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Forecasting oil prices volatility with Google searches
Tolstoguzova, Ekaterina ; Krištoufek, Ladislav (advisor) ; Zafeiris, Dimitrios (referee)
Oil market pricing is highly susceptible to geopolitical and economic events. With the rapid development of information technology, energy market can quickly get external information shocks through the Internet. This thesis examines the relationship between prices of three oil benchmarks, CBOE Crude Oil Volatility Index, and Google search queries. We built VAR model to study Granger causality and to provide impulse response analysis. Results indicate both one side and two-side causal relationship between oil-related series and most of the search queries. Out-of sample forecasting with measures of predictive accuracy and Diebold-Mariano test demonstrated that Google trends can improve short-run prediction potential only for models with WTI price and volatility index.
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The impact of renewable resources on price volatility in the European power markets
Líšková, Katarína ; Krištoufek, Ladislav (advisor) ; Luňáčková, Petra (referee)
Integration of renewable energy sources impacts electricity spot price and its variation. Remaining open question is, in which direction. Volatility fluctuations threaten secur- ity of electricity supply, influence trading strategies and create uncertainty in optimal installed capacity planning. In this thesis, drivers of price volatility in Czech and Ger- man day-ahead power market are analysed with an emphasis on penetration of renewable energy sources. To the best of our knowledge, this is the first study focused on this issue in Czech electricity market. We apply recently developed approach of quadratic variation theory with an adjustment for electricity prices. Realised volatility is divided into its continuous and jump component. The continuous part is modelled by three het- erogeneous autoregressive models, differing in complexity and inclusion of market-specific fundamental variables. Amendments to each model for the particular market are proposed and the models are evaluated both in-sample and out-of-sample. Addition of exogenous variables − commodity prices, weather conditions and seasonal variables − to simpler heterogeneous autoregressive model is found to improve volatility forecast accuracy. The results suggest higher continuous volatility due to increased penetration of power from wind...
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The Feltham-Ohlson Model: Goodwill and Price Volatility
Janský, Michael ; Novák, Jiří (advisor) ; Baruník, Jozef (referee)
This paper derives and tests the hypothesis that there exists a positive relationship between the amount of unrecognized goodwill a company has in relation to the book value of its equity, and the volatility of the price of its stock and the average trading volume of its shares, and that further this relationship is stronger when the source of that goodwill cannot be traced to items recognized in accounting. The hypothesis is derived from the theory of residual income valuation and the Feltham-Ohlson model of company valuation, and is tested on the accounting and market data of 92 companies listed on the New York Stock Exchange. While the results do not offer sufficient reason to reject any of the paper's hypotheses, they provide only partial support to them, and further research is required.
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