Long Feng
Biographic Data
| ID | 8920060 |
|---|---|
| NAME | Long Feng |
| GIVEN NAMES | Long |
| FAMILY NAME | Feng |
| SIGNATURE | FENG L |
| AFFILIATIONS | Nankai University |
| ORCID | 0000-0002-9623-2345 |
| VERIFIED | Yes |
| TOTAL WORKS | 12 |
| TOTAL CITATIONS | 6 |
| AUTHOR COUNT | 12 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2009 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
Sensory impairment, loneliness, and the emergence of physical–psychological–cognitive multimorbidity
The co-occurrence of physical diseases, psychological disorders, and cognitive impairment—here termed physical–psychological–cognitive multimorbidity (PPC-M)—poses growing challenges to healthy aging but its upstream, modifiable determinants remain underexplored. Sensory impairments are common in later life and may be associated with the emergence of PPC-M, partly through psychosocial factors such as loneliness. This study aimed to examine the as…
Robust High Dimensional Alpha Test for Linear Factor Pricing Model
In this paper, we investigate alpha testing for high‐dimensional linear factor pricing models. We propose a spatial‐sign‐based max‐type test to detect sparse alternatives. Additionally, the asymptotic independence between this test and the existing spatial‐sign‐based sum‐type test is established. Based on this result, we introduce a Cauchy combination test procedure that combines both the max‐type and sum‐type tests. Simulation studies and real d…
High Frequency Anova that is Robust to Jumps, Microstructure Noise and Asynchronous Observation Times
This paper develops the necessary methodology for high frequency ANOVA, focusing on the estimations of idiosyncratic volatility and averaged R-Squared. As a nonlinear and complicated functional of the spot covariance matrix, idiosyncratic volatility estimation poses significant challenges, particularly with jumps, microstructure noise, and asynchronous observation times. Averaged R-Squared, a newly introduced quantity in high frequency econometri…
Association of circadian syndrome with the risk of physical, psychological, and cognitive multimorbidities
Background: Multimorbidity involving physical, psychological, and cognitive decline is a major public health challenge with poorly understood upstream risk factors. Circadian syndrome (CircS), which integrates metabolic, sleep, and mood dysregulation, is a potential predictor of this condition. We aimed to investigate the prospective association between baseline CircS and the incidence of distinct multimorbidity patterns. Methods: We conducted a …
Maximum-Subsampling Test of Equal Predictive Ability
In comparing the accuracy of any two competing forecasts, under the assumption that the loss differentials are covariance stationary, Diebold and Mariano (DM) proposed a test statistic that is asymptotically normal. This test is further studied by Giacomini and White (GW). However, under the DM-GW framework, the estimator of the variance of the DM test can be inaccurate in small samples, which yields size distortions; see, for example, Coroneo an…
A One-Sided Refined Symmetrized Data Aggregation Approach to Robust Mutual Fund Selection
We consider the problem of identifying skilled funds among a large number of candidates under the linear factor pricing models containing both observable and latent market factors. Motivated by the existence of non-strong potential factors and diversity of error distribution types of the linear factor pricing models, we develop a distribution-free multiple testing procedure to solve this problem. The proposed procedure is established based on the…
Adaptive Testing for Alphas in Conditional Factor Models with High Dimensional Assets
This article focuses on testing for the presence of alpha in time-varying factor pricing models, specifically when the number of securities N is larger than the time dimension of the return series T. We introduce a maximum-type test that performs well in scenarios where the alternative hypothesis is sparse. We establish the limit null distribution of the proposed maximum-type test statistic and demonstrate its asymptotic independence from the sum…
Potential use of the S-protein–Angiotensin converting enzyme 2 binding pathway in the treatment of coronavirus disease 2019
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen that causes coronavirus disease 2019 (COVID-19), infects humans through a strong interaction between the viral spike protein (S-protein) and angiotensin converting enzyme 2 (ACE2) receptors on the cell surface. The infection of host lung cells by SARS-CoV-2 leads to clinical symptoms in patients. However, ACE2 expression is not restricted to the lungs; altered receptors ha…
Impact of China's environmental protection tax on corporate performance
An Inverse Norm Sign Test of Location Parameter for High-Dimensional Data
We consider the one sample location testing problem for high-dimensional data, where the data dimension is potentially much larger than the sample size. We devise a novel inverse norm sign test (INST) that is consistent and has much improved power than many existing popular tests. We further construct a general class of weighted spatial sign tests which includes these existing tests, and show that INST is the optimal member within this class, in …
Rank‐based Tests for Cross‐sectional Dependence in Large ( N , T ) Fixed Effects Panel Data Models
Most existing methods for testing cross‐sectional dependence in fixed effects panel data models are actually conducting tests for cross‐sectional uncorrelation, which are not robust to departures of normality of the error distributions as well as nonlinear cross‐sectional dependence. To this end, we construct two rank‐based tests for (static and dynamic) fixed effects panel data models, based on two very popular rank correlations, that is, Kendal…
China’s Total Emission Control Policy
China’s Total Emission Control Policy
Rank‐based Tests for Cross‐sectional Dependence in Large ( N , T ) Fixed Effects Panel Data Models
Most existing methods for testing cross‐sectional dependence in fixed effects panel data models are actually conducting tests for cross‐sectional uncorrelation, which are not robust to departures of normality of the error distributions as well as nonlinear cross‐sectional dependence. To this end, we construct two rank‐based tests for (static and dynamic) fixed effects panel data models, based on two very popular rank correlations, that is, Kendal…
An Inverse Norm Sign Test of Location Parameter for High-Dimensional Data
We consider the one sample location testing problem for high-dimensional data, where the data dimension is potentially much larger than the sample size. We devise a novel inverse norm sign test (INST) that is consistent and has much improved power than many existing popular tests. We further construct a general class of weighted spatial sign tests which includes these existing tests, and show that INST is the optimal member within this class, in …
Potential use of the S-protein–Angiotensin converting enzyme 2 binding pathway in the treatment of coronavirus disease 2019
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen that causes coronavirus disease 2019 (COVID-19), infects humans through a strong interaction between the viral spike protein (S-protein) and angiotensin converting enzyme 2 (ACE2) receptors on the cell surface. The infection of host lung cells by SARS-CoV-2 leads to clinical symptoms in patients. However, ACE2 expression is not restricted to the lungs; altered receptors ha…
Impact of China's environmental protection tax on corporate performance
Maximum-Subsampling Test of Equal Predictive Ability
In comparing the accuracy of any two competing forecasts, under the assumption that the loss differentials are covariance stationary, Diebold and Mariano (DM) proposed a test statistic that is asymptotically normal. This test is further studied by Giacomini and White (GW). However, under the DM-GW framework, the estimator of the variance of the DM test can be inaccurate in small samples, which yields size distortions; see, for example, Coroneo an…
A One-Sided Refined Symmetrized Data Aggregation Approach to Robust Mutual Fund Selection
We consider the problem of identifying skilled funds among a large number of candidates under the linear factor pricing models containing both observable and latent market factors. Motivated by the existence of non-strong potential factors and diversity of error distribution types of the linear factor pricing models, we develop a distribution-free multiple testing procedure to solve this problem. The proposed procedure is established based on the…
Adaptive Testing for Alphas in Conditional Factor Models with High Dimensional Assets
This article focuses on testing for the presence of alpha in time-varying factor pricing models, specifically when the number of securities N is larger than the time dimension of the return series T. We introduce a maximum-type test that performs well in scenarios where the alternative hypothesis is sparse. We establish the limit null distribution of the proposed maximum-type test statistic and demonstrate its asymptotic independence from the sum…
Association of circadian syndrome with the risk of physical, psychological, and cognitive multimorbidities
Background: Multimorbidity involving physical, psychological, and cognitive decline is a major public health challenge with poorly understood upstream risk factors. Circadian syndrome (CircS), which integrates metabolic, sleep, and mood dysregulation, is a potential predictor of this condition. We aimed to investigate the prospective association between baseline CircS and the incidence of distinct multimorbidity patterns. Methods: We conducted a …
Sensory impairment, loneliness, and the emergence of physical–psychological–cognitive multimorbidity
The co-occurrence of physical diseases, psychological disorders, and cognitive impairment—here termed physical–psychological–cognitive multimorbidity (PPC-M)—poses growing challenges to healthy aging but its upstream, modifiable determinants remain underexplored. Sensory impairments are common in later life and may be associated with the emergence of PPC-M, partly through psychosocial factors such as loneliness. This study aimed to examine the as…
Robust High Dimensional Alpha Test for Linear Factor Pricing Model
In this paper, we investigate alpha testing for high‐dimensional linear factor pricing models. We propose a spatial‐sign‐based max‐type test to detect sparse alternatives. Additionally, the asymptotic independence between this test and the existing spatial‐sign‐based sum‐type test is established. Based on this result, we introduce a Cauchy combination test procedure that combines both the max‐type and sum‐type tests. Simulation studies and real d…
High Frequency Anova that is Robust to Jumps, Microstructure Noise and Asynchronous Observation Times
This paper develops the necessary methodology for high frequency ANOVA, focusing on the estimations of idiosyncratic volatility and averaged R-Squared. As a nonlinear and complicated functional of the spot covariance matrix, idiosyncratic volatility estimation poses significant challenges, particularly with jumps, microstructure noise, and asynchronous observation times. Averaged R-Squared, a newly introduced quantity in high frequency econometri…
Computer Science (6 works) · Mathematics (6 works) · Statistics (6 works) · Econometrics (4 works) · Economics (4 works) · China (3 works) · Statistical Methods and Inference (3 works) · Advanced Statistical Methods and Models (2 works) · Business (2 works) · Chemistry (2 works)