Home > Search Results: Řanda, Martin
Search:
Search Tips :: Advanced Search
Search collections:
Sort by: Display results: Output format:
National Repository of Grey Literature 2 records found  Search took 0.01 seconds. 
Short-term Electric Load Forecasting Using Czech Data
 Řanda, Martin ; Krištoufek, Ladislav (advisor) ; Čech, František (referee)
Forecasting electric load accurately is a critical prerequisite to dependable power grid operation. It is thus in the best interests of the responsible institutions to develop and maintain performant models for predicting load. In this thesis, we analyze Czech electric load data and execute three pseudo-out-of-sample forecasting exercises. We employ standard econometric as well as machine learning methods and compare the results to benchmarks, including the predictions published by the Czech transmission system operator. The results of the first task examining the predictability of minute loads using 11 years of data indicate that the high-frequency load series is predictable. In the second and third exercises, we utilize hourly loads with additional explanatory variables. We generate one-step-ahead and 48-hours-ahead forecasts on the 2021 out- of-sample set and evaluate the performance of several methods. In both exercises, the most accurate results are produced by averaging forecasts of our specified recurrent neural network and the seasonal autoregressive integrated moving average model, achieving a mean absolute percentage error of less than 0.5% on the out-of-sample set in the one-step-ahead analysis and 2.3% in the 48-hours-ahead exercise, outperforming the operator's predictions.
Detailed record
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.
Detailed record

See also: similar author names
3 Randa, Michal
1 Randa, Miloslav
Interested in being notified about new results for this query?
Subscribe to the RSS feed.
Digital Repository :: Search :: Submit :: Personalize :: Help
Powered by Invenio v1.1.2
Maintained by admin.invenio@techlib.cz
This site is also available in the following languages:
Česky  English