The unpredictability of returns counts as a stylized fact of financial markets. To reproduce this fact, modelers
usually implement noise terms − a method with several downsides. Above all, systematic patterns are not
eliminated but merely blurred. The present article introduces a model in which systematic patterns are removed
endogenously. This is achieved in a reality-oriented way: Intelligent traders are able to identify patterns and
exploit them. To identify and predict patterns, a very simple artificial neural network is used. As neural network
mimic the cognitive processes of the human brain, this method might be regarded as a quite accurate way of how
traders identify patterns and forecast prices in reality. The simulation experiments show that the artificial traders
exploit patterns effectively and thereby remove them, which ultimately leads to the unpredictability of prices.
Further results relate to the influence of pattern exploiters on market efficiency.
This article explores the influence of competitive conditions on the
evolutionary fitness of different risk preferences. As a practical example, the
professional competition between fund managers is considered. To explore how
different settings of competition parameters, the exclusion rate and the exclusion
interval, affect individual investment behavior, an evolutionary model based on a
genetic algorithm is developed. The simulation experiments indicate that the
influence of competitve conditions on investment behavior and attitudes towards risk
is significant. What is alarming is that intense competitive pressure generates riskseeking
behavior and undermines the predominance of the most skilled.
We develop a simple behavioral macro model to study interactions between the real
economy and the stock market. The real economy is represented by a Keynesian goods
market approach while the setup for the stock market includes heterogeneous speculators.
Using a mixture of analytical and numerical tools we find, for instance, that speculators may
create endogenous boom-bust dynamics in the stock market which, by spilling over into the
real economy, can cause lasting fluctuations in economic activity. However, fluctuations in
economic activity may, by shaping the firms’ fundamental values, also have an impact on
the dynamics of the stock market.
The market structure can be described by concentration ratios based on the
oligopoly theory or the structure – conduct – performance paradigm. Measures of
concentration and also competition are essential for banks conduction in the
banking industry. Several researchers have proved concentration level to be major
determinants of banking system efficiency. Theoretical characteristics of market
concentration measures are illustrated with empirical evidence. The market
structure of the Albanian Banking Sector has changed dramatically in recent years.
On 1990s, our country has experienced deregulation, foreign bank penetration, and
an accelerated process of consolidation and competition in the banking sector.
Particularly, the working paper examines the nature and the extent of changes in
market concentration of Albanian banking sector. It focused primarily on a
descriptive and dynamic analysis of change in the concentration indices in banking
sector from year to year. Also it examines how the inherited structure of the
banking system affects the way of the distribution of market shares amongst the
different banks that comprise on the banking sector.