Showing 1 - 13 results of 13 for search '"Shanghai Stock Exchange"', query time: 0.05s Refine Results
  1. 1

    Corporate financial strategies and performance: Insights from China’s Shanghai Stock Exchange by Ronald Ebenezer Essel

    Published 2025-01-01
    “…This study investigated the impact of corporate financial strategies-(CFSs) on the performance of companies listed on the Shanghai Stock Exchange-(SSE) from 2010-2023, analyzing data from 2,269 firms, yielding 31,766 balanced firm-year observations. …”
    Article
  2. 2

    Multivariate Nonlinear Analysis and Prediction of Shanghai Stock Market by Junhai Ma, Lixia Liu

    Published 2008-01-01
    “…This study attempts to characterize and predict stock returns series in Shanghai stock exchange using the concepts of nonlinear dynamical theory. …”
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    Article
  3. 3

    Forecasting Volatility with Time-Varying Coefficient Regressions by Qifeng Zhu, Miman You, Shan Wu

    Published 2020-01-01
    “…We extend the heterogeneous autoregressive- (HAR-) type models by explicitly considering the time variation of coefficients in a Bayesian framework and comprehensively comparing the performances of these time-varying coefficient models and constant coefficient models in forecasting the volatility of the Shanghai Stock Exchange Composite Index (SSEC). The empirical results suggest that time-varying coefficient models do generate more accurate out-of-sample forecasts than the corresponding constant coefficient models. …”
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  4. 4

    Frequency-Division Combination Forecasting of Stock Market Based on Wavelet Multiresolution Analysis by Shihua Luo, Jiangyou Huo, Zian Dai

    Published 2018-01-01
    “…Using the daily closing price data of SSE (Shanghai Stock Exchange) Composite Index and Shenzhen Component Index as samples, compared with conventional wavelet prediction model, ARIMA model, and BP neural network model, the empirical results show that the new algorithm M-ARIMA-BP can improve the accuracy of volatility forecasting and perform better in predicting prices rising and falling.…”
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    Article
  5. 5

    Nonlinear Fluctuation Behavior of Financial Time Series Model by Statistical Physics System by Wuyang Cheng, Jun Wang

    Published 2014-01-01
    “…From this financial model, we study the statistical behaviors of return time series, and the corresponding behaviors of returns for Shanghai Stock Exchange Composite Index (SSECI) and Hang Seng Index (HSI) are also comparatively studied. …”
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    Article
  6. 6

    Economic Policy Uncertainty and Conditional Dependence between China and U.S. Stock Markets by Xinyu Wu, Meng Zhang, Mengqi Wu, Hao Cui

    Published 2022-01-01
    “…The empirical analysis based on the Shanghai Stock Exchange Composite (SSEC) index in China and the S&P 500 index in the U.S. shows that the tail dependence between China and U.S. stock markets is symmetrical, and the t Copula outperforms alternative Copulas in terms of in-sample goodness of fit. …”
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    Article
  7. 7

    DO FIRM CHARACTERISTICS AFFECT PRICE DISCOVERY? EVIDENCE FROM CHINESE CROSS-LISTED STOCKS by Yen-Sheng Lee, Yi-Heng Tseng

    Published 2021-11-01
    “… This study examines the price movement relationship for Chinese firms that cross-list their shares on the Hong Kong Stock Exchange and the Shanghai Stock Exchange or Shenzhen Stock Exchange in mainland China. …”
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    Article
  8. 8

    DO FIRM CHARACTERISTICS AFFECT PRICE DISCOVERY? EVIDENCE FROM CHINESE CROSS-LISTED STOCKS by Yen-Sheng Lee, Yi-Heng Tseng

    Published 2021-11-01
    “… This study examines the price movement relationship for Chinese firms that cross-list their shares on the Hong Kong Stock Exchange and the Shanghai Stock Exchange or Shenzhen Stock Exchange in mainland China. …”
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    Article
  9. 9

    A Hybrid Approach by Integrating Brain Storm Optimization Algorithm with Grey Neural Network for Stock Index Forecasting by Yanqiu Sun

    Published 2014-01-01
    “…Experimental results from the Shanghai Stock Exchange (SSE) Composite Index, the Shenzhen Composite Index, and the HuShen 300 Index opening price forecasting show that the proposed BSO-GNN model is effective and robust in the stock index forecasting and superior to the individual GNN model.…”
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    Article
  10. 10

    Advantages of Combining Factorization Machine with Elman Neural Network for Volatility Forecasting of Stock Market by Fang Wang, Sai Tang, Menggang Li

    Published 2021-01-01
    “…In this paper, the Standard & Poor’s 500 Composite Stock Price (S&P 500) index, the Dow Jones industrial average (DJIA) index, the Shanghai Stock Exchange Composite (SSEC) index, and the Shenzhen Securities Component Index (SZI) were used to demonstrate the validity of our proposed FM-Elman model in time-series prediction. …”
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    Article
  11. 11

    Financial contagion in the US, European and Chinese stock markets during global shocks by Marina Yu. Malkina

    Published 2025-01-01
    “…The data are average daily indices: the Ameri can S&P 500, the European STOXX 600, and the Shanghai Stock Exchange (SSE) Composite Index – for December 2018 – March 2024 obtained from the financial portal Investing.com. …”
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    Article
  12. 12

    A Hybrid Approach Integrating Multiple ICEEMDANs, WOA, and RVFL Networks for Economic and Financial Time Series Forecasting by Jiang Wu, Tengfei Zhou, Taiyong Li

    Published 2020-01-01
    “…The proposed MICEEMDAN-WOA-RVFL remarkably outperforms the compared single and ensemble benchmark models in terms of forecasting accuracy and stability, as demonstrated by the experiments conducted using various economic and financial time series, including West Texas Intermediate (WTI) crude oil prices, US dollar/Euro foreign exchange rate (USD/EUR), US industrial production (IP), and Shanghai stock exchange composite index (SSEC).…”
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  13. 13

    Solving the choice puzzle: Financial and non-financial stakeholders preferences in corporate disclosures by Oleh Pasko, Li Zhang, Alvina Oriekhova, Nataliia Gerasymenko, Olena Polishchuk

    Published 2023-12-01
    “…Employing an accrual-based proxy for accounting conservatism and the social contribution value per share from the Shanghai Stock Exchange as a proxy for CSP, the study utilizes a sample of 25,490 year-company observations of A-share listed companies on China’s Shanghai and Shenzhen stock exchanges spanning from 2008 to 2019. …”
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