Zhipeng Yan

ORCID: 0000-0003-3251-0577
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About
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Research Areas
  • Financial Markets and Investment Strategies
  • Corporate Finance and Governance
  • Auditing, Earnings Management, Governance
  • Financial Reporting and Valuation Research
  • Capital Investment and Risk Analysis
  • Firm Innovation and Growth
  • Stock Market Forecasting Methods
  • Market Dynamics and Volatility
  • Financial Risk and Volatility Modeling
  • Housing Market and Economics
  • Financial Literacy, Pension, Retirement Analysis
  • Climate Change Policy and Economics
  • Sentiment Analysis and Opinion Mining
  • Supply Chain and Inventory Management
  • Blockchain Technology Applications and Security
  • Monetary Policy and Economic Impact
  • Environmental Impact and Sustainability
  • Sustainable Supply Chain Management
  • Advanced Text Analysis Techniques
  • Expert finding and Q&A systems
  • Economic Growth and Productivity
  • Organizational and Employee Performance
  • Job Satisfaction and Organizational Behavior
  • Credit Risk and Financial Regulations
  • Higher Education Governance and Development

Shanghai Advanced Research Institute
2024

Shanghai Jiao Tong University
2014-2024

North University of China
2020-2023

Chengdu University of Technology
2023

New Jersey Institute of Technology
2010-2021

Zhejiang University
2017-2018

City College of New York
2012

10.1016/j.ijpe.2021.108144 article EN International Journal of Production Economics 2021-05-11

We identify firms according to two life cycle stages, namely growth and maturity, test the pecking order theory of financing. find a strong maturity effect, i.e. describes financing behavior mature better than firms. Our findings show that firm is an alternative proxy for debt capacity. In particular, are older, more stable highly profitable with good credit histories. Thus, they naturally have greater After controlling fairly well.

10.2139/ssrn.1760505 article EN SSRN Electronic Journal 2010-01-01

The Securities and Exchange Commission's (SEC) Electronic Data Gathering Retrieval (EDGAR) log files provide a direct, powerful measure of attention from relatively sophisticated investors. authors apply this to sample earnings announcements 2003 2016. find that the stock market is less surprised, post–earnings-announcement drift weaker for receiving more preannouncement investor attention, measured in downloads by humans EDGAR. further show it profitable utilize different patterns. An...

10.1080/15427560.2019.1575829 article EN Journal of Behavioral Finance 2019-03-28

10.1016/j.irfa.2019.05.005 article EN International Review of Financial Analysis 2019-05-17

Corporate life-cycle concept is widely used in a variety of disciplines, including management, economics and accounting, also the real-world investment. However, current commonly methodologies measuring stages are either only suitable for small sample studies or applicable cross-sectional analysis corporations over stages. None them can be employed large-sample, time-series analysis. This paper develops new methodology which makes study large-sample properties within each stage possibility,...

10.2139/ssrn.893826 article EN SSRN Electronic Journal 2009-01-01

This study of the post–earnings announcement drift and value–glamour anomaly finds that value stocks have greater information uncertainty, exhibit more-muted initial market reactions to earnings surprises, better (more positive or less negative) drifts than do glamour stocks. A trading strategy based on these findings can generate an average annual abnormal return 16.6–18.8 percent before transaction costs.

10.2469/faj.v67.n6.3 article EN Financial Analysts Journal 2011-11-01

Using a broad sample of earnings announcements, we show that the initial stock market's response substantially increases and post‐earnings announcement drift becomes much weaker in presence more active pre‐earnings option trading. We find strongest originates from those announcements with higher trading, fewer competing made on non‐Fridays. Our interpretation is heightened investor attention, as captured by non‐Friday accelerates mitigates market under‐reaction.

10.1002/fut.21890 article EN Journal of Futures Markets 2017-11-23

Theoretical models on herd behavior predict that under different assumptions, herding can drive prices away from (or toward) fundamentals and reduce enhance) market efficiency. In this article, we study the joint effect of momentum at industry level. We find is magnified when there a low level investor herding. Herd in investors helps move asset toward fundamentals, enhances efficiency, reduces effect. A trading strategy taking long position winner industries short loser generate significant...

10.3905/joi.2012.21.1.089 article EN The Journal of Investing 2012-02-28

This paper investigates investor inattention as a plausible explanation for market reaction to repurchase announcements. We use prior turnover the proxy attention examine difference in stock price performance between low-attention stocks and high-attention stocks. find that low firms experience greater underreaction announcements than high firms. Low also larger positive long-run excess returns following Furthermore, higher level of investor's leads degree underreactions, resulting actual...

10.1080/15427560.2015.1065264 article EN Journal of Behavioral Finance 2015-07-03

We examine the central prediction of pecking order theory financing among firms in two distinct life cycle stages, namely growth and maturity. In general, we find that both stages follow order. More specifically, within a stage after sufficiently controlling for debt capacity constraints across several dimensions, with high adverse selection costs more closely, as predicts. further show certain determinants are specific to each stage, cannot simply be generalized broad sample firms. Our...

10.2139/ssrn.1347430 article EN SSRN Electronic Journal 2009-01-01

Abstract In this paper, we show that the individual skewness, defined as average of monthly skewness across firms, performs very well at predicting return S&P 500 index futures. This result holds after controlling for liquidity risk or current business cycle conditions. We also find futures returns out‐of‐sample.

10.1002/fut.22112 article EN Journal of Futures Markets 2020-03-12

Using a multi-stage filtering procedure based on both algorithms and human judgement, we develop Chinese Financial Sentiment Dictionary (CFSD) with the hope to help advance textual analysis of documents in accounting finance. There are 1,489 negative words 1,108 positive CFSD. We translate all 2,597 into English. also briefly discuss two unique settings which researchers can investigate some important interesting research questions that rarely studied due lack data.

10.2139/ssrn.3446388 article EN SSRN Electronic Journal 2019-01-01
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