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許偉才 and Wai-choi Hui. "Optimal asset allocation under GARCH model." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2000. http://hub.hku.hk/bib/B31222717.
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Hui, Wai-choi. "Optimal asset allocation under GARCH model /." Hong Kong : University of Hong Kong, 2000. http://sunzi.lib.hku.hk/hkuto/record.jsp?B2160616X.
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Khalilzadeh, Amir Hossein. "Variance Dependent Pricing Kernels in GARCH Models." Thesis, Uppsala universitet, Analys och tillämpad matematik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-180373.
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Sze, Mei Ki. "Mixed portmanteau test for ARMA-GARCH models /." View abstract or full-text, 2009. http://library.ust.hk/cgi/db/thesis.pl?MATH%202009%20SZE.
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ARAUJO, GUSTAVO SILVA. "ANALYSIS OF THE GARCH OPTION PRICING MODEL USING TELEBRAS CALLS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2002. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=3343@1.
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Este trabalho procura confirmar a hipótese de o modelo de
apreçamento de opções GARCH reduzir alguns dos já
amplamente estudados vieses do modelo de Black & Scholes,
utilizando opções de compra da Telebras no período julho de
1995 a junho de 2000. Para isso, comparam-se os preços
encontrados por intermédio do modelo GARCH com os do modelo
de Black & Scholes, cotejando-os com os preços de mercado.
Os resultados indicaram que o modelo GARCH foi capaz de
diminuir alguns dos vieses, principalmente para opções fora-
do-dinheiro com curto tempo para o vencimento. Desta forma,
o modelo GARCH se mostrou uma alternativa eficaz ao modelo
de Black e Scholes, sobretudo para opções com pouca
liquidez, nas quais não é possível a utilização da
volatilidade implícita da equação de Black e Scholes.This study attempts to confirm the hypothesis that the GARCH option pricing model reduces some of the well- documented biases associated with the Black & Scholes model, using Telebras calls in the period of July 1995 to June 2000. For this purpose, the prices obtained by the GARCH model are compared with the ones obtained by the Black and Scholes model, and both of them are checked with the market prices. The results of this research indicate that the GARCH model is able to lessen some biases, specially for out-of-the-money options with short maturity. Thus, the GARCH model is an efficient alternative to the Black and Scholes model, mainly for options with low liquidity, in which it is not possible to use the implicit volatility of the Black and Scholes equation.
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De, Wet Walter Albert. "A structural GARCH model an application to portfolio risk management /." Pretoria : [s.n.], 2005. http://upetd.up.ac.za/thesis/available/etd-04132005-143137.
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Yuan, Huimin. "Analysis of Fractionally Differenced Processes with Heteroscedastic Errors." Thesis, The University of Sydney, 2018. http://hdl.handle.net/2123/18585.
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The prime goal of this research is to model the long-range dependency and volatility factors fitting in fractionally differenced ARMA (ARFIMA) and Gegenbauer ARMA processes (GARMA) in financial time series. This extends the efficiency in computing the exact maximum likelihood established by Sowell through conditional quasi maximum likelihood (QMLE) for ARFIMA and GARMA with conditional heteroscedastic errors. In particular, an extended algorithm together with corresponding asymptotic results of QMLE estimators are presented. The Monte Carlo simulation methods are used to study asymptotic properties and report the convergence rate for parameter estimates. Portmanteau test statistics are employed to check the model adequacy. As an application of this theory in the financial industry, a GARMA-GARCH model is fitted to daily returns of China Shanghai Composite stock index.
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Fučík, Vojtěch. "Principal component analysis in Finance." Master's thesis, Vysoká škola ekonomická v Praze, 2015. http://www.nusl.cz/ntk/nusl-264205.
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The main objective of this thesis is to summarize and possibly interconnect the existing methodology on principal components analysis, hierarchical clustering and topological organization in the financial and economic networks, linear regression and GARCH modeling. In the thesis the clustering ability of PCA is compared with the more conventional approaches on a set of world stock market indices returns in different time periods where the time division is represented by The World Financial Crisis of 2007-2009. It is also observed whether the clustering of DJIA index components is underlied by the industry sector to which the individual stocks belong. Joining together PCA with classical linear regression creates principal components regression which is further in the thesis applied to the German DAX 30 index logarithmic returns forecasting using various macroeconomic and financial predictors. The correlation between two energy stocks returns - Chevron and ExxonMobil is forecasted using orthogonal (or PCA) GARCH. The constructed forecast is then compared with the predictions constructed by the conventional multivariate volatility models - EWMA and DCC GARCH.
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Liu, Qingfeng. "Econometric methods for market risk analysis : GARCH-type models and diffusion models." Kyoto University, 2007. http://hdl.handle.net/2433/136053.
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Ozkan, Pelin. "Analysis Of Stochastic And Non-stochastic Volatility Models." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/3/12605421/index.pdf.
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Changing in variance or volatility with time can be modeled as deterministic by using autoregressive conditional heteroscedastic (ARCH) type models, or as stochastic by using stochastic volatility (SV) models. This study compares these two kinds of models which are estimated on Turkish / USA exchange rate data. First, a GARCH(1,1) model is fitted to the data by using the package E-views and then a Bayesian estimation procedure is used for estimating an appropriate SV model with the help of Ox code. In order to compare these models, the LR test statistic calculated for non-nested hypotheses is obtained.
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Boerlin, Christoph. "Robustness Issues in the Statistical Analysis of GARCH Processes with Applications to Finance." St. Gallen, 2007. http://www.biblio.unisg.ch/org/biblio/edoc.nsf/wwwDisplayIdentifier/01648856002/$FILE/01648856002.pdf.
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Loh, Lixia. "Volatility spillovers in Asian bond markets: comparative analysis using GARCH and wavelet methods." Thesis, University of Nottingham, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.493339.
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This thesis uses GARCH and wavelets methods to study the volatility spillovers from other financial markets into the Asian local currency bond markets. The cross-border analysis focuses on volatility spillover effects from the Japanese and US bond markets to the Asian bond market. The cross-market analysis focuses on the volatility spillover effects from the foreign exchange and stock markets to the Asian bond markets. We have shown that by using wavelets to derive volatility, the volatility spillovers can be captured more effectively than by using the more complex multivariate GARCH-based model. Three models, namely CCC EGARCH with residuals (Model 1), regression with wavelets (Model 2) and CCC EGARCH with wavelets (Model 3) were considered. Model 2 and Model 3 which use wavelets are found to perform better than the traditional GARCH with residuals model. However, our stress test shows that Model 2 is the least robust compared to Model 1 and Model 3 although it outperforms Model 1 and Model 3 in the in-sample forecast.
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Li, Dan. "Efficient Bayesian estimation for GARCH-type models via sequential Monte Carlo." Thesis, Queensland University of Technology, 2020. https://eprints.qut.edu.au/180752/1/Dan_Li_Thesis.pdf.
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This thesis develops a new and principled approach for estimation, prediction and model selection for a class of challenging models in econometrics, which are used to predict the dynamics of the volatility of financial asset returns. The results of both the simulation and empirical study in this research showcased the advantages of the proposed approach, offering improved robustness and more appropriate uncertainty quantification. The new methods will enable practitioners to gain more information and evaluate different models' predictive performance in a more efficient and principled manner, for long financial time series data.
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Zhou, Jin Shun. "Transmission of equity returns and volatility in Asia-Pacific markets : a multivariate GARCH analysis." Thesis, University of Macau, 2009. http://umaclib3.umac.mo/record=b1951112.
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Letra, Ivo José Santos. "What drives cryptocurrency value? A volatility and predictability analysis." Master's thesis, Instituto Superior de Economia e Gestão, 2016. http://hdl.handle.net/10400.5/12556.
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Mestrado em Decisão Económica e EmpresarialEsta tese descreve como as moedas digitais se tornaram no novo fenómeno nos mercados financeiros e como a mais popular das moedas digitais - Bitcoin - originou perguntas cruciais sobre o seu valor e como ao mesmo tempo as suas séries financeiras criaram uma oportunidade para estudar várias dinâmicas sobre o preço, que tipicamente estão fortemente ligadas a movimentos especulativos e sem análise fundamental. Com a utilização de um modelo GARCH(1,1) sobre dados diários e centrando-se em dois fenómenos recentes - moedas digitais, nomeadamente Bitcoin e conteúdo web oriundo do Google Trends, Wikipedia e Twitter - verificámos que os retornos da Bitcoin são fortemente impulsionados pela sua popularidade. Assim, analisando este relacionamento e modelando a existência de variâncias condicionais heterocedásticas demonstramos que o conteúdo proveniente de motores de busca e redes sociais e a flutuação nos preços Bitcoin estão intensamente ligados e que esta relação exibe alguma previsibilidade.
This thesis describes how digital currencies have rose as a new interesting phenomenon in the financial markets and how the most popular of the digital currencies - BitCoin - have risen crucial questions about their exchange rates and also represents a field to study the dynamics of this market, which is strongly connected with speculative traders with no fundamentals as there is no fundamental value to the currency. Using a GARCH(1,1) model on daily data and focusing on two emerging phenomena of recent years - digital currencies, particularly Bitcoin, and web content provided by search queries on Google Trends and Wikipedia and tweets from Twitter - we discover that Bitcoin returns are driven primarily by its popularity. Thus, we analyze their relationship, the existence of volatility clustering and demonstrate that the web content and Bitcoin prices are connected and they exhibit some predictable power.
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Xie, Yingfu. "Maximum likelihood estimation and forecasting for GARCH, Markov switching, and locally stationary wavelet processes /." Umeå : Dept. of Forest Economics, Swedish University of Agricultural Sciences, 2007. http://epsilon.slu.se/2007107.pdf.
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BRITO, Leonardo Mendes Primo. "A risk analysis of the brazilian stock market using value-at-risk and GARCH models." Universidade Federal de Pernambuco, 2016. https://repositorio.ufpe.br/handle/123456789/17390.
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DISSERTAÇÃO Leonardo Mendes Primo Brito.pdf: 9894168 bytes, checksum: 744a23c4dfd0eacd1c0d7c83e27bc6a6 (MD5)Made available in DSpace on 2016-07-14T17:30:10Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) DISSERTAÇÃO Leonardo Mendes Primo Brito.pdf: 9894168 bytes, checksum: 744a23c4dfd0eacd1c0d7c83e27bc6a6 (MD5) Previous issue date: 2016-02-24
O objetivo desta dissertação é estudar um conjunto de metodologias de Valor-em-Risco (VaR) que apresentam bom desempenho na literatura e avaliar como elas podem ser usadas para estimar o risco de diferentes setores da economia brasileira partindo de uma perspectiva de um investidor. VaR é a medida de risco mais usada na indústria financeira, e é utilizado por bancos privados e governos do mundo todo. Há uma vasta literatura tratando do VaR, porém há poucos estudos que investigam o uso do VaR como uma ferramenta para pequenos investimentos. Também há poucos estudos analisando estimativas do VaR para ações de empresas brasileiras. Este trabalho inicia-se com a revisão de algumas metodologias de cálculo de VaR e a identificação das metodologias com melhor desempenho. Em seguida, fazemos dois experimentos. O primeiro experimento consiste numa análise estatística de dados provenientes de diversas ações e índices setoriais da bolsa de valores brasileira em vários momentos diferentes afim de identificar quais metodologias VaR são potencialmente mais adequadas para cada ativo. O segundo experimento avalia o desempenho de uma seleção de metodologias VaR utilizando dados dos mesmos ativos e épocas do experimento anterior. Na última parte deste trabalho, otimizamos uma seleção de metodologias VaR para atuarem com dados recentes da bolsa de valores e analisamos os VaRs estimados supondo a visão de um potencial investidor. Os resultados dos nossos experimentos indicam que o VaR pode ser uma ferramenta eficiente na minimização da exposição ao risco, e pode potencialmente reduzir ou evitar perdas em negociações na bolsa de valores brasileira. Os experimentos também mostram que diferentes setores da economia brasileira tem propriedades de risco significativamente diferentes umas das outras.
The purpose of this dissertation is to study several leading Value-at-Risk (VaR) methodologies and evaluate how they can be used to assess the risk of different sectors of the Brazilian economy with the perspective of a potential investor. VaR is the financial industry’s most widely used risk measure, commonly adopted by banks and governments around the world. There is a great amount of ongoing research on VaR; however, there are few studies that use VaR as a potential tool for small investments. There are also very few studies that analyze VaR estimation of Brazilian companies. This dissertation first reviews VaR methodologies and elects a few among the best performing according to current literature. In a second stage, two experiments are conducted. The first experiment consists of a statistical evaluation of data from the Brazilian stock market during different time ranges so that adequate VaR methodologies may be chosen according to the data. The second experiment benchmarks the chosen VaR methodologies during the same time ranges. In a third and final stage, the chosen VaR methodologies are backtested using recent data from sectoral indices of the Brazilian stock market. The results of the experiments suggest that VaR may be an effective tool in minimizing risk exposure and potentially reducing or avoiding losses when trading in the Brazilian stock market. The experiments also show that different sectors of the economy have significantly different risk properties.
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Harrisberg, Richard. "An Analysis of the Low-Volatility Anomaly on the Johannesburg Stock Exchange." Master's thesis, Faculty of Commerce, 2019. https://hdl.handle.net/11427/31727.
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The low-volatility anomaly can be described as the unexpected outperformance of low-volatility stocks compared to high-volatility stocks over the long-term. This dissertation investigates the low-volatility anomaly and its presence on the Johannesburg Stock Exchange (JSE). Possible reasons behind why low-volatility stocks consistently outperform their high volatility counterparts, as well as their own expected return, over the long-term are discussed. This includes analysing how financial risk is measured and whether this plays a role in obscuring the expected risk-return relationship, in addition to other fundamental factors impacting expected returns. It is found that the low-volatility anomaly is present on the JSE and that using a number of different risk metrics does not significantly change where a stock is ranked on the risk spectrum. Additionally, including an interest rate exposure factor, a value factor and a momentum factor lowers the unexpected portion (Alpha) of the returns of low volatility stocks, at the same time as narrowing the gap between the unexpected performance of the lowest and highest volatility stocks.
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Ozdemir, Duygu. "Stock Market Liquidity Analysis: Evidence From The Istanbul Stock Exchange." Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613789/index.pdf.
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The purpose of this thesis is to identify the factors playing a key role in the determination of the Turkish stock market liquidity in aggregate terms in a time series context and discuss the joint dynamics of the market-wide liquidity with its selected determinants and the trade volume. The main determinants tested are the level of return, the return volatility and the monetary stance of the Central Bank of the Republic of Turkey. The expected positive relationship between the liquidity and the return is confirmed, while the negative effect of the volatility on liquidity appears one-week later. The behavior of various liquidity variables are also examined around the macroeconomic data announcement dates, during the 2008 financial crisis, and after the tick size change in the Istanbul Stock Exchange (ISE). The time series dynamics between the trade volume, return, volatility and the liquidity are put forward within the Vector Autoregression analysis framework. The GARCH modeling of the return series, which is an input to the liquidity model estimations, is a byproduct of this thesis. It is observed that the return series exhibits volatility clustering, persistence, leverage effects and mean reversion. In addition, while the level of the ISE market return decreased, the volatility of the return increased during the 2008 crisis. Accordingly, EGARCH model assuming normally distributed error terms and allowing a shift in the variance during the crisis period is chosen as the best model.
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Elgammal, Mohammed. "An empirical analysis of the relationship between the value premium and financial distress within a GARCH framework." Thesis, University of Aberdeen, 2010. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=137007.
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This thesis provides an empirical analysis of the relationship between the value premium and financial distress. Measures of leverage and default are used as proxies for financial distress. Using both an international data set, 1991 to 2006 and a long time series data set for the United States, 1927 – 2007, the thesis adds knowledge about the role of the value premium in asset pricing theory. Generalised autoregressive conditional heteroscedastic modelling (GARCH) is used and information gathered on the volatility of the value premium. A vector autoregressive (VAR) framework and Granger Causality tests are utilised in order to offer a deeper examination of the relationship between risk premium and economic activity. The results add further evidence to support the view that the value premium appears to be linked to variables associated with financial distress, although it is noted that this does not necessarily mean that participants in financial markets behave rationally.
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Selik, Michael Andrew. "Analysis of four alternative energy mutual funds." Thesis, Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/37236.
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We analyze four alternative energy mutual funds using a multi-factor capital asset pricing model with generalized autoregressive conditionally heteroskedastic errors (CAPM-GARCH). Our findings will help portfolio managers and others who seek to predict the return on investment in alternative energy firms. We find that alternative energy firms tend to be riskier than the general US stock market, have a low, but significant and positive response to oil prices, and have a significantly high and negative response to the value of the dollar relative to other currencies. Our results also suggest that alternative energy firms should hedge against currency exchange rate fluctuation.
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MAHAJAN, SHRIRANG A. "ANALYSIS OF VALUE AT RISK MODELS BASED ON THE SHANGHAI STOCK INDEX." University of Cincinnati / OhioLINK, 2003. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1069768595.
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Niklewski, Jacek. "Multivariate GARCH and portfolio optimisation : a comparative study of the impact of applying alternative covariance methodologies." Thesis, Coventry University, 2014. http://curve.coventry.ac.uk/open/items/a8d7bf49-198d-49f2-9894-12e22ce2d7f1/1.
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This thesis investigates the impact of applying different covariance modelling techniques on the efficiency of asset portfolio performance. The scope of this thesis is limited to the exploration of theoretical aspects of portfolio optimisation rather than developing a useful tool for portfolio managers. Future work may entail taking the results from this work further and producing a more practical tool from a fund management perspective. The contributions made by this thesis to the knowledge of the subject are that it extends literature by applying a number of different covariance models to a unique dataset that focuses on the 2007 global financial crisis. The thesis also contributes to the literature as the methodology applied also enables a distinction to be made in respect to developed and emerging/frontier regional markets. This has resulted in the following findings: First, it identifies the impact of the 2007–2009 financial crisis on time-varying correlations and volatilities as measured by the dynamic conditional correlation model (Engle 2002). This is examined from the perspective of a United States (US) investor given that the crisis had its origin in the US market. Prima facie evidence is found that economic structural adjustment has resulted in long-term increases in the correlation between the US and other markets. In addition, the magnitude of the increase in correlation is found to be greater in respect to emerging/frontier markets than in respect to developed markets. Second, the long-term impact of the 2007–2009 financial crisis on time-varying correlations and volatilities is further examined by comparing estimates produced by different covariance models. The selected time-varying models (DCC, copula DCC, GO-GARCH: MM, ICA, NLS, ML; EWMA and SMA) produce statistically significantly different correlation and volatility estimates. This finding has potential implication for the estimation of efficient portfolios. Third, the different estimates derived using the selected covariance models are found to have a significant impact on the calculated weights and turnovers of efficient portfolios. Interestingly, however, there was no significant difference between their respective returns. This is the main finding of the thesis, which has potentially very important implications for portfolio management.
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Duarte, Felipe Machado. "Acurácia de previsões para vazão em redes: um comparativo entre ARIMA, GARCH e RNA." Universidade Federal de Pernambuco, 2014. https://repositorio.ufpe.br/handle/123456789/16238.
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Em consequência da evolução da internet, causada por mudanças de paradigma como a Internet das coisas, por exemplo, surgem novas demandas tecnológicas por conta do crescimento do número de dispositivos conectados. Um dos novos desafios que vieram junto a esta demanda é gerenciar esta rede em expansão, de maneira a garantir conectividade aos dispositivos que a integram. Um dos aspectos que merecem atenção no gerenciamento da rede é o provisionamento da largura de banda, que deve ser realizado de maneira a evitar o desperdício de banda, sem por outro lado comprometer a conectividade ao restringi-la demais. No entanto, balancear esta equação não é uma tarefa simples, pois o tráfego de dados na rede é bastante complexo e exibe componentes, como a volatilidade, que tornam difícil a sua modelagem. Já há algum tempo, estudos são publicados apresentando a utilização de ferramentas de análise de séries temporais para prever a vazão de dados em redes de computadores, e entre as técnicas aplicadas com mais sucesso estão os modelos ARMA, GARCH e RNA. Embora estas técnicas tenham sido discutidas como alternativa para modelar dados de tráfego de redes, pouco material está disponível sobre a comparação de suas acurácias, de maneira que neste estudo foi proposta uma avaliação das acurácias dos modelos ARIMA, GARCH e RNA. Esta avaliação foi realizada em cenários configurados em diferentes granularidades de tempo e para múltiplos horizontes de previsão. Para cada um destes cenários foram ajustados modelos ARIMA, GARCH e RNA, e a validação das métricas de acurácia das previsões obtidas se deu através do Rolling Forecast Horizon. Os resultados obtidos mostraram que a RNA exibiu melhor acurácia em grande parte dos cenários propostos, chegando a exibir RMSE até 32% menor que as previsões geradas pelos modelos ARIMA e GARCH. No entanto, na presença de alta volatilidade, o GARCH conseguiu apresentar as previsões com melhor desempenho, exibindo RMSE até 29% menores que os outros modelos estudados. Os resultados deste trabalho servem de auxílio para a área de gerenciamento de redes, em especial a tarefa de provisionamento de largura de banda de tráfego, pois trazem mais informações sobre os desempenhos dos modelos ARIMA, GARCH e RNA ao gerar previsões para este tipo de tráfego.
The Internet evolution, caused by paradigm changes as the Internet of Things, fosters technological advances to cope with the rising number of connected devices. One of the new challenges that appeared with this new reality is the management of such expanding networks, assuring connectivity to every device within them. One of the major aspects of network management is bandwidth provisioning, which must be performed in a way to avoid bandwidth wasting, but without compromising connectivity by restricting it too much. Balancing such an equation is not a simple task, as network data traffic is very complex and presents property features, such as volatility, that turns its modeling rather difficult. It has been some time since research is published with the use of temporal analysis tools to predict data throughput in computer networks, among them, the most successful techniques employ the ARMA, GARCH and ANN models. Although these approaches have been discussed as alternatives do network data traffic modeling, there is little literature available concerning their accuracy, which motivated this work to perform an accuracy evaluation of the ARIMA, GARCH and ANN models. This evaluation was conducted in scenarios configured with different time granularities and for multiple forecast horizons. For each scenario, ARIMA, GARCH and ANN models were set, and the accuracy metrics evaluation was performed with a Rolling Forecast Horizon. Results show that ANN yielded better accuracy in most proposed scenarios, having a RMSE up to 32% lower than the forecasts generated by the ARIMA and GARCH models. However, when there is a high volatility, GARCH provided better forecasts, with a RMSE up to 29% lower than its counterparts. The results from this work provide a useful assistance to network management, especially to bandwidth provisioning, by shedding light on the accuracy presented by the ARIMA, GARCH and ANN models when generating forecasts for this type of traffic.
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Amadu, Abubakari, and Samarai Alexandre Al. "Swedish Sustainability Trend : Empirical analysis on the volatility effect of sustainable news on Swedish oil companies using GARCH 1.1." Thesis, Umeå universitet, Företagsekonomi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-142083.
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Purpose The main purpose of this thesis was to evaluate the investment attractiveness of oil and gas stocks (registered on Nasdaq Stockholm) in face of the increasing campaigns for the adoption of clean energy. The findings can help in the formulation of relevant policy implications on the campaign for a cleaner environment Design/Methodology/Approach The authors assume positivism and objectivity as the philosophical aspects for the purpose of this study. Following these initial considerations, the nature of the study was adopted as quantitative. This follows a longitudinal design and a deductive approach, basing the paper on previous literature in the areas of environmental sustainability, market efficiency, financial news items and their effect on stock volatility in order to test own hypothesis. Theory Following the methodological assumptions and the adoption of a deductive approach, relevant theory was selected to address the focus of previous research on which the research gaps and purpose are based. It also plays a role in introducing the reader to the relevant theories which will aid comprehension of further sections of this paper. Theories surrounding market efficiency, risk and return, the oil and gas industry and sustainability have all been mentioned. Findings In order to fulfil the purpose of the study, the authors studied whether the volatility of oil and gas stocks are affected by clean energy related news. The empirical results suggest that the volatility of oil and gas stocks decline whenever news of clean energy is introduced, implying clean energy news cause lower volatility. To this end, oil and gas stocks are better off whenever clean energy/sustainability news are introduced into the market. Analysis The empirical results seem to point to the fact that oil and gas firms may be benefiting from the investment they have made within the last two decades towards the issue of doing business in a more sustainable and socially responsible manner. It is therefore possible that investors get to reward them whenever news relating to sustainability and clean energy are announced. Conclusions This thesis confirms the attractiveness of oil and gas stocks notwithstanding the increasing campaigns and initiatives aimed at promoting the adoption of clean energy. Research limitations The research was limited in terms of setting since it only covered Sweden and therefore cannot answer questions regarding the overall attractiveness of oil and gas stocks across the globe.
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Muzinda, Edmond Toreva. "The impact of good news and bad news on South Africa’s sectoral stock return volatility: an asymmetric GARCH analysis." Thesis, Rhodes University, 2017. http://hdl.handle.net/10962/6425.
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This study explores the impact of good news and bad news on South Africa’s sectoral stock return volatility using an asymmetric GARCH analysis. Understanding the different impact of news on stock return volatility in different economic sectors has important implications for investors’ risk management practices, portfolio allocation strategies and asset pricing. The study employs data of daily closing prices for nine sectors and three benchmark indices for the period 2nd January 1997 - 17th August 2016. The data was split into sub-samples of pre-, during and post-global financial crisis, as well as the overall sample period. The incorporation of sub-samples was to help explain the outcomes of the overall sample period. To capture the different impact of good news and bad news on stock return volatility for each sector, asymmetric GARCH models namely, TGARCH and EGARCH were employed. The findings from this study revealed that volatility asymmetry was present in all sectors and benchmark indices of South African equity market. Bad news had more impact on stock return volatility for all sectors except the Oil and Gas sector, than good news of the same magnitude. In the Oil and Gas sector, good news was found to have an amplified effect on return volatility compared with bad news of the same magnitude. High volatility persistence was also found to be present in the Consumer goods, Financials, Industrials, All-share index and Mid-cap index. High differential impact of good and bad news were found in the Industrials, Financials, Basic materials, Consumer goods and the All-share index. Since the main objective of this study was to provide explanations of volatility asymmetry found in the South African sectors, the following were proposed as possible explanations of the findings. Within sectors, volatility asymmetry was explained by financial leverage, the role of the media, loss-averse investors and the behaviour of traders (overconfidence and extrapolation bias). Volatility asymmetry across sectors was explained by information flow, the uneven distribution of information by the media, investor sentiments, investor expectations and trading volumes. Overall, the results indicate that the stock return volatility of individual sectors of the South African equity market is driven mainly by bad news (except for Oil and Gas) and that leverage effects exist in all the sectors and in the benchmark indices.
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Paukeje, Ján. "Analýza a modelování provozu v datových sítích." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-219448.
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Theses deals with network traffic modeling focused on elaboration by time series analysis. The nature of network traffic is discussed above all http traffic. First three chapters are theoretical, which describes time series and basic models, linear AR, MA, ARMA, ARIMA and nonlinear ARCH. Other chapters define terms like self-similarity and long range dependence. It is demonstrated a failure of conventional models which cannot capture these specific properties of network data traffic. On the basis of study in chapter 6. is closely described the combined ARIMA/GARCH model and its parameter estimation procedure. Applied part of this theses deals with procedure of estimation and fitting the estimation model to observed network traffic. After an estimation a few future values are predicted on the basis of estimated model. These predicted values are consequently compared with real data.
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Altinsoy, Gozde. "Time Varying Beta Estimation For Turkish Real Estate Investment Trusts: An Analysis Of Alternative Modeling Techniques." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/3/12611309/index.pdf.
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This study investigates the time varying behavior of the betas (systematic risk) for the Turkish REIT sector in an attempt to identify whether the betas for the Turkish REITs are stable and if not whether the declining trend valid for the REIT betas of many developed and developing countries is also observed for the Turkish REITs. Three different techniquesnamely, Diagonal BEKK (DBEKK) GARCH model, the Schwert and Seguin model and the Kalman Filter algorithm, are employed in order to estimate and analyze the time varying betas of the Turkish REIT sector over the period 2002-2009. The empirical results suggest that, similar to many other countries, betas are not stable in the Turkish REIT sector. The general view of a declining beta trend for the REITs appears to prevail for Turkish REITs as well, reinforcing the defensive characteristics of these publicly traded real estate companies. Comparing the relative forecast accuracy of the three techniques employed, Schwert and Seguin model performs the worst both for weekly and daily data
whereas the Kalman Filter and the DBEKK Garch models provide the lowest forecast errors for the weekly and the daily data, respectively. This study also shows that the use of the data sets with different frequency could lead to different empirical findings.
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Karadag, Mehmet Ali. "Analysis Of Turkish Stock Market With Markov Regime Switching Volatility Models." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/3/12609787/index.pdf.
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In this study, both uni-regime GARCH and Markov Regime Switching GARCH (SW-GARCH) models are examined to analyze Turkish Stock Market volatility. We investigate various models to find out whether SW-GARCH models are an
improvement on the uni-regime GARCH models in terms of modelling and forecasting Turkish Stock Market volatility. As well as using seven statistical loss functions, we apply Superior Predictive Ability (SPA) test of Hansen (2005) and
Reality Check test (RC) of White (2000) to compare forecast performance of various models.
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Ainkaran, Ponnuthurai. "Analysis of Some Linear and Nonlinear Time Series Models." Thesis, The University of Sydney, 2004. http://hdl.handle.net/2123/582.
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Abstract This thesis considers some linear and nonlinear time series models. In the linear case, the analysis of a large number of short time series generated by a first order autoregressive type model is considered. The conditional and exact maximum likelihood procedures are developed to estimate parameters. Simulation results are presented and compare the bias and the mean square errors of the parameter estimates. In Chapter 3, five important nonlinear models are considered and their time series properties are discussed. The estimating function approach for nonlinear models is developed in detail in Chapter 4 and examples are added to illustrate the theory. A simulation study is carried out to examine the finite sample behavior of these proposed estimates based on the estimating functions.
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Khalfaoui, Rabeh. "Wavelet analysis of financial time series." Thesis, Aix-Marseille, 2012. http://www.theses.fr/2012AIXM1083.
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Cette thèse traite la contribution des méthodes d'ondelettes sur la modélisation des séries temporelles économiques et financières et se compose de deux parties: une partie univariée et une partie multivariée. Dans la première partie (chapitres 2 et 3), nous adoptons le cas univarié. Premièrement, nous examinons la classe des processus longue mémoire non-stationnaires. Une étude de simulation a été effectuée afin de comparer la performance de certaines méthodes d'estimation semi-paramétrique du paramètre d'intégration fractionnaire. Nous examinons aussi la mémoire longue dans la volatilité en utilisant des modèles FIGARCH pour les données de l'énergie. Les résultats montrent que la méthode d'estimation Exact Local Whittle de Shimotsu et Phillips [2005] est la meilleure méthode de détection de longue mémoire et la volatilité du pétrole exhibe une forte évidence de phénomène de mémoire longue. Ensuite, nous analysons le risque de marché des séries de rendements univariées de marchés boursier, qui est mesurée par le risque systématique (bêta) à différents horizons temporels. Les résultats montrent que le Bêta n'est pas stable, en raison de multi-trading stratégies des investisseurs. Les résultats basés sur l'analyse montrent que le risque mesuré par la VaR est plus concentrée aux plus hautes fréquences. La deuxième partie (chapitres 4 et 5) traite l'estimation de la variance et la corrélation conditionnelle des séries temporelles multivariées. Nous considérons deux classes de séries temporelles: les séries temporelles stationnaires (rendements) et les séries temporelles non-stationnaires (séries en niveaux)This thesis deals with the contribution of wavelet methods on modeling economic and financial time series and consists of two parts: the univariate time series and multivariate time series. In the first part (chapters 2 and 3), we adopt univariate case. First, we examine the class of non-stationary long memory processes. A simulation study is carried out in order to compare the performance of some semi-parametric estimation methods for fractional differencing parameter. We also examine the long memory in volatility using FIGARCH models to model energy data. Results show that the Exact local Whittle estimation method of Shimotsu and Phillips [2005] is the better one and the oil volatility exhibit strong evidence of long memory. Next, we analyze the market risk of univariate stock market returns which is measured by systematic risk (beta) at different time horizons. Results show that beta is not stable, due to multi-trading strategies of investors. Results based on VaR analysis show that risk is more concentrated at higher frequency. The second part (chapters 4 and 5) deals with estimation of the conditional variance and correlation of multivariate time series. We consider two classes of time series: the stationary time series (returns) and the non-stationary time series (levels). We develop a novel approach, which combines wavelet multi-resolution analysis and multivariate GARCH models, i.e. the wavelet-based multivariate GARCH approach. However, to evaluate the volatility forecasts we compare the performance of several multivariate models using some criteria, such as loss functions, VaR estimation and hedging strategies
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Ainkaran, Ponnuthurai. "Analysis of Some Linear and Nonlinear Time Series Models." University of Sydney. Mathematics & statistics, 2004. http://hdl.handle.net/2123/582.
Full textAbstract:
Abstract This thesis considers some linear and nonlinear time series models. In the linear case, the analysis of a large number of short time series generated by a first order autoregressive type model is considered. The conditional and exact maximum likelihood procedures are developed to estimate parameters. Simulation results are presented and compare the bias and the mean square errors of the parameter estimates. In Chapter 3, five important nonlinear models are considered and their time series properties are discussed. The estimating function approach for nonlinear models is developed in detail in Chapter 4 and examples are added to illustrate the theory. A simulation study is carried out to examine the finite sample behavior of these proposed estimates based on the estimating functions.
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Heymans, André. "Managing an agricultural commodities portfolio in South Africa with pairs trading / André Heyman." Thesis, North-West University, 2007. http://hdl.handle.net/10394/2308.
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Kume, Ortenca. "Determinants of U.S. corporate credit spreads." Thesis, Robert Gordon University, 2012. http://hdl.handle.net/10059/735.
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This thesis deals with various issues regarding determinants of US corporate credit spreads. These spreads are estimated as the difference between yields to maturity for corporate bonds and default-free instruments (Treasury bonds) of the same maturity. Corporate credit spreads are considered as measures of default risk. However, the premium required by investors for holding risky rather than risk-free bonds will incorporate a compensation not only for the default risk but also for other factors related to corporate bonds such as market liquidity or tax differential between corporate and Treasury bonds. In this study we firstly examine the relationship between bond ratings and credit spreads given that bond rating changes are expected to carry some informational value for debt investors. The findings indicate that bond ratings generally carry some informational value for corporate bond investors. The Granger causal relationship is more evident for negative watch lists and during periods of uncertainty in financial markets. In line with previous studies, our results suggest that changes in credit spreads are significantly related to interest rate levels, systematic risk factors (Fama and French) factors and equity returns.
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Neves, Miguel Alberto de Melo Afonso Reis das. "Análise crítica da volatilidade dos retornos das ações de algumas instituições bancárias." Master's thesis, Instituto Superior de Economia e Gestão, 2017. http://hdl.handle.net/10400.5/14795.
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Mestrado em Mathematical FinanceNeste trabalho é analisada a evolução da volatilidade condicionada dos retornos no período compreendido entre outubro de 2003 e junho de 2017 dos principais bancos cotados na Euronext Lisboa, nomeadamente, o BPI, o BCP e o Santander Totta. Para o efeito, recorreu-se aos modelos de heterocedasticidade condicionada GARCH, TGARCH e EGARCH, para obter estimativas da volatilidade condicionada. Estes valores foram depois usados para analisar o impacto de acontecimentos nacionais e globais na evolução da volatilidade. Os resultados permitem concluir que, em consequência da emergência da crise financeira, os acontecimentos globais passaram a influenciar de forma mais acentuada a volatilidade dos títulos financeiros em análise. Verifica-se ainda uma semelhança no tipo de acontecimentos que afetam o setor financeiro, sendo que as notícias negativas tendem a gerar um impacto superior na volatilidade condicionada.
The present study aims to examine the effects of conditional volatility between October 2003 and June 2017 of the main banks listed on Euronext Lisbon, namely BPI, BCP and Santander Totta. For this purpose, it was implemented conditional heteroscedasticity models - GARCH, TGARCH and EGARCH - to obtain conditional volatility estimations. Those values were then used to analyse the impact of national and global events on volatility behaviour. Conclusions revealed that after the global financial crisis, global events started to have higher influence on stock price volatility. Also, a similarity in the type of events which influence financial sector, with negative news tending to generate a major impact on conditional volatility
info:eu-repo/semantics/publishedVersion
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Strohe, Hans Gerhard. "Time series analysis : textbook for students of economics and business administration ; [part 2]." Universität Potsdam, 2004. http://stat.wiso.uni-potsdam.de/documents/zeitr/Time_Series_Analysis_Script2.pdf.
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Luo, Dan, and Yajing Ran. "Micro Drivers behind the Changes of CET1 Capital Ratio : An empirical analysis based on the results of EU-wide stress test." Thesis, Internationella Handelshögskolan, Högskolan i Jönköping, IHH, Företagsekonomi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-44140.
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Background: Stress tests have been increasingly used as a part of the supervisory tool by national regulators after the financial crisis, which can also be used to conduct authorities’ supervisory for determining bank capital levels, assessing the health of a bank. Purpose: The main purpose of this study is to assess whether some micro factors play important roles on the changes of Common Equity Tier One Capital Ratio (between the bank accounting value and the stress testing results under the adverse scenarios). Our secondary purpose is to investigate if our empirical results will help to provide some theoretical suggestions to regulators when they exercise stress tests. Method: An empirical analysis by using Panel Data, introducing GARCH model to measure volatility. Empirical foundation: The results of EU-wide stress tests and bank financial statements Conclusion: The coefficient associated with non-performing loans to total loans is positively significant and the coefficient associated with bank size is negatively significant. In addition, the financial system of strong banks is better to absorb financial shocks. These findings are useful, as banks is a reflection of the financial stability of an economic entity, we can use these findings as another reason to pay attention to the process of the stress testing rather just stress testing results.
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Mozayyan, Esfahani Sina. "Algorithmic Trading and Prediction of Foreign Exchange Rates Based on the Option Expiration Effect." Thesis, KTH, Matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-252297.
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The equity option expiration effect is a well observed phenomenon and is explained by delta hedge rebalancing and pinning risk, which makes the strike price of an option work as a magnet for the underlying price. The FX option expiration effect has not previously been explored to the same extent. In this paper the FX option expiration effect is investigated with the aim of finding out whether it provides valuable information for predicting FX rate movements. New models are created based on the concept of the option relevance coefficient that determines which options are at higher risk of being in the money or out of the money at a specified future time and thus have an attraction effect. An algorithmic trading strategy is created to evaluate these models. The new models based on the FX option expiration effect strongly outperform time series models used as benchmarks. The best results are obtained when the information about the FX option expiration effect is included as an exogenous variable in a GARCH-X model. However, despite promising and consistent results, more scientific research is required to be able to draw significant conclusions.Effekten av aktieoptioners förfall är ett välobserverat fenomen, som kan förklaras av delta hedge-ombalansering och pinning-risk. Som följd av dessa fungerar lösenpriset för en option som en magnet för det underliggande priset. Effekten av FX-optioners förfall har tidigare inte utforskats i samma utsträckning. I denna rapport undersöks effekten av FX-optioners förfall med målet att ta reda på om den kan ge information som kan användas till prediktioner av FX-kursen. Nya modeller skapas baserat på konceptet optionsrelevanskoefficient som bestämmer huruvida optioner har en större sannolikhet att vara "in the money" eller "out of the money" vid en specificerad framtida tidpunkt och därmed har en attraktionseffekt. En algoritmisk tradingstrategi skapas för att evaluera dessa modeller. De nya modellerna baserade på effekten av FX-optioners förfall överpresterar klart jämfört med de tidsseriemodeller som användes som riktmärken. De bästa resultaten uppnåddes när informationen om effekten av FX-optioners förfall inkluderas som en exogen variabel i en GARCH-X modell. Dock, trots lovande och konsekventa resultat, behövs mer vetenskaplig forskning för att kunna dra signifikanta slutsatser.
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Alsaedi, Yasir H. "An Investigation of the Effects of Solar and Wind Prices on the Australia Electricity Spot and Options Markets: A Time Series Analysis." Thesis, Griffith University, 2021. http://hdl.handle.net/10072/410472.
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Electricity pricing is recognised as being among the most important contemporary policy issues in Australia, and it also represents a critical component of current discussions concerning energy and climate-change policies. Attempts to move forward with energy and climate-change policies have been mostly stymied by concerns regarding potential increases in electricity prices. In relation to such policy discussions, renewable electricity generation is currently considered to be a fundamental factor influencing electricity prices. Due to the increasing penetration of both wind and solar power generation in Australia, which happens to be coinciding with increasing wholesale and retail electricity prices, there is now a widely held belief that the observed wholesale electricity price increases are related to the increased penetration of renewable energy sources.
Overall, the present study aims to investigate the nature and influence of the solar and wind electricity prices on the Australian spot and options markets. To accomplish this aim, the study begins by investigating wind, solar, spot and options pricing and then developing relevant models on the basis of a univariate state-by-state analysis of Australia’s electricity markets. Next, the study investigates the effects of the solar and wind prices on the Australian spot and options markets by means of a multivariate analysis. In addition, the study investigates the impacts of solar and wind pricing on the “global” electricity spot and options markets, with a particular focus on the Australian, German and American electricity markets. Moreover, the study examines how energy companies develop and manage policies concerning electricity production and pricing, as well as the use of solar and wind power, in the Australian markets.
More specifically, the first part of this study (Paper 1) involves a univariate analysis of the solar, wind, spot and options electricity prices intended to facilitate a more in-depth understanding of the nature of each variable in terms of forecasting, correlations and volatilities with regard to the Australian electricity markets. Quantitative data concerning the electricity markets in five Australian states, namely New South Wales (NSW), Queensland (QLD), South Australia (SA), Victoria (VIC) and Tasmania (TAS), are considered in this study. The results of the analyses reveal increases of between 30.46% and 40.42% in relation to the spot electricity prices as well as between 14.80% and 15.13% in relation the options electricity prices within the Australian National Electricity Market (ANEM) with a two-year horizon. The results also show that wind prices are expected to increase by an average of 5.43%, while the average solar electricity price is expected to decrease by 67.7%.
The second part of this study (Paper 2) involves a multivariate analysis designed to examine the dynamics within the Australian electricity markets, particularly those that may exist between the solar and wind prices and the electricity spot and options markets in each Australian state. The results of the Granger causality analysis indicate there to be a significant unidirectional Granger causal relationship between the solar and wind electricity prices and the spot prices in NSW, QLD, VIC and TAS at the 1% significance level, while in the case of SA, the relationship appears to be significant at less than the 10% level. Moreover, the forecast results suggest that the solar and wind electricity prices reduce the spot and options electricity market prices within the ANEM.
The third part of this study (Paper 3) involves a multivariate analysis conducted to investigate the movements within the international electricity markets. The aim was to examine the impacts of the solar and wind prices on the global electricity spot and options markets, with a particular focus on the Australian, German and US or American markets. The results indicate that the electricity markets in Australia, Germany and the United States are interdependent and related to any changes in solar and wind pricing, which means that all the investigated electricity markets are influenced by movements in other electricity markets.
The fourth part of this study (Paper 4) involves the application of in-depth qualitative technique of analysis. This part was used to investigate the nature and influence of policies and regulations concerning solar and wind pricing and their relationship to the Australian electricity spot and options markets. The analysis was based on data gathered through interviews conducted with chief executive officers, energy managers and other significant personnel from within the Australian electricity industry. The interviewees’ responses regarding the solar and wind policies that were considered relevant to the Australian electricity markets were analysed, and the “thick and in-depth” content data was derived data from the interviews. This set was then used to examine how their views and personal politics tend to influence pricing within the electricity markets. The results suggest that renewable energy policies lower the electricity prices, reduce the risk for investors and result in larger deployment mechanisms.Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Environment and Sc
Science, Environment, Engineering and Technology
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Mozayyan, Sina. "Statistisk undersökning av valutakurser : En jämförelse mellan olika prognosmodeller." Thesis, Stockholms universitet, Statistiska institutionen, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-152182.
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Valutamarknaden är världens största marknad och en nödvändig del av dagens globala samhälle, som gör det möjligt för företag att göra affärer i olika valutor och mellan olika gränser. Marknaden utgör en stor handelsplattform för både små och stora aktörer, för vilka det är viktigt att prognostisera valutakurser med gott resultat. Att modellera finansiella instrument i form av tidsserier är en av de vanligaste investeringsstrategierna och dess användningsområde sträcker sig från valutamarknaden till bland annat aktiemarknaden och råvarumarknaden. I denna uppsats undersöks fyra olika statistiska metoder för att modellera valutakursen Euro-US Dollar givet historisk data, och prognoser görs med de framtagna modellerna. Dessa metoder är slumpvandring, ARIMA, ARIMA-GARCH och VAR. Vidare undersöks för den dynamiska VAR-modellen hur valutamarkanden påverkar, och blir påverkad av, långa och korta räntan. Resultaten visar att ARIMA(3,1,2) förklarar valutakursen bäst medan VAR(2) med valutakursen och skillnaden mellan långa räntor som ingående variabler ger de bästa prediktionerna.The foreign exchange market is the world’s largest market and is an essential part of the global society of today. The FX market enables companies to trade with different currencies across country borders. It is also a large trade-platform for both big and small financial actors, who greatly benefit from the advantages of good predictions. Modeling of financial instruments is one of the most commonly used investment strategies and its area of application ranges from the FX market to markets suchas the stock market and the commodity market. In this paper, four different statistical models are used to model the currency pair Euro-US Dollar. These methods are random walk, ARIMA, ARIMA-GARCH and VAR. Besides investigating which method that gives the best forecasts, the method that best describes the training datais also found. Furthermore, for the dynamic VAR model, it is explored how the FX market affects, and is affected by, the long term and short term interest. The results show that ARIMA(3,1,2) is the best at describing the exchange rate while VAR(2) with the exchange rate and the difference between long term interests as variables gives the best predictions.
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Skopal, Martin. "Analýza a předpověď ekonomických časových řad pomocí vybraných statistických metod." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2019. http://www.nusl.cz/ntk/nusl-400475.
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V této diplomové práci se zaměřujeme na vytvoření plně automatizovaného algoritmu pro předpovědi finančních řad, který se snaží využít kombinační proceduru na dvou úrovních mezi dvěma rodinami předpovědních modelů, Box-Jenkins a Exponenciální stavové modely, které jsou schopny modelovat jak homoskedastické tak heteroskedastické časové řady. Pro tento účel jsme navrhli selekční proceduru v prostředí MATLAB pro modely ARIMA. Výsledný kombinovaný model je pak aplikován několik finančních časových řad a jeho výkonost je diskutována.
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Cheng, Yung-An, and 陳泳安. "Raw materials commodity price index fluctuation analysis- Application of GARCH Model &MS-GARCH Model." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/28828500268452509522.
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碩士銘傳大學
財務金融學系碩士在職專班
98
This research analyzes the feature of commodities future index price. There are four kind of data be adopted in this research. To compare the difference return ratios between MRS-GARCH model and GARCH model we found that all results performed in MRS-GARCH model are quite well than GARCH model. We found that if included the different situation of economy in MRS-GARCH model. It could perform well results. There are three distributions in the assumptions of data. Student’s distribution can state the situation of economy clearly. All of return ratios that mentioned in research are higher in the economic expansion than recession. Conditional variances of indexes of agricultural and metal are higher in expansion than recession. But the index of oil and food has higher conditional variance in recession. All of conditional variances have the feature of high persistence of shock in price except food index.
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Huang, Zhan-Ran, and 黃湛然. "Bayesian Analysis of GARCH Model in BUGS Language." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/fwuc6c.
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碩士中原大學
應用數學研究所
106
The Bayesian time series analysis is commonly used in many fields, especially the financial engineering. In particular, we consider the GARCH models that fit the time varying volatility and volatility clustering. However, the main difficulty in Bayesian statistics is that statisticians often need to write tedious computational codes to execute the idea of the MCMC methods. For the last twenty years, the OpenBUGS or WinBUGS with simple syntax, named BUGS language, has been a popular tool to Bayesian statisticians since it applies MCMC method and avoids the lengthy details for its users. Recently, a newly developed R package, called NIMBLE, also in BUGS language is much faster than OpenBUGS. In addition, NIMBLE provides more functions and is more flexible in conjugating general prior information and the likelihood of the models of interest. In this study, we demonstrate the Bayesian inference of GARCH time series model in both simulated data and real data using NIMBLE. Further complicated Bayesian researches in related GARCH models are then possibly applied by the use of NIMBLE package.
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Chen, Yi-Fang, and 陳義方. "Applying Technical Analysis to FX Volatility ForecastingUsing GARCH Model." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/52237122548679605674.
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碩士國立中興大學
統計學研究所
105
The main purpose of this paper is to applying technical analysis to promote GARCH model of predictive ability in the foreign exchange volatility. We use realized volatility as data and applying four technical indicators (FR, MA, SR, CB ) to produce technical trading signals, so we can apply to four different foreign exchange rates . Respectively, is the mature market of AUD and EUR, emerging markets of SGD and ZAR. Then we use these trading signals adding to the conditional variance of GARCH model which is obtained from daily return data, and we estimate the parameters of GARCH model by using rolling-window forecast method. To avoid the data snooping problem, we use the SSPA test to evaluate the effectiveness of forecasting, by using the MAE and MSE as two evaluation criterions to build up the loss functions. Our results show a few adjusted GARCH model in emerging markets can outperform the benchmark model.
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Yu, Ming-Han, and 游明翰. "Bivariate Options Pricing with Copula-GARCH Model- Simulation Analysis." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/45224192346235938953.
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碩士國立臺灣大學
財務金融學研究所
97
Bivariate option is the contingent claims derives from a pair of underlying assets. The underlying assets can be equity, commodities, foreign exchange rate, interest rate or any index with quotations. In this paper, we present a copula-GARCH model and the Monte Carlo simulation method base on the model. We examine the pricing result of three kinds of bivariate options - digital, rainbow and spread option, in many different cases and find that the choosing of pricing copula may cause a significant difference of the pricing result. Furthermore, the pricing result of rainbow option is most sensitive to the choosing of copulas in the three kinds of bivariate options.
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Lin, Ben-Shou, and 林笨守. "Interest Rate Sensitivity Analysis On Bank-A GARCH-M Model." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/76157353271500449613.
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碩士國立中央大學
產業經濟研究所
96
This study will explore the impact that the short and long-term interest rates risk changes on bank earnings. Under the influences of long-term interest rates (the 10-year bond interest rates in Taiwan and the U.S. 10-year bond interest rates) and short-term interest rates (30,90,180-day commercial paper interest rate),exploring SKFH listed commercial bank interest rates sensitivity. The sample period spans from August 21, 2002 to March 31, 2008. We use 1389 daily datas from Taiwan Economy Journal (TEJ) database. Consider the size of factors、the financial system will be divided into the Bank、Taishin、the three commercial banks investment portfolio、the weighted average market value of mining. Bank of return on existing heterogeneous information variation、using GARCH-M model described conditions variance、Stone (1974) two-factor model of empirical research. Preliminary study found that long-term interest rates on financial institutions to negative correlation is related to short-term interest rates. Adding the policy effect and found that under different investment portfolio, banks will consider the external environment and have taken measures related to hedge their interest rate risk decreased.
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Hsu, Kai-Wen, and 許凱雯. "Bivariate Options Pricing with Copula-Based GARCH Model -Empirical Analysis." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/92164432177086432378.
Full textAbstract:
碩士國立臺灣大學
財務金融學研究所
97
Multivariate options have experienced significant development in the last decade, due to their excellent abilities for hedging the risk of multiple assets. The most important issue in the valuation of multivariate options is the dependence structure among these underlying assets. In this paper, we use copula-based GARCH model as pricing device to describe the dependence structures of underlying assets, rather than the traditional linear correlation and Gaussian assumptions to price multivariate claims. Particularly, the skewed-t GARCH model is applied to capture the marginal distributions of underlying financial assets. To compare the impact of difference dependence structures on option pricing, we perform Monte-Carlo simulation to simulate the bivariate option prices, and observe the error of option prices caused from different model dependence structures, time-to-maturities, strike prices and option payoff functions. We use goodness-of-fit tests to choose one dependence model that fit the empirical distributions best, and then the paired t-test is also implemented to determine whether the pricing errors are significant enough.
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Rahayu, Meinar Fithria, and 麥娜. "Volatility Analysis of Indonesian Coffee Price Using ARCH/GARCH Model." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/71997340881915117083.
Full textAbstract:
碩士國立屏東科技大學
農企業管理系所
103
This study aims to analyze the best model to expected volatility of Indonesia’s coffee price using ARCH/GARCH model and to measure the coffee price volatility spillover of International market to Indonesia’s coffee price using EGARCH model. These models use different conditional variance specifications to catch up the asymmetry. The empirical results show that GARCH (1.1) model seems to better describe the Indonesia’s coffee price volatility. From the EGARCH analysis known that International coffee price has an asymmetric effect to Indonesia’s return coffee price and indicate that domestic coffee market is not efficient.
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Hung, Kuo-Chou, and 洪國洲. "Analysis of Short-Term Rate in Taiwan- Multivariate GARCH Model." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/44042334768048098581.
Full textAbstract:
碩士銘傳大學
財務金融學系碩士在職專班
98
Short-Term Rate is a key role in the place of monetary policy. Moreover, new financial products developed rapidly, the short-term rate is also very important toward varies asset pricing models. This research is based on basic liquidity effect theory for empirical study in Taiwan via certain variables, as of micro-economics, banks excess reserve, income, product price, and rate, for two multivariate models, as of practicing diagonal-vech model, and BEKK model. The empirical result claims that diagonal-vech model is better than BEKK model in estimation. It is also implied that TAIBOR is more recommended than commercial paper rate.
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hua, wu ching, and 吳晴華. "Analysis of RMB’s Exchange Rate Floating：Application of ARMA-GARCH Model." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/02867589526989931301.
Full textAbstract:
碩士清雲科技大學
經營管理研究所
95
Mainland China keep reducing the currency under the standard value since its economical development intermediate stage. Because China is the export country under the weak monetary policy, the exporting product price is more competitive which is similar to the export oriented policy. Due to the advantage of Mainland China export trade continues to grow, Driving Taiwan’s the hot money goes to China .The favorable balance of trade keep increasing, however Taiwan and the mainland mutually dependent highly. No matter Taiwanese businessman, who is trading with mainland China in Taiwan, or directly trading in the mainland, the Renminbi exchange rate will impact on their business. Therefore grasping the change of the Renminbi exchange rate becomes urgent. This paper discusses exchange rate statistical characteristics and its econometrics by reading the Renminbi exchange rate path and using the ARMA-GARCH to establish exchange rate model. We discovered the Renminbi exchange rate presents continues small revaluation. Further we can forecast the trend of the Renminbi exchange rate and the undulation in the short term. Renminbi exchange rate by using ones differencing estimated parameters is significant。Using estimated models to simulate the tendency of the characteristics of the Renminbi sequence, and all there models present good export forecast performance.