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Evaluating the predictability of virtual exchange rates using daily data
Řanda, Martin ; Polák, Petr (advisor) ; Kukačka, Jiří (referee)
Virtual worlds have garnered the attention of researchers from various disci- plines and are viewed as particularly valuable to economists due to their open- ended design. In this thesis, we review a popular online multiplayer game's economy and focus on exchange rate predictability in a virtual setting as only a limited body of literature investigated this topic. The well-established unpre- dictability puzzle is addressed by exploiting a unique daily time series dataset using a vector autoregressive framework. Apart from a significant Granger- causal relationship between the virtual exchange rate and the player popula- tion, the system is shown to be less interconnected than expected. Furthermore, an out-of-sample exercise is conducted, and the forecasting performance of our models is examined in comparison to that of a simple no-change benchmark in the short term. Based on the evaluation methods used, the two measures of the virtual exchange rate are found to be somewhat predictable. We suggest two explanations for this inconsistency between the virtual and real-world exchange rates: data frequency and lack of complexity in the considered online economy.
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Quality control and homogeneity testing of daily time series of eca ECA&D
Zahradníček, Pavel ; Štěpánek, Petr ; Farda, Aleš ; Skalák, Petr
For any meaningful climate analysis, it is necessary for analysed time series to be homogeneous, which means that their variations are caused solely by variations in weather and climate (Conrad and Pollak 1950). Th us, prior to any analysis, the need to homogenize data and check their quality arises. Unfortunately, most of the climatological series that span over decades, to centuries, contain inhomogeneities caused by station relocations, exchange of observers, changes in the vicinity of the stations (e.g. urbanization), changes in instruments, observing practices (e.g. diff erent formulas for calculating daily means, diff erent observation times), etc. In this work we focused on testing the quality and homogeneity of daily data produced by ECA&D. Th is is a free available dataset of daily meteorological elements from the European Climate Assessment & Dataset (http://eca.knmi.nl/). Th is database was used to create a regular grid of EOBS points, which are oft en used to validate climate models.
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