Stock Model Analysis and Investment Strategy Based on Chinese-Style Stock Valuation System

Le Luo (), Pan Deng () and Yufei Zou ()
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Le Luo: University of Washington (Seattle), Economics, Department of Economics
Pan Deng: The Chinese University of Hong Kong (Shenzhen), Data Science, School of Data Science
Yufei Zou: University of California (Davis), Economics and Psychology, College of Letters and Science

A chapter in Proceedings of the 2024 3rd International Conference on Public Service, Economic Management and Sustainable Development (PESD 2024), 2024, pp 416-435 from Springer

Abstract: Abstract This study delves into the Chinese-style stock valuation system (CSVS), considering factors such as China’s economic transformation, regulatory changes, and industry upgrades. The research first establishes a unique valuation system based on multidimensional features (policy background, market positioning, and expert analysis), screens stocks that meet Chinese characteristics, and constructs profiles for these stocks. It then extracts the features of these stocks (risk indicators, growth rates, etc.), including using the ARIMA model to capture the dynamic fluctuations in stock returns. Subsequently, the K-means clustering method is employed to classify Chinese-style stock companies into five types. Finally, the study designs and empirically tests investment portfolio strategy combining CSVS and economic hotspots, using both Markowitz optimization and equal weighting methods. The event-driven strategy with Markowitz optimization as a weighted approach achieved a 13.54% return rate from January to June 2024, outperforming the traditional equal weighting approach and providing valuable decision support for investors.

Keywords: Chinese-style stock valuation system (CSVS); Multidimensional Valuation System; K-means clustering; Investment Portfolio Strategy; Economic Hotspots (search for similar items in EconPapers)
Date: 2024
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DOI: 10.2991/978-94-6463-598-0_43

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