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This research provides some evidence by the vine copula approach, suggesting the significant and symmetric causal relation between subsections of Baltic Exchange and hence concluding that investing in different indexes, which is currently a risk diversification system, is not a correct risk reduction strategy.

The daily observations of Baltic Capesize Index (BCI), Baltic Handysize Index (BHSI), Baltic Dirty Tanker Index (BDTI) and Baltic LNG Tanker Index (BLNG) over an eight-year period have been used. After collecting data, calculating the return and estimating the marginal distribution of return rates for each of the indexes applying asymmetric power generalized autoregressive conditional heteroskedasticity and autoregressive moving average (APGARCH-ARMA), and with the assumption of skew student's t-distribution, the dependence of Baltic indexes was modeled based on Vine-R structures.

A positive and symmetrical correlation was observed between the study groups. High and low tail dependence is observed between all four indexes. In other words, the sector business groups associated with each of these indexes react similarly to the extreme events of other groups. The BHSI has a pivotal role in examining the dependency structure of Baltic Exchange indexes. That is, in addition to the direct dependence of Baltic groups, the dependence of each group on the BHSI can transmit accidents and shocks to other groups.

Since the Baltic Exchange indexes are tradable, these findings have implications for portfolio design and hedging strategies for investors in shipping markets.

Vine copula structures proves the causal relationship between different Baltic Exchange indexes, which are derived from different types of markets.

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.

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.

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.

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.

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.

Recently, domestic market participants have a growing interest in synthetic Collateralized Debt Obligation (CDO) as a security to reduce credit risk and create new profit. Therefore, the valuation method and hedging strategy for synthetic CDO become an important issue. However, there is no won-denominated credit default swap transactions, which are essential for activating synthetic CDO transaction‘ In addition, there is no transparent market information for the default probability, asset correlation, and recovery rate, which are critical variables determining the price of synthetic CDO.

This study first investigates the method of estimating the default probability, asset correlation coefficient, and recovery rate. Next, using five synthetiC CDO pricing models‘ widely used OFGC (One-Factor Non-Gaussian Copula) model. OFNGC (One-Factor Non-Gaussian Copula) model such as OFDTC (One-Factor Double T-distribution Copula) model of Hull and White (2004) or NIGC (Normal Inverse Gaussian Copula) model of Kalemanova et al.(2005), SC<Stochastic Correlation) model of Burtschell et al.(2005), and FL (Forward Loss) model of Bennani (2005), I Investigate and compare three points: 1) appropriateness for portfolio loss distribution, 2) explanation for standardized tranche spread, 3) sensitivity for delta-neutral hedging strategy. To compare pricing models, parameter estimation for each model is preceded by using the term structure of iTraxx Europe index spread and the tranch spreads with different maturities and exercise prices Remarkable results of this study are as follows. First, the probability for loss interval determining mezzanine tranche spread is lower in all models except SC model than OFGC model. This result shows that all mαdels except SC model in some degree solve the implied correlation smile phenomenon, where the correlation coefficient of mezzanine tranche must be lower than other tranches when OFGC model is used. Second, in explaining standardized tranche spread, NIGC model is the best among various models with respect to relative error. When OFGC model is compared with OFDTC model, OFOTC model is better than OFGC model in explaining 5-year tranche spreads. But for 7-year or 10-year tranches, OFDTC model is better with respect to absolute error while OFGC model is better with respect to relative error. Third, the sensitivity sign of senior tranctle spread with respect to asset correlation is sometime negative in NIG model while it is positive in other models. This result implies that a long position may be taken by the issuers of synthet.ic COO as a correlation delta-neutral hedging strategy when OFGC model is used, while a short position may be taken when NIGC model is used.

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 article aims to open the black box of the relationship between customer experience and customer satisfaction. The authors also take a fine-grained approach to the concept of customer experience analysis in terms of four dimensions: basic service experience (BSE), moments of truth (MT), focus on results (FR) and peace of mind (PM).

A total sample of 185 industrial customers in Spain was collected via an online platform from March to April 2020. The data were analysed using partial least squares-structural equation modelling (PLS-SEM).

The results indicated that the four dimensions of customer experience are the foundation of commercial success (i.e. customer satisfaction) for express parcel companies in the business-to-business (B2B) environment. Therefore, the most innovative express parcel companies should not only pay attention to providing services in accordance with the customer agreement but also go beyond that; hence, these companies must understand customer needs to be able to offer a unique experience. Therefore, these companies must design experiences that go beyond pure technical delivery services.

Although previous work has linked customer experience to customer satisfaction, there is little work that does so specifically in an industry as in vogue as express parcels and less so in the B2B environment. In addition, this work analyses fine-grained customer experience in terms of grain's four dimensions, and therefore, the authors analyse how each dimension (e.g. more rational or more subjective dimensions) impacts customer satisfaction. Few studies have focussed on this type of analysis for express parcel companies in the B2B environment.