A geometrical description of visual sensation
A geometrical description of visual sensation II
A gradient-type algorithm for the numerical solution of two-player zero-sum differential game problems
A graph-theoretic characterization of the core in a homogeneous generalized assignment game
An exchange network is a socioeconomic system in which any two actors are allowed to negotiate and conclude a transaction if and only if their positions-mathematically represented by the points of a connected graph-are joined by a line of this graph. A transaction consists in a bilaterally agreed-on division of a profit pool assigned to a given line. Under the one-exchange rule, every actor is permitted to make no more than one transaction in each negotiation round. Bienenstock and Bonacich ([1])...
A Group Decision-Making Aggregation Process
A heuristic forecasting model for stock decision making.
This paper describes a heuristic forecasting model based on neural networks for stock decision-making. Some heuristic strategies are presented for enhancing the learning capability of neural networks and obtaining better trading performance. The China Shanghai Composite Index is used as case study. The forecasting model can forecast the buying and selling signs according to the result of neural network prediction. Results are compared with a benchmark buy-and-hold strategy. The forecasting model...
A Journey from Statistics and Probability to Risk Theory An interview with Ludger Rüschendorf
A kinetic approach to the study of opinion formation
In this work, we use the methods of nonequilibrium statistical mechanics in order to derive an equation which models some mechanisms of opinion formation. After proving the main mathematical properties of the model, we provide some numerical results.
A k-noisy, n-silent vs. one-noisy duel with equal accuracy functions
A Language for the construction of preferences under uncertainty.
A Leontief-type input-output inclusion.
A linear assignment formulation of the multiattribute decision problem
A Logic and computer algebra approach to a decision-making problem in medicine
A lot-size model for deteriorating items under conditions of a one-time only extended credit period.
A Markov chain model for traffic equilibrium problems
We consider a stochastic approach in order to define an equilibrium model for a traffic-network problem. In particular, we assume a markovian behaviour of the users in their movements throughout the zones of the traffic area. This assumption turns out to be effective at least in the context of urban traffic, where, in general, the users tend to travel by choosing the path they find more convenient and not necessarily depending on the already travelled part. The developed model is a homogeneous Markov...
A Markov chain model for traffic equilibrium problems
We consider a stochastic approach in order to define an equilibrium model for a traffic-network problem. In particular, we assume a Markovian behaviour of the users in their movements throughout the zones of the traffic area. This assumption turns out to be effective at least in the context of urban traffic, where, in general, the users tend to travel by choosing the path they find more convenient and not necessarily depending on the already travelled part. The developed model is a homogeneous...
A Markov regime-switching marked point process for short-rate analysis with credit risk.
A martingale control variate method for option pricing with stochastic volatility
A generic control variate method is proposed to price options under stochastic volatility models by Monte Carlo simulations. This method provides a constructive way to select control variates which are martingales in order to reduce the variance of unbiased option price estimators. We apply a singular and regular perturbation analysis to characterize the variance reduced by martingale control variates. This variance analysis is done in the regime where time scales of associated driving volatility...
A mathematical analysis of the card game of betweenies through Kelly's criterion.
A mathematical framework for learning and adaption: (generalized) random systems with complete connections.
The aim of this paper is to show that the theory of (generalized) random systems with complete connection may serve as a mathematical framework for learning and adaption. Chapter 1 is of an introductory nature and gives a general description of the problems with which one is faced. In Chapter 2 the mathematical model and some results about it are explained. Chapter 3 deals with special learning and adaption models.