Un modèle d'interaction réaliste pour la simulation de marchés financiers

Dans les modèles de marché multi-agents utilisés habituellement, la structure du marché est presque toujours réduite à une équation qui aggrège les décisions des agents de façon synchrone pour mettre à jour le prix de l'action à chaque pas de temps. Sur les marchés réels, ce processus est totalement différent : le prix de l'action émerge d'interactions survenant de manière asynchrone entre les acheteurs et les vendeurs. Dans cet article, nous introduisons un modèle de marché artificiel conçu pour être le plus proche possible de la structure des marchés réels. Ce modèle est basé sur un carnet d'ordres à travers lequel les agents échangent des actions de manière asynchrone. Nous montrons que, sans émettre d'hypothèses particulières sur le comportement des agents, ce modèle exhibe de nombreuses propriétés statistiques des marchés réels. Nous soutenons que la plupart de ces propriétés proviennent de la manière dont les agents interagissent plutôt que de leurs comportements. Ce résutat expérimental est validé et renforcé grâce à l'utilisation de nombreux tests statistiques utilisés par les économistes pour caractériser les propriétés des marchés réels. Nous finissons par quelques perspectives ouvertes par les avantages de l'utilisation de tels modèles pour le développement, le test et la validation d'automates d'investissement. In usual multi-agent stock market models, market structure is mostly reduced to an equation matching supply and demand, which synchronously aggregates agents decisions to update stock price at each time steps. On real markets, the process is however very different: stock price emerges from one-to one asynchronous interactions between buyers and sellers at various time step. In this article, we introduce an artificial stock market model designed to be close to real market structure. The model is based on a centralized orderbook through which agents exchange stocks asynchronously.We show that, without making any strong assumption on agents behaviors, this model exhibits many statistical properties of real stock markets. We argue that most of market features are implied by the exchange process more than by agents behaviors. This experimental result is validated and strengthen using several tests used by economists to characterize real market. We finally put in perspective the advantages of such a realistic model to develop, test and validate behavior of automated trading agents

Ergodic transition in a simple model of the continuous double auction

We study a phenomenological model for the continuous double auction, whose aggregate order process is equivalent to two independent M/M/1 queues. The continuous double auction defines a continuous-time random walk for trade prices. The conditions for ergodicity of the auction are derived and, as a consequence, three possible regimes in the behavior of prices and logarithmic returns are observed. In the ergodic regime, prices are unstable and one can observe a heteroskedastic behavior in the logarithmic returns. On the contrary, non-ergodicity triggers stability of prices, even if two different regimes can be seen

Data envelopment analysis in financial services: a citations network analysis of banks, insurance companies and money market funds

Development and application of the data envelopment analysis (DEA) method, have been the subject of numerous reviews. In this paper, we consider the papers that apply DEA methods specifically to financial services, or which use financial services data to experiment with a newly introduced DEA model. We examine 620 papers published in journals indexed in the Web of Science database, from 1985 to April 2016. We analyse the sample applying citations network analysis. This paper investigates the DEA method and its applications in financial services. We analyse the diffusion of DEA in three sub-samples: (1) banking groups, (2) money market funds, and (3) insurance groups by identifying the main paths, that is, the main flows of the ideas underlying each area of research. This allows us to highlight the main approaches, models and efficiency types used in each research areas. No unique methodological preference emerges within these areas. Innovations in the DEA methodologies (network models, slacks based models, directional distance models and Nash bargaining game) clearly dominate recent research. For each subsample, we describe the geographical distribution of these studies, and provide some basic statistics related to the most active journals and scholars