961, Spring 2019 – ECON 6964, Fall 2019 – ECON 6961, Spring 2020 – ECON 6030/4961, Fall 2020 – ECON 6030/4960, Spring 2021 – ECON 6030/4580.
  • Advanced Data Analytics and Policy Evaluation (Graduate and Undergraduate), Spring 2020 – ECON 6020, Spring 2021/ Spring 2022 – ECON 6040/4590.
  • Panel Data Econometrics (Graduate), Spring 2019 – ECON 6965.  
  • Data Analysis in Economics and Finance (Graduate and Undergraduate), Fall 2021/ Fall 2022 – ECON 6030/4580.
  • Econometrics (Undergraduate, core), Fall 2021/ Spring 2022/ Fall 2022 – ECON 4570.
Current Courses
  • Econometrics (Undergraduate, core), ECON 4570.
  • Data Analysis in Economics and Finance (Graduate and Undergraduate), ECON 6030/4580.
  • Advanced Data Analytics and Policy Evaluation (Graduate and Undergraduate), ECON 6040/4590.

Recognition

Awards & Honors
  • Research Fellowship, Department of Economics, University of Illinois at Urbana-Champaign, June-July 2016.
  • Research Fellowship, Department of Economics, University of Illinois at Urbana-Champaign, June-July 2015.
  • Fellowship and Awards for the 5th Lindau Nobel Laureates Meeting on Economic Sciences, the National Science Foundation (NSF) and Oak Ridge Associated Universities (ORAU), August 2014.
  • Paul W. Boltz Research Fellowship, University of Illinois at Urbana-Champaign, May 2014.
  • Fellowship, University of Illinois at Urbana-Champaign, August 2011.
  • The Excellent Research Thesis Award (Thesis for Master Degree), Xiamen University, October 2010.
  • Fellowship for the 2010 Moscow Workshop on Institutional Analysis, the Ronald Coase Institute, May 2010.
Presentations & Appearances
  • The Seventh (2022) Cross Country Perspectives in Finance (CCPF) Conference, hybrid, June 23 – 25, 2022.
  • 4th International Conference on Econometrics and Statistics (EcoSta 2021), Virtual Conference, HKUST, Hong Kong, June 24 – 26, 2021.
  • The 2020 SEA Virtual Meeting, November 21, 2020.
  • Invited Seminar at National Tsing Hua University, Taiwan, December 27, 2019.
  • The 12th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2019), University of London, United Kingdom, December 14 – 16, 2019.
  • Invited Seminar at University of Rochester Medical Center, United States, November 20, 2019.
  • 2019 Asian Meeting of the Econometric Society, Xiamen University, China, June 14 – 16, 2019.
  • Invited Seminar at Shanghai University of Finance and Economics, China, May 17, 2019.
  • Invited Seminar at Fudan University, China, May 16, 2019.
  • Invited Seminar at Xiamen University, China, May 6, 2019.
  • New York Camp Econometrics XIV, Syracuse University, United States, April 12 – 14, 2019.
  • The 2019 Chinese Economists Society North America Conference (Invited Session), The University of Kansas, United States, April 6 – 7, 2019.
  • Invited Seminar at University at Albany, SUNY, United States, November 13, 2018.
  • The 2018 Meeting of the Midwest Econometrics Group, University of Wisconsin-Madison, United States, October 26 – 27, 2018.
  • The 2016 Meeting of the Midwest Econometrics Group, University of Illinois at Urbana-Champaign, United States, October 21 – 23, 2016.
  • The 2014 Meeting of the Midwest Econometrics Group, University of Iowa, United States, September 26 – 27, 2014.
  • The 5th Lindau Nobel Laureates Meeting on Economic Sciences, Lindau, Germany, August 2014.
  • The 2010 Chinese Economists Society (CES) Annual Conference: The Role of China in the Post-Crisis Era, Xiamen University, China, June 19 – 21, 2010.
  • The Ronald Coase Institute Workshop 2010 on Institutional Analysis, the Ronald Coase Institute and the State University − Higher School of Economics, Moscow, Russia, May 2 – 8, 2010.
  • The 2010 Young Economist Society (YES) Meeting: Empirical Study on China’s Economy, the Wang Yanan Institute for Studies in Economics, Xiamen University, China, April 2 – 4, 2010.
  • Co-organized an international Zoom workshop on the 35th Association for the Advancement of Artificial Intelligence (AAAI) Conference. Workshop title: “Scientific Discovery with Artificial Intelligence”. Co-organizer: Lydia Manikonda.  Date: February 9, 2021.

Publications

The following is a selection of recent publications in Scopus. Rui Fan has 4 indexed publications in the subjects of Economics, Econometrics and Finance, Computer Science, Business, and Management and Accounting.

Lydia Manikonda, Mee Young Um, Rui Fan
ACM International Conference Proceeding Series
, 2022
, pp.364-369
.
Rui Fan, Ji Hyung Lee
Journal of Econometrics
, 213
, 2019
, pp.261-280
.
Haiqi Li, Rui Fan, Sung Y. Park
Economics Letters
, 171
, 2018
, pp.149-153
.
Rui Fan, Haiqi Li, Sung Y. Park
Journal of Futures Markets
, 36
, 2016
, pp.968-991
.

View All Scopus Publications

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