Tao Yin
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Research Interests
Tao Yin has a total of 9 co-authors. Here are the top co-authors by number of shared publications:
- Yiming Wang
School of Economics, Peking University, Beijing, China
4 shared publications Yiming Wang
Peking Univ, Sch Econ, Beijing 100871, Peoples R China
3 shared publicationsGeorge Xianzhi Yuan
College of Economics and Finance Chongqing University of Technology Chongqing China
1 shared publication- George Xianzhi Yuan
Chongqing University of Technology
1 shared publication Han Gao
School of Business East China University of Political Science and Law Shanghai China
1 shared publicationHongying Shu
Department of Mathematics Tongji University Shanghai 200092 China
1 shared publication
Latest Publications
- 30 April 2025
- Published by Wiley in Managerial and Decision Economics
- Vol. 46 (6) , 3638-3656
The Effect of ESG on Stock Mispricing: Empirical Evidence From China's A‐Share Listed Companies
In this paper, the effect of ESG performance on stock mispricing is explored across all A‐share listed companies from 2010 to 2022. The research scope consists of all A‐share listed companies from 2010 to 2022, and both the effect of ESG performance and the underlying mechanisms are explored. The findings of this study indicate a negative relationship between ESG performance and stock mispricing which suggests that improved ESG performance is effective in decreasing stock price discrepancies. In addition, corporate heterogeneity was considered in additional analysis and indicates that the reducing influence of ESG performance on stock mispricing becomes more evident in specific types of companies consisting of those with weaker internal controls, non–state‐owned status, operation outside of polluting industries, and those experiencing considerable financing limitations. Mechanism tests suggest that ESG performance contributes to the reduction of stock mispricing through the enhancement of digital transformation and greater transparency. Finally, the study considered conditions of low credibility in corporate information disclosure and market instability. Under these specific conditions, ESG performance demonstrates a significant negative effect on stock mispricing for companies with a smaller proportion of institutional investors. Through the insights gained from this research, companies can effectively work to lower stock mispricing. Enhancing corporate value can be achieved by companies through rigorous ESG standard disclosure and increased transparency. These actions, accordingly, promote market transparency and stability. Finally, these improvements contribute to the advancement of overall environmental and social governance. This study holds practical implications for both corporations and the financial market.
- 30 April 2025
- Published by Wiley in Managerial and Decision Economics
- Vol. 46 (6) , 3638-3656
The Effect of ESG on Stock Mispricing: Empirical Evidence From China's A‐Share Listed Companies
In this paper, the effect of ESG performance on stock mispricing is explored across all A‐share listed companies from 2010 to 2022. The research scope consists of all A‐share listed companies from 2010 to 2022, and both the effect of ESG performance and the underlying mechanisms are explored. The findings of this study indicate a negative relationship between ESG performance and stock mispricing which suggests that improved ESG performance is effective in decreasing stock price discrepancies. In addition, corporate heterogeneity was considered in additional analysis and indicates that the reducing influence of ESG performance on stock mispricing becomes more evident in specific types of companies consisting of those with weaker internal controls, non–state‐owned status, operation outside of polluting industries, and those experiencing considerable financing limitations. Mechanism tests suggest that ESG performance contributes to the reduction of stock mispricing through the enhancement of digital transformation and greater transparency. Finally, the study considered conditions of low credibility in corporate information disclosure and market instability. Under these specific conditions, ESG performance demonstrates a significant negative effect on stock mispricing for companies with a smaller proportion of institutional investors. Through the insights gained from this research, companies can effectively work to lower stock mispricing. Enhancing corporate value can be achieved by companies through rigorous ESG standard disclosure and increased transparency. These actions, accordingly, promote market transparency and stability. Finally, these improvements contribute to the advancement of overall environmental and social governance. This study holds practical implications for both corporations and the financial market.
- Open Access
- 17 December 2024
- Published by MDPI AG in Mathematics
- Vol. 12 (24) , 3960
The Analysis of Volatility for Non-Ferrous Metal Futures in Chinese Market Based on Multifractal Perspective
The goal of this paper is to study the behavior of non-ferrous metal futures’ volatilities in Chinese future market by applying a multifractal perspective. In particular, in order to obtain key indicators that describe the characterization of non-ferrous metal futures’ volatility behavior, we uses noise-removed EMD-MF-DFA and original MF-DFA methods to conduct a comparative analysis on the return time series of four non-ferrous metal futures, which are Aluminum future, Copper future, Zinc future and Lead future traded on the Shanghai Futures Exchange. This numerical study shows that the indicator established in characterizing the volatility of four non-ferrous metal futures is robust. In addition, we have the following four conclusions: First, there are obvious multifractal phenomena of non-ferrous metal futures in Chinese market, and it shows that Aluminum future has the largest degree of multifractality, and Copper future has the smallest degree of multifractality, which indicates that Aluminum future has the highest volatility complexity, and Copper future has the smallest volatility complexity. Second, it is found that the volatility complexity of these four non-ferrous metal futures is caused by long-range correlation. Third, this study also supports the current judgment that “Copper future has the greatest investment opportunity”. Finally, combined with analysis results, we also give suggestions to investors, producers, and regulators body for non-ferrous metal futures market in China.
- 17 December 2024
- Published by MDPI AG in Mathematics
- Vol. 12 (24) , 3960
Open AccessThe Analysis of Volatility for Non-Ferrous Metal Futures in Chinese Market Based on Multifractal Perspective
The goal of this paper is to study the behavior of non-ferrous metal futures’ volatilities in Chinese future market by applying a multifractal perspective. In particular, in order to obtain key indicators that describe the characterization of non-ferrous metal futures’ volatility behavior, we uses noise-removed EMD-MF-DFA and original MF-DFA methods to conduct a comparative analysis on the return time series of four non-ferrous metal futures, which are Aluminum future, Copper future, Zinc future and Lead future traded on the Shanghai Futures Exchange. This numerical study shows that the indicator established in characterizing the volatility of four non-ferrous metal futures is robust. In addition, we have the following four conclusions: First, there are obvious multifractal phenomena of non-ferrous metal futures in Chinese market, and it shows that Aluminum future has the largest degree of multifractality, and Copper future has the smallest degree of multifractality, which indicates that Aluminum future has the highest volatility complexity, and Copper future has the smallest volatility complexity. Second, it is found that the volatility complexity of these four non-ferrous metal futures is caused by long-range correlation. Third, this study also supports the current judgment that “Copper future has the greatest investment opportunity”. Finally, combined with analysis results, we also give suggestions to investors, producers, and regulators body for non-ferrous metal futures market in China.
- 1 June 2022
- Published by Technical University of Liberec in E+M Ekonomie a Management
- Vol. 25 (2) , 102-117
NONLINEAR ANALYSIS AND PREDICTION OF BITCOIN RETURN’S VOLATILITY
- 1 June 2022
- Published by Technical University of Liberec in E+M Ekonomie a Management
- Vol. 25 (2) , 102-117
NONLINEAR ANALYSIS AND PREDICTION OF BITCOIN RETURN’S VOLATILITY
- Open Access
- 20 May 2021
- Published by Czech Academy of Agricultural Sciences in Agricultural Economics (zemědělská Ekonomika)
- Vol. 67 (5) , 200-207
Nonlinear analysis and prediction of soybean futures
Nonlinear analysis and prediction of soybean futures | Tao Yin, Yiming Wang | Agricultural Journals
- 20 May 2021
- Published by Czech Academy of Agricultural Sciences in Agricultural Economics (zemědělská Ekonomika)
- Vol. 67 (5) , 200-207
Open AccessNonlinear analysis and prediction of soybean futures
Nonlinear analysis and prediction of soybean futures | Tao Yin, Yiming Wang | Agricultural Journals
- Open Access
- 7 January 2021
- Published by MDPI AG in Sustainability
- Vol. 13 (2) , 518
Market Efficiency and Nonlinear Analysis of Soybean Futures
In this paper, the multifractal detrended fluctuation analysis (MF-DFA) method is used to identify the multifractal structure of in the Chicago Board of Trade (CBOT) soybean futures and quantitatively describe the inefficiency and nonlinearity of the market. The data is the daily price of CBOT soybean futures from 3 January 2000 to 20 December 2019, with a total of 5025 trading days. The empirical results also show that the perspective based on MF-DFA can explain the market’s nonlinear, long-range correlation, predictability and other financial anomalies. At the same time, the prediction of price change direction and risk degree of the market are further studied. It is pointed out that multifractal characteristics are generated under the joint action of fat-tail distribution and long-range correlation. Investors can make use of these market characteristics to make arbitrage possible. Finally, based on the empirical results, some policy suggestions are put forward: strengthening rational investment education, strengthening supervision, reducing information asymmetry and other measures to improve market efficiency.
- 7 January 2021
- Published by MDPI AG in Sustainability
- Vol. 13 (2) , 518
Open AccessMarket Efficiency and Nonlinear Analysis of Soybean Futures
In this paper, the multifractal detrended fluctuation analysis (MF-DFA) method is used to identify the multifractal structure of in the Chicago Board of Trade (CBOT) soybean futures and quantitatively describe the inefficiency and nonlinearity of the market. The data is the daily price of CBOT soybean futures from 3 January 2000 to 20 December 2019, with a total of 5025 trading days. The empirical results also show that the perspective based on MF-DFA can explain the market’s nonlinear, long-range correlation, predictability and other financial anomalies. At the same time, the prediction of price change direction and risk degree of the market are further studied. It is pointed out that multifractal characteristics are generated under the joint action of fat-tail distribution and long-range correlation. Investors can make use of these market characteristics to make arbitrage possible. Finally, based on the empirical results, some policy suggestions are put forward: strengthening rational investment education, strengthening supervision, reducing information asymmetry and other measures to improve market efficiency.
- Open Access
- 28 October 2019
- Published by MDPI AG in Sustainability
- Vol. 11 (21) , 5980
Predicting the Price of WTI Crude Oil Using ANN and Chaos
This paper mainly studied the chaotic characteristics and prediction of WTI crude oil monthly price time series from January 1980 to June 2017. Meanwhile, we analyzed whether the major shock of the financial crisis in July 2008 would break the chaotic character of the time series. In addition, when using the largest lyapunov exponent to determine chaotic characteristics, the robustness test of the largest lyapunov exponent was carried out using bootstrap method. Then, we utilized three types of prediction models (ANN+Chaos-type models, Chaos-type model and ANN-type models) to predict the price of crude oil in different months. And we found that the prediction accuracy of ANN-type model is lower than the other type models. This indicated that the accuracy of the prediction with ANN model under the model misspecification is not high because the time series of WTI crude oil price has chaotic characteristics. At last, we constructed a new predictive model, namely HWP-CHAOS model, to compare the prediction accuracy of the above three type models, and discovered the best prediction model among these models is HWP-CHAOS model.
- 28 October 2019
- Published by MDPI AG in Sustainability
- Vol. 11 (21) , 5980
Open AccessPredicting the Price of WTI Crude Oil Using ANN and Chaos
This paper mainly studied the chaotic characteristics and prediction of WTI crude oil monthly price time series from January 1980 to June 2017. Meanwhile, we analyzed whether the major shock of the financial crisis in July 2008 would break the chaotic character of the time series. In addition, when using the largest lyapunov exponent to determine chaotic characteristics, the robustness test of the largest lyapunov exponent was carried out using bootstrap method. Then, we utilized three types of prediction models (ANN+Chaos-type models, Chaos-type model and ANN-type models) to predict the price of crude oil in different months. And we found that the prediction accuracy of ANN-type model is lower than the other type models. This indicated that the accuracy of the prediction with ANN model under the model misspecification is not high because the time series of WTI crude oil price has chaotic characteristics. At last, we constructed a new predictive model, namely HWP-CHAOS model, to compare the prediction accuracy of the above three type models, and discovered the best prediction model among these models is HWP-CHAOS model.
- 19 July 2017
- Published by Wiley in Mathematical Methods in the Applied Sciences
- Vol. 40 (18) , 6451-6467
Dynamics of a ratio‐dependent stage‐structured predator‐prey model with delay
In this paper, we investigate the dynamics of a time‐delay ratio‐dependent predator‐prey model with stage structure for the predator. This predator‐prey system conforms to the realistically biological environment. The existence and stability of the positive equilibrium are thoroughly analyzed, and the sufficient and necessary conditions for the stability and instability of the positive equilibrium are obtained for the case without delay. Then, the influence of delay on the dynamics of the system is investigated using the geometric criterion developed by Beretta and Kuang. We show that the positive steady state can be destabilized through a Hopf bifurcation and there exist stability switches under some conditions. The formulas determining the direction and the stability of Hopf bifurcations are explicitly derived by using the center manifold reduction and normal form theory. Finally, some numerical simulations are performed to illustrate and expand our theoretical results.
- 19 July 2017
- Published by Wiley in Mathematical Methods in the Applied Sciences
- Vol. 40 (18) , 6451-6467
Dynamics of a ratio‐dependent stage‐structured predator‐prey model with delay
In this paper, we investigate the dynamics of a time‐delay ratio‐dependent predator‐prey model with stage structure for the predator. This predator‐prey system conforms to the realistically biological environment. The existence and stability of the positive equilibrium are thoroughly analyzed, and the sufficient and necessary conditions for the stability and instability of the positive equilibrium are obtained for the case without delay. Then, the influence of delay on the dynamics of the system is investigated using the geometric criterion developed by Beretta and Kuang. We show that the positive steady state can be destabilized through a Hopf bifurcation and there exist stability switches under some conditions. The formulas determining the direction and the stability of Hopf bifurcations are explicitly derived by using the center manifold reduction and normal form theory. Finally, some numerical simulations are performed to illustrate and expand our theoretical results.