In this paper we compare the performance of the Differential Evolution (DE) and the Repulsive Particle Swarm (RPS) methods of global optimization. To this end, seventy test functions have been chosen. Among these test functions, some are new while others are well known in the literature; some are...

This paper discusses a tool for optimization of econometric models based on genetic algorithms. First, we briefly describe the concept of this optimization technique. Then, we explain the design of a specifically developed algorithm and apply it to a difficult econometric problem, the...

The goal of a Virtual Organization is to find the most appropriate partners in terms of expertise, cost wise, quick response, and environment. In this study we propose a model and a solution approach to a partner selection problem considering three main evaluation criteria: cost, time and risk....

This paper studies option pricing based on a reverse engineering (RE) approach. We utilize artificial intelligence in order to numerically compute the prices of options. The data consist of more than 5000 call- and put-options from the German stock market. First, we find that option pricing...

Computational methods both open the frontiers of economic analysis and serve as a bottleneck in what can be achieved. Using the quantum Monte Carlo (QMC) algorithm, we are the first to study whether quantum computing can improve the run time of economic applications and challenges in doing so....

We introduce the market resources method (MRM) for solving dynamic optimization problems. MRM extends Carroll's (2006) endogenous grid point method (EGM) for problems with more than one control variable using policy function iteration. The MRM algorithm is simple to implement and provides...

We introduce the market resources method (MRM) for solving dynamic optimization problems. MRM extends Carroll’s (2006) endogenous grid point method (EGM) for problems with more than one control variable using policy function iteration. The MRM algorithm is simple to implement and provides...

The proliferation of algorithmic high-frequency trading in financial markets has also led to an increase in new types of fraudulent activity. Since the flash-crash of 2010 first brought it to popular prominence, layering or spoofing fraud has become a major concern for financial regulators...

We study a generalized version of Coleman (1990)'s time iteration method (GTI) for solving dynamic optimization problems. Our benchmark framework is an irreversible investment model with labor-leisure choice. The GTI algorithm is simple to implement and provides advantages in terms of speed...

We introduce the market resources method (MRM) for solving dynamic optimization problems. MRM extends Carroll's (2006) endogenous grid point method (EGM) for problems with more than one control variable using policy function iteration. The MRM algorithm is simple to implement and provides...