Search results

To discuss subcopula estimation for discrete models.

The convergence of estimators is considered under the weak convergence of distribution functions and its equivalent properties known in prior works.

The domain of the true subcopula associated with discrete random variables is found to be discrete on the interior of the unit hypercube. The construction of an estimator in which their domains have the same form as that of the true subcopula is provided, in case, the marginal distributions are binomial.

To the best of our knowledge, this is the first time such an estimator is defined and proved to be converged to the true subcopula.

A Copula function is an useful tool for constructing and simulating multivariate distributions. It relates one-dimensional marginals with multi-dimensional distribution. By doing so, one can separately model the distribution of individual series and the dependence structure and the estimation becomes a much simpler problem. As such, data simulated from a copula allows one to price complex financial products that would be impossible otherwise and to measure both market and credit risks more realistically and accurately. This paper intends to summarize the copula methodology and applies it to the problem of simulating default-free and risky spot rates. More specifically, this paper estimates the dependence structure of daily Korean Treasury and A-rated corporate spot rates (3-year to maturity) for the 1/2/01~11/11/02 period using t-marginals and bivariate t-copula. The data appear to support the empirical fact that these rates have fat-tails and t_(3.7)-copula seems to be the reasonable description of the daily changes in spot rates. This paper also demonstrates the simulation of the data from t_(3.7)-copula.

In this paper, the authors applied the empirical likelihood method, which was originally proposed by Owen, to the copula moment based estimation methods to take advantage of its properties, effectiveness, flexibility and reliability of the nonparametric methods, which have limiting chi-square distributions and may be used to obtain tests or confidence intervals. The authors derive an asymptotically normal estimator of the empirical likelihood based on copula moment estimation methods (ELCM). Finally numerical performance with a simulation experiment of ELCM estimator is studied and compared to the CM estimator, with a good result.

In this paper we applied the empirical likelihood method which originally proposed by Owen, to the copula moment based estimation methods.

We derive an asymptotically normal estimator of the empirical likelihood based on copula moment estimation methods (ELCM). Finally numerical performance with a simulation experiment of ELCM estimator is studied and compared to the CM estimator, with a good result.

In this paper we applied the empirical likelihood method which originally proposed by Owen 1988, to the copula moment based estimation methods given by Brahimi and Necir 2012. We derive an new estimator of copula parameters and the asymptotic normality of the empirical likelihood based on copula moment estimation methods.

Unlimited quantitative easing (QE) is one of the monetary policies used to stimulate the economy during the coronavirus disease 2019 (COVID-19) pandemic. This policy has affected the financial markets worldwide. This empirical research aims at studying the dependence among stock markets before and after unlimited QE announcements.

The copula-based GARCH (1,1) and minimum spanning tree models are used in this study to analyze 14 series of stock market data, on 6 ASEAN and 8 other countries outside the region. The data are divided into two periods to compare the differences in dependence.

The findings show changes in dependence among the volatility of daily returns in 14 stock markets during each period. After the unlimited QE announcement, the upper tail dependence became more apparent, while the role of the lower tail dependence was reduced. The minimum spanning tree can show the close relationships between stock markets, indicating changes in the connection network after the announcement.

This study allows the dependency to be compared between stock market volatility before and after the announcement of unlimited QE during the COVID-19 pandemic. Moreover, the study fills the literature gap by combining the copula-based GARCH and the minimum spanning tree models to analyze and reveal the systemic network of the relationships.

This article studies the particle qad in standard Arabic (SA) and Asiri Arabic (AA). In SA, qad is pronounced as [qæd], whereas in AA it is pronounced as [q?d] and written as qid. Qad in SA is different from qid in AA regarding its functional use and syntactic distribution. Accordingly, the study discusses the semantics and selection properties of qad/qid.

Contrasting analyses are presented to verify which syntactic analysis better suits extended projection principle (EPP) extension, and tree structures are provided to elucidate ongoing problematic configurations and to provide solutions.

The SA particle qad has three functions: (1) a probability modal, as in may or might; (2) a perfective auxiliary, as in have, has and had; and (3) indicating emphatic purpose, as in do, does and did. Contrariwise, qid in AA has two meanings: (1) have, has and had (perfective auxiliary); and (2) the past tense of the English copula was/became (a linking verb). Given this background, there has been a debate in the syntax literature about whether qid/qad is an adverb. The current article provides evidence indicating that qid and qad are not adverbs.

The study is limited to the analysis of qid in Asiri dialect. Further research needs to be done on the different branches of the Asiri dialects according to the tribe. Sometimes, tribes have different sound for some words. There is not any literature review found on the Asiri dialects in the designated area of study; the particle qid.

The study can be counted towards the Asiri linguistic heritage in documenting the syntactic and semantic properties of qid particle. The study contributes to the linguistic field of the Arabic language and its varieties.

The study offers a general review of the linguistic background of Asir region. The study introduces the reader to qad particle in SA and holds a comparison between the two researched versions of qad in SA and qid in AA.

The paradoxical analysis between qad and qid on all levels is presented (semantics, functional use, selection properties and level of configuration (EPP)). Also, it introduces the particle qid in AA as it was never investigated before.

This study aims to investigate the existence of contagion between liquid and illiquid assets in the credit default swap (CDS) market around the recent financial crisis. The authors perform analyses based on vector autoregression model and the dynamic conditional correlation model. The estimation of vector autoregression models reveals that changes in liquid CDS (LCDS) spreads lead to changes in illiquid CDS spreads at least one week ahead during the financial crisis period, whereas the leading direction is reversed during the post-crisis period. Moreover, the results are robust after controlling for structural variables which are proven as determinants of CDS spreads and are empirically supported. This study interprets that information was incorporated first into the LCDSs because of the flight-to-liquidity during the recent crisis period but there is a default contagion effect by reflecting illiquidity-induced credit risk after the crisis. Finally, the dynamic conditional correlation analysis also confirms the main results.

The performance of financial markets is significantly influenced by the political environment during general elections. This study investigates the effect of general elections on stock market performance in selected African markets.

Prior studies have been inconsistent in determining whether electioneering events negatively or positively influence stock market performance. The study utilized panel data set with annual observations from 1990 to 2020. The generalized method of moments (GMM) is employed to investigate the effect of electioneering and change in government on key stock market performance indicators, including stock market capitalization, stock market turnover ratio and the value of stock traded.

The study finds that electioneering activities generally have a positive impact on the performance of the stock market, whereas a change in government has a negative impact. As a result, the study recommends that stakeholders of the stock market remain vigilant and actively monitor electioneering events to devise and implement effective policies aimed at mitigating political risks during general elections. By adopting these measures, investor confidence can be significantly enhanced, fostering a more robust and secure investment environment.

The study investigates a neglected section of the literature by highlighting not only the effect of elections on stock market indicators but also possible change in government during elections.

The purpose of this paper is to examine, in a global perspective, the oil, gold, US dollar and stock prices interdependencies and to identify instantaneously direct and indirect linkages among them.

A methodology based on simultaneous equations system was used to identify direct and indirect linkages for the period 1995-2015. The authors try initially to find theoretical answers to main question of the study by discussing causal bilateral relationships while focusing on multilateral interactions.

The results show significant interactions between all markets. The authors found a negative relation between oil and stock prices but oil price is significantly and positively affected by gold and USD. Oil price is also affected by oil futures prices and by Chinese oil gross imports. Gold rate is concerned by changes in oil, USD and stock markets. The US dollar is negatively affected by stock market and significantly by oil and gold price. Indirect effects always exist which confirm the presence of global interdependencies and involve the financialization process of commodity markets.

Motivation of this research paper is the substantial implications of price movements on real economy and financial markets. Understanding that co-movement has great value for investors, policy makers and portfolio managers. This paper differs from previous studies in several aspects. First, most of the research papers focus on bilateral linkages solely, while the authors’ investigation was implemented on all the four markets simultaneously. Second, the study was developed in a global framework using international data. The global analysis allows avoiding country specific effects.

While there exist many surveys on the use stochastic frontier analysis (SFA), many important issues and techniques in SFA were not well elaborated in the previous surveys, namely, regular models, copula modeling, nonparametric estimation by Grenander’s method of sieves, empirical likelihood and causality issues in SFA using regression discontinuity design (RDD) (sharp and fuzzy RDD). The purpose of this paper is to encourage more research in these directions.

A literature survey.

While there are many useful applications of SFA to econometrics, there are also many important open problems.

This is the first survey of SFA in econometrics that emphasizes important issues and techniques such as copulas.

This paper aims mainly at introducing applied statisticians and econometricians to the current research methodology with non-Euclidean data sets. Specifically, it provides the basis and rationale for statistics in Wasserstein space, where the metric on probability measures is taken as a Wasserstein metric arising from optimal transport theory.

The authors spell out the basis and rationale for using Wasserstein metrics on the data space of (random) probability measures.

In elaborating the new statistical analysis of non-Euclidean data sets, the paper illustrates the generalization of traditional aspects of statistical inference following Frechet's program.

Besides the elaboration of research methodology for a new data analysis, the paper discusses the applications of Wasserstein metrics to the robustness of financial risk measures.