Classical quantitative finance models such as the Geometric Brownian Motion or its later extensions such as local or stochastic volatility models do not make sense when seen from a physics-based perspective, as they are all equivalent to a negative mass oscillator with a noise. This paper...

Estimation du prix d'une option sur maximum proche de sa maturite.

The Value-at-Risk (VAR) measurements are widely applied to estimate exposure to market risks. The traditional approaches to VAR computations - the variance-covariance method, historical simulation, Monte Carlo simulation, and stress-testing - do not provide satisfactory evaluation of possible...

We describe in this paper a method allowing to order submodels in linear regression. A real function is attached to each submodel, allowing to graphically compare and order them. Our procedure defines an objective function depending on two factors (lack of fit and multicolinearity) with the...

As the structure of consumer preferences plays a crucial role in the analysis of differentiated product markets, estimation of demand systems is a sensitive task. This paper contributes to this project in two ways. First, we develop a method to deal with the simultaneous choice of an equipment...

The ARFIMA model has become a popular approach for analyzing time series that exhibit long-range dependence. For the Gaussian case, there has been substantial advances in the area of likelihood-based inference, including development of the asymptotic properties of the maximum likelihood...

We investigate local strong rationality (LSR) in a one step forward looking univariate model with memory one. Eductive arguments are used to determine when common knowledge (CK) that the solution is near some perfect foresight path is sufficient to trigger complete coordination on that path...

In this paper we consider a new analytic center cutting plane method in a projective space. We prove the efficiency estimates for the general schemeand show that these results can be used in the analysis of a feasibility problem, the variational inequality problem and the problem of constrained...

We explore in this paper the use of deep signature models to predict equity financial time series returns. First, we use signature transformations to model the underlying shape of the input equity returns; further assuming the underlying shape remains the same, we predict future values based on...