Shanghai, China

The Shanghai University of Finance and Economics , founded in 1917, is a finance- and economics-oriented research university located in Shanghai, the People's Republic of China. The university is under the direct administration of the Ministry of Education of the People's Republic of China and is among the national Project 211. The Shanghai University of Finance and Economics is a top-ranked research university specializing in economics, finance and business studies. As the oldest financial university in China, SUFE has developed its own spirit over the years., SUFE has enjoyed a reputation of being the best finance and economics universities in China for many years. The university had been consistently ranked No. 1 in the “finance and economics” category in 2003, 2004, 2005, 2007 and 2008 by the Chinese university ranking . Since 2005, the university has achieved substantial improvements in terms of research and started to gain international reputation. According to Tilburg University’s Economics Schools Research Ranking in 2012, SUFE is ranked 120th in the world, 9th in Asia and 3rd in mainland China, only after Tsinghua University and Peking University.In 2005, SUFE introduced the academic tenure and became the first university in China to adopt this system. As of December 2012, there were more than 120 tenure-track faculty members at SUFE, of which most are Ph.D. graduates from renowned overseas universities. Wikipedia.


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HONG KONG, CHINA--(Marketwired - Feb 28, 2017) - The following article was first published in the China Business Knowledge (CBK) website by CUHK Business School -- https://goo.gl/X6UkJr: Research in sociology and psychology tells us that beauty can have a significant impact on people's earning, job opportunities and career success and that attractive individuals generally receive better treatments in the workplace and other social settings. In the working paper "More than Skin-deep? Analysts' Beauty and Their Performance", Prof. George Yang, Associate Professor at the School of Accountancy of The Chinese University of Hong Kong (CUHK) Business School, extends the study to information acquisition and forecast performance in China's capital market. It reveals that the attractiveness of financial analysts is positively associated with their earnings forecast accuracy and stock recommendation informativeness. "Our study aims to look at whether a predetermined attribute of a financial analyst, namely, their physical attractiveness, affects his or her success in information acquisition and job performance," says Prof. Yang who works on the study in collaboration with Prof. Ying Cao, Associate Professor of the School of Accountancy of CUHK Business School, Prof. Feng Guan of Shanghai Lixin University of Commerce, as well as Prof. Zengquan Li, Dean of the School of Accountancy at Shanghai University of Finance and Economics. In capital markets, sell-side financial analysts who are generally employed by broker-dealers and investment banks, play an important role in disseminating the information on particular securities or stocks, giving investors the necessary information they need to judge the attractiveness of certain investments. "In China, the influence of financial analysts on the stock market is even greater because the market is dominated by retail investors who are more likely to be influenced by the so-called expert opinions than institutional investors," says Prof. Yang. Therefore, the financial analysts would actively seek out information from various sources, and the private communication with firm management is one of the critical sources, being viewed as more useful to their earnings forecasts and stock recommendations than firms' public disclosure and even their own primary research. Prior research already reveals that analysts who cater to the interests of managers enjoy an information advantage and exhibit superior forecast performance, according to researchers. The Study In the study, the researchers studied a sample of 89,056 earnings forecasts made by 2,328 analysts from 2005 to 2014. The analysts in their sample come from 102 unique brokerages, which cover all the largest brokerages in China. At the same time, they downloaded the head-to-shoulder ID photos of all sell-side financial analysts in the sample from the website of the Securities Association of China and asked 63 raters with different education background, occupation, income, and social experience to score them on a five-point scale: 1 for homely or not good looking; 2 for below average; 3 for average; 4 for above average and; 5 for strikingly beautiful or handsome. The 63 raters were from different settings including a Big Four accounting firm, a brokerage firm, a large private company, as well as university faculty members and students. Of the group, 27 of them are males while the rest are females. All the raters were reminded to use the common people in the Chinese population, not the sample analysts, as the benchmark for rating and that age should not be considered in rating. Hence, the rating score would be solely based on attractiveness, not depending on how young or old he or she looks. Lookism Matters As expected, the study reveals that the beauty ratings of financial analysts are significantly negatively associated with their forecast errors. That is to say, more attractive analysts make more accurate forecasts. The research team points out that their evidence suggests that more attractive financial analysts possess an advantage in acquiring information from firm management. "Compared with other analysts, attractive analysts are more likely to gain advance access to information about pending significant corporate events, and they are more likely to issue a stock recommendation in the quarter prior to the public announcement of three types of corporate news, including restructuring, signing of important business contracts and earning warning. Accordingly, they can produce more informative stock recommendations," says Prof. Yang. When it comes to information access, it is important to go to the right people. Again, attractive analysts have better access to them. "Attractive analysts are more likely to get more information from corporate site visits when they can directly interact with firm management. Our results show that firm managers are more likely to disclose information to those attractive analysts," he says. Taste-Driven Discrimination However, what's interesting is that the study also shows that the beauty effect disappears when managers are allowed to trade their shares in the open market or when their firm is under a share pledge agreement. To explore the reason behind, Prof. Yang went on to find out if the effect was attributed to managers' taste-based discrimination on the attractiveness of the analysts or on the notion that attractive people possess superior job-related skills and can better serve the interests of the firm. If managers believe that more attractive analysts are more capable and valuable to firms, the beauty effect would persist when there is a strong incentive for managers to boost the firm performance and increase the stock value. But, the researchers didn't find such evidence in the study. "In other words, it suggests that managers' discrimination among financial analysts is just taste-driven," Prof. Yang comments. "When managers need to rely more on analysts to inform and guide the market, they are less likely to allow their taste for beauty to sway the decision about which analysts to rely on for disseminating firm information," he explains. Apart from the relation between analysts' attractiveness level and their forecast performance, the study also demonstrates the impact of analysts' attractiveness on their career opportunities. Specifically, it finds that a more attractive analyst is more likely to be voted as a star analyst who is more likely to be hired by top-notch brokerage firms even if, for some reason, he or she could only get into a smaller firm initially. A New Challenge While social science has documented and extensively studied the beauty effect, this study provides a new perspective into the practice by financial analysts in capital markets. Unlike in previous research suggesting that analysts who issue favorable opinions would obtain more information from firm management, the current study documents a different incentive -- the indulgence of managers' taste for beauty, which affects the interaction between managers and financial analysts. "Since this form of discrimination originates from psychological and social bias and is difficult to regulate, it brings new challenges to regulators and practitioners in the industry," Prof. Yang says. Reference Ying Cao, Feng Guan, Zengquan Li and Yong George Yang, "More than Skin-deep? Analysts' Beauty and Their Performance", 2016. Working paper. This article was first published in the China Business Knowledge (CBK) website by CUHK Business School: https://goo.gl/X6UkJr. About CUHK Business School CUHK Business School comprises two schools -- Accountancy and Hotel and Tourism Management -- and four departments -- Decision Sciences and Managerial Economics, Finance, Management and Marketing. Established in Hong Kong in 1963, it is the first business school to offer BBA, MBA and Executive MBA programs in the region. Today, the School offers 8 undergraduate programs and 13 graduate programs including MBA, EMBA, Master, MSc, MPhil and PhD. In the Financial Times Global MBA Ranking 2017, CUHK MBA is ranked 36th. In FT's 2016 EMBA ranking, CUHK EMBA is ranked 37th in the world. CUHK Business School has the largest number of business alumni (32,000+) in Hong Kong - many of whom are key business leaders. The School currently has about 4,400 undergraduate and postgraduate students and Professor Kalok Chan is the Dean of CUHK Business School. More information is available at: http://www.bschool.cuhk.edu.hk or by connecting with CUHK Business School on Facebook: http://www.facebook.com/cuhkbschool and LinkedIn: http://www.linkedin.com/company/cuhk-business-school. About China Business Knowledge (CBK) CBK is a portal belonging to the Chinese University of Hong Kong (CUHK) Business School which provides easy access to the China-related research conducted at CUHK Business School. Through feature articles, mini case studies, discussions and a research paper database, CBK aim to narrow the knowledge gap between China and the rest of the world, providing in-depth knowledge and practical tips about doing business in China. Free content is available at http://www.bschool.cuhk.edu.hk/faculty/cbk/index.aspx or by connecting with CBK@CUHK on Facebook: http://www.facebook.com/CBKCUHK, Twitter: https://twitter.com/CBK_CUHK and LinkedIn: http://linkd.in/1B8cGdU.


Wang L.,Shanghai University of Finance and Economics
Neurocomputing | Year: 2013

In this paper, we are concerned with a class of high-order neural networks (HONNs). Rigorous analysis shows that the state components exhibit different dynamical behaviors with respect to external inputs lying in different ranges. And by dividing the index set {1, 2, ...., n} into four subsets Nj,j=1,2,3,4, according to different external input ranges, we can conclude that the HONNs have exact 3#N2 equilibrium points, 2#N2 of them are locally stable and others are unstable, here #N2 represents the number of elements in the subset N2. The results obtained improve and extend some related works. A numerical example is presented to illustrate the effectiveness of our criteria. © 2013 Elsevier B.V.


Chang N.,Shanghai University of Finance and Economics
Journal of Cleaner Production | Year: 2014

Increasing concern about carbon dioxide (CO2) emission reduction demands knowledge about the production structure of an economy. Information on productive linkages yields insight about forward and backward emission effects associated with sectoral inputs and outputs and serves as an essential starting point to identify the optimised industrial structure under the constraint of CO2 emission. This paper proposes a combined linkage analysis and multi-objective programming approach to identify the key CO2 emission sectors and the optimised production structure with respect to emission reduction target. As a demonstration, the proposed approach is applied to data from China in 2007. The result shows that to reduce CO2 emissions from 5707.16 to 5452.12 million tonnes, China needs to change its industrial structure by focussing on industrial groups as defined by linkage characteristics, which would lead to a subsequent GDP decrease of 82.59 billion Yuan. From a policy standpoint, the analytical techniques described in this paper can provide valuable information for planners and decision makers to formulate feasible and practical industrial polices with implications for CO2 emissions. © 2014 Elsevier Ltd. All rights reserved.


Hu Y.,Shanghai University of Finance and Economics
Energy Policy | Year: 2012

Fast economic growth in China has generated energy and environmental problems. Fixed-asset investments have contributed significantly to energy consumption. In China, an energy conservation assessment (ECA), a mechanism similar to the existing environmental impact assessment (EIA), has been applied to improve the energy efficiency of new fixed-asset investment projects. In this paper the origin and development of the ECA system is analyzed and the major features of ECA are discussed. To identify the success and failure of the ECA system, case studies are analyzed and comparison between ECA and EIA, which has been used in China for over 30 years, is made. Based on the analysis, recommendations are provided for the improvement of the ECA system in China. Despite the ECA system only being established for a relatively short time, it has clearly achieved significant success. With further efforts it could play an important role in achieving the goals of improving China's energy efficiency and reducing green house gas emissions. © 2012 Elsevier Ltd.


Chang N.,Shanghai University of Finance and Economics
Energy Policy | Year: 2013

Concerns about the equity and efficiency of current allocation principles related to responsibility for carbon dioxide (CO2) emissions have been presented in the recent literature. The objective of this paper is to design a calculation framework for shared responsibility from the perspective of border tax adjustments. The advantage of this framework is that it makes the shared responsibility principle and border carbon taxation complementary to each other; these are important policies for reducing global CO2 emissions, but they are individually supported by developing and developed countries. As an illustration, the proposed framework is applied to data from China in 2007. The empirical results show that for the Chinese economy as a whole, changing from the production-based criterion to the shared responsibility approach would lead to an 11% decrease in its responsibility for CO2 emissions. Moreover, the differences observed between the production-based criterion and the shared responsibility approach are considerable in several sectors; for example, changing from the production-based criterion to the shared principle would lead to a 60% decrease in the responsibility of the textile sector. © 2013 Elsevier Ltd.


Zhang L.-H.,Shanghai University of Finance and Economics
Pattern Recognition Letters | Year: 2011

For linear discriminant analysis (LDA), the ratio trace and trace ratio are two basic criteria generalized from the classical Fisher criterion function, while the orthogonal and uncorrelated constraints are two common conditions imposed on the optimal linear transformation. The ratio trace criterion with both the orthogonal and uncorrelated constraints have been extensively studied in the literature, whereas the trace ratio criterion receives less interest mainly due to the lack of a closed-form solution and efficient algorithms. In this paper, we make an extensive study on the uncorrelated trace ratio linear discriminant analysis, with particular emphasis on the application on the undersampled problem. Two regularization uncorrelated trace ratio LDA models are discussed for which the global solutions are characterized and efficient algorithms are established. Experimental comparison on several LDA approaches are conducted on several real world datasets, and the results show that the uncorrelated trace ratio LDA is competitive with the orthogonal trace ratio LDA, but is better than the results based on ratio trace criteria in terms of the classification performance. © 2010 Elsevier B.V. All rights reserved.


Tong C.,Shanghai University of Finance and Economics
Operations Research Letters | Year: 2010

We show for products featuring an exponential demand with Gamma prior, if the demand forecast improves over time and the manufacturer sets the wholesale price, the expected order size increases when the order is placed later. Both the manufacturer and the retailer gain when the order is placed later. © 2009 Elsevier B.V. All rights reserved.


Wang Q.,Shanghai University of Finance and Economics
Nonlinear Analysis: Real World Applications | Year: 2011

In this paper, the optimal homotopy-analysis method is used to find the travelling-wave solution of the Kawahara equation. The method used here contains three auxiliary convergence-control parameters, which provide us with a simple way to adjust and control the convergence region of the solution. By minimizing the averaged residual error, the optimal convergence-control parameters can be obtained, which give much better approximations than those given by usual homotopy-analysis method. © 2010 Elsevier Ltd. All rights reserved.


Tang L.,Shanghai University of Finance and Economics
Journal of Informetrics | Year: 2013

China's status as a scientific power, particularly in the emerging area of nanotechnology, has become widely accepted in the global scientific community. The role of knowledge spillover in China's nanotechnology development is generally assumed, albeit without much convincing evidence. Very little has been investigated on the different mechanisms of knowledge spillover. Utilizing both cross-sectional data and longitudinal data of 77 Chinese nanoscientists' publications, this study aims to differentiate individual effects from the effect of international collaboration on the research performance of Chinese researchers. The study finds evidence in support of the " birds of a feather flock together" argument - that China's best scientists collaborate at international level. It also finds that collaboration across national boundaries has a consistently positive effect on China's nano research quality with a time-decaying pattern. Language turns out to be the most influential factor impacting the quality or visibility of Chinese nano research. Policy implications on research evaluation, human capital management, and public research and development allocation are also discussed in the end. © 2012 Elsevier Ltd.


Long Y.,Shanghai University of Finance and Economics
Physica A: Statistical Mechanics and its Applications | Year: 2013

Mapping time series into a visibility graph network, the characteristics of the gold price time series and return temporal series, and the mechanism underlying the gold price fluctuation have been explored from the perspective of complex network theory. The network degree distribution characters, which change from power law to exponent law when the series was shuffled from original sequence, and the average path length characters, which change from L∼lnN into lnL∼lnN as the sequence was shuffled, demonstrate that price series and return series are both long-rang dependent fractal series. The relations of Hurst exponent to the power-law exponent of degree distribution demonstrate that the logarithmic price series is a fractal Brownian series and the logarithmic return series is a fractal Gaussian series. Power-law exponents of degree distribution in a time window changing with window moving demonstrates that a logarithmic gold price series is a multifractal series. The Power-law average clustering coefficient demonstrates that the gold price visibility graph is a hierarchy network. The hierarchy character, in light of the correspondence of graph to price fluctuation, means that gold price fluctuation is a hierarchy structure, which appears to be in agreement with Elliot's experiential Wave Theory on stock price fluctuation, and the local-rule growth theory of a hierarchy network means that the hierarchy structure of gold price fluctuation originates from persistent, short term factors, such as short term speculation. © 2013 Elsevier B.V. All rights reserved.

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