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2015•Science Journal of Applied Mathematics and StatisticsOpen access

The Application of ARIMA Model in 2014 Shanghai Composite Stock Price Index

Renhao Jin

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Abstract

In order to study the changes of Shanghai Composite Stock Price Index (SCSPI) and predict the trend of stock market fluctuations, this paper constructed a time-series analysis．A non-stationary trend is found, and an ARIMA model is found to sufficiently model the data. A short trend of Shanghai composite stock price index is then predicted using the established model.

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What this paper is about

In order to study the changes of Shanghai Composite Stock Price Index (SCSPI) and predict the trend of stock market fluctuations, this paper constructed a time-series analysis．A non-stationary trend is found, and an ARIMA model is found to sufficiently model the data. A short trend of Shanghai composite stock price index is then predicted using the established model.

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Available abstract

In order to study the changes of Shanghai Composite Stock Price Index (SCSPI) and predict the trend of stock market fluctuations, this paper constructed a time-series analysis．A non-stationary trend is found, and an ARIMA model is found to sufficiently model the data. A short trend of Shanghai composite stock price index is then predicted using the established model.

Key concepts: Composite index, Autoregressive integrated moving average, Econometrics, Capitalization-weighted index, Index (typography), Stock market index, Stock (firearms), Economics

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