Economics and Finance

We propose [1] a new model of the liquidity-driven banking system focusing on overnight interbank loans. This significant branch of the interbank market is commonly neglected in the banking system modeling and systemic risk analysis. We construct a model where banks are allowed to use both the interbank and the securities markets to manage their liquidity demand and supply as driven by prudential requirements in a volatile environment. The network of interbank loans is dynamic and simulated every day.

Stochastic volatility is an omnipresent property of all financial time series. Due to this phenomenon, equidistant time-stamps - synchronized with the flow of physical time and used to make snapshots of the market states - are either (1) too sparse and do not capture all the available high-frequency information or are (2) too dense which results in superfluous noisy events in the final time series. Returns, computed with equal time intervals, might erroneously contribute to the volatility estimation.

Network analysis has become a primary tool in fields as diverse as systems biology, ecology, epidemiology, sociology, economics and finance. We present the work that demonstrates the existence of an empirical linkage between nominal financial networks and the underlying economic fundamentals, across countries [1].

There is growing interest in the use of critical slowing down and critical fluctuations as early warning signals (EWSs) for critical transitions in different complex systems. However, while some studies found them effective, others found the opposite. In this talk, we report our systematic tests of three commonly used indicators: lag-1 autocorrelation, variance, and low-frequency power spectrum at anticipating critical transitions in the very-high-frequency time series data of the Australian Dollar-Japanese Yen (AUD-JPY) and Swiss Franc-Japanese Yen (CHF-JPY) exchange rates [1].

Currency trading (Forex) is the largest world market in terms of volume. We analyzed trading and tweeting about the EUR-USD currency pair over a period of three years. First, a large number of tweets were manually labeled, and a Twitter stance classification model was constructed. We used the model to classify all the tweets by the trading stance signal: buy, hold, or sell (EUR vs. USD). The Twitter stance was compared to the actual currency rates by applying the event study methodology, well-known in financial economics.

Game theory is widely used to model strategic interactions in economics and finance. Concepts from game theory are applied in fields ranging from evolutionary economics and behavioral economics to political economy and further to political science and to ecology and evolutionary biology. Especially in economics, it is common practice to assume that players in strategic games instantly coordinate on an equilibrium. However, when the players have to learn their strategies by playing a game repeatedly the strategic dynamics may fail to converge.

This paper analyzes the impact of technological development on environmental performance using annual data on 88 developed and developing countries for the period 2002-2012. As a proxy for technological development, we use the Economic Complexity Index and we highlight that a country's productive structure is associated with the amount of knowledge and know-how embodied in its productive structure, which is a straightforward proxy-measure of the country's level of technology. We measure environmental performance by considering the recently developed Environmental Performance Index.

This paper proposes a two-countries model for the determination of the exchange rate, mixing the agent-based (AB) and the stock-flow consistent (SFC) methodologies. This artificial economy is populated by heterogeneous traders who can be either fundamentalist or chartist in exchange rate expectations (De Grauwe and Grimaldi, 2003; Lavoie & Daigle, 2011). Chartist traders are further split between trend followers and trend contrarians, consistently with empirical surveys witnessing both types of strategies in the Forex (Schulmeister, 2007).

We develop a multi-agent model of the insurance and reinsurance sectors and study systemic risk arising from risk model homogeneity. Risk models are accurate only up to a certain degree. In particular, they may err with respect to the correlation of risk events. With a small but significant probability, they would therefore lead to the insolvency and bankruptcy of the company. Would all insurance and reinsurance companies use the same risk model, bankruptcies in the insurance sector would happen in clusters. This would result in structural problems for the entire sector.

Throughout the last centuries Central and Eastern Europe (CEE) has been a territory dominated by different Empires and countries, contributing to shape certain tradition of exchanges (Brunet&Rey, 1996; Castles, 1995). After the fall of the Berlin wall in 1989, the transition to market economy has stimulated a significant inflow of foreign capital towards CEE cities (Hamilton et al. 2005).