In this article we present new results for the pricing of arithmetic Asian options within a Black-Scholes context. To derive these results we make extensive use of the local scale invariance that exists in the theory of contingent claim pricing. This allows us to derive, in a natural way, a...

In this article we present a new approach to the numerical valuation of derivative securities. The method is based on our previous work where we formulated the theory of pricing in terms of tradables. The basic idea is to fit a finite difference scheme to exact solutions of the pricing PDE. This...

This note derives new expressions for the moments of the average of values taken by Wiener paths at an arbitrary number, N, of discrete times. The expressions are closed summations, which entail only the N-th powers of, and the successive differences between, the moments of the lognormal finite...

In this paper we propose a jump diffusion type model which recovers the main characteristics of electricity spot price dynamics, including seasonality, mean reversion, and spiky behavior. Calibration of the market price of risk allows for pricing of Asian-type options written on the spot...

Multi-Agent Based Simulation is a branch of Distributed Artificial Intelligence that builds the base for computer simulations which connect the micro and macro level of social and economic scenarios. This paper presents a new method of modelling the formation and change of patterns of action in...

Learning is modeled as an infection, which jumps from person to person. The rate of infection mimics individual discount rates and induces savings behavior on its own. It is shown that the apparent discount rate, the combination of the agents' true discount rate and the infection rate, decreases...

In this paper, I develop an algorithm for solving heterogeneous agent dynamic models in which individual decision rules influence each other. This approach is more general than the other heterogeneous agent solution methods in that it only requires a well formed objective function. The key...

This paper studies an adaptive artificial agent model using a genetic algorithm to analyze how a population of decision-makers learns to coordinate on the selection of an equilibrium or a social convention in a two-sided matching game. In the contexts of centralized and decentralized entry-level...

The uncertainty of predicting stock prices emanates pre-eminent concerns around the functionality of the stock market. The possibility of utilising Genetic Algorithms to forecast the momentum of stock price has been previously explored by many optimisation models that have subsequently addressed...

This paper proposes an algorithm to obtain maximum likelihood estimates of structural parameters in discrete games with multiple equilibria. The method combines a genetic algorithm (GA) with a pseudo maximum likelihood (PML) procedure. The GA searches efficiently over the huge space of possible...