An Empirical Analysis and Forecast Study Between the Baidu Index Based on the Amount of Web Search and Trading Volume on the Platform of P2P

Zhang Xing

doi:doi:10.11648/j.si.20170505.12

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An Empirical Analysis and Forecast Study Between the Baidu Index Based on the Amount of Web Search and Trading Volume on the Platform of P2P

Zhang Xing

Published in Science Innovation (Volume 5, Issue 5)

Received: 19 July 2017 Accepted: Published: 19 July 2017

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Abstract

There is a positive correlation between Baidu index based on the amount of web search and trading volume on the platform of P2P. In this paper, there are 184 daily data between July 1, 2016 to December 31, 2016 as sample data. I constract two regression modles, one includes Baidu index and the other is included with lagged Baidu index to predict trading volume from pat platform. Therefore, I select randomly 20 daily data from January 1, 2017 to February 28, 2017. Compared with the true value and predicted value results show that the prediction effect, containing lag regression model of a Baidu index is better than the regression model with Baidu index. Taking into account the Baidu index factor P2P volume research, both in line with the development trend of Internet financial data, but also enrich the research content and research methods P2P.

Published in	Science Innovation (Volume 5, Issue 5)
DOI	10.11648/j.si.20170505.12
Page(s)	256-262
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Baidu Index, Trading Volume, Forecast Result

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APA Style

Zhang Xing. (2017). An Empirical Analysis and Forecast Study Between the Baidu Index Based on the Amount of Web Search and Trading Volume on the Platform of P2P. Science Innovation, 5(5), 256-262. https://doi.org/10.11648/j.si.20170505.12

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ACS Style

Zhang Xing. An Empirical Analysis and Forecast Study Between the Baidu Index Based on the Amount of Web Search and Trading Volume on the Platform of P2P. Sci. Innov. 2017, 5(5), 256-262. doi: 10.11648/j.si.20170505.12

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AMA Style

Zhang Xing. An Empirical Analysis and Forecast Study Between the Baidu Index Based on the Amount of Web Search and Trading Volume on the Platform of P2P. Sci Innov. 2017;5(5):256-262. doi: 10.11648/j.si.20170505.12

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@article{10.11648/j.si.20170505.12,
  author = {Zhang Xing},
  title = {An Empirical Analysis and Forecast Study Between the Baidu Index Based on the Amount of Web Search and Trading Volume on the Platform of P2P},
  journal = {Science Innovation},
  volume = {5},
  number = {5},
  pages = {256-262},
  doi = {10.11648/j.si.20170505.12},
  url = {https://doi.org/10.11648/j.si.20170505.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.si.20170505.12},
  abstract = {There is a positive correlation between Baidu index based on the amount of web search and trading volume on the platform of P2P. In this paper, there are 184 daily data between July 1, 2016 to December 31, 2016 as sample data. I constract two regression modles, one includes Baidu index and the other is included with lagged Baidu index to predict trading volume from pat platform. Therefore, I select randomly 20 daily data from January 1, 2017 to February 28, 2017. Compared with the true value and predicted value results show that the prediction effect, containing lag regression model of a Baidu index is better than the regression model with Baidu index. Taking into account the Baidu index factor P2P volume research, both in line with the development trend of Internet financial data, but also enrich the research content and research methods P2P.},
 year = {2017}
}

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TY  - JOUR
T1  - An Empirical Analysis and Forecast Study Between the Baidu Index Based on the Amount of Web Search and Trading Volume on the Platform of P2P
AU  - Zhang Xing
Y1  - 2017/07/19
PY  - 2017
N1  - https://doi.org/10.11648/j.si.20170505.12
DO  - 10.11648/j.si.20170505.12
T2  - Science Innovation
JF  - Science Innovation
JO  - Science Innovation
SP  - 256
EP  - 262
PB  - Science Publishing Group
SN  - 2328-787X
UR  - https://doi.org/10.11648/j.si.20170505.12
AB  - There is a positive correlation between Baidu index based on the amount of web search and trading volume on the platform of P2P. In this paper, there are 184 daily data between July 1, 2016 to December 31, 2016 as sample data. I constract two regression modles, one includes Baidu index and the other is included with lagged Baidu index to predict trading volume from pat platform. Therefore, I select randomly 20 daily data from January 1, 2017 to February 28, 2017. Compared with the true value and predicted value results show that the prediction effect, containing lag regression model of a Baidu index is better than the regression model with Baidu index. Taking into account the Baidu index factor P2P volume research, both in line with the development trend of Internet financial data, but also enrich the research content and research methods P2P.
VL  - 5
IS  - 5
ER  -

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Author Information

Zhang Xing

School of Economics, Shanghai University, Shanghai, China

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Plain Text BibTeX RIS

APA Style

Zhang Xing. (2017). An Empirical Analysis and Forecast Study Between the Baidu Index Based on the Amount of Web Search and Trading Volume on the Platform of P2P. Science Innovation, 5(5), 256-262. https://doi.org/10.11648/j.si.20170505.12

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ACS Style

Zhang Xing. An Empirical Analysis and Forecast Study Between the Baidu Index Based on the Amount of Web Search and Trading Volume on the Platform of P2P. Sci. Innov. 2017, 5(5), 256-262. doi: 10.11648/j.si.20170505.12

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AMA Style

Zhang Xing. An Empirical Analysis and Forecast Study Between the Baidu Index Based on the Amount of Web Search and Trading Volume on the Platform of P2P. Sci Innov. 2017;5(5):256-262. doi: 10.11648/j.si.20170505.12

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@article{10.11648/j.si.20170505.12,
  author = {Zhang Xing},
  title = {An Empirical Analysis and Forecast Study Between the Baidu Index Based on the Amount of Web Search and Trading Volume on the Platform of P2P},
  journal = {Science Innovation},
  volume = {5},
  number = {5},
  pages = {256-262},
  doi = {10.11648/j.si.20170505.12},
  url = {https://doi.org/10.11648/j.si.20170505.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.si.20170505.12},
  abstract = {There is a positive correlation between Baidu index based on the amount of web search and trading volume on the platform of P2P. In this paper, there are 184 daily data between July 1, 2016 to December 31, 2016 as sample data. I constract two regression modles, one includes Baidu index and the other is included with lagged Baidu index to predict trading volume from pat platform. Therefore, I select randomly 20 daily data from January 1, 2017 to February 28, 2017. Compared with the true value and predicted value results show that the prediction effect, containing lag regression model of a Baidu index is better than the regression model with Baidu index. Taking into account the Baidu index factor P2P volume research, both in line with the development trend of Internet financial data, but also enrich the research content and research methods P2P.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - An Empirical Analysis and Forecast Study Between the Baidu Index Based on the Amount of Web Search and Trading Volume on the Platform of P2P
AU  - Zhang Xing
Y1  - 2017/07/19
PY  - 2017
N1  - https://doi.org/10.11648/j.si.20170505.12
DO  - 10.11648/j.si.20170505.12
T2  - Science Innovation
JF  - Science Innovation
JO  - Science Innovation
SP  - 256
EP  - 262
PB  - Science Publishing Group
SN  - 2328-787X
UR  - https://doi.org/10.11648/j.si.20170505.12
AB  - There is a positive correlation between Baidu index based on the amount of web search and trading volume on the platform of P2P. In this paper, there are 184 daily data between July 1, 2016 to December 31, 2016 as sample data. I constract two regression modles, one includes Baidu index and the other is included with lagged Baidu index to predict trading volume from pat platform. Therefore, I select randomly 20 daily data from January 1, 2017 to February 28, 2017. Compared with the true value and predicted value results show that the prediction effect, containing lag regression model of a Baidu index is better than the regression model with Baidu index. Taking into account the Baidu index factor P2P volume research, both in line with the development trend of Internet financial data, but also enrich the research content and research methods P2P.
VL  - 5
IS  - 5
ER  -

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