Time-frequency causality and dependence structure between crude oil,EPU and Chinese industry stock: Evidence from multiscale quantile perspectives

This article investigates the time-frequency causality and dependence structure of Chinese industry stock returns on crude oil shocks and China's economic policy uncertainty (EPU) across quantiles over the period from January 2001 to June 2021. We use wavelet-based decomposition series to establish a multiscale causality-in-quantiles test and a quantile-on-quantile regression approach to reveal the complicated relationships involving crude oil, EPU and stock returns. Our empirical results are as follows: First, the predictability of crude oil and EPU on industry stock returns is significantly strong under extreme market conditions. Second, the explanatory ability of EPU on industry stock returns in the long term is stronger than EPU’s ability to explain short term returns. Third, the impacts of crude oil and EPU on industry stock returns remain remarkably asymmetric across quantile levels. Finally, nonenergy-intensive industries are also affected by crude oil shocks, but less than energy-intensive industries. Overall, these empirical findings can provide implications for policymakers to stabilize stock markets and investors to hedge the potential risks from crude oil and EPU.     

Neutrality in arrow and other impossibility theorems

Summary. Although not assumed explicitly, we show that neutrality plays an important role in Arrow and other impossibility theorems. Applying it to pivotal voters we produce direct proofs of classical impossibility theorems, including Arrow's, as well as extend some of these theorems. We further explore the role of neutrality showing that it is equivalent to Pareto or reverse Pareto, and to effective dictatorship for non-null social welfare functions satisfying the principle of independence of irrelevant alternatives. It is also equivalent to Wilson's Citizens' Sovereignty--which is related to the intuition that symmetry over alternatives makes social preference depend only on citizens' preferences. We show that some of these results are more fundamental than others in that they extend both to infinite societies and to considerably smaller domains of preferences. Finally, as an application of Arrow's theorem, we provide a simple proof of the Gibbard-Satterthwaite theorem.Received: 13 April 2000, Revised: 6 December 2002, JEL Classification Numbers: D71, C70.I thank Salvador Barberá, Luis Corchón, Cesar Martinelli, Eric Maskin, Tomas Sjöström, Ricard Torres, José Pedro Ubeda, and an anonymous referee for feedback. The proofs of Arrow's theorem and two Wilson's theorems come from a note I wrote in 1987 at Universitat Autónoma de Barcelona (Ubeda [16]). In 1996 Geanakoplos [7] wrote a proof of Arrow's theorem similar but not identical to mine. All work in this paper is independent of his.     

COVID-19, stock market and sectoral contagion in US: a time-frequency analysis

We assess the conditional relationship in the time-frequency domain between the return on S&P 500 and confirmed cases and deaths by COVID-19 in Hubei, China, countries with record deaths and the world, for the period from January 29 to June 30, 2020. Methodologically, we follow Aguiar-Conraria et al. (2018), by using partial coherencies, phase-difference diagrams, and gains. We also perform a parametric test for Granger-causality in quantiles developed by Troster (2018). We find that short-term cycles of deaths in Italy in the first days of March, and soon afterwards, cycles of deaths in the world are able to lead out-of-phase US stock market. We find that low frequency cycles of the US market index in the first half of April are useful to anticipate in an anti-phasic way the cycles of deaths in the US. We also explore sectoral contagion, based on dissimilarities, Granger causality and partial coherencies between S&P sector indices. Our findings, such as the strategic role of the energy sector, which first reacted to the pandemic, or the evidence about predictability of the Telecom cycles, are useful to tell the history of the pass-through of this recent health crises across the sectors of the US economy.     

输油管的布置数学建模

本文主要采用数形结合的方法讨论了输油管线建设的单目标优化问题。以总的管线建设费用最小为目标,以两炼油厂到铁路线距离、两炼油厂间距离,共用管线与非共用管线的建设费用、长度和管线节点取址等为约束条件,为输油管线的建设和车站的选址建立了一般化的框架模型。为方便模型求得解析解,只针对非共用管线的费用相同的情形进行探讨,应用几何知识缩小搜索域并进行降维分析,采用Matlab求导工具箱,求得该情况下所有满足条件的最优方案。     

浅谈word域及其应用

Word是微软公司开发的一款非常优秀的文字处理软件,它是人们日常工作、学习、生活中非常重要的工具。但是在某些情况下,用户会感觉word的灵活性、功能和自动化程度不够高,其实不然,造成这种情况的原因往往是因为用户还没有掌握word的精髓———域。如何使得文档的排版更具灵活性,免去不必要的重复性操作步骤,促进工作又好又快的发展需要掌握word域的应用。     

Time-frequency dynamics of return spillover from crude oil to agricultural commodities

ABSTRACT

We explore return spillover from crude oil to ethanol, corn, soybean and wheat on daily data during 17 May 2005–27 June 2018. This study is unique in capturing the time-frequency dynamics of return spillover. We use the frequency-dependent spillover measure that jointly captures information from time and frequency domain. We also identify two endogenous break dates that segregate the study period in three sub-periods. Our results indicate that return spillover from crude oil to ethanol, major feed stocks (i.e. corn and soybean) and food crop (i.e. wheat) is pronounced only in lower frequency band or long-term (more than 1 month). We find that return spillover is stronger only during 2005–2010, i.e. the period of energy and food crisis.     

Time-frequency effect of crude oil and exchange rates on stock markets in BRICS countries: Evidence from wavelet quantile regression analysis

This study examines the effects of oil prices and exchange rates on stock market returns in BRICS countries (Brazil, Russia, China, India and South Africa) from a time–frequency perspective over the period 2009–2020. We use wavelet decomposition series to develop a threshold rolling window quantile regression to detect time–frequency effects at various scales. The empirical results are as follows. First, our findings confirm that the effects of both crude oil prices and exchange rates on BRICS stock returns are asymmetric. Positive shocks of crude oil have a greater impact on a bull market, whereas negative shocks have a greater impact on a bear market. Second, there is a short-term enhancement effect of crude oil and exchange rate on BRICS stock markets. In addition, volatility in the macro financial environment also exacerbates the impacts of oil prices and exchange rates on the stock market, and these fluctuations are heterogeneous. Overall, these findings provide useful insights for international investors and policy makers.     

On additivity of tail comonotonic risks

ABSTRACT

As perceived from daily experience together with numerous empirical studies, the multivariate risks demonstrate a strong coherence in the extremal dependence structure especially over the course of financial turmoil or industrial accidents and outbreaks. Under this motivating paradigm, we show the universal asymptotic additivity under upper tail comonotonicity, as the probability level approaching to 1, for Value-at-Risk and Conditional Tail Expectation for a portfolio of fixed number of risks, in which each marginal risk could be any one having a finite endpoint or belonging to one of the three max domains of attraction. Our obtained results do not require the tail equivalence assumption as needed in the existing literature. This resolves a lasting problem in quantitative risk management and covers most distributions commonly encountered in practice.     

Causal relationship between spot and futures prices with multiple time horizons: A nonparametric wavelet Granger causality test

This study investigates the causal information flow between 45 major daily spot returns and their corresponding futures in developing, emerging, and commodity indices through a novel nonparametric wavelet Granger causality test (NWGC) that is capable of detecting causality patterns in various time scales without any stationarity assumption or multivariate autoregressive modeling requirement. We provide new evidence for a complex causality pattern phenomenon. First, there may not be just one dichotomous answer about the Granger causality test for each market data in a time domain, as markets exhibit different causal information flows for different time scales. Second, each market may show distinct causality patterns compared to other markets.