Original title: Modelování dynamiky korelací finančních trhů pomocí vysokofrekvenčních dat
Translated title: Modeling Dynamics of Correlations between Stock Markets with High-frequency Data
Authors: Lypko, Vyacheslav ; Baruník, Jozef (advisor) ; Krištoufek, Ladislav (referee)
Document type: Master’s theses
Year: 2012
Language: eng
Abstract: [eng] [cze]
In this thesis we focus on modelling correlation between selected stock markets using high-frequency data. We use time-series of returns of following indices: FTSE, DAX PX and S&P, and Gold and Oil commodity futures. In the first part of our empirical work we compute daily realized correlations between returns of subject instruments and discuss the dynamics of it. We then compute unconditional correlations based on average daily realized correlations and using feedforward neural network (FFNN) to assess how well the FFNN approximates realized correlations. We also forecast daily realized correlations of FTSE:DAX and S&P:Oil pairs using heterogeneous autoregressive model (HAR), autoregressive model of order p (AR(p)) and nonlinear autoregressive neural network (NARNET) and compare performance of these models. Tato prace je zamerena na modelovani korelaci mezi vybranymi akciovymi trhy a komoditami s pouzitim vysokofrekvencnich dat. Nasledujici casove rady jsou pouzite pro ucely teto analyzy: FTSE, DAX, PX, S&P, Gold commodity futures a Oil commodity futures. V prvni casti teto prace denni realizovane korelace jsou vypocitane a jejich dynamika je diskutovana. Dal jsou vypocitane korelace pomoci neuronove site (feed forward neural network, nebo FFNN). Tyto korelace jsou porovane s prumernymi dennimi realizovanymi korelacemi. V posledni casti teto prace jsou vypocitane prognozy dennich realizovanych korelaci pomoci HAR modelu, AR(p) modelu a dynamicke neuronove site NARNET.
Keywords: correaltion; high-frequency data; neural network; realzied correaltion; korelace; neuronove site; realizovane korelace; vysokofrekvencni data

Institution: Charles University Faculties (theses) (web)
Document availability information: Available in the Charles University Digital Repository.
Original record: http://hdl.handle.net/20.500.11956/40730

Permalink: http://www.nusl.cz/ntk/nusl-305034


The record appears in these collections:
Universities and colleges > Public universities > Charles University > Charles University Faculties (theses)
Academic theses (ETDs) > Master’s theses