利用高频数据的 GARCH 模型比较印度新兴纺织业和金融科技业的投资决策

IF 1 4区 工程技术 Q3 MATERIALS SCIENCE, TEXTILES
Bharat Kumar Meher, G. Puntambekar, Ramona Birau, Iqbal Thonse Hawaldar, C. Spulbar, M. Simion
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引用次数: 0

摘要

2021 年,印度国内纺织品和服装业的产值为 1,520 亿美元,年复合增长率为 12%,到 2025 年将达到 2,250 亿美元。印度的纺织品和服装行业在从纤维、纱线、面料到服装的整个价值链中都具有优势。另一方面,在 "非货币化 "和 "COVID-19 "大流行期间,许多金融科技公司获得了足够的重视和关注,因为在这种情况下,大多数人都依赖并喜欢无现金支付和收据,而不是硬现金支付和收据。由于印度金融科技公司的发展,印度的消费贷款金融科技公司占金融科技企业总数的 17%。许多天使投资人纷纷前来投资此类金融科技公司,因为该行业未来的发展潜力巨大。由于印度的金融科技公司有足够的扩张空间,散户投资者纷纷前来投资金融科技上市公司的股票。由于散户投资者总是期待以股息或股价升值的形式获得回报,因此在投资前对印度金融科技公司的股价波动进行分析和建模也很有必要。因此,本研究尝试使用高频数据,即 1 分钟收盘价,为上市纺织品公司和金融科技公司的股票价格波动建立合适的 GARCH(广义自回归条件异方差)模型,如果由于 COVID-19 大流行病第三阶段和俄罗斯-乌克兰战争而存在非对称波动,该模型也可以捕捉到这种非对称波动。结果得出结论,COVID-19 大流行病的第三波可能再次刺激了对这些金融科技公司(即 Paytm 和 PolicyBazaar)的金融产品和服务的需求,因此存在正向冲击,而俄乌战争则不存在负向冲击。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparative investment decisions in emerging textile and FinTech industries in India using GARCH models with high-frequency data
The domestic textiles and apparel industry stood at $152 billion in 2021, growing at a CAGR of 12% to reach $225 billion by 2025. The textiles and apparel industry in India has strengths across the entire value chain from fibre, yarn, and fabric to apparel. On the other hand, many FinTech companies gained enough importance and attention during the Demonetization and COVID-19 pandemic situation where most people are dependent and prefer cashless payments and receipts over hard cash payments and receipts. Due to the growth of FinTech companies in India, consumer lending FinTech companies in India make up 17% of total FinTech enterprises. Many angel investors are coming forward to invest in such FinTech companies as this industry has much potential to grow in future. As there is enough scope for the expansion of FinTech companies in India, retail investors come forward to invest in the stocks of listed FinTech companies. As retail investors always look forward to returns either in the form of dividends or appreciation of stock prices, it is also necessary to analyse and model the stock price volatility of FinTech companies in India before investing. Hence, this research study is an attempt to use high-frequency data i.e. 1-minute closing prices, to formulate suitable GARCH (Generalised Autoregressive Conditional Heteroscedasticity) models for stock price volatility of listed textiles and FinTech companies that could also capture the asymmetric volatility if it exists due to third phase of COVID-19 pandemic and Russia-Ukraine war. The results concluded that there is a presence of positive shocks which might be due to the third wave of the COVID-19 pandemic that might have again shot the demand for financial products and services of these FinTech companies namely Paytm and PolicyBazaar and there is no negative shock of Russia-Ukraine war.
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来源期刊
Industria Textila
Industria Textila 工程技术-材料科学:纺织
CiteScore
1.80
自引率
14.30%
发文量
81
审稿时长
3.5 months
期刊介绍: Industria Textila journal is addressed to university and research specialists, to companies active in the textiles and clothing sector and to the related sectors users of textile products with a technical purpose.
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