The price of crude oil has been subject to periodical fluctuations as a consequence of changes in seasonal demand and supply, as well as weather, natural disasters, and global political unrest. Accurate forecast of crude oil prices is of utmost importance for decision-makers and industry players...

This study proposes an alternative, fully probabilistic approach to combining model-based forecasts with surveys or other judgmental forecasts. This approach allows data to determine how informative survey forecasts are regarding the data-generating process by probabilistically exploiting...

This paper presents a summation of series of binomial coefficients in combinatorial geometric series. The coefficient for each term in combinatorial geometric series refers to a binomial coefficient. This idea can enable the scientific researchers to solve the real life problems

Climate-related financial risks (CRFR) pose unique challenges for capital requirements regulation. CRFR are forward looking, non-linear, systemic and endogenous – attributes that render quantitative estimates of physical and transition risk subject to radical uncertainty. CRFR are also...

This paper focuses on the successive partitions of a binomial coefficient in combinatorial geometric series. The coefficient for each term in combinatorial geometric series refers to a binomial coefficient. These ideas can enable the scientific researchers to solve the real life problems

This paper proposes IV-based estimators for the semiparametric distribution regression model in the presence of an endogenous regressor, which are based on an extension of IV probit estimators. We discuss the causal interpretation of the estimators and two methods (monotone rearrangement and...

In this paper we estimate the skewness of the unconditional distribution of energy returns and test its statistical significance. We compare the performance of traditional and robust tests for symmetry with those based on the implied unconditional skewness in a TGARCH model with Gram-Charlier...

We investigate a new family of distributionally robust optimization problem under marginal and copula ambiguity with applications to portfolio optimization problems. The proposed model considers the ambiguity set of portfolio return in which the marginal distributions and their copula are close...

We introduce a new stochastic order for the tail dependence between random variables. We then study different measures of tail dependence which are monotone in the proposed order, thereby extending various known tail dependence coefficients from the literature. We apply our concepts in an...

Estimating the market risk is conditioned by the fat tail of the distribution of returns. But the tail index depends on the threshold of this distribution fat tail. We propose a methodology based on the decomposition of the series into positive outliers, Gaussian central part and negative...