Sökning: "GARCH"

Visar resultat 1 - 5 av 285 uppsatser innehållade ordet GARCH.

  1. 1. Volatility forecasting using the GARCH framework on the OMXS30 and MIB30 stock indices

    Kandidat-uppsats, Göteborgs universitet/Institutionen för nationalekonomi med statistik

    Författare :Peter Johansson; [2019-01-22]
    Nyckelord :Volatility forecasting; Random Walk; Moving Average; Exponentially Weighted Moving Average; GARCH; EGARCH; GJR-GARCH; APGARCH; volatility model valuation; regression; information criterion;

    Sammanfattning : There are many models on the market that claim to predict changes in financial assets as stocks on the Stockholm stock exchange (OMXS30) and the Milano stock exchange index (MIB30). Which of these models gives the best forecasts for further risk management purposes for the period 31st of October 2003 to 30th of December 2008? Is the GARCH framework more successful in forecasting volatility than more simple models as the Random Walk, Moving Average or the Exponentially Weighted Moving Average?The purpose of this study is to find and investigate different volatility forecasting models and especially GARCH models that have been developed during the years. LÄS MER

  2. 2. Portfolio Optimization : A DCC-GARCH forecast with implied volatility

    Magister-uppsats, Linnéuniversitetet/Institutionen för ekonomistyrning och logistik (ELO); Linnéuniversitetet/Institutionen för ekonomistyrning och logistik (ELO)

    Författare :Sam Bigdeli; Filip Bengtsson; [2019]
    Nyckelord :DCC-GARCH; Portfolio Optimization; Certainty Equivalence Tangency; CET; Global Minimum Variance; GMV; Minimum Conditional Value-at-Risk; MinCVaR; Implied volatility index; VIX;

    Sammanfattning : This thesis performs portfolio optimization using three allocation methods, Certainty Equivalence Tangency (CET), Global Minimum Variance (GMV) and Minimum Conditional Value-at-Risk (MinCVaR). We estimate expected returns and covariance matrices based on 7 stock market indices with a DCC-GARCH model including an ARMA (1. LÄS MER

  3. 3. How to Avoid Bankruptcy?: Monte Carlo Simulation of Three Financial Markets, using the Multifractal Model of Asset Returns

    D-uppsats, Handelshögskolan i Stockholm/Institutionen för finansiell ekonomi

    Författare :Rostislav Sibirtsev; [2019]
    Nyckelord :Multifractal Model of Asset Returns MMAR ; Simulation; Fractal; Kurtosis; Dependence;

    Sammanfattning : This paper has been an effort to apply fractal mathematics to understanding the general behaviour of financial markets. Fractals are special shapes that look similar at various scales. The specific model used is called the Multifractal Model of Asset Returns (MMAR) - the first ever model used for multifractal financial analysis. LÄS MER

  4. 4. A STUDY ON THE DCC-GARCH MODEL’S FORECASTING ABILITY WITH VALUE-AT-RISK APPLICATIONS ON THE SCANDINAVIAN FOREIGN EXCHANGE MARKET

    Kandidat-uppsats, Uppsala universitet/Statistiska institutionen; Uppsala universitet/Statistiska institutionen

    Författare :Tim Andersson-Säll; Johan Lindskog; [2019]
    Nyckelord :Multivariate GARCH; Conditional Correlations; Forecasting; Time-varying covariance matrices; Exchange rate returns; Variance-Covariance matrix;

    Sammanfattning : This thesis has treated the subject of DCC-GARCH model’s forecasting ability and Value-at- Risk applications on the Scandinavian foreign exchange market. The estimated models were based on daily opening foreign exchange spot rates in the period of 2004-2013, which captured the information in the financial crisis of 2008 and Eurozone crisis in the early 2010s. LÄS MER

  5. 5. Analysis of Cryptocurrency volatility and statistical distributions using ARMA and GARCH-type models

    Magister-uppsats, Lunds universitet/Statistiska institutionen

    Författare :Zhiyi You; [2019]
    Nyckelord :Cryptocurrency; Bitcoin; Litecoin; Ethereum; volatility; ARMA; GARCH-type models; eGARCH; Student s t-distribution; Laplace distribution; statistical distributions; Mathematics and Statistics;

    Sammanfattning : This study aims to investigate and model statistical properties of Bitcoin and other major cryptocurrencies. There were recent drastic changes in the level of Bitcoin prices as it moved from $740 in 2014 to $19,187 in 2017, and down to $3,830 in 2018. LÄS MER