G12 - Asset Pricing; Trading Volume; Bond Interest RatesReturn

The comparative method is one of the methods of assessment of equity securities in theory and practice. The practical application of the comparative method is arranged in MS Decree No. 492/2004 Coll. on the establishment of the universal value of property and in Act No. 431/2002 Coll. on accounting, as amended by later regulations. According to this method, internal (general, real) value is derived from information on specific prices or values of shares of similar companies. The comparative method can be applied without serious problems only provided that the differences between the companies are small; otherwise, its use has been problematic. To find a comparable public limited company on a mature capital market, where the number of traded comparable companies is high, is not a problem. It is very difficult for a small market such as Slovakia's stock market. This paper discusses the application of comparative methods to the non-standard Slovak capital market.

Motivated by the changing nature of the natural gas industry in the European Union, driven by the liberalisation process, we focus on the introduction and pricing of gas swing options. These options are embedded in typical gas sales agreements in the form of offtake flexibility concerning volume and time. The gas swing option is actually a set of several American puts on a spread between prices of two or more energy commodities. This fact, together with the fact that the energy markets are fundamentally different from traditional financial security markets, is important for our choice of valuation technique. Due to the specific features of the energy markets, the existing analytic approximations for spread option pricing are hardly applicable to our framework. That is why we employ Monte Carlo methods to model the spot price dynamics of the underlying commodities. The price of an arbitrarily chosen gas swing option is then computed in accordance with the concept of risk-neutral expectations. Finally, our result is compared with the real payoff from the option realised at the time of the option execution and the maximum ex-post payoff that the buyer could generate in case he knew the future, discounted to the original time of the option pricing.

Estimation of volatility of financial time series plays a crucial role in pricing derivatives. Volatility is often estimated from historical data; however, it is well known that volatility varies in time. We propose a method to choose a suitable length of historical data to estimate contemporary volatility. The method is based on adaptation of a procedure used in statistical quality control - a hypothesis, that data contains a changepoint of volatility, is tested and if the test gives a positive answer, the changepoint is estimated. Then, a period of data where no changepoint is statistically significant is used to estimate contemporary volatility. The approach is illustrated on an analysis of CZK/EUR exchange rates.

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.

The Efficient Market Hypothesis (EMH) asserts that the prices of securities correctly and fully reflect all available information. But there are some empirical facts in capital markets thatEMHis not able to explain. Recently, a lot of new models with heterogeneous agents in expectation formation of future asset prices have arisen. The main aim of this paper is to compare three of them - model introduced by C. Chiarella in 1992, where the equilibrium price is determined by the excess demands of different groups of agents, model developed by W. Brock and C. Hommes with additional variable of proportion of agents with different strategies and further extended D. Goldbaum's model. Statistical properties of the time series of S&P 500 index are compared with the price time series generated by these models. This can be done due to chaotic price behaviour, which occurs for partially estimated, partially selected model values of parameters in these nonlinear dynamical systems. The results show that the third model achieves the best performance. This model is the most complex one and thus the most closely to reality but at the expense of mathematical tractability.