|
Publication |
Details |
|---|---|
|
Fan, J. and Yao, Q. (2015). The Elements of Financial Econometrics (383pp). Science Press, Beijing Table of Contents, a sample chapter, Figures and Computer Programs Order the book; Shipping Information |
|
Fan, J. and Yao, Q. (2003). Nonlinear Time Series: Nonparametric and Parametric Methods (576pp). Springer, New York - Table of Contents, Figures and Computer Programs / Errata - Book Review---Technometrics (2004) - Book Review---Quantitative Finance (2004) - Book Review--- International Institute of Statistics (2004) - Book Review---Journal of American Statistical Association (2005) |
Manuscripts
- Fan J., Liu, Q., and Zheng, K. (2023).
PeerMeta: A Framework of Financial Statement Fraud Detection Based on Peer Effects and Meta Learning.
Manuscript. - Fan, J., Ke, Z., Liao, Y., and Neuhierl (2022).
Structural Deep Learning in Conditional Asset Pricing.
Manuscript. - Ait-Sahalia, Y., Fan, J., Xue, L., and Zhou, Y. (2022).
How and When are High-Frequency Stock Returns Predictable?
Manuscript. - Fan, J., Masini, R., and Medeiros, M. (2023+).
Bridging factor and sparse models.
Annals of Statistics, to appear. - Fan, J., Xue, L., and Zhou, Y. (2023+).
How much can machines learn finance from Chinese text data?
Management Science, to appear.
Articles
R-code: POET package
- Almeida, C., Fan, J., Freire, G., and Tang, F. (2023).
Can a Machine Correct Option Pricing Models?
Journal of Business and Economics Statistics, 41, 995-1009. - Zhou, Y., Xue, L., Shi, Z., Wu, L., and Fan, J. (2022).
Measuring housing vitality from multi-source big data and machine learning.
Journal of American Statistical Association, 117, 1045-1059 Manuscript - Fan, J. and Liao, Y. (2022).
Learning latent factors from diversified projections and its applications to over-estimated and weak factors.
Journal of American Statistical Association, 117, 909-924. Manuscript - Fan, J., Guo, J., and Zheng, S. (2022).
Estimating number of factors by adjusted eigenvalues thresholding.
Journal of American Statistical Association, 117, 852-861. Manuscript
R-code, matlab-code, python - Fan, J., Masini, R., and Medeiros, M. (2022).
Do we exploit all information for counterfactual analysis? Benefits of factor models and idiosyncratic correction.
Journal of American Statistical Association, 117, 574-590. Manuscript - Fan, J., Jiang, B., and Sun, Q. (2022).
Bayesian factor-adjusted sparse regression.
Journal of Econometrics , 230, 3-19. Manuscript - Zhang, L., Shen, H. and Fan, J. (2022).
Research on the proper size of investment funds: Evidence from Chinese mutual funds.
Journal of Financial Research, 501, 189-206. (in Chinese) - Fan, J., Li, K. and Liao, Y. (2021).
Recent developments on factor models and applications in econometric learning. Annual Review of Financial Economics, 13, 401-430. - Fan, J., Ke, Y., and Liao, Y. (2021).
Augmented Factor Models with Applications to Validating Market Risk Factors and Forecasting Bond Risk Premia.
Journal of Econometrics , 22, 269-294. Manuscript - Fan, J., Feng, Y. and Xia, L. (2020).
A projection-based conditional dependence measure with applications to undirected graphical models.
Journal of Econometrics,218, 119-139. Manuscript - Fan, J., Ke, Y., and Wang, K. (2020).
Factor-adjusted regularized model selection
Journal of Econometrics , 216, 71-85. Mansucript, R-software package - Chiang, C.H., Dai, W., Fan, J., Hong, H.G., Tu, J. (2019).
Robust Measures of Earnings Surprisess.
Journal of Finance , 74, 943-983. Manuscript - Fan, J., Gong, W., and Zhu, Z. (2019).
Generalized High-Dimensional Trace Regression via Nuclear Norm Regularization.
Journal of Econometrics, 212, 177-202. Manuscript - Fan, J. and Kim, D. (2019).
Structured Volatility Matrix Estimation for Non-Synchronized High-Frequency Financial Data.
Journal of Econometrics , 61-78. Manuscript - Kim, D. and Fan, J. (2019).
Factor GARCH-Ito models for high-frequency data with application to large volatility matrix prediction.
Journal of Econometrics , 208, 395-417 Manuscript - Fan, J., Wang, W. and Zhong, Y. (2019).
Robust Covariance Estimation for Approximate Factor Models.
Journal of Econometrics, 208, 5-22 Manuscript - Fan, J. and Kim, D. (2018).
Robust high-dimensional volatility matrix estimation for high-frequency factor model.
Journal of American Statistical Association, 113, 1268-1283. Manuscript - Ait-Sahalia, Y., Fan, J., Laeven, R. J. A., Wang, C.D., and Yang, X. (2017)
Estimation of the continuous and discontinuous leverage effects.
Journal of American Statistical Association, 112, 1744-1758. Manuscript - Fan, J., Xue, L. and Yao, J. (2017).
Sufficient forecasting using factor models.
Journal of Econometrics , 201, 292-306. Manuscript - Fan, J., Han, F., Liu, H., and Vickers, B. (2016)
Robust Inference of Risks of Large Portfolios.
Journal of Econometrics , 194, 298-308. Manuscript - Fan, J., Imerman, M.B. and Dai, W. (2016).
What does the volatility risk premium say about liquidity provision and demand for hedging tail risk?
Journal of Business and Economics Statistics , 34, 519-535. Manuscript - Fan, J., Furger, A., and Xiu, D. (2016).
Incorporating global industrial classification standard into portfolio allocation: A simple factor-based large covariance matrix estimator with high frequency data.
Journal of Business and Economics Statistics, 34, 489-503. Manuscript - Fan, J., Liao, Y. and Wang, W. (2016).
Projected Principal Component Analysis in Factor Models.
Annals of Statistics, 44, 219-254. - Fan, J., Liao, Y. and Liu, H. (2016).
An overview on the estimation of large covariance and precision matrices.
Econometrics Journal, 19, C1--C32. Manuscript - Fan, J., Liao, Y. and Yao, J. (2015).
Power Enhancement in High Dimensional Cross-Sectional Tests.
Econometrica , 83, 1497-1541
An older version: Large panel test of factor pricing models. - Fan, J., Tong, X., and Zeng, Y. (2015).
Multi-Agent Inference in Social Networks: A Finite Population Approach.
Journal of American Statistical Association, 83, 1497-1541 - Fan, J., Liao, Y. and Shi, X. (2015).
Risks of large portfolios.
Journal of Econometrics, 186, 367-387. - Fan, J., Qi, L., and Xiu, D. (2014).
Quasi Maximum Likelihood Estimation of GARCH Models with Heavy-Tailed Likelihoods.(with discussion)
Journal of Business and Economics Statistics, 32, 178-205. - Fan, J. and Liao, Y. (2014).
Endogeneity in Ultrahigh Dimension.
Annals of Statistics 42, 872-917. - Ait-Sahalia, Y., Fan, J., and Li, Y. (2013).
The leverage effect puzzle: disentangling sources of bias in high frequency inference.
Journal of Financial Economics 109, 224-249. (Manuscript) - Fan, J., Liao, Y. and Micheva, M. (2013).
Large Covariance Estimation by Thresholding Principal Orthogonal Complements (with discussion).
Journal of Royal Statistical Society B, 75, 603-680. Manuscript - Fan, J., Li, Y. and Ke, Y. (2012).
Vast volatility matrix estimation using high frequency data for portfolio selection.
Journal of American Statistical Association, 107, 412-428. (Manuscript) - Fan, J., Zhang, J., and Yu, K. (2012).
Vast portfolio selection with gross-exposure constraints.
Journal of American Statistical Association, 107, 592-606. (Manuscript) - Fan, J. , Liao, Y., and Mincheva, M. (2011).
High Dimensional Covariance Matrix Estimation in Approximate Factor Models.
The Annals of Statistics, 39, 3320-3356. (Manuscript) - Fan, Y. and Fan, J. (2011).
Testing and detecting jumps based on a discretely observed process.
Journal of Econometrics, , 164, 331-344. - Fan, J., Lv, J., and Qi, L. (2011).
Sparse high-dimensional models in economics.
Annual Review of Economics, 3, 291-317 - Ait-Sahalia, Y., Fan, J., and Xiu, D.(2010).
High Frequency Covariance Estimates with Noisy and Asynchronous Financial Data.
Journal of American Statistical Association, 105, 1504-1517. - A"it-Sahalia, Y., Fan, J. and Jiang, J. (2010).
Nonparametric tests of the Markov hypothesis in continuous-time models.
Annals of Statistics, 38, 3129-3163. - Ait-Sahalia, Y., Fan, J. and Peng, H. (2009).
Nonparametric transition-based tests for diffusions.
Journal of American Statistical Association, 104, 1102-1116. - Fan, J. and Mancini, L. (2009).
Option Pricing with aggregation of physical models and nonparametric statistical learning.
Journal of American Statistical Association, 104, 1351-1372.
Manuscript. - Fan, J. and Wang, Y. (2008).
Spot volatility estimation for high-frequency data.
Statistics and Its Interface, 1, 279-288. - Fan, J., Fan, Y. and Lv, J. (2008).
High dimensional covariance matrix estimation using a factor model.
Journal of Econometrics, 147, 186-197.
Manuscript. - Fan, J., Wang, M. and Yao, Q. (2008).
Modelling Multivariate Volatilities via Conditionally Uncorrelated Components.
Journal of Royal Statistical Society B, 70, 679-702.
Manuscript. - Fan, J.and Wang, Y. (2007).
Multi-scale jump and volatility analysis for high-Frequency financial data.
Journal of American Statistical Association,102,1349-1362.
Manuscript - Fan, J., Fan, Y. and Jiang, J. (2007).
Dynamic integration of time- and state-domain methods for volatility estimation.
Journal of American Statistical Association, 102, 618-631. - Fan, J., Fan, Y. and Lv, J. (2007).
Aggregation of nonparametric estimators for volatility matrix.
Journal Financial Econometrics, 5, 321-357.
Manuscript - Fan, J. (2005).
A selective overview of nonparametric methods in financial econometrics (with discussion).
Statistical Science, 20, 317-357.
Rejoinder, Research report 2003-03, Institute of Mathematical Sciences, Chinese University of Hong Kong.
Related elementary introduction: An introduction to financial econometrics. - Fan, J. and Yim, T.H. (2004).
A data-driven method for estimating conditional densities.
Biometrika , 91, 819-834. Research report 2003-05,
Institute of Mathematical Sciences , Chinese University of Hong Kong. - Fan, J. and Gu, J. (2003).
Semiparametric Estimation of Value-at-Risk.
Econometrics Journal, 6, 261-290. - Fan, J., Jiang, J., Zhang, C. and Zhou, Z. (2003).
Time-dependent Diffusion Models for Term Structure Dynamics and the Stock Price Volatility.
Statistica Sinica , 13, 965-992. - Fan, J. and Zhang, C.(2003).
A re-examination of Stanton's diffusion estimations with applications to financial model validation.
Journal of American Statistical Association , 98, 118-134.