Recent decades have seen advances in using econometric methods to produce more timely and higher-frequency estimates of economic activity at the national level, enabling better tracking of the economy in real time. These advances have not generally been replicated at the sub–national level,...

In this paper, we present an arithmetic electricity spot price model based on generalized Langevin equations. In this setup, we investigate electricity forward pricing under future information modeled by initially enlarged filtrations. Hence, our model not only accounts for memory effects via...

Inflation derivatives have been widely used by various institutions to transfer or hedge inflation risks. They have experienced substantial growth since early 2000s and a liquid market has been developing in both Europe and U.S. In order to price inflation derivatives, calculate their risks or...

Dynamic equilibrium models are specified to track time series with unit root-like behavior.Thus, unit roots are typically introduced and the optimality conditions adjusted. This step requires tedious algebra and often leads to algebraic mistakes, especially in models with several unit roots.We...

In Section 2 of Bernard et al. (2020), we study bounds on Range Value-at-Risk (RVaR) under the assumption of non-negative risk. However, Proposition 3 is erroneous, and hence Theorems 3, 4, and 5 and Corollary 5 are no longer valid. In this corrigendum, we provide a direct replacement of these...

SABR model is a reference in financial industry to price fixed income derivatives, thanks to its ability to capture the volatility smile. The goal of this thesis is to develop a technique based on SABR model which captures all non-linearities, be more robust, gives tradable parameters...

Different sustainability dimensions have been proposed in the scientific literature to quantify the economic, environmental, and social impacts of transport activities. Besides, real-life transport operations are often subject to uncertainty in travelling times or in customers’ demands. Hence,...

In this paper, we present several optimal control approaches which are designed to control and regulate the evolution of infection numbers in the COVID-19 disease. In our setting, the number of infected people at a certain location is modeled by a continuous-time stochastic process which can be...

The emergence of oscillatory behaviour represents fundamental information about the interactions of the underlying system. In biological systems, oscillations have been observed in experimental data, but due to the significant level of noise, it is difficult to characterize whether observed...

Solving non-linear parabolic partial differential equations (PDEs) in high dimension becomes an interest for its curse of dimensionality problem. Recently, a deep learning method associated with a backward stochastic differential equation (deep-BSDE) to solve the PDEs draws intensive discussions...