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ACD Model and the Czech Capital Market
Moravová, Anna ; Beneš, Viktor (referee) ; Šmíd, Martin (advisor)
This study is concerned with the autoregressive conditional duration model (ACD) and its applications on the data from the Prague Stock exchange. The ACD model is particularly suitable for the analysis of data which arrive at irregular time intervals. We treat the time between events as a stochastic process. We apply the ACD model to model the intervals between the trades with the stock of Komerčn' Banka at the Prague Stock Exchange in the year 2004. The parameters are estimated by the maximum likelihood method. Further, an extension of the ACD model - the ACD-ACM model - is studied. ACM model is used to model the discrete price changes in the stock prices. The distribution of each price change is considered to be a random variable with distribution conditional on the past price changes and other explanatory variables. The ACD-ACM model is applied to the quote data of the stock of Czech Telecom from the year 2004. The results of the calculations are compared with the results presented by Engle and Russel in their studies from the years 1998 and 2005.
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Value-at-Risk estimation - non standard approaches.
Picková, Radka ; Šmíd, Martin (referee) ; Dupačová, Jitka (advisor)
The topic of the presented work is Value-at-Risk (VaR) and its estimation. VaR is a financial risk measure and is defined as a quantile of the distribution of future returns, resp. losses. There exist various methods based on different assumptions how to estimate VaR. The most commonly used methods usually assume that the returns, resp. losses, are independently and identically distributed, especially that they are normally distributed. Since this assumption is not satisfied for most daily financial data, many alternative approaches have been suggested to estimate VaR. In the presented work two of them are discussed in detail, the CAViaR method and its asymptotic properties and the method of filtered historical simulation. One part of the work are numerical experiments with real data.
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Generating of Random Samples with Given Properties and Application to Banking
Voronin, Alexander ; Franěk, Petr (advisor) ; Šmíd, Martin (referee)
The work concerns the searching for the algorithm for generating of the random variables with the given properties. There are made analyses of comparisons of the algorithms, and the optimal algorithm was chosen based on it. Since we focus on generating of random variables of defaults and explanatory variables of defaults, it concentrates mainly on the conservation of the dependence of these variables. Further we are looking for the optimal sample size of the generated samples under conservation of the required properties. And in the last Chapter we have applied the surveyed techniques to the real data.
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Statistical Properties of the Czech Capital Market.
Horák, Jiří ; Kaňková, Vlasta (referee) ; Šmíd, Martin (advisor)
This diploma thesis tackles the behavioral description of stocks which are offered at Prague Stock Exchange (PSE). This is carried out by comparison of Statistical properties of returns of individual trades and market makers' quotes during the random walk , tail behavior and ARCH modeling studies. Achieved results are then confronted with the results observed at large financial markets such as New York Stock Exchange (NYSE) and London Stock Exchange (LSE). Based on approaches mentioned above we conclude, that market makers behavior at PSE is quite dependent on the individual trades which have been made on the market and that the reac tion time of the whole market to these changes is nearly instantaneous, thus PSE could be regarded as a very effec tive market. Anoth er property of PSE is, that the price of individual trades is considerably stable in a few days horizon and market makers' quotes are oscillating around this price, thus Czech market could be considered as substantially stable and competitive.
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Decision of a Steel Company Trading with Emissions
Zapletal, F. ; Šmíd, Martin
We formulate a Mean-CVaR decision problem of a production company obliged to cover its CO2 emissions by allowances. Certain amount of the allowances is given to the company for free, the missing/redundant ones have to be bought/sold on a market. To manage their risk, the company can use derivatives on emissions allowances (in particular futures and options), in addition to spot values of allowances. We solve the decision problem for the case of an real-life Czech steel company for different levels of risk aversion and different scenarios of the demand. We show that the necessity of emissions trading generally, and the risk caused by the trading in particular, can influence the production significantly even when the risk is decreased by means of derivatives. The results of the study show that even for low levels of the risk aversion, futures on allowances are optimal to use in order to reduce the risk caused by the emissions trading.
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