Trend Forecast of Shanghai Stock Exchange Composite Index Based on Monetary Supply and Consumer Price Index
- 1 Minhang Crosspoint Academy at Shanghai Wenqi Middle School
- 2 Minhang Crosspoint Academy at Shanghai Wenqi Middle School
* Author to whom correspondence should be addressed.
Abstract
Stock market indices often serve as indicators of a country's economic conditions. Therefore, analysing the trends of stock market indices can assist individuals, institutions, and even governments in comprehending the state of the economy and developing suitable investment strategies or economic policies. However, accurately predicting these indices poses a significant challenge. In recent years, machine learning has displayed remarkable learning capabilities in various industries, making it an intriguing and viable avenue for trend prediction. In this article, we have selected two closely linked data sources, namely monetary supply and consumer price index, which are highly correlated with economic operations. By combining these data with regression models, we have developed an algorithm for predicting China's Shanghai Stock Exchange Composite Index (SSECI). Experimental results illustrate a strong correlation between the collected data and the index, highlighting their value in indicating economic conditions.
Keywords
Stock Index Prediction, Linear Regression, AdaBoost
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Cite this article
Peng,Y.;Xu,Y. (2024). Trend Forecast of Shanghai Stock Exchange Composite Index Based on Monetary Supply and Consumer Price Index. Advances in Economics, Management and Political Sciences,67,173-178.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of the 3rd International Conference on Business and Policy Studies
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