Economics and Finance


Predicting Global Stock Crash Events Using a Complex System of Deep Neural Networks and an XGBOOST Aggregation Layer

The global financial system is a complex network with many stakeholders and nonlinear feedback interactions among them. A core component of the global financial system is the major stock markets, the crashes of which are rare events that are driven by large-scale collective behavior, and are accompanied by high magnitude of both social and economic consequences (Bluedorn et al. (2013), Farmer (2012)).

The emergence of properties of the Japanese production network: How do listed firms choose their partners?

This work aims to explain how firms behave and select their partners in the Tokyo Stock Exchange (TSE) production network (network of suppliers and customers). Based on the microscopic interactions between firms, we look at the mechanism behind the emergence of the topology of the TSE production network. The supplier-customer network of listed firms in Japan (3,189 firms with 20,369 links) is estimated by the so-called exponential random graph model (ERGM).

A cluster driven log-volatility factor model: a deepening on the source of the volatility clustering

We introduce a new factor model for log volatilities that performs dimensionality reduction and considers contributions globally through the market, and locally through cluster structure and their interactions. We do not assume a-priori the number of clusters in the data, instead using the Directed Bubble Hierarchical Tree (DBHT) algorithm, which originates from complex systems, to fix the number of factors. We use the factor model and a new integrated non parametric proxy to study how volatilities contribute to volatility clustering.

Does the centrality of a stock in a financial network is determinant factor of its future returns?

Following the work of F. Pozzi et al. [1] who provided evidence that stocks lying at the periphery of a stock network tend to outperform those lying at the center, in this work we attempt to create an algorithmic stock selection and portfolio construction strategy based on stock network analysis.

Dynamical variety of multifractal characteristics for financial data

Nowadays, quantification of complex time series, in terms of multifractality, finds a multitude of applications in diverse areas. However, thus far the majority of the related studies presented in the scientific literature often focus on analysis of singularity spectrum width as a signature of the hierarchical organization and measure of the complexity degree. The time series generated by intricate processes may include many convoluted components with different hierarchy. Even more, contribution of such components in aggregated signal vary in time and results in its sophisticated dynamics.

Firms’ Complexity: Technological Scope, Coherence and Performance

The aim of this work is to shed light on the relationship between firms’ performance and their technological portfolios using tools borrowed from the complexity science. In particular, we ask whether the accumulation of knowledge and capabilities related to a coherent set of technologies leads firms to experience advantages in terms of productive efficiency. To this end, we analyzed both the balance sheets and the patenting activities of about 70 thousand firms that have filed at least one patent over the period 2004-2013.

Unfolding the Innovation System for the Development of Countries: Co-evolution of Science, Technology and Production

In this work [arXiv:1707.05146] we show that the space in which scientific, technological and economic developments interplay with each other can be mathematically shaped using pioneering multilayer network and complexity techniques. We build the tri-layered network (see Fig.1) of human activities (research, patenting, and industrial production) and study the interactions among them, also taking into account the possible time delays.

Economic Complexity Transition in Emerging Economies: A multi-criteria analysis of the case of Paraguay

Like many emerging economies, the productive structure of the Paraguayan economy is not complex. It relies extensively on low value-added activities in the primary sector such as agriculture and cattle ranching. In 2014, these activities represented more than 51% of the exports registered in Paraguay. These activities have a lower return in terms of economic and social benefits than other potential productive activities and do not contribute to increasing capability accumulation.


The official Hotel of the Conference is
Makedonia Palace.

Conference Organiser: NBEvents

The official travel agency of the Conference is: Air Maritime

Photo of Thessaloniki seafront courtesy of Juli Bellou
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