Asia-Pacific Financial Markets最新文献

Human Capital Based Six-Factor Asset Pricing Model in the Era of Covid-19 新冠肺炎时代基于人力资本的六因素资产定价模型

IF 2.6

Asia-Pacific Financial Markets Pub Date : 2025-12-02 DOI: 10.1007/s10690-025-09579-7

Wing-Keung Wong, Riffat Mughal, Mustafa Afeef, Naveed Khan, Hassan Zada

{"title":"Human Capital Based Six-Factor Asset Pricing Model in the Era of Covid-19","authors":"Wing-Keung Wong, Riffat Mughal, Mustafa Afeef, Naveed Khan, Hassan Zada","doi":"10.1007/s10690-025-09579-7","DOIUrl":"10.1007/s10690-025-09579-7","url":null,"abstract":"<div>\u0000 \u0000 <p>In recent years, the COVID-19 pandemic has heightened trade tensions and geopolitical risks, affecting stock market volatility and the factors that determine the pricing of financial securities. This study examines the role of human capital in the Fama-French (2015) five-factor model to explain excess portfolio returns. For this purpose, we collected daily stock prices data for 73 non-financial firms listed on the Pakistan Stock Exchange from July 2018 to June 2023. For estimation, we employed two models: first, the Fama-French time-series regression, second, the Fama–Macbeth (1973) rolling-window two-pass regression. We find that the six-factor model significantly explains time-series variations in excess portfolio returns. Notably, the human capital premium is significantly and negatively related to excess portfolio returns. However, a significant and positive coefficient for the COVID-19 dummy and a significant and negative coefficient for the interaction between human capital and COVID-19 across several portfolios indicate that, on average, during COVID-19, excess portfolio returns have improved. In contrast, increased expenditures on human capital are negatively related to excess portfolio returns. The results have meaningful implications for investors, portfolio managers, and policymakers. It is suggested that the human capital factor be incorporated into asset pricing. Further, it emphasizes developing strategies to maintain investor confidence during crises like the COVID-19 pandemic.</p>\u0000 </div>","PeriodicalId":54095,"journal":{"name":"Asia-Pacific Financial Markets","volume":"33 1","pages":"25 - 63"},"PeriodicalIF":2.6,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147335895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Correction: Modeling Electricity Prices with Stochastic Langevin Equations 修正：用随机朗格万方程建模电价

IF 2.6

Asia-Pacific Financial Markets Pub Date : 2025-10-16 DOI: 10.1007/s10690-025-09573-z

Markus Hess

引用次数: 0

Supply Chain Network Design Focused on Financial Measures and Performance Metrics: A Systematic Literature Review 供应链网络设计关注财务措施和绩效指标：系统的文献综述

IF 2.6

Asia-Pacific Financial Markets Pub Date : 2025-06-18 DOI: 10.1007/s10690-025-09533-7

Sina Abbasi, Çiğdem Sıcakyüz

{"title":"Supply Chain Network Design Focused on Financial Measures and Performance Metrics: A Systematic Literature Review","authors":"Sina Abbasi, Çiğdem Sıcakyüz","doi":"10.1007/s10690-025-09533-7","DOIUrl":"10.1007/s10690-025-09533-7","url":null,"abstract":"<div><p>Through an extensive literature review, this study determines which metrics and measures are relevant for supply chain (SC) performance. We reviewed several universal papers published between 2012 and 2023. A selection of review papers was made according to the methods, contribution, and scope for measuring SC performance metrics and measures. By reviewing the literature, this survey prepares benchmarks and approaches for determining SC performance from a financial viewpoint. As core financial measures of SC performance, we investigation looked at inventory turnover ratios, logistics costs, and cash flows expressed as return on investment (ROI), return on equity (ROE), return on asset (ROA), profit margins, assets/liabilities, and working capital. Additionally, the study determined that key non-financial measures of SC performance are customer satisfaction, delivery performance, quality services, improved relationships, and competitive advantages. According to the study, the appropriate approaches for assessing SC performance are financial and non-financial measures. Using the same approach, measures, and metrics at all SC nodes is essential to determine SC performance appropriately. Moreover, research is needed to identify the benefits and issues preventing SC measurements and performance across different industries.</p></div>","PeriodicalId":54095,"journal":{"name":"Asia-Pacific Financial Markets","volume":"33 2","pages":"505 - 535"},"PeriodicalIF":2.6,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147682721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Market Timing and Managerial Talent 市场时机与管理人才

IF 2.6

Asia-Pacific Financial Markets Pub Date : 2025-04-25 DOI: 10.1007/s10690-025-09529-3

Keming Li

引用次数: 0

Predicting Financial Distress Using Machine Learning Techniques 使用机器学习技术预测财务困境

IF 2.6

Asia-Pacific Financial Markets Pub Date : 2025-04-24 DOI: 10.1007/s10690-025-09525-7

Pallavi Sethi, Archana Singh, Vikas Gupta

{"title":"Predicting Financial Distress Using Machine Learning Techniques","authors":"Pallavi Sethi, Archana Singh, Vikas Gupta","doi":"10.1007/s10690-025-09525-7","DOIUrl":"10.1007/s10690-025-09525-7","url":null,"abstract":"<div><p>Bankruptcy in future would lead to heavy losses, and attempts should be made to reduce it and prevent such a loss in advance. Potential misclassification of potential and futurist bankruptcy can be referred to as an audit failure. Predicting bankruptcy for different users, including investors, auditors, creditors and regulators, is essential. Various prediction models have been considered in other studies, and this research study includes multiple techniques like random forest, ANN, and logistic regression. The main reason behind the prediction of financial distress is that it will help ensure an increase in compatibility with the decision-making process. In this study, 1111 companies were considered liquidated and restructured by NCLT since its inception, i.e., 2016. Of these, 342 companies had their resolution plan approved from 2017 to 18 till December 2023, while 769 companies were liquidated. The selected companies’ financial information has been considered for the last five years, and machine learning (Random forest, Artificial neural network) and traditional models (Logistic regression) have been used to predict the outcome of the firm (in terms of bankruptcy or restructuring) with their respective level of accuracy. The study, firstly, reveals that machine learning models have better predictive accuracy than statistical models. Secondly, the model’s predictive accuracy is highest near the year/event of distress; as we move further from the year of liquidation/restructuring, the accuracy declines. Thirdly, financial variables and firm-specific characteristics have better precision and accuracy than only assessing the firms based on economic parameters.</p></div>","PeriodicalId":54095,"journal":{"name":"Asia-Pacific Financial Markets","volume":"33 2","pages":"857 - 879"},"PeriodicalIF":2.6,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147682720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

From Global Financial Crisis to COVID-19: The Changing Multiscale Systematic Risks in Asian Stock Markets 从全球金融危机到新冠肺炎：亚洲股市多尺度系统性风险的变化

IF 2.6

Asia-Pacific Financial Markets Pub Date : 2025-04-17 DOI: 10.1007/s10690-025-09526-6

Aswini Kumar Mishra, Mihir Dinesh Mahajan, Bibhu Prasad Kar, K Kamesh Anand

{"title":"From Global Financial Crisis to COVID-19: The Changing Multiscale Systematic Risks in Asian Stock Markets","authors":"Aswini Kumar Mishra, Mihir Dinesh Mahajan, Bibhu Prasad Kar, K Kamesh Anand","doi":"10.1007/s10690-025-09526-6","DOIUrl":"10.1007/s10690-025-09526-6","url":null,"abstract":"<div><p>This paper examines the impact of the 2008 subprime mortgage crisis and the 2020 COVID-19 crisis on the multiscale nature of systemic and market risk by examining daily return data for eight Asian stock indices from 2005 to 2020, divided into five periods: precrisis, crisis, recovery, post recovery, and COVID-19. The daily log returns data for stock market indices are decomposed using the maximal overlap discrete wavelet transform is used to decompose the daily log returns of the stock indices. This decomposition is then utilized and then used to estimate the linear CAPM (capital asset pricing model) beta and R<sup>2</sup> values using the US equity market as a benchmark. The findings show that beta and R<sup>2</sup> values tend to rise at larger scales and are regarded as high during crisis situations relative to other times (when the correlation is statistically insignificant). Multiscale betas confirm that investors’ trading techniques affect their time horizons. The variance decomposition study revealed that transitory variables influenced the financial contagion of the COVID-19 crisis.</p></div>","PeriodicalId":54095,"journal":{"name":"Asia-Pacific Financial Markets","volume":"33 2","pages":"881 - 908"},"PeriodicalIF":2.6,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147682757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Nexus Between ESG Performance and Credit Risk in Chinese FinTech Companies 中国金融科技公司ESG绩效与信用风险的关系

IF 2.6

Asia-Pacific Financial Markets Pub Date : 2025-04-11 DOI: 10.1007/s10690-025-09528-4

Li Zeng, Wee-Yeap Lau

引用次数: 0

Do Business Group Affiliation and Corporate Social Responsibility help or Hurt Firm Performance? An Empirical Investigation 企业集团隶属关系和企业社会责任对企业绩效是有利还是有害？实证调查

IF 2.6

Asia-Pacific Financial Markets Pub Date : 2025-04-07 DOI: 10.1007/s10690-025-09527-5

Ritu Pareek, Subhas Mondal, Krishna Dayal Pandey, Tarak Nath Sahu

{"title":"Do Business Group Affiliation and Corporate Social Responsibility help or Hurt Firm Performance? An Empirical Investigation","authors":"Ritu Pareek, Subhas Mondal, Krishna Dayal Pandey, Tarak Nath Sahu","doi":"10.1007/s10690-025-09527-5","DOIUrl":"10.1007/s10690-025-09527-5","url":null,"abstract":"<div><p>The study aims to explore the dynamic relationship between CSR and firm performance, in light of business group affiliation. Then the study also provides efforts to identify the threshold level of CSR, that has a favorable impact on FP.The study explores the relationship by applying both the static and dynamic panel estimation (i.e. System-GMM) techniques, based on a sample of 283 non-financial firms listed in the National Stock Exchange (NSE), for the period of six years from 2017 to 18 to 2022-23. The study shows a significant negative impact of business group on firm performance. In addition, an inverted-U shaped relationship has been found while analyzing the relationship between CSR and FP. An increase in the level of CSR is found to positively affect the firm’s market value until a threshold level of 67.75 disclosure scores. The two-fold impact of CSR on performance demonstrates that the beneficial antecedents provide increasing outcomes till a particular level, beyond which it yields negative outcomes due to the additional cost. From the study, it can be inferred that the corporate managers must be concerned towards optimizing the level of CSR, as beyond a certain threshold indulging in CSR might be a hindrance for FP. The presence of non-linear relationship between CSR and FP in light of BG, and the certain threshold level providing the two-fold outcome endeavored by this research is a rare effort in an emerging economy like India.</p></div>","PeriodicalId":54095,"journal":{"name":"Asia-Pacific Financial Markets","volume":"33 2","pages":"909 - 933"},"PeriodicalIF":2.6,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147682718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analyst Reports and Stock Performance: Evidence From the Chinese Market 分析师报告与股票表现：来自中国市场的证据

IF 2.6

Asia-Pacific Financial Markets Pub Date : 2025-04-03 DOI: 10.1007/s10690-025-09522-w

Rui Liu, Jiayou Liang, Haolong Chen, Yujia Hu

引用次数: 0

Modeling Electricity Prices with Stochastic Langevin Equations 用随机朗格万方程建模电价

IF 2.6

Asia-Pacific Financial Markets Pub Date : 2025-03-26 DOI: 10.1007/s10690-024-09508-0

Markus Hess

引用次数: 0