Asia-Pacific Financial Markets最新文献_第5页

Carry Trade Dynamics Under Capital Controls: The Case of China 资本管制下的套利交易动态：中国案例

IF 2.5

Asia-Pacific Financial Markets Pub Date : 2023-11-22 DOI: 10.1007/s10690-023-09441-8

Christopher Balding, Andros Gregoriou, Domenico Tarzia, Xiao Zhang

引用次数: 0

Anomaly Identification and Premium Mining: Evidence from Chinese Urban Construction Investment Bonds 异常识别与溢价挖掘：中国城市建设投资债券的证据

IF 2.5

Asia-Pacific Financial Markets Pub Date : 2023-11-20 DOI: 10.1007/s10690-023-09437-4

Ping Li, Jiahong Li, Dong Wang

引用次数: 0

An Empirical Investigation on Financing Choice Descendants of Indian Start-ups 印度初创企业融资选择后代的实证研究

IF 2.5

Asia-Pacific Financial Markets Pub Date : 2023-11-15 DOI: 10.1007/s10690-023-09434-7

Priyanka Runach, Shubham Garg, Karam Pal Narwal

{"title":"An Empirical Investigation on Financing Choice Descendants of Indian Start-ups","authors":"Priyanka Runach, Shubham Garg, Karam Pal Narwal","doi":"10.1007/s10690-023-09434-7","DOIUrl":"10.1007/s10690-023-09434-7","url":null,"abstract":"<div><p>The primary goal of the study is to examine the factors affecting the financial leverage of unicorn start-ups in India. In order to achieve this goal, the study has employed the panel data techniques on the financial data of 25 start-ups unicorn of India from 2017 to 2021. The study has employed three proxies to measure the financial leverage namely short-run, long-run, and total debt ratio. The result of the study indicates that firm size and profitability are significantly negatively correlated with debt ratios, whilst tangibility, business risk, and firm age are positively and significantly associated. Moreover, short-term debt is found to be more prevalent in unicorn firms when we bifurcate total debt into short and long-term debt. As per the best of author’s knowledge, this is the first research that identified the financial choice of startups. Furthermore, this study provides a pathway for conducting future study in this domain on startup firms’ capital structure decisions. This study has major implications for unicorn managements in taking decisions regarding their finance choice that may lead them to plan adequately their capital structure more efficiently and effectively.</p></div>","PeriodicalId":54095,"journal":{"name":"Asia-Pacific Financial Markets","volume":"31 4","pages":"867 - 888"},"PeriodicalIF":2.5,"publicationDate":"2023-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138506447","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

Identifying Cryptocurrencies as Diversifying Assets and Safe Haven in the Indian Stock Market 将加密货币确定为印度股市的多元化资产和避风港

IF 2.5

Asia-Pacific Financial Markets Pub Date : 2023-11-03 DOI: 10.1007/s10690-023-09436-5

Susovon Jana, Tarak Nath Sahu

{"title":"Identifying Cryptocurrencies as Diversifying Assets and Safe Haven in the Indian Stock Market","authors":"Susovon Jana, Tarak Nath Sahu","doi":"10.1007/s10690-023-09436-5","DOIUrl":"10.1007/s10690-023-09436-5","url":null,"abstract":"<div><p>This study investigates the interconnectedness between cryptocurrency and the Indian stock market and explores the diversification, hedge, and safe haven potential of cryptocurrency. The study employs the wavelet approach on daily data from October 6, 2017, to October 5, 2022, to execute the empirical analysis. The findings confirm that, in a healthy economic environment, cryptocurrencies are not connected with the Indian stock market. However, during times of financial turmoil, Bitcoin, Ethereum, and Cardano are positively correlated with the stock market. Additionally, the study identifies Bitcoin, Ethereum, Dogecoin, and Cardano as competent in providing diversification, or hedge opportunities in normal economic situations. But during periods of financial stress, only Dogecoin may act as a safe haven asset. This is the first study to explore the time-varying correlations and causal dependencies between the stock and cryptocurrency markets in India using the wavelet approach. It extends the literature in finance by examining both normal and economic turmoil periods, providing insights for portfolio managers, policymakers, and investors on how to manage their portfolios during these periods.</p></div>","PeriodicalId":54095,"journal":{"name":"Asia-Pacific Financial Markets","volume":"31 4","pages":"925 - 944"},"PeriodicalIF":2.5,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135818517","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

Network Nexus: Exploring the Impact of Alumni Connections of Managers on Mutual Fund Performance in India 网络联系：探索经理人的校友关系对印度共同基金业绩的影响

IF 2.5

Asia-Pacific Financial Markets Pub Date : 2023-10-29 DOI: 10.1007/s10690-023-09435-6

Sudipta Majumdar, Sayantan Kundu, Sankalp Bose, Abhijeet Chandra

引用次数: 0

Systemic Risk in Indian Financial Institutions: A Probabilistic Approach 印度金融机构的系统性风险：概率论方法

IF 2.5

Asia-Pacific Financial Markets Pub Date : 2023-10-18 DOI: 10.1007/s10690-023-09426-7

Subhash Karmakar, Gautam Bandyopadhyay, Jayanta Nath Mukhopadhyay

{"title":"Systemic Risk in Indian Financial Institutions: A Probabilistic Approach","authors":"Subhash Karmakar, Gautam Bandyopadhyay, Jayanta Nath Mukhopadhyay","doi":"10.1007/s10690-023-09426-7","DOIUrl":"10.1007/s10690-023-09426-7","url":null,"abstract":"<div><p>In this paper, we have carried out the predictions for growth or spurt in Systemic Risk across the different categories of financial institutions in India relative to the change in the market prices. We have used Bayes Theorem along with Logistic regressions to work out the actual probabilities regarding the growth in Systemic Risk with the fall in stock prices and Wilcoxon Rank sum Test to validate the robustness of the models. In this paper, we have studied the period from July 2007 to December 2020. An important feature observed was any fall in closing prices beyond 30%, is contributing for 90% growth in systemic risk. A policy implication can follow—that it is imperative to monitor a sharp decline in market prices to the tune of 30% or more by regulators to avoid a crisis. We generally presume that state ownership of Banks particularly in India generates public confidence. Our paper has been able to support the theory of public confidence wherein the Public Sector Banks are contributing less towards the growth of Systemic Risk as compared to Private Banks and NBFCs. The NBFCs are the highest contributor of the growth in systemic risk which we have differentiated from our results. So, in coming days NBFCs are to be closely monitored by the regulators and suitable regulatory measures need to be placed.</p></div>","PeriodicalId":54095,"journal":{"name":"Asia-Pacific Financial Markets","volume":"31 3","pages":"579 - 656"},"PeriodicalIF":2.5,"publicationDate":"2023-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135883154","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

Can Clean Energy Stocks Predict Crude Oil Markets Using Hybrid and Advanced Machine Learning Models? 清洁能源股票能否利用混合和高级机器学习模型预测原油市场？

IF 2.5

Asia-Pacific Financial Markets Pub Date : 2023-10-11 DOI: 10.1007/s10690-023-09432-9

Anis Jarboui, Emna Mnif

{"title":"Can Clean Energy Stocks Predict Crude Oil Markets Using Hybrid and Advanced Machine Learning Models?","authors":"Anis Jarboui, Emna Mnif","doi":"10.1007/s10690-023-09432-9","DOIUrl":"10.1007/s10690-023-09432-9","url":null,"abstract":"<div><p>The volatility of crude oil markets and the pressing need for sustainable energy solutions have sparked significant interest in forecasting methodologies that can better capture market dynamics and incorporate environmentally responsible indicators. In this study, we address the gaps in the literature by proposing novel hybrid approaches based on combining wavelet decomposition with machine learning techniques (ANN-Wavelet and SVR-Wavelet) and advanced machine learning techniques (XGBoost and GBM) with advanced clean energy indicators to predict crude oil prices. These hybrid models significantly advance the field by reducing noise and improving result accuracy. Besides, these approaches were used to determine the best model for predicting crude oil market prices. Additionally, we employed the SHapely Additive exPlanations (SHAP) algorithm to analyze and interpret the models, enhancing transparency and explainability. Subsequently, we applied SHAP to investigate the predictive value of various asset classes, including the volatility index (VIX), precious metal markets (gold and silver), fuel markets (gasoline and natural gas), as well as green and renewable energy indices, about crude oil prices. The results reveal that the wavelet-SVR model demonstrates consistent and robust forecasting performance with low RMSE and MAPE values. Additionally, the GBM model emerges as highly accurate, yielding shallow forecasting errors. Conversely, the wavelet-ANN and XGBoost models exhibit mixed performance, showing effectiveness in the Full Sample but reduced accuracy during the Russia–Ukraine conflict. Notably, green and renewable energy markets, such as CGA and NextEra energy (NEE), emerge as significant predictors in forecasting crude oil prices. This research provides critical guidance amidst the Russia–Ukraine conflict in predicting oil prices by emphasizing the importance of incorporating environmentally responsible indicators into investment portfolios and policy choices.</p></div>","PeriodicalId":54095,"journal":{"name":"Asia-Pacific Financial Markets","volume":"31 4","pages":"821 - 844"},"PeriodicalIF":2.5,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136099474","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

Functional Cointegration Test for Expectation Hypothesis of the Term Structure of Interest Rates in China 中国利率期限结构预期假说的函数协整检验

IF 2.5

Asia-Pacific Financial Markets Pub Date : 2023-10-05 DOI: 10.1007/s10690-023-09431-w

Yizheng Fu, Zhifang Su, Aihua Lin

引用次数: 0

Reactions of Global Stock Markets to the Russia–Ukraine War: An Empirical Evidence 全球股市对俄乌战争的反应：经验证据

IF 2.5

Asia-Pacific Financial Markets Pub Date : 2023-10-05 DOI: 10.1007/s10690-023-09429-4

Emon Kalyan Chowdhury, Iffat Ishrat Khan

{"title":"Reactions of Global Stock Markets to the Russia–Ukraine War: An Empirical Evidence","authors":"Emon Kalyan Chowdhury, Iffat Ishrat Khan","doi":"10.1007/s10690-023-09429-4","DOIUrl":"10.1007/s10690-023-09429-4","url":null,"abstract":"<div><p>This study measures the immediate impact of Russia–Ukraine war on the global stock markets for the first four months since Russia’s first invasion attempt on February 24, 2022. Daily closing stock indices have been used from selected stock markets of six different continents. By applying event study method, it observes mixed impact on different stock markets. Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH 1,1) indicates the presence of significant volatility and leverage effect in all the markets. Regression estimates show significantly positive impact of VIX and negative impact of oil on the abnormal returns of the global stock markets. Diversifying energy supply and source, accelerating deployment of renewables and promoting electronic vehicles and machines might bring positive result for the financial market. It is expected that this research will provide policymakers, regulatory authorities, investors and all concerned stakeholders a precise guideline to handle the immediate impact of war on the stock prices and to formulate appropriate strategies to keep investment free from risk and uncertainties.</p></div>","PeriodicalId":54095,"journal":{"name":"Asia-Pacific Financial Markets","volume":"31 3","pages":"755 - 778"},"PeriodicalIF":2.5,"publicationDate":"2023-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134975167","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

Expected Power Utility Maximization of Insurers 保险公司的预期功率效用最大化

IF 2.5

Asia-Pacific Financial Markets Pub Date : 2023-10-03 DOI: 10.1007/s10690-023-09425-8

Hiroaki Hata, Kazuhiro Yasuda

引用次数: 0