The influence of six different distances on the structure of minimum spanning trees is presented in this paper. Measures of complex networks are built based on the closing prices of stocks of the main companies traded on the Mexican Stock Market. We find that the City block and Chi distances not...

There are prospective Projects that can provide significant development for the further development of civilization.The first Project introduces a classification of the individual person behavior, on the basis of which the behavior of groups of people (including hierarchically structured ones)...

We study the diffusion of an idea, a product, a disease, a cultural fad, or a technology among agents in a social network that exhibits segregation or homophily (the tendency of agents to associate with others similar to themselves). Individuals are distinguished by their types - e.g., race,...

We introduce two neural network models designed for application in statistical learning. The mean-variance neural network regression model allows us to simultaneously model the mean and the variance of a response variable. In case of a two-dimensional response vector, the...

The main idea of this paper is to embed a classical actuarial regression model into a neural network architecture. This nesting allows us to learn model structure beyond the classical actuarial regression model if we use as starting point of the neural network calibration exactly the classical...

The Lee-Carter model is a basic approach to forecasting mortality rates of a single population. Although extensions of the Lee-Carter model to forecasting rates for multiple populations have recently been proposed, the structure of these extended models is hard to justify and the models are...

The aim of this project is to analyse high-frequency GPS location data (second per second) of individual car drivers (and trips). We extract feature information about speeds, acceleration, braking and changes of direction from this high-frequency GPS location data. Time series of this feature...

We present an actuarial loss reserving technique that takes into account both claim counts and claim amounts. Separate (over-dispersed) Poisson models for the claim counts and the claim amounts are combined by a joint embedding into a neural network architecture. As starting point of the neural...

The aim of this manuscript is to provide the mathematical and statistical foundations of actuarial learning. This is key to most actuarial tasks like insurance pricing, product development, claims reserving and risk management. The basic approach to these tasks is regression modeling. This...

Portfolio optimization has been a central problem in finance, often approached with two steps: calibrating the parameters and then solving an optimization problem. Yet, the two-step procedure sometimes encounter the ``error maximization'' problem where inaccuracy in parameter estimation...