Master-Arbeit Univ. St. Gallen, 2007.

Thesis (doctoral)--Universität St. Gallen, 2006.

Background: The day-of-the-week effect has been a widely studied field ever since the concept was introduced in the early 1970s. Historically, negative returns on Mondays have been the most common finding. In line with improved market efficiency, researchers have started to question the existence of this anomaly. Purpose: The purpose of this study is to examine the weak-form efficiency level within the Swedish stock market by using sophisticated statistical approaches. The authors aim to investigate if the day-of-the-week effect was demonstrated between 2000 and 2017. Method: To properly provide answers to this investigation, a quantitative study has been conducted on the OMXS30. The data has been analysed by using different kind of sophisticated statistical methods such as GARCH and TGARCH. Conclusion: The results show that the day-of-the-week effect was not demonstrated within the OMXS30 during this time period, providing evidence for improved market efficiency.

The models for volatility, autoregressive conditional heteroscedastic (ARCH) and generalized autoregressive conditional heteroscedastic (GARCH) are discussed. Stationarity condition and forecasting for simple ARCH(1) and GARCH(1,1) models are given. The model for discrete time series is proposed to be negative binomial integer-valued GARCH model, which is a generalization of the Poisson INGARCH model. The stationarity conditions and the autocorrelation function are given. For parameter estimation, three methodologies are presented with a focus on maximum likelihood approach. Simulation study on a sample size of 100 and 500 are carried out and the results are presented. An application of the model to a real time series with numerical example is given indicating that the proposed methodology performs better than the Poisson and double Poisson model-based methods.

Submitted by Morgana Silva (morgana_linhares@yahoo.com.br) on 2016-06-29T19:29:16Z No. of bitstreams: 1 arquivototal.pdf: 2567247 bytes, checksum: 1b69ea69689d98843e4c8b25dbf6e8f6 (MD5) / Made available in DSpace on 2016-06-29T19:29:16Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 2567247 bytes, checksum: 1b69ea69689d98843e4c8b25dbf6e8f6 (MD5) Previous issue date: 2015-08-28 / The present essay studied the conceptual, innovative, market-oriented and qualitative aspects of Bitcoin. After the exposure of the key concepts about the Bitcoin, digital currency and currency, there is a contextualization of the Bitcoin as a financial innovation. In regards to the innovative aspects, the birth of Bitcoin represented a radical and paradigmatic innovation with potential of creating a creative destruction. The most modern concepts of the Innovation Theory are also exposed and so it is perceived that the Bitcoin exhibits characteristics of Disruptive Innovation (DI) of two kinds: Low and (DI) and New Market (DI). In regards to the market-oriented and structural aspects it was investigated the existence of similarities between the credit and debit market of Bitcoin and the traditional structure of the payment card's market (two sided market - 2SM). It was verified the adequacy of Bitcoin to the 2SM structure, but only on the debit card's market. The credit system of the Bitcoin market does not fit to the one of the traditional system. This work sought to understand the volatility of determinants of the Bitcoin prices. To attain this objective two different kinds of analysis were made: univariate and multivariate analysis. To estimate the univariate volatility the following models were plotted: ARCH, GARCH, EGARCH and TARCH whose results showed the existence of persistent volatility. The multivariate quantitative analysis aimed to understand the volatilities interaction between Bitcoin the other financial variables. It was applied the DCC M-GARCH methodology which allows the achievement of the statistical parameters using the quasi-correlation of the volatility. The results showed the existence of ARCH and GARCH effects in all cases. While the explanatory variables don't indicate any significance, the multivariate analysis of the subsample realize a convergence movement of the variables. In all cases it was considered the return toward the mean. All models were estimated for a sample considering the period between September 13th of 2011 and June 23th of 2015 and for a subsample that covers the period from March 10th of 2013. / A presente dissertação realizou uma análise sobre aspectos conceituais, inovativos, mercadológicos e quantitativos do Bitcoin. Após expostos conceitos basilares sobre o Bitcoin, moedas digitais e moeda buscou-se contextualizar o Bitcoin como inovação financeira. Com relação aos aspectos inovativos o surgimento do Bitcoin representou uma inovação radical e pré-paradigmática com potencial de destruição criativa. Também foram expostos os conceitos mais modernos da teoria da inovação e percebeu-se que o Bitcoin apresenta características de Inovação Disruptiva (ID) de dois tipos: Low and (ID) e New Market (ID). Quanto aos aspectos mercadológicos e estruturais foi investigada a existência de semelhanças entre o mercado de crédito e débito do Bitcoin e a estrutura tradicional do mercado de cartões conhecida por Mercado de Dois Lados (M2L). Verificou-se a perfeita adequação do Bitcoin à estrutura M2L, mas apenas no mercado de cartões de débito. O sistema de crédito existente no mercado do Bitcoin não se conforma da maneira tradicional. Buscou-se também compreender os determinantes da volatilidade dos preços do Bitcoin. Para atingir este objetivo foram realizados dois tipos de análises: univariadas e multivariadas. Para estimar a volatilidade univariada foram estimados os modelos ARCH, GARCH, EGARCH e TARCH cujos resultados apontaram existência de volatilidade persistente. Já análise quantitativa multivariada apresentou o objetivo de compreender a interação das volatilidades entre o Bitcoin e outras variáveis financeiras. Foi aplicada a metodologia DCC M-GARCH que possibilita a obtenção dos parâmetros por meio das quasicorrelações da volatilidade. Os resultados apontaram a existência dos efeitos ARCH e GARCH em todos os casos. Embora as variáveis explicativas não apontem significância a análise multivariada da subamostra aparentemente realiza movimento de convergência. Em todos os casos foram considerados os retornos das séries. Todos os modelos foram estimados para a amostra considerando o período de 13 de Setembro de 2011 e 23 de Junho de 2015 e para uma subamostra que abrange o período a partir de 10 de Março de 2013.

The purpose of this paper is to offer a review of the history of oil in order to build an understanding of the factors that make the commodity innately volatile. Then, we explain the recent development of US shale production, which may threaten to disrupt the status quo in oil markets. In the last decade, markets have endured two price collapses that are historic both in their frequency and individual magnitudes; however, recent volatility has remained low. We hypothesize that the shale revolution in the United States may have played a role in this new trend. Following the tradition of Pindyck (2004), we utilize a GARCH model in order to analyze crude-oil price volatility since 2004. In order to measure the effects of the shale revolution, we leverage a major news shock in August 2013, at which time Pioneer Natural Resources made the single largest announcement of new retrievable shale reserves in history. We find that the news announcement had a positive effect on the conditional variance of oil and a negative effect on daily returns. The limitations of our instrument for shale production constrain our interpretation of these results, preventing any definitive conclusions about shale companies’ possible role as a volatility-reducing swing producers.

The thesis deals with modeling and forecasting of natural gas spot prices, con- sumption of natural gas and average daily temperature. We assume that these three variables are influenced by each other, because as temperature decreases, consumption increases, which in turn increases the price with the increasing de- mand. Therefore, we propose to model these variables by vector autoregression. We compare this model with one-dimensional models where for each one we build a model from the ARMA-GARCH class. Models are estimated using historic va- lues and then designed models are used to simulate scenarios. Analysis of scenarios provides information to gas supply companies estimates of portfolio consumption and financial flows related to the purchase concerning natural gas. 1

Submitted by Isaac Francisco de Souza Dias (isaac.souzadias@ufpe.br) on 2016-07-14T17:30:09Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) 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.

The thesis focuses at the evolution of cryptocurrencies or more precisely at the competition process between them in expanding to broader usage. The first main goal of the work is to find out, whether Bitcoin, as the first and still most capitalized cryptocurrency, has an advantage of higher maturity than alternative cryptocurrencies. The second goal is to analyze whether the individual cryptocurrencies are perceived individually by market participants, which could grant the alternative cryptocurrencies an option to compete with Bitcoin by offering better features as safer technology or faster transaction. The analysis of volatility patterns in their exchange rates via various GARCH models suggests that Bitcoin still has advantage in higher maturity. The analysis of the correlation between various alternative cryptocurrencies and Bitcoin finds positive correlation and thus suggests that the cryptocurrencies are rather perceived together. JEL Classification G17, G19, E40, E41 Keywords cryptocurrencies, volatility, GARCH, money, correlation Author's e-mail 79828843@fsv.cuni.cz Supervisor's e-mail frantisek.cech@fsv.cuni.cz

Japanese monetary authorities used to employ various intervention techniques to adjust the level of the dollar/yen exchange rate and reduce its volatility. Application of the GARCH-in- mean model for estimation of the effect of these operations demonstrates that depreciating interventions reduced volatility effectively from 1995 until 2002. Frequent interventions of the small scale had a tendency to increase volatility during period 1991-1995. Foreign exchange interventions conducted by US Fed have increasing, means negative, effect, on the conditional variance. Frequent interventions of the great scale do not affect the volatility; it is determined mostly by the persistent level of the conditional variance from the latter periods. Recent interventions conducted by the Bank of Japan after the financial crisis do not show any considerable effect on both the volatility and the level of the exchange rate.