When constructing parametric models to predict the cost of future claims, several important details have to be taken into account: (i) models should be designed to accommodate deductibles, policy limits, and coinsurance factors, (ii) parameters should be estimated robustly to control the...

With some regularity conditions maximum likelihood estimators (MLEs) al-ways produce asymptotically optimal (in the sense of consistency, efficiency, sufficiency,and unbiasedness) estimators. But in general, the MLEs lead to non-robust statisticalinference, for example, pricing models and risk...

We propose a deep learning approach to probabilistic forecasting of macroeconomic and financial time series. Being able to learn complex patterns from a data rich environment, our approach is useful for a decision making that depends on uncertainty of large number of economic outcomes....

This paper investigates the predictive power of the shadow rate for the inflation rate in countries with a zero lower bound (the US, the UK and Canada) and in those with negative rates (Japan, the Euro Area and Switzerland). Using shadow rates obtained from two different models (the Wu-Xia...

We study the tail probability of linear factor models generated from non-identically distributed components with regularly-varying tails, a large subclass of heavy-tailed distributions. An efficient sampling method for tail probability estimation for this class is introduced and theoretically...

The present paper combines nonlinear shrinkage with the Multivariate Generalized Hyperbolic (MGHyp) distribution to account for heavy tails in estimating the first and second moments in high dimensions. An Expectation-Maximization (EM) algorithm is developed that is fast, stable, and applicable...

The Markowitz model is still the cornerstone of modern portfolio theory. In particular, when focusing on the minimum-variance portfolio, the covariance matrix or better its inverse, the so-called precision matrix, is the only input required. So far, most scholars worked on improving the...

We study average topological summaries of Vietoris–Rips complexes built on top of random point clouds in the D-dimensional Euclidian space in two setups: i) a homogeneous Poisson point process (HPPP) with intensity n and ii) N i.i.d. points sampled from a uniform elliptical distribution. In...

The standard Zipf regression involves a linear relation between the natural logs of the rank and the natural logs of a score on a certain variable. If there are measurement errors in the scores, then the regressor is endogenous and renders Ordinary Least Squares inappropriate. Instrumental...

Based on the method proposed by Aly and Benkherouf (2011) to generate new distributionfamilies, a new distribution based on the Lomax (Lomax, 1954) and Harris (Harris, 1948)distributions is defined and analyzed in this article. The proposed distribution, called theHarris Lomax distribution, can...