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Impact of climate change on dynamic tail-risk connectedness among stock market social sectors: Evidence from the US, Europe, and China
IF 3.8 3区 经济学 Q1 BUSINESS, FINANCE Pub Date : 2024-11-26 DOI: 10.1016/j.najef.2024.102319
Yufei Cao
This paper studies the impact of climate change risk (including physical and transition risk) on the tail-risk connectedness among ten stock market social sectors in the US, Europe and China. To this end, we first combine ARMA-GJR-GARCH models with a time-varying parameter autoregression (TVP-VAR) approach to examine the transmission of tail-risk among sectors. Then, we use predictive regression models to examine the contribution of climate change to tail-risk spillovers. Over the sample period from January 2013 to September 2023, we obtain two main results. First, the COVID-19 epidemic has resulted in significantly greater losses for social sectors in the US and Europe than for those in China. Additionally, the industrial sector is a common source of tail-risk shocks across all three economies. Second, physical risk contributes to higher overall and directional tail-risk connectedness, while an increase in transition risk has the opposite effect on both. However, the impact of physical and transition risk on the net tail-risk connectedness for each sector shows both positive and negative effects. Our findings indicate that physical and transition risk have different effects on tail-risk connectedness among social sectors.
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引用次数: 0
Financial regulatory policy uncertainty: An informative predictor for financial industry stock returns
IF 3.8 3区 经济学 Q1 BUSINESS, FINANCE Pub Date : 2024-11-26 DOI: 10.1016/j.najef.2024.102321
Yaojie Zhang , Xinyi Zhao , Zhikai Zhang
We find that financial regulatory policy uncertainty is an informative indicator for predicting returns of financial industry stocks, outperforming popular predictive variables both in-sample and out-of-sample. Mean-variance investors can achieve substantial economic gains by allocating assets based on the information provided by the financial regulatory policy uncertainty index. Placebo tests suggest that other policy uncertainty indices do not provide predictive information for stock returns of the financial industry, and financial regulatory policy uncertainty cannot forecast stock returns of other industries. We demonstrate that the predictive power of financial regulatory policy uncertainty stems from the cash flow channel, potentially due to the inhibitory effect of uncertainty on firms’ economic activities.
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引用次数: 0
A multifaceted graph-wise network analysis of sector-based financial instruments’ price-based discrepancies with diverse statistical interdependencies
IF 3.8 3区 经济学 Q1 BUSINESS, FINANCE Pub Date : 2024-11-22 DOI: 10.1016/j.najef.2024.102316
Insu Choi, Woo Chang Kim
We explore discrepancies in financial networks, focusing on sector-based exchange-traded funds, through an in-depth analysis using statistical measures to validate interdependencies. By adopting methodologies such as the Minimum Spanning Tree, Average Linkage Minimum Spanning Tree, p-value-based networks, and Planar Maximally Filtered Graph, we investigate price-based discrepancies to uncover underlying network structures within financial data. Our key contribution is showing how employing a variety of measures and network analyses can offer diverse insights into financial markets. This approach enhances our understanding of market dynamics and provides a comprehensive framework for examining the intricate web of relationships that underpin the financial market.
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引用次数: 0
Which opinion is more trustworthy: An analysts’ earnings forecast quality assessment framework based on machine learning 哪种观点更值得信赖?基于机器学习的分析师盈利预测质量评估框架
IF 3.8 3区 经济学 Q1 BUSINESS, FINANCE Pub Date : 2024-11-22 DOI: 10.1016/j.najef.2024.102318
Yingying Song , Xinxin Chen
Analysts’ Earnings Forecast (AEF) is a crucial reference in investment decision-making and significantly impact capital market efficiency. While much research has focused on the factors influencing AEF, the variability and disparity in its quality have often been overlooked. This study presents a machine learning (ML)-based framework for assessing and forecasting AEF quality, including multi-perspective feature generation, rank aggregation-based heterogeneous ensemble feature selection, and quality forecasting. We validate this framework on a real-world dataset and use an explainable approach to identify the key features affecting AEF quality from a data-driven perspective. Our analyses reveal the unique characteristics of the China’s A-share market in terms of AEF quality forecasting and investigate the sensitivity of feature combinations from the perspectives of state ownership and industry. On the basis of our assessment, we develop an investment strategy to demonstrate economic value. Our findings offer insights for regulators and brokerage houses, helping investors mitigate the risks associated with low-quality opinions.
分析师盈利预测(AEF)是投资决策的重要参考,对资本市场的效率有重大影响。尽管许多研究都关注 AEF 的影响因素,但其质量的可变性和差异往往被忽视。本研究提出了一种基于机器学习(ML)的评估和预测 AEF 质量的框架,包括多视角特征生成、基于等级聚合的异构集合特征选择和质量预测。我们在真实世界的数据集上验证了这一框架,并使用可解释的方法从数据驱动的角度识别影响 AEF 质量的关键特征。我们的分析揭示了中国 A 股市场在 AEF 质量预测方面的独特性,并从国有制和行业的角度研究了特征组合的敏感性。在评估的基础上,我们制定了投资策略,以展示经济价值。我们的研究结果为监管机构和券商提供了启示,帮助投资者降低与低质量意见相关的风险。
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引用次数: 0
Volatility estimation through stochastic processes: Evidence from cryptocurrencies 通过随机过程估算波动率:加密货币的证据
IF 3.8 3区 经济学 Q1 BUSINESS, FINANCE Pub Date : 2024-11-21 DOI: 10.1016/j.najef.2024.102320
Murad Harasheh , Ahmed Bouteska
We apply stochastic volatility modeling enriched with leverage and an asymmetrically heavy-tailed distribution to analyze the returns of Bitcoin and Ethereum. Our methodology leverages the generalized hyperbolic skew Student’s t-distribution (GH-ASV-skw-st) framework, as proposed by Nakajima and Omori (2012), employing a Bayesian Markov chain Monte Carlo (MCMC) sampling technique for effectiveness evaluation. The GH-ASV-skw-st model is demonstrated to adeptly capture the stochastic volatility patterns present in the returns of cryptocurrencies. After validation with several diagnostics and robustness checks, we illustrate the model’s suitability for high-volatility series by capturing asymmetry, leverage effects, and tail risk. Our findings indicate that the model fits the data more precisely than traditional models and provides a more reliable foundation for risk measures essential to portfolio management, such as Value at Risk (VaR) and Expected Shortfall (ES).
我们采用富含杠杆和非对称重尾分布的随机波动率模型来分析比特币和以太坊的收益。我们的方法利用了 Nakajima 和 Omori(2012 年)提出的广义双曲偏斜学生 t 分布(GH-ASV-skw-st)框架,采用贝叶斯马尔科夫链蒙特卡罗(MCMC)抽样技术进行有效性评估。结果表明,GH-ASV-skw-st 模型能很好地捕捉加密货币收益中存在的随机波动模式。经过若干诊断和稳健性检查验证后,我们通过捕捉非对称性、杠杆效应和尾部风险说明了该模型对高波动性系列的适用性。我们的研究结果表明,该模型比传统模型更精确地拟合数据,并为风险价值(VaR)和预期缺口(ES)等投资组合管理所必需的风险度量提供了更可靠的基础。
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引用次数: 0
Does economic policy uncertainty matter to corporate default probability? findings from theoretic analyses and China’s listed firms 经济政策的不确定性对企业违约概率有影响吗? 来自理论分析和中国上市公司的结论
IF 3.8 3区 经济学 Q1 BUSINESS, FINANCE Pub Date : 2024-11-16 DOI: 10.1016/j.najef.2024.102313
Junrong Liu , Guoying Deng , Jingzhou Yan , Shibo Ma
This paper conducts a theoretical–empirical study to investigate the nexus between economic policy uncertainty (EPU) and corporate default probability (CDP) and documents a significant and positive impact of EPU on CDP, which is validated through rigorous robustness tests and local project estimations. The study also reports that the increasing term structure of bond maturity aggravates the impact of EPU on CDP systematically. Our findings pronounce that EPU brings about the erosion of firm financing capacity, management quality deterioration, lowered stock liquidity, and corporate sentimental depression, providing an effective conducting mechanism to breed an increase in CDP. Additionally, state ownership, high technology, and internationalization curtail the CDP-increasing effect of EPU, and the same in the manufacturing sector. Whereas, this effect is intensified in non-state-owned, low-tech, service, and non-internationalized enterprises. We also highlight that EPU can robustly predict in the subsequent 2 years. This study suggests that the corporate financial position well reflects EPU and the relevant stakeholders, both governments and firms, may improve financial risk management by considering EPU and the attribute of its impacting CDP.
本文通过理论-实证研究探讨了经济政策不确定性(EPU)与企业违约概率(CDP)之间的关系,并记录了经济政策不确定性对企业违约概率的显著正向影响,通过严格的稳健性检验和局部项目估计验证了这一点。研究还指出,债券到期期限结构的增加会系统性地加剧 EPU 对 CDP 的影响。我们的研究结果表明,EPU 带来了企业融资能力的削弱、管理质量的下降、股票流动性的降低和企业情绪的低落,为 CDP 的增长提供了有效的传导机制。此外,国有制、高科技和国际化抑制了 EPU 的 CDP 增加效应,制造业也是如此。而在非国有、低技术、服务和非国际化企业中,这种效应则会加强。我们还强调,EPU 可以稳健地预测随后两年的情况。这项研究表明,企业财务状况能够很好地反映 EPU,相关利益方(包括政府和企业)可以通过考虑 EPU 及其影响 CDP 的属性来改进财务风险管理。
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引用次数: 0
Spatial linkages of positive feedback trading among the stock index futures markets 股指期货市场间正反馈交易的空间联系
IF 3.8 3区 经济学 Q1 BUSINESS, FINANCE Pub Date : 2024-11-15 DOI: 10.1016/j.najef.2024.102315
Shuxi Tian , Shuyi Liu , Lijie Mu
Positive feedback trading, a destabilizing sentiment-driven strategy, executes purchases after price upswings and vice versa, driving price away from economic fundamentals in the short term. We apply spatial econometric approach to investigate the linkages of positive feedback trading among the stock index futures markets of 27 countries from 2010 to 2023, and the empirical results reveal that there exist not only significant local effects but also strong spatial spillovers in positive feedback trading among these markets. Moreover, we find that the spatial linkages of positive feedback trading are stronger in an upward trend when market volatility exceeds 2 % but more pronounced in the downward trend when the market volatility exceeds 4 %. Overall, our empirical findings are of considerable concern for global investors who use index futures to hedge or exploit arbitrage opportunities, as well as inspiring for policymakers to manage financial derivatives trading risk.
正反馈交易是一种破坏稳定的情绪驱动策略,在价格上涨后进行购买,反之亦然,在短期内使价格偏离经济基本面。我们运用空间计量经济学方法研究了 2010 年至 2023 年 27 个国家股指期货市场之间正反馈交易的联系,实证结果表明,这些市场之间的正反馈交易不仅存在显著的局部效应,而且存在很强的空间溢出效应。此外,我们还发现,当市场波动率超过 2% 时,正反馈交易的空间联系在上升趋势中更为强烈,而当市场波动率超过 4% 时,正反馈交易的空间联系在下降趋势中更为明显。总体而言,我们的实证研究结果对于利用股指期货套期保值或利用套利机会的全球投资者来说相当值得关注,对于政策制定者管理金融衍生品交易风险也有启发意义。
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引用次数: 0
ESG rating and default risk: Evidence from China ESG评级与违约风险:来自中国的证据
IF 3.8 3区 经济学 Q1 BUSINESS, FINANCE Pub Date : 2024-11-15 DOI: 10.1016/j.najef.2024.102314
Huihui Li, Yonghong Hu
Based on the data of Chinese A-share listed companies from 2009 to 2022, this study constructs a bivariate panel vector autoregression (PVAR) model to examine the dynamic equilibrium relationship between default risk and environmental, social, and governance (ESG) performance and its individual dimensions. Results indicate that ESG performance and corporate stability exhibit growth inertia and self-reinforcing mechanisms, with overall ESG performance significantly mitigating default risk. Although no bidirectional causality was found between environmental and governance performance and default risk, corporate stability positively impacts both over time. The findings indicate a synergistic relationship between social performance and default risk, in which strong social performance helps mitigate default risk. Financial stability encourages companies to engage in social responsibility initiatives. Heterogeneity analysis demonstrates that the mitigating effects of ESG performance on default risk are more pronounced for non-state-owned enterprises (non-SOEs) and small- and medium-sized enterprises (SMEs). Social responsibility and corporate governance are more significant in enhancing financial stability in manufacturing firms. These findings provide valuable insights for investors and policymakers in mitigating default risks while promoting the development of green finance.
本研究基于2009-2022年中国A股上市公司数据,构建双变量面板向量自回归(PVAR)模型,检验违约风险与环境、社会和治理(ESG)绩效及其各维度之间的动态均衡关系。结果表明,环境、社会和治理绩效与企业稳定性之间呈现出增长惯性和自我强化机制,环境、社会和治理的整体绩效显著降低了违约风险。虽然在环境和治理绩效与违约风险之间没有发现双向因果关系,但随着时间的推移,公司稳定性对两者都有积极影响。研究结果表明,社会绩效与违约风险之间存在协同关系,即强有力的社会绩效有助于降低违约风险。财务稳定性鼓励公司参与社会责任倡议。异质性分析表明,环境、社会和治理绩效对违约风险的缓解作用在非国有企业和中小型企业中更为明显。社会责任和公司治理对提高制造业企业的财务稳定性更有意义。这些发现为投资者和政策制定者在促进绿色金融发展的同时降低违约风险提供了有价值的见解。
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引用次数: 0
Decoding the stock market dynamics in the banking sector: Short versus long-term insights 解密银行业的股市动态:短期与长期见解
IF 3.8 3区 经济学 Q1 BUSINESS, FINANCE Pub Date : 2024-11-13 DOI: 10.1016/j.najef.2024.102311
Barbara Čeryová, Peter Árendáš
The severity of extreme fluctuations and crises within the global banking sector is escalating. Conventional models, operating on a single time scale, may misinterpret any shift as a change in the long-term trend, distorting market insights. To address this issue, the present paper introduces a hierarchical structure into the standard hidden Markov model, enabling the differentiation of short and long-term trends within the U.S. banking industry. Using NASDAQ Bank stock market index data from January 1, 2007, to July 31, 2023 at two different frequencies, we construct and evaluate different calibrations of the hierarchical hidden Markov model. Results reveal two long-term regimes: turbulent periods with high volatility, instability, and negative returns, and prevalent stable markets. Within each of them, two distinct states representing short-term trends are identified, exhibiting significant differences in persistence, likelihood, expected returns, and risk profiles. The results show that an investor should carefully differentiate between regimes on both hierarchies to make informed investment decisions.
全球银行业极端波动和危机的严重程度正在不断升级。在单一时间尺度上运行的传统模型可能会将任何变化误解为长期趋势的变化,从而扭曲市场洞察力。为了解决这个问题,本文在标准隐马尔科夫模型中引入了分层结构,从而能够区分美国银行业的短期和长期趋势。利用 2007 年 1 月 1 日至 2023 年 7 月 31 日两种不同频率的纳斯达克银行股票市场指数数据,我们构建并评估了分层隐马尔可夫模型的不同校准。结果显示了两种长期机制:具有高波动性、不稳定性和负收益的动荡时期,以及普遍稳定的市场。在每种情况下,都能识别出代表短期趋势的两种截然不同的状态,它们在持续性、可能性、预期收益和风险概况方面都存在显著差异。结果表明,投资者应仔细区分这两个层次上的不同状态,以做出明智的投资决策。
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引用次数: 0
Static and dynamic return and volatility connectedness between transportation tokens and transportation indices: Evidence from quantile connectedness approach 交通代币与交通指数之间的静态和动态收益率与波动率关联性:量化关联性方法的证据
IF 3.8 3区 经济学 Q1 BUSINESS, FINANCE Pub Date : 2024-11-10 DOI: 10.1016/j.najef.2024.102312
Erkan Ustaoglu
The aim of the study is to examine the return and volatility connectedness between transportation tokens and transportation stock indices. Since the QVAR model is used in the study, we can obtain information about the return and volatility connectedness between assets not only under normal market conditions but also under extreme market conditions. The return and volatility spillovers between transportation tokens and transportation stock indices are time-varying and also vary under different market conditions. Under normal market conditions, transportation tokens and transportation indices are largely unconnected. The return connectedness between the assets increases significantly during extreme market downturns and upturns, with similar increases in volatility connectedness during periods of extreme volatility. Return and volatility connectedness between assets are affected by extreme events such as COVID-19, the Russia–Ukraine war, and the collapse of the cryptocurrency market. The study investigates the determinants of total return and volatility connectedness between transportation tokens and transportation stock indices. It is found that EPU, GVZ, VIX, and crises are significant determinants affecting the return and volatility connectivity between transportation tokens and transportation stock indices across all market conditions. The results are significant for strategies to be implemented by investors and portfolio managers.
本研究的目的是考察交通代币与交通股指数之间的收益和波动关联性。由于研究中使用了 QVAR 模型,因此我们不仅可以获得正常市场条件下的资产回报率和波动率关联信息,还可以获得极端市场条件下的资产回报率和波动率关联信息。交通代币与交通股指之间的收益和波动溢出效应是时变的,在不同的市场条件下也各不相同。在正常市场条件下,交通代币和交通指数之间基本没有联系。在市场极度低迷和上升期间,资产之间的收益关联性会显著增加,在极度波动期间,波动关联性也会类似增加。资产间的收益率和波动率关联性受到 COVID-19、俄乌战争和加密货币市场崩溃等极端事件的影响。本研究调查了交通代币与交通股指之间总回报率和波动率关联性的决定因素。研究发现,在所有市场条件下,EPU、GVZ、VIX 和危机都是影响交通代币与交通股指之间回报和波动连接性的重要决定因素。研究结果对投资者和投资组合经理实施策略具有重要意义。
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引用次数: 0
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North American Journal of Economics and Finance
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