This paper analyzes the dynamics of the US inflation time series using two classes of models: structural change models and long memory processes. For the first class, the Markov Switching Autoregressive (MS-AR) model of Hamilton (1989) and the Structural Change-Autoregressive (SCH-AR) model...

Business surveys are an important element in the analysis of the short-term economic situation because of the timeliness and nature of the information they convey. Especially, surveys are often involved in econometric models in order to provide an early assessment of the current state of the...

The aim of this paper is to study the cross-sectional effects present in the market using a new framework based on graph theory. Within this framework, we represent the evolution of a dynamic portfolio, i.e. a portfolio whose weights vary over time, as a rank-based multivariate model where the...

Sharpe-like ratios have been traditionally used to measure the performances of portfolio managers. However, they are known to suffer major drawbacks. Among them, two are intricate: (1) they are relative to a peer's performance and (2) the best score is generally assumed to correspond to a "good"...

The study of dependence between random variables is the core of theoretical and applied statistics. Static and dynamic copula models are useful for describing the dependence structure, which is fully encrypted in the copula probability density function. However, these models are not always able...

Due to the hyper technology associated to Big Data, data availability and computing power, most banks or lending financial institutions are renewing their business models. Credit risk predictions, monitoring, model reliability and effective loan processing are key to decision making and...

We are interested in the analysis of the concept of interpretability associated with a ML algorithm. We distinguish between the “How”, i.e., how a black box or a very complex algorithm works, and the “Why”, i.e. why an algorithm produces such a result. These questions appeal to many...

The central question of this paper is how to enhance supervised learning algorithms with fairness requirement ensuring that any sensitive input does not "`unfairly"' influence the outcome of the learning algorithm. To attain this objective we proceed by three steps. First after introducing...

n this paper, we bring a new econometric perspective for CO2 emission prices modelling and we provide with an innovative methodological approach to compute option prices in incomplete markets. We apply our methodology to carbon derivative. We calibrate several Generalized Hyperbolic and GARCH...

This paper presents a theoretical framework to model the evolution of a portfolio whose weights vary over time. Such a portfolio is called a dynamic portfolio. In a first step, considering a given investment policy, we define the set of the investable portfolios. Then, considering portfolio...