G14 - Information and Market Efficiency; Event Studies; Insider TradingReturn

The paper deals with high-frequency algorithmic trading (HFT), which has recently come to dominate some financial markets, e.g. the US equity markets. The author first attempts to establish a clear definition of high-frequency trading. With the most important characteristics having been analysed, it is concluded that such a definition would not bring more clarity into the debate over HFT. Strategies pursued by traders should be given consideration instead. On this account, the text proceeds with the examination of the most common strategies. Afterwards, the question is raised whether the rise of high-frequency algorithmic traders has resulted in more efficient financial markets. Based on robust evidence from academic research, important market participants and exchanges, HFT indeed seems to improve market quality by narrowing spreads and providing additional liquidity - the market-making strategy is mainly responsible for the latter. Issues such as possible system risks (flash crashes, herd behaviour) are also discussed.

The paper is concerned with an implementation of behavioral aspects of a heterogeneous agents model (HAM) with the worst out algorithm (WOA). The WOA replaces periodically the trading strategies that have the lowest performance level of all strategies presented on the market by the new ones. The model includes a possibility to change the mood of the investors on the market. This modification allows for changing phases of optimism and pessimism. This feature enables generation of more realistic financial time series. It is shown how a mood change on the financial market influence a persistence of financial time series.

This article focuses on determination of risk factors of stock returns in 3 countries of central Europe, such as the Czech Republic, Poland and Hungary. Firstly, it tries to characterize a group of emerging markets and overview its stock returns in the last decade. After that it tries to identify significant risk factors of stock returns of these three countries in different levels of global, European and local.