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    Wyświetlanie 1-6 z 6
    Tytuł:
    A Note on Option Pricing with the Use of Discrete-Time Stochastic Volatility Processes
    Autorzy:
    Pajor, Anna
    Powiązania:
    https://bibliotekanauki.pl/articles/483255.pdf
    Data publikacji:
    2009
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    option pricing
    SV model
    Bayesian forecasting
    Opis:
    In this paper we show that in the lognormal discrete-time stochastic volatility model with predictable conditional expected returns, the conditional expected value of the discounted payoff of a European call option is infinite. Our empirical illustration shows that the characteristics of the predictive distributions of the discounted payoffs, obtained using Monte Carlo methods, do not indicate directly that the expected discounted payoffs are infinite.
    Źródło:
    Central European Journal of Economic Modelling and Econometrics; 2009, 1, 1; 71-81
    2080-0886
    2080-119X
    Pojawia się w:
    Central European Journal of Economic Modelling and Econometrics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Using VARs and TVP-VARs with Many Macroeconomic Variables
    Autorzy:
    Koop, Gary
    Powiązania:
    https://bibliotekanauki.pl/articles/483265.pdf
    Data publikacji:
    2012
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    Bayesian VAR
    forecasting
    time-varying coefficients
    state-space model
    Opis:
    This paper discusses the challenges faced by the empirical macroeconomist and methods for surmounting them. These challenges arise due to the fact that macroeconometric models potentially include a large number of variables and allow for time variation in parameters. These considerations lead to models which have a large number of parameters to estimate relative to the number of observations. A wide range of approaches are surveyed which aim to overcome the resulting problems. We stress the related themes of prior shrinkage, model averaging and model selection. Subsequently, we consider a particular modelling approach in detail. This involves the use of dynamic model selection methods with large TVP-VARs. A forecasting exercise involving a large US macroeconomic data set illustrates the practicality and empirical success of our approach.
    Źródło:
    Central European Journal of Economic Modelling and Econometrics; 2012, 4, 3; 143-167
    2080-0886
    2080-119X
    Pojawia się w:
    Central European Journal of Economic Modelling and Econometrics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Forecasting the distribution of methane concentration levels in mine headings by means of model-based tests and in-situ measurements
    Autorzy:
    Brodny, Jarosław
    Tutak, Magdalena
    Powiązania:
    https://bibliotekanauki.pl/articles/229542.pdf
    Data publikacji:
    2019
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    CFD
    forecasting the distribution of methane
    mining heading
    in-situ measurements
    model tests
    Opis:
    The methane hazard is one of the most dangerous phenomena in hard coal mining. In a certain range of concentrations, methane is flammable and explosive. Therefore, in order to maintain the continuity of the production process and the safety of work for the crew, various measures are taken to prevent these concentration levels from being exceeded. A significant role in this process is played by the forecasting of methane concentrations in mine headings. This very problem has been the focus of the present article. Based on discrete measurements of methane concentration in mine headings and ventilation parameters, the distribution of methane concentration levels in these headings was forecasted. This process was performed on the basis of model-based tests using the Computational Fluid Dynamics (CFD). The methodology adopted was used to develop a structural model of the region under analysis, for which boundary conditions were adopted on the basis of the measurements results in real-world conditions. The analyses conducted helped to specify the distributions of methane concentrations in the region at hand and determine the anticipated future values of these concentrations. The results obtained from model-based tests were compared with the results of the measurements in real-world conditions. The methodology using the CFD and the results of the tests offer extensive possibilities of their application for effective diagnosis and forecasting of the methane hazard in mine headings.
    Źródło:
    Archives of Control Sciences; 2019, 29, 1; 25-39
    1230-2384
    Pojawia się w:
    Archives of Control Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Construction of the passenger rail traffic generation model
    Budowa modelu generacji ruchu kolejowego
    Autorzy:
    Brzeziński, Andrzej
    Waltz, Andrzej
    Powiązania:
    https://bibliotekanauki.pl/articles/2174027.pdf
    Data publikacji:
    2022
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    ruch kolejowy
    model generacji ruchu
    analiza regresyjna
    prognozowanie ruchu
    ruch pasażerski
    railway traffic
    traffic model
    generation model
    regression analysis
    traffic forecasting
    passenger traffic
    Opis:
    The article presents a new approach to building a passenger rail traffic generation model. It uses data on the number of passengers at stations and railway stops obtained from the databases of operators on the rail transport market through the Office of Rail Transport - market regulator - combined with data on the model of the area around the station built based on population, number of beds, individual motorization and gross domestic product (GDP). This enabled analyzing the potential of railway traffic generation at a very detailed level. The article presents a methodology for building a passenger rail traffic generation model and verification of this model based on limited variables describing railway stations and stops as well as traffic zones and available statistical data. The model takes into account three segments of the railway market: regional, interregional and inter-agglomeration transport. The results of these analyzes can be used to increase the accuracy and the reliability of rail traffic models used in the analysis of transport networks.
    W artykule przedstawiono nowe podejście do budowy modelu generacji pasażerskiego ruchu kolejowego. Przedstawiono propozycję metodyki budowy modelu generacji pasażerskiego ruchu kolejowego oraz weryfikacji tego modelu w oparciu o ograniczone zmienne opisujące stacje i przystanki kolejowe oraz rejony komunikacyjne i dostępne dane statystyczne. Wykorzystano w nim dane o liczbie pasażerów na stacjach i przystankach kolejowych w połączeniu z danymi opisującymi model obszaru wokół stacji budowany w oparciu o liczbę ludności, liczbę miejsc noclegowych, motoryzację indywidualną i produkt krajowy brutto (PKB).Wykorzystanie tych danych umożliwiło przeprowadzenie analizy potencjału generacji ruchu kolejowego na dużym poziomie szczegółowości. W metodzie uwzględniono trzy segmenty rynku kolejowego: przewozy regionalne, międzyregionalne i międzyaglomeracyjne.
    Źródło:
    Archives of Civil Engineering; 2022, 68, 3; 107--123
    1230-2945
    Pojawia się w:
    Archives of Civil Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    City Backbone Network Traffic Forecasting
    Autorzy:
    Serikov, Tansaule
    Zhetpisbayeva, Ainur
    Аkhmediyarova, Аinur
    Mirzakulova, Sharafat
    Aigerim, Kismanova
    Tolegenova, Aray
    Wójcik, Waldemar
    Powiązania:
    https://bibliotekanauki.pl/articles/1844529.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    time series
    packet intensity
    Dickey-Fuller test
    Kwiatkowski-Phillips-Perron-Shin-Schmitt test
    forecasting
    integrated moving average autoregression model
    Opis:
    The work considers a one-dimensional time series protocol packet intensity, measured on the city backbone network. The intensity of the series is uneven. Scattering diagrams are constructed. The Dickie Fuller test and Kwiatkowski-Phillips Perron-Shin-Schmitt test were applied to determine the initial series to the class of stationary or non-stationary series. Both tests confirmed the involvement of the original series in the class of differential stationary. Based on the Dickie Fuller test and Private autocorrelation function graphs, the Integrated Moving Average Autoregression Model model is created. The results of forecasting network traffic showed the adequacy of the selected model.
    Źródło:
    International Journal of Electronics and Telecommunications; 2021, 67, 3; 319-324
    2300-1933
    Pojawia się w:
    International Journal of Electronics and Telecommunications
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Spatiotemporal attention mechanism-based multistep traffic volume prediction model for highway toll stations
    Autorzy:
    Huang, Zijing
    Lin, Peiqun
    Lin, Xukun
    Zhou, Chuhao
    Huang, Tongge
    Powiązania:
    https://bibliotekanauki.pl/articles/2124715.pdf
    Data publikacji:
    2022
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    ITS
    traffic volume forecasting
    attention mechanism
    highway toll station
    model interpretation
    natężenia ruchu
    prognozowanie
    mechanizm uwagi
    stacja poboru opłat
    Opis:
    As the fundamental part of other Intelligent Transportation Systems (ITS) applications, short-term traffic volume prediction plays an important role in various intelligent transportation tasks, such as traffic management, traffic signal control and route planning. Although Neural-network-based traffic prediction methods can produce good results, most of the models can’t be explained in an intuitive way. In this paper, we not only proposed a model that increase the short-term prediction accuracy of the traffic volume, but also improved the interpretability of the model by analyzing the internal attention score learnt by the model. we propose a spatiotemporal attention mechanism-based multistep traffic volume prediction model (SAMM). Inside the model, an LSTM-based Encoder-Decoder network with a hybrid attention mechanism is introduced, which consists of spatial attention and temporal attention. In the first level, the local and global spatial attention mechanisms considering the micro traffic evolution and macro pattern similarity, respectively, are applied to capture and amplify the features from the highly correlated entrance stations. In the second level, a temporal attention mechanism is employed to amplify the features from the time steps captured as contributing more to the future exit volume. Considering the time-dependent characteristics and the continuity of the recent evolutionary traffic volume trend, the timestamp features and historical exit volume series of target stations are included as the external inputs. An experiment is conducted using data from the highway toll collection system of Guangdong Province, China. By extracting and analyzing the weights of the spatial and temporal attention layers, the contributions of the intermediate parameters are revealed and explained with knowledge acquired by historical statistics. The results show that the proposed model outperforms the state-of-the-art model by 29.51% in terms of MSE, 13.93% in terms of MAE, and 5.69% in terms of MAPE. The effectiveness of the Encoder-Decoder framework and the attention mechanism are also verified.
    Źródło:
    Archives of Transport; 2022, 61, 1; 21--38
    0866-9546
    2300-8830
    Pojawia się w:
    Archives of Transport
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-6 z 6

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