National Repository of Grey Literature 3 records found  Search took 0.01 seconds. 
Regulation of green banking
Ivančová, Simona ; Teplý, Petr (advisor) ; Juhászová, Jana (referee)
This thesis provides an assessment of potential impacts of the regulation of green banking proposed by the European Commission. Two types of data and methodologies are used. The sample consisting of 28 green banks and 63 of its peers, observed from 2012 to 2018, is analysed via panel regression to es- timate the impact of green banking on profitability and volatility of banks. We use the Within-between estimation which allows the studied dummy vari- able Green to be estimated. Profitability is measured by Return on Assets and Return on Equity and to measure volatility we use their 7-year standard deviations. Aggregated data from the European Central Bank on European banks asset breakdown by instrument are used for the sensitivity analysis esti- mating the impact of the proposed regulation on the bank capital. Firstly, we did not find statistically significant impact of green banking practice on banks profitability. We found the green banks tend to demonstrate lower volatility in terms of Return on Equity. Secondly, we estimated that planned regulation of green banking practice will probably have negligible impact on the banks capital. However, it might decrease lending to carbon-intensive industries by commercial banks. Keywords brown penalty, green banking, green supporting factor, panel...
Statistická arbitráž při algoritmickém obchodování amerických dluhopisů
Juhászová, Jana ; Stádník, Bohumil (advisor) ; Janda, Karel (referee)
This thesis deals with statistical arbitrage as a strategy applied in algorithmic trading of US Treasury bonds in the selected timeframe from 1980 until 2017. Our aim is to prove that a specific event on the treasury market, namely reopening of the bonds, constitutes an arbitrage opportunity that enables the investor to systematically yield extraordinary profits on the market. This thesis includes a theoretical introduction to algorithmic trading and statistical arbitrage. Based on this introduction we formulate hypotheses, which are then tested in the application part by constructing an algorithm that simulates a trading strategy on historical data. Comparing three strategies we determined that this strategy is meaningful, or performs better than a random walk and that it is profitable.

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