Econophysics: empirical facts

This article aims at reviewing recent empirical and theoretical developments usually grouped under the term Econophysics. Since its name was coined in 1995 by merging the words "Economics" and "Physics", this new interdisciplinary field has grown in various directions: theoretical macroeconomics (wealth distributions), microstructure of financial markets (order book modeling), econometrics of financial bubbles and crashes. We give a brief introduction in the first part and begin with discussing interactions between Physics, Mathematics, Economics and Finance that led to the emergence of Econophysics in the second part. Then the third part is dedicated to empirical studies revealing statistical properties of financial time series. We begin the presentation with the widely acknowledged "stylized facts" describing the distribution of the returns of financial assets: fat-tails, volatility clustering, etc. Then we show that some of these properties are directly linked to the way "time" is taken into account, and present some new remarks on this account. We continue with the statistical properties observed on order books in financial markets. For the sake of illustrations in this review, (nearly) all the stated facts are reproduced using our own high-frequency financial database. Contributions to the study of correlations of assets such as random matrix theory and graph theory are finally presented in this part. The fourth part of our review deals with models in Econophysics through the point of view of agent-based modeling. Using previous work originally presented in the fields of behavioural finance and market microstructure theory, econophysicists have developed agent-based models of orderdriven markets that are extensively reviewed here. We then turn to models of wealth distribution where an agent-based approach also prevails: kinetic theory models, and continue with game theory models and review the now classic minority games. We end this review by providing an outlook on possible directions of research.

WHAT SHOULD AN UNMANAGED EARNINGS DISTRIBUTION LOOK LIKE?

In asserting that the number of firms reporting small profits is abnormally high, thus suggesting that earnings management has taken place, accounting researchers assume that the distribution of reported earnings should be smooth for unmanaged earnings. This has never in fact been demonstrated. This article seeks to confirm this assumption through a laboratory experiment, and also sets out to identify the general distribution pattern to be expected for unmanaged earnings. Normal distribution does not appear to be a good fit. The study's results also highlight the existence of downward management of earnings by firms with higher-than-average profits.Earnings management, earnings distribution, experiment, accounting threshold.

New activity pattern in human interactive dynamics

We investigate the response function of human agents as demonstrated by written correspondence, uncovering a new universal pattern for how the reactive dynamics of individuals is distributed across the set of each agent's contacts. In long-term empirical data on email, we find that the set of response times considered separately for the messages to each different correspondent of a given writer, generate a family of heavy-tailed distributions, which have largely the same features for all agents, and whose characteristic times grow exponentially with the rank of each correspondent. We furthermore show that this universal behavioral pattern emerges robustly by considering weighted moving averages of the priority-conditioned response-time probabilities generated by a basic prioritization model. Our findings clarify how the range of priorities in the inputs from one's environment underpin and shape the dynamics of agents embedded in a net of reactive relations. These newly revealed activity patterns might be present in other general interactive environments, and constrain future models of communication and interaction networks, affecting their architecture and evolution.Comment: 15 pages, 7 figure

Actors and factors - bridging social science findings and urban land use change modeling

Recent uneven land use dynamics in urban areas resulting from demographic change, economic pressure and the cities’ mutual competition in a globalising world challenge both scientists and practitioners, among them social scientists, modellers and spatial planners. Processes of growth and decline specifically affect the urban environment, the requirements of the residents on social and natural resources. Social and environmental research is interested in a better understanding and ways of explaining the interactions between society and landscape in urban areas. And it is also needed for making life in cities attractive, secure and affordable within or despite of uneven dynamics.\ud The position paper upon “Actors and factors – bridging social science findings and urban land use change modeling” presents approaches and ideas on how social science findings on the interaction of the social system (actors) and the land use (factors) are taken up and formalised using modelling and gaming techniques. It should be understood as a first sketch compiling major challenges and proposing exemplary solutions in the field of interest