检索结果-内蒙古大学图书馆

Economic policy uncertainty and stock market volatility in China: Evidence from SV-MIDAS-t model

INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS 2024年 92卷

作者： Wang, Nianling Yin, Jiyuan Li, Yong Capital Univ Econ & Business Sch Finance Beijing Peoples R China Renmin Univ China Sch Econ Beijing Peoples R China

This study combines the stochastic volatility (SV) model with a mixed data sampling (MIDAS) structure under tdistribution to investigate the effect of economic policy uncertainty (EPU) on Chinese stock market volatility. Furthermore, we compare eight volatility models regarding using "GARCH or SV" model, "with or without" the MIDAS structure, under "normal or t" distributions. The model comparison results show that SV-MIDAS-t model is the best in terms of data fitting, AIC, BIC, and various loss function criteria. Based on the SV-MIDAS-t model, we find that a rise in EPU index significantly increases the long-term component of volatility, and this impact has a time lag effect.

关键词： Economic policy uncertainty Stochastic volatility mixed data sampling Efficient importance sampling Model comparison

来源：评论

学校读者我要写书评

暂无评论

Modeling and forecasting commodity market volatility with long-term economic and financial variables

引用

JOURNAL OF FORECASTING 2020年第2期39卷 126-142页

作者： Duc Khuong Nguyen Walther, Thomas IPAG Business Sch IPAG Lab 184 Blvd St Germain F-75006 Paris France Indiana Univ Sch Publ & Environm Affairs 107 S Indiana Ave Bloomington IN 47405 USA Univ St Gallen Inst Operat Res & Computat Finance CH-9000 St Gallen Switzerland Tech Univ Dresden Fac Business & Econ D-01062 Dresden Germany

This paper investigates the time-varying volatility patterns of some major commodities as well as the potential factors that drive their long-term volatility component. For this purpose, we make use of a recently proposed generalized autoregressive conditional heteroskedasticity-mixed data sampling approach, which typically allows us to examine the role of economic and financial variables of different frequencies. Using commodity futures for Crude Oil (WTI and Brent), Gold, Silver and Platinum, as well as a commodity index, our results show the necessity for disentangling the short-term and long-term components in modeling and forecasting commodity volatility. They also indicate that the long-term volatility of most commodity futures is significantly driven by the level of global real economic activity as well as changes in consumer sentiment, industrial production, and economic policy uncertainty. However, the forecasting results are not alike across commodity futures as no single model fits all commodities.

关键词： commodity futures GARCH long-term volatility macroeconomic effects mixed data sampling

来源：评论

学校读者我要写书评

暂无评论

Diaspora investments in low & high interest rate environments

RESEARCH IN GLOBALIZATION

引用

RESEARCH IN GLOBALIZATION 2022年 5卷

作者： Adediran, Idris A. Okunade, Solomon O. Aor, Raymond L. Ctr Econometr & Appl Res Ibadan Nigeria Chrisland Univ Dept Econ Abeokuta Nigeria Benue State Univ Dept Econ Makurdi Nigeria

Diaspora investment flows measured as foreign direct investments represent one of the major outcomes of the activities of diaspora investors, entrepreneurs, and venture capitalists in the economy. This paper contributes to the literature with distinct analysis of diaspora investment flows in low interest rate environments (Canada, Denmark, Euro area, Japan, Korea Republic, Sweden and the US) and high interest rate environments (Brazil, China, Colombia, India, Indonesia, Mexico and Turkey). First, we employ the Bounds cointegration analysis to investigate whether diaspora investment integrates either of the two groups of economies. Second, we apply the Toda-Yamamoto causality approach to examine whether the interest rate environment causes diaspora investment inflows. Third, we employ the Autoregressive Distributed Lag-mixed data sampling (ADL-MIDAS) technique to evaluate the role of macroeconomic performance for attracting diaspora investments. We find proof of financial integration of diaspora investments in all the low interest rate economies, whereas the evidence is limited to three countries in the high interest rate environment. We also find that the low interest rate environment (more than the high interest rate environment) engenders diaspora investment inflows and also enhances the positive impact of macroeconomic performance in attracting diaspora investments. We highlight some insightful investment and policy implications from the findings.

关键词： Diaspora investment Interest rate environment Cointegration mixed data sampling

来源：评论

学校读者我要写书评

暂无评论

Does high crude oil dependence influence Chinese military expenditure decision-making?

引用

ENERGY STRATEGY REVIEWS 2021年 35卷 100653-100653页

作者： Wang, Kai-Hua Su, Chi-Wei Qingdao Univ Sch Econ Qingdao Peoples R China

This paper employs the mixed frequency vector autoregression (MF-VAR) to discuss the causal link between crude oil dependence and military expenditure in China. The empirical results demonstrate that the crude oil dependence Granger causes military expenditure and accounts for 66.8% of the long-run forecast error variance decomposition. That means the MF-VAR model owns stronger explanatory and asymptotic powers than conventional VAR with single frequency data. Besides, the impulse-response analysis finds time varying relationship between crude oil dependence and military expenditure across four quarters within one year period. Therefore, the Chinese People's Liberation Army, especially its Navy, is needed to take responsibility and active activities to assure crude oil transport security. Government, enterprises and institutes should increase investment in military innovation to promote the upgrading of weapons and equipment. The peaceful rise strategy should be reasserted to construct harmonious international relations, which is helpful for crude oil security, foreign energy investment and reduce unnecessary military expenditure.

关键词： Economic growth Military expenditure Crude oil dependence mixed data sampling mixed frequency vector autoregression

来源：评论

学校读者我要写书评

暂无评论

Do measures of systemic risk predict US corporate bond default rates?

引用

INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS 2020年 71卷 101553-101553页

作者： Kanas, Angelos Molyneux, Philip Univ Piraeus Piraeus Greece Univ Sharjah Sharjah U Arab Emirates Hellen Parliament Parliamentary Budget Off Athens Greece

Using univariate and multivariate mixed data sampling (MIDAS) and LASSO estimation methodologies, we explore whether the U.S. annual average corporate bond default rate can be predicted by 12 monthly systemic risk measures proposed in the literature. We find that nearly all of the systemic risk indicators have predictive power for the default rate. Granger causality tests based on multivariate mixed frequency VAR models further support this conclusion. On the basis of MIDAS models, we illustrate that five of these indicators are able to forecast out-of-sample the 2009 corporate default crisis. Using a LASSO multivariate model, it is further shown that the systemic risk indicators can forecast out-of-sample both the 2009 default rate and the default rates during the buildup before the crisis and in the aftermath of the crisis. Institution-specific and volatility systemic risk measures are the most relevant for modeling U.S. corporate bond default rates, with the Conditional VaR measure of Adrian and Brunnermeier (2016) exhibiting the best performance.

关键词： Systemic risk Corporate bond defaults mixed data sampling LASSO Predictive ability

来源：评论

学校读者我要写书评

暂无评论

Systemic risk-shifting in US commercial banking

引用

REVIEW OF QUANTITATIVE FINANCE AND ACCOUNTING 2020年第2期54卷 517-539页

作者： Kanas, Angelos Zervopoulos, Panagiotis D. Univ Piraeus Piraeus Greece Univ Sharjah Sharjah U Arab Emirates Hellen Parliament Sci Comm Parliamentary Budget Off Athens Greece

This paper puts forward the proposition that U.S. commercial banks use dividends as a mechanism to shift systemic risk to debt-holders and the deposit insurer. Using a mixed data sampling modeling approach, it is shown that monthly systemic risk factors are associated with a positive effect on future quarterly bank dividends indicating systemic risk-shifting. These factors include absorption (Kritzman et al. in MIT working paper, 2010), catfin (Allen et al. in Rev Financ Stud 25:3000-3036, 2012), covar (Adrian and Brunnermeier in CoVaR. NBER Working Paper 17454. National Bureau Economic Research, Cambridge, MA, 2011), delta_covar (Adrian and Brunnermeier 2011, mes (Acharya et al. in Rev Financ Stud 24:2166-2205, 2011b), real_vol (Giglio et al. in J Financ Econ 119:457-471, 2016), and size_con (Giglio et al. 2016). In addition, they can now-cast the upward trend in systemic risk-shifting in the 1990s and the downward trend from the early 2000s to 2007. The findings suggest that the rules governing bank dividends need be revised, support the imposition of a dividend tax to mitigate the negative externalities of dividends as a risk-shifting mechanism, and document a reduced effectiveness of Prompt Corrective Action in controlling risk-shifting.

关键词： Systemic risk Dividend payout mixed data sampling Risk-shifting

来源：评论

学校读者我要写书评

暂无评论

Nowcasting Unemployment Rates with Smartphone GPS data 1

引用

1st International Workshop on Multiple-Aspect Analysis of Semantic Trajectories (MASTER)

作者： Moriwaki, Daisuke CyberAgent Inc Shibuya Ku 1-12-1 Dogenzaka Tokyo Japan

ISBN: (数字)9783030380816

ISBN: (纸本)9783030380816;9783030380809

Unemployment rate is one of the most important macroeconomic indicators. Central governments and market participants heavily rely on the index to assess the economies. However, official statistics of unemployment rate are released infrequently with substantial delay. Prediction of official statistics of labor market will be helpful for these authorities as well as private companies and even workers. In this paper, we combine massive location data coming from smartphones and mixed data sampling (MIDAS) techniques to predict current unemployment rate in Japan. We found GPS data is very useful to predict the status of labor markets.

关键词： GPS data MIDAS mixed data sampling Location data Unemployment rate Time series analysis Macroeconomic policy Nowcasting Forecasting

来源：评论

学校读者我要写书评

暂无评论

Economic drivers of volatility and correlation in precious metal markets

引用

JOURNAL OF COMMODITY MARKETS 2022年 28卷

作者： Dinh, Theu Goutte, Stephane Nguyen, Duc Khuong Walther, Thomas Natl Econ Univ Hanoi Vietnam Univ Paris Saclay UMI SOURCE F-78280 Guyancourt France Paris Sch Business PSB Paris France IPAG Business Sch Paris France Vietnam Natl Univ Int Sch Hanoi Vietnam Univ Utrecht Utrecht Sch Econ Utrecht Netherlands Tech Univ Dresden Fac Business & Econ Dresden Germany

We investigate the time-varying dynamics of the precious metal markets. We employ a mixed data sampling technique to identify the impact of macroeconomic and financial drivers from G7 and BRICS countries on the daily volatility and pairwise correlation of Gold, Silver, Platinum, and Palladium. We find that the U.S. and Chinese economies in particular influence the precious metal markets, but in opposite directions. The stock markets and trade balance of both G7 and BRICS countries, as well as the consumer confidence of G7 countries, are the key drivers for the volatility of precious metals. The most influential drivers for correlation are stock markets, money supply, and the inflation rate. Surprisingly, the economic policy uncertainty does not affect the dynamics as much as expected. Lastly, the global financial crisis in 2008 affected the direction of most of the macroeconomic and financial drivers.

关键词： Precious metals Long-term volatility Long-term correlation Macroeconomic drivers Financial drivers Economic policy uncertainty mixed data sampling

来源：评论

学校读者我要写书评

暂无评论

Tilting the evidence: the role of firm-level earnings attributes in the relation between aggregated earnings and gross domestic product

引用

REVIEW OF ACCOUNTING STUDIES 2019年第2期24卷 570-592页

作者： Ball, Ryan T. Gallo, Lindsey Ghysels, Eric Univ Michigan Stephen M Ross Sch Business Ann Arbor MI 48109 USA Univ North Carolina Chapel Hill Dept Econ Chapel Hill NC USA

We examine whether the contribution of firm-level accounting earnings to the informativeness of the aggregate is tilted towards earnings with specific financial reporting characteristics. Specifically, we investigate whether considering the smoothness of firm-level earnings increases the informativeness of aggregate earnings for future real GDP, and if so, whether macroeconomic forecasters use this information efficiently. Using recently-developed mixed data sampling methods, we find that the aggregate is tilted towards firms with smoother earnings and that this composition of aggregate earnings outperforms traditional weighting schemes. Further, this tilted aggregate has a stronger positive association with forecast revisions;in fact, analysts who utilize earnings the most in their forecasts appear to fully impound the informativeness of earnings smoothness. Our results synthesize and span parallel yet distinct streams of research on the role of accounting earnings in firm-level and macroeconomic outcomes and suggest an important role for financial reporting characteristics in the aggregate.

关键词： Gross domestic product Aggregated earnings Tilt mixed data sampling

来源：评论

学校读者我要写书评

暂无评论

A TVM-Copula-MIDAS-GARCH model with applications to VaR-based portfolio selection

引用

NORTH AMERICAN JOURNAL OF ECONOMICS AND FINANCE 2020年 51卷 101074-101074页

作者： Jiang, Cuixia Ding, Xiaoyi Xu, Qifa Tong, Yongbo Hefei Univ Technol Sch Management Hefei 230009 Anhui Peoples R China Minist Educ Key Lab Proc Optimizat & Intelligent Decis Making Hefei Peoples R China Chainfin Informat Technol Beijing Co Ltd Beijing Peoples R China

This paper develops a novel time-varying multivariate Copula-MIDAS-GARCH (TVM-Copula-MIDAS-GARCH) model with exogenous explanatory variables to model the joint distribution of returns. The model accounts for mixed frequency factors that affect the time-varying dependence structure of financial assets. Furthermore, we examine the effectiveness of the proposed model in VaR-based portfolio selection. We conduct an empirical analysis on estimating the 90%, 95%, 99% VaRs of the portfolio constituted of the Shanghai Composite Index, Shanghai SE Fund Index, and Shanghai SE Treasury Bond Index. The empirical results show that the proposed TVM-Copula-MIDAS-GARCH model is effective to investigate the nonlinear time-varying dependence among those three indices and performs better in portfolio selection.

关键词： Time-varying multivariate copula mixed data sampling MIDAS-Copula GARCH Portfolio VaR

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：