{"title":"使用数据分析识别表现不佳的上市公司","authors":"Derrick W. H. Fung","doi":"10.1177/18479790231165603","DOIUrl":null,"url":null,"abstract":"This study presents a teaching case that analyzes the applicability of the Z-Score bankruptcy prediction model to manufacturing firms listed in Hong Kong. Although the Z-Score model has been studied extensively, there are very few studies in the context of the Hong Kong stock market. Given that the Hong Kong stock market has high retail investor participation and low liquidity, whether the Z-Score model is relevant to Hong Kong investors is an important but unanswered question. The Z-Score model predicts the bankruptcy of firms by considering financial ratios involving firm liquidity, solvency, profitability, leverage, and activity. Financial and stock return data on the manufacturing firms listed in the Hong Kong Stock Exchange from 1981 to 2020 are collected from Thomson Reuters Datastream to examine the applicability of the Z-Score model in Hong Kong. Firms are then classified into bankrupt or non-bankrupt groups based on their Z-Scores. The annual stock returns in the subsequent year are analyzed for the two groups after classification. When the Z-Score threshold is set at 0, investing in the non-bankrupt group and short-selling the bankrupt group earns an annual return of 11.99% in the subsequent year. The results are robust to alternative periods and lagged values of the Z-Score. This suggests that stock prices do not reflect all the accounting data and that investors can increase their returns using the Z-Score model. As retail investors have limited resources, it may be difficult for them to fully implement the Z-Score model for a portfolio that consists of thousands of stocks. However, they can still avoid substantial losses by not investing in firms with low Z-Scores.","PeriodicalId":45882,"journal":{"name":"International Journal of Engineering Business Management","volume":null,"pages":null},"PeriodicalIF":4.9000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identifying poorly performing listed firms using data analytics\",\"authors\":\"Derrick W. H. Fung\",\"doi\":\"10.1177/18479790231165603\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study presents a teaching case that analyzes the applicability of the Z-Score bankruptcy prediction model to manufacturing firms listed in Hong Kong. Although the Z-Score model has been studied extensively, there are very few studies in the context of the Hong Kong stock market. Given that the Hong Kong stock market has high retail investor participation and low liquidity, whether the Z-Score model is relevant to Hong Kong investors is an important but unanswered question. The Z-Score model predicts the bankruptcy of firms by considering financial ratios involving firm liquidity, solvency, profitability, leverage, and activity. Financial and stock return data on the manufacturing firms listed in the Hong Kong Stock Exchange from 1981 to 2020 are collected from Thomson Reuters Datastream to examine the applicability of the Z-Score model in Hong Kong. Firms are then classified into bankrupt or non-bankrupt groups based on their Z-Scores. The annual stock returns in the subsequent year are analyzed for the two groups after classification. When the Z-Score threshold is set at 0, investing in the non-bankrupt group and short-selling the bankrupt group earns an annual return of 11.99% in the subsequent year. The results are robust to alternative periods and lagged values of the Z-Score. This suggests that stock prices do not reflect all the accounting data and that investors can increase their returns using the Z-Score model. As retail investors have limited resources, it may be difficult for them to fully implement the Z-Score model for a portfolio that consists of thousands of stocks. However, they can still avoid substantial losses by not investing in firms with low Z-Scores.\",\"PeriodicalId\":45882,\"journal\":{\"name\":\"International Journal of Engineering Business Management\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.9000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Engineering Business Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/18479790231165603\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Engineering Business Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/18479790231165603","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS","Score":null,"Total":0}
Identifying poorly performing listed firms using data analytics
This study presents a teaching case that analyzes the applicability of the Z-Score bankruptcy prediction model to manufacturing firms listed in Hong Kong. Although the Z-Score model has been studied extensively, there are very few studies in the context of the Hong Kong stock market. Given that the Hong Kong stock market has high retail investor participation and low liquidity, whether the Z-Score model is relevant to Hong Kong investors is an important but unanswered question. The Z-Score model predicts the bankruptcy of firms by considering financial ratios involving firm liquidity, solvency, profitability, leverage, and activity. Financial and stock return data on the manufacturing firms listed in the Hong Kong Stock Exchange from 1981 to 2020 are collected from Thomson Reuters Datastream to examine the applicability of the Z-Score model in Hong Kong. Firms are then classified into bankrupt or non-bankrupt groups based on their Z-Scores. The annual stock returns in the subsequent year are analyzed for the two groups after classification. When the Z-Score threshold is set at 0, investing in the non-bankrupt group and short-selling the bankrupt group earns an annual return of 11.99% in the subsequent year. The results are robust to alternative periods and lagged values of the Z-Score. This suggests that stock prices do not reflect all the accounting data and that investors can increase their returns using the Z-Score model. As retail investors have limited resources, it may be difficult for them to fully implement the Z-Score model for a portfolio that consists of thousands of stocks. However, they can still avoid substantial losses by not investing in firms with low Z-Scores.
期刊介绍:
The International Journal of Engineering Business Management (IJEBM) is an international, peer-reviewed, open access scientific journal that aims to promote an integrated and multidisciplinary approach to engineering, business and management. The journal focuses on issues related to the design, development and implementation of new methodologies and technologies that contribute to strategic and operational improvements of organizations within the contemporary global business environment. IJEBM encourages a systematic and holistic view in order to ensure an integrated and economically, socially and environmentally friendly approach to management of new technologies in business. It aims to be a world-class research platform for academics, managers, and professionals to publish scholarly research in the global arena. All submitted articles considered suitable for the International Journal of Engineering Business Management are subjected to rigorous peer review to ensure the highest levels of quality. The review process is carried out as quickly as possible to minimize any delays in the online publication of articles. Topics of interest include, but are not limited to: -Competitive product design and innovation -Operations and manufacturing strategy -Knowledge management and knowledge innovation -Information and decision support systems -Radio Frequency Identification -Wireless Sensor Networks -Industrial engineering for business improvement -Logistics engineering and transportation -Modeling and simulation of industrial and business systems -Quality management and Six Sigma -Automation of industrial processes and systems -Manufacturing performance and productivity measurement -Supply Chain Management and the virtual enterprise network -Environmental, legal and social aspects -Technology Capital and Financial Modelling -Engineering Economics and Investment Theory -Behavioural, Social and Political factors in Engineering