Dissertations / Theses: 'Price volatility'

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Acree, E. Bryan. "Volatility spillovers in international equity markets." Thesis, Georgia Institute of Technology, 1996. http://hdl.handle.net/1853/30969.

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Sharma, Namit. "Forecasting Oil Price Volatility." Thesis, Virginia Tech, 1998. http://hdl.handle.net/10919/36815.

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This study compares different methods of forecasting price volatility in the crude oil futures market using daily data for the period November 1986 through March 1997. It compares the forward-looking implied volatility measure with two backward-looking time-series measures based on past returns - a simple historical volatility estimator and a set of estimators based on the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) class of models.

Tests for the relative information content of implied volatilities vis-Ã -vis GARCH time series models are conducted within-sample by estimating nested conditional variance equations with returns information and implied volatilities as explanatory variables. Likelihood ratio tests indicate that both implied volatilities and past returns contribute volatility information. The study also checks for and confirms that the conditional Generalized Error Distribution (GED) better describes fat-tailed returns in the crude oil market as compared to the conditional normal distribution.

Out-of-sample forecasts of volatility using the GARCH GED model, implied volatility, and historical volatility are compared with realized volatility over two-week and four-week horizons to determine forecast accuracy. Forecasts are also evaluated for predictive power by regressing realized volatility on the forecasts. GARCH forecasts, though superior to historical volatility, do not perform as well as implied volatility over the two-week horizon. In the four-week case, historical volatility outperforms both of the other measures. Tests of relative information content show that for both forecast horizons, a combination of implied volatility and historical volatility leaves little information to be added by the GARCH model.
Master of Arts

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Planting, Ronald James. "Petroleum futures trading and price volatility." Thesis, Virginia Polytechnic Institute and State University, 1986. http://hdl.handle.net/10919/91138.

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This study investigates the effects of futures trading on petroleum price variability. Though a number of critics from various quarters claim futures markets have made petroleum prices more volatile, economic reasoning does not support this viewpoint. A review of theoretical studies and empirical investigations of other commodities shows general support for the hypothesis that futures markets do not destabilize prices and may, in fact, add to price stability. In this study, regression analysis is used to explain the price variability of heating oil and gasoline in terms of factors that may affect this variability, including the existence of futures markets. Though the empirical tests performed are biased towards finding destabilizing effects of futures markets, no statistically significant increase in price volatility is found, and in the case of gasoline, indications of stabilizing effects are found. Thus, neither the results of other studies of futures markets nor examination of petroleum futures trading support the critics' contention that futures trading has destabilized petroleum prices.
M.A.

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Yang, Yue, and Viorica Gonta. "The relationship between volatility of price multiples and volatility of stock prices : A study of the Swedish market from 2003 to 2012." Thesis, Umeå universitet, Handelshögskolan vid Umeå universitet (USBE), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-72769.

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The purpose of our study was to examine the relationship between the volatility of price multiples and the volatility of stock prices in the Swedish market from 2003 to 2012. Our focus was on the price-to-earnings ratio and the price-to-book ratio. Some previous studies showed a link between the price multiples and the volatility of stock prices, this made us question whether there should be a link between the volatility of the price multiples and the volatility of the stock prices. The importance of this subject is accentuated by the financial crisis, as we provide investors with information regarding the movements of price multiples and stock prices. Moreover, we test if the volatility of the price multiples can be used to create a prediction model for the volatility of stock prices. Also we fill the gap in the previous researches as there is no previous literature about this topic. We conducted a quantitative research using statistical tests, such as the correlation test and the linear regression test. For our data sample we chose the Sweden Datastream index. We first calculated the volatility using the GARCH model and then continued with our statistical tests. The results of our tests showed that there is a relationship between the volatility of the price multiples and the volatility of the stock prices in the Swedish market in the past ten years. Our findings show that the correlation coefficients vary across industries and over time in both strength and direction. The second part of our tests is concerned with the linear regression tests, mainly calculating the coefficient of determination. Our results show that the volatility of the price multiples do explain changes in the volatility of stock prices. Thus, the volatility of the P/E ratio and the volatility of the P/B ratio can be used in creating a prediction model for the volatility of stock prices. Nevertheless, we also find that this model is best suited when the economic situation is unstable (i.e. crisis, bad economic outlook) as both the correlation coefficient and the coefficient of determination had the highest values in the last five years, with the peak in 2008.

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Nasir, Samia. "Volatility- An investigation of the relationship between price- and yield volatility." Thesis, Mälardalens högskola, Akademin för utbildning, kultur och kommunikation, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-51054.

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This report investigates the relationship between the yield volatility and the price volatility in the Swedish market. The method given in our report can be used to analyze any market with appropriate data set. We have used a time-series data of interest rate yield curves from Swedish government bonds. The curves are bootstrapped from the bills and bonds. The linear interpolation on these curves results in the nodes i.e. 1Y, 2Y,..., 10Y. We also need prices for instruments. A good choice is to use the synthetic government bonds namely SE GVB 2Y, SE GVB 5Y, and SE GVB 10Y. They are issued every day with maturity 2, 5, and 10 years. We also use the time-series of these bonds. These bonds have a yearly coupon of 6%. We can get zero-coupon values of these bonds by stripping their coupons using the interest rate yield curves. We have time-series data of zero-coupon prices with maturities 2, 5, and 10 years and time-series data of interest rates with the same tenors. We can use our data to calculate their respective volatilities to investigate how they are related to each other.

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Stråle, Johansson Nathalie, and Malin Tjernström. "The Price Volatility of Bitcoin : A search for the drivers affecting the price volatility of this digital currency." Thesis, Umeå universitet, Företagsekonomi, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-98397.

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Created in 2009, the digital currency of bitcoin is a relatively new phenomenon. During this short period of time, it has however displayed a strong development of both price and trade volume. This has led to increased media attention, but also regulators and researchers have developed an interest. At this moment, the amount of available research is however limited. With a focus on the price volatility of bitcoin and an aim of finding drivers of this volatility, this study is taking a unique position. The research has its basis in the philosophical position of positivism and objectivism. This has shaped the research question as well as the construction of the study. The result is a describing and explaining research with a deductive research approach, a quantitative research method and an archival research strategy. This has in turn stimulated an extensive literature review and information search. Areas of discussion are microstructure theory, the efficient market hypothesis, behavioural finance and informational structures. Due to the limited amount of previous bitcoin research within the area of price volatility, the study has drawn extensively on research performed on more classical assets such as stocks. Nevertheless, when available, bitcoin research has been used as a foundation/reference and an inspiration. Reviews of academic literature and economic theories, as well as public news helped to identify the variables for the empirical study. These variables are; information demand, trade volume, world market index, trend and six specified events, occurring during the chosen sample period and included in the study as dummy variables. The variables are all analysed and included in a GARCH (1,1) model, modified following a similar research by Vlastakis & Markellos (2012) on stocks. This GARCH (1,1) model is then fitted to the bitcoin volatility registered for the sample period and is able thereby able to generate data of if and how the variables affect the bitcoin volatility. The test result suggests that five of the ten variables are significant on a 5 %-level. More specifically it suggests that information demand is a significant variable with a positive influence on the bitcoin volatility, something that corresponds to the literature on information demand and price volatility. This also relates to the events found significant, as they generated bitcoin related information. The significant events of the Cypriot crisis and the failure of the bitcoin exchange MtGox are thus specific examples of how information affects price volatility. Another significant variable is trade volume, which also displays a positive influence on the volatility. The last significant variable turned out to be a constructed positive trend, suggesting that increasing acceptance of bitcoin decreases its volatility.

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Santana, Verônica de Fátima. "IFRS adoption, stock price synchronicity and volatility." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/12/12136/tde-30032015-143815/.

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This research aimed to investigate whether and how the adoption of the International Financial Reporting Standards (IFRS) has affected the synchronicity of stock prices in the Brazilian capital market and how this was reflected in the behavior of idiosyncratic and systematic risk. In order to do so, it was first conducted a regression analysis associating the Transition (2008 and 2009) and the Post-Adoption (from 2010) period with a measure of stock price synchronicity, controlling for structural aspects that affect the functioning of stock markets as a whole and for aspects of individual firms that affect the process of incorporating information into their stock prices and their incentives to report transparent financial statements. Then, it was built series of volatility decomposed into two components, market-wide (capturing the systematic risk) and firm-specific (capturing the idiosyncratic risk), according to the methodology of Campbell et al. (2001), and performed an analysis based on tests for identifying trends on the series. The study predicted that if IFRS was able to increase the amount of firm-specific information incorporated into stock prices, it could (i) reduce synchronicity (J. Kim & Shi, 2012), and idiosyncratic volatility would have become more intense relatively to systematic volatility; or (ii) it could increase synchronicity (Beuselinck et al., 2010; Dasgupta et al., 2010), and idiosyncratic volatility would, then, have become less intense. The results confirmed that stock price synchronicity has decreased from the Post-Adoption period, in line with the view of J. Kim & Shi (2012), that the reducing effect can be more intense for less developed countries, which tend to be more synchronous (Morck et al, 2000) and because the improvement in the informational environment acts as a substitute to the weak institutional environment. These results indicate that stock prices became more informative (Durnev, Morck, & Yeung, 2004), making the market less obscure (K. Li et al., 2003) and better able to efficiently allocate resources (Wurgler, 2000; Habib, 2008). However, although a visual analysis of the volatility series suggests a slightly upward trend for the firm-level series, the statistical tests were not able to identify any significant trend, so, only the first part of the hypothesis could be confirmed. Nevertheless, despite of this limitation and the possible caveats with the models that were used, this research provides evidence that IFRS adoption brought positive changes to the functioning of the Brazilian capital market.
Esta pesquisa buscou investigar se, e de que forma, a adoção dos International Financial Reporting Standards (IFRS) afetou a sincronicidade dos preços das ações no mercado de capitais brasileiro e como isso se refletiu no comportamento dos riscos idiossincrático e sistemático. Para tanto, foi feita uma análise de regressão associando o período de Transição (2008 e 2009) e o de Pós-Adoção (a partir de 2010) com uma medida de sincronicidade dos preços das ações, controlando por aspectos estruturais que afetam o funcionamento do mercado de capitais e por aspectos individuais das firmas que afetam a incorporação de informações em seus preços e seus incentivos para reportar demonstrações financeiras transparentes. Em seguida, foram construídas séries de volatilidade decompostas em dois componentes: o mercado em geral (capturando o risco sistemático) e específica da firma (capturando o risco idiossincrático), segundo a metodologia de Campbell et al. (2001), e foi feita uma análise baseada em testes para identificar tendências nessas séries. O estudo previa que se a adoção das IFRS foi capaz de aumentar a quantidade de informação específica das firmas incorporada nos preços das ações, então ela poderia (i) diminuir a sincronicidade (J. Kim & Shi, 2012), e a volatilidade idiossincrática teria se tornado mais intensa em relação à volatilidade sistemática; ou (ii) ela poderia aumentar a sincronicidade (Beuselinck et al., 2010; Dasgupta et al., 2010), e a volatilidade idiossincrática teria, então, se tornado menos intensa. Os resultados confirmaram que a sincronicidade diminuiu a partir do período de Pós-Adoção, em consonância com a visão de J. Kim & Shi (2012), de que o efeito redutor pode ser mais intenso para países menos desenvolvidos, que tendem a ter mercados mais sincronizados (Morck et al, 2000) e porque a melhora no ambiente informacional funciona como uma substituta para o ambiente institucional fraco. Esse resultado indica que os preços das ações se tornaram mais informativos (Durnev, Morck, & Yeung, 2004), tornando o mercado menos obscuro (K. Li et al., 2003) e melhor capaz de alocar recursos eficientemente (Wurgler, 2000; Habib, 2008). No entanto, apesar de uma análise visual das séries de volatilidade mostrar uma leve tendência crescente para a série do nível da firma, os testes estatísticos não puderam identificar qualquer tendência significativa, então, somente a primeira parte da hipótese pôde ser confirmada. Contudo, apesar dessa limitação e das possíveis ressalvas quanto aos modelos que foram usados, esta pesquisa fornece evidências de que a adoção das IFRS trouxe mudanças positivas para o funcionamento do mercado de capitais brasileiro.

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Moabelo, Julith Tsebisi. "Analysing potato price volatility in South Africa." Thesis, University of Limpopo, 2019. http://hdl.handle.net/10386/3049.

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Thesis ( M.Sc.(Agricultural Economics)) --University of Limpopo, 2019.
Potato is perceived as an excellent crop in the fight against hunger and poverty. The recent high potato price in South Africa has pushed the vegetable out of reach of the poorest of the poor. The study attempts to analyse potato price volatility in South Africa and furthermore assess how various factors were responsible for the recent potato price volatility. Quarterly data for potato price, number of hectares planted, rainfall and temperature levels from 2006q1 to 2017q4 was collected from various sources and were used for analysis. The total observation of 48. The volatility in the series was determined by performing ARCH/GARCH model. GARCH model indicates an evidence of GARCH effect in the series, meaning that GARCH model influences potato price volatility in South Africa. The Johansen cointegration used both trace and eigenvalue to test the existence of a long run relationship between potato price and various variables. The cointegration results were positive indicating that there exists long run relationship amongst variables. The study further used Johansen cointegration as well as standard error to determine the number of cointegrating variables in the long run. The results indicated that the number of hectares planted and rainfall level have significant relationship with potato price. Wald tests was used to check whether the past values of number of hectares planted and rainfall level influenced the current value of potato price. The Walt test results concluded that there is no evidence of short run causality running from number of hectares planted and rainfall level to potato price. In the study, ECM model was used to forecast the potato price fluctuation in South Africa. The study recommends that farmers need to engage in contract market so as to minimize the risk of potato price volatility. The Department of Agriculture should forecast agricultural commodities price volatility and make information accessible to the farmers so that they are able to adopt strategies that will assist them to overcome crisis.

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Ndiaye, Moctar. "Maize price volatility in Burkina Faso : Measurement, Causes and Consequences." Thesis, Montpellier, 2016. http://www.theses.fr/2016MONTD042.

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La volatilité des prix alimentaires est devenue un sujet de préoccupation constante dans les pays en développement suite à la flambée des prix des produits alimentaires en 2007/08 et 2010/11. Cette thèse s’intéresse à la caractérisation de la volatilité des prix au Burkina Faso. La volatilité des prix est définie comme la part imprévisible des variations de prix. Les objectifs de cette thèse sont en particulier i) d’évaluer les caractéristiques de la volatilité des prix du maïs au Burkina Faso, ii) d’analyser ses déterminants et iii) ses impacts sur le comportement des producteurs. Pour répondre à ces questions complémentaires, nous avons combiné des données originales et riches de prix céréaliers sur plusieurs marchés et des données sur l’activité agricole de près de 2000 producteurs sur l’ensemble du territoire Burkinabé. Plusieurs résultats émergent dans cette thèse. Premièrement, ces données ont permis d’isoler le secteur clé du maïs pour ensuite présenter de manière détaillée les données sur les prix du maïs et sur l’activité agricole des ménages utilisés dans la suite de la thèse (chapitre 1). Deuxièmement, l’analyse des séries de prix du maïs sur chaque marché propose le processus ARCH comme modèle de séries chronologiques qui explique le mieux les caractéristiques de la volatilité des prix sur la majorité des marchés. Sur ces marchés les baisses et les hausses de prix ont une contribution similaire sur la volatilité des prix, et seuls les chocs de court terme l’affectent. Les autres marchés sont caractérisés par une persistance de la volatilité avec un effet différencié des variations de prix qui s’expliquent par les caractéristiques géographiques (chapitre 2). Troisièmement, l'analyse des séries de prix en panel révèle que la volatilité des prix du maïs est élevée sur les marchés les plus enclavés (chapitre 3). Quatrièmement, l’analyse des séries de prix du maïs combinés aux données sur l’activité agricole des ménages indiquent qu’une hausse des prix du maïs accroît l'utilisation des engrais chimiques. Toutefois, les variations de prix imprévisibles diminuent le niveau d'utilisation de ces engrais ; tandis que les variations des prix prévisibles n’ont aucun effet significatif sur leur utilisation (chapitre 4). La principale originalité de cette thèse réside dans le traitement des questions relatives à la volatilité des prix à l’échelle des marchés locaux et à un niveau microéconomique avec des données de ménage, alors que cette problématique est généralement perçue sous un angle macroéconomique à l’échelle internationale
Food price volatility is an ongoing concern in developing countries since the food price spikes in 2007/08 and 2010/11. This dissertation focuses on the patterns of food price volatility in Burkina Faso. Price volatility is defined as the unpredictable component of price variations. The aim of this dissertation is to contribute to a better understanding of three complementary issues i) the nature of maize price volatility in Burkina Faso, ii) its determinants and iii) its impacts on agricultural producers’ behavior. We combine an original database of grain prices on 28 local markets in the last 15 years and a panel database of almost 2,000 farm households’ production choices throughout the. Our results can be summarized as follows. First, these data allowed isolating the key sector of maize and then presenting detailed data on maize price series and the agricultural activity of households used in the remainder of this thesis (chapter 1). Second, the analysis of maize price series in each market suggests that ARCH model as the dominant time-series model to describe price volatility patterns in most markets in Burkina Faso. In these markets, price drops and peaks have a similar contribution to price volatility, and only recent episodes of price variations increase current volatility. Other markets are characterized by long term volatility episodes with a differential effect of price variations due to the geographical position (Chapter 2).Third, the analysis with panel method of maize price series shows that maize price volatility is greater in remote markets (Chapter 3). Fourth, by combining price series on local cereal markets and a panel data set on farm households’ production choices, we find that higher maize prices increase the quantity of chemical fertilizer use. However, unpredictable maize price variations decrease the level of fertilizer use; while predictable maize prices have no significant effect on fertilizer use (Chapter 4). The novelty of this thesis lies in the analysis of price volatility on local markets and at a micro level with household data, whereas this issue is usually perceived at the macroeconomic scale

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Venter, Rudolf Gerrit. "Pricing options under stochastic volatility." Diss., Pretoria : [s.n.], 2003. http://upetd.up.ac.za/thesis/available/etd09052005-120952.

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McKay, Sarah Michele. "Understanding Organic Prices: An Analysis of Organic Price Risk and Premiums." Thesis, Virginia Tech, 2016. http://hdl.handle.net/10919/71677.

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Organic food products are produced without synthetic chemicals, including herbicides, pesticides, and fertilizers. Food grown in organic systems that are certified organic by the United States Department of Agriculture command a price premium, whether it is direct to consumer via farmers markets or in conventional grocery stores. Organic food and food products are representing a relatively larger portion of overall food sales in recent years, and the demand for organic meat has also increased. However, there is a lack of available U.S.-grown organic grains and soybeans to feed the growing number of organic certified livestock to produce organic meat to meet this demand. This shortage results from many factors, yet is primarily due to organic production requirements for significantly more land and operating capital when compared to conventionally grown counterparts. There is a lack of information detailing the relative costs and returns of organic grain production, and, limited understanding of organic premiums. The overall goal of this study is to examine differences in price levels between organic and conventional corn, soybeans, wheat, oats, and barley between 2007 and 2015, as well as factors that may affect the organic premium. For organic grain and soybean producers, study findings reveal that the least risky organic commodities to grow include corn and soybeans, especially if sold in the cash market. However, the author suggests that growers may consider growing wheat, barley, and oats if they have a buyer willing to contract in advance to ensure a premium and reduce price risk. For purchasers of organic grains and soybeans, including major food companies as well as livestock producers, it is recommended they continue to study developments in organic grain supplies as producers continue to consider adoption of organic production methods.
Master of Science

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Sadik, Zryan. "Asset price and volatility forecasting using news sentiment." Thesis, Brunel University, 2018. http://bura.brunel.ac.uk/handle/2438/17079.

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The aim of this thesis is to show that news analytics data can be utilised to improve the predictive ability of existing models that have useful roles in a variety of financial applications. The modified models are computationally efficient and perform far better than the existing ones. The new modified models offer a reasonable compromise between increased model complexity and prediction accuracy. I have investigated the impact of news sentiment on volatility of stock returns. The GARCH model is one of the most common models used for predicting asset price volatility from the return time series. In this research, I have considered quantified news sentiment as a second source of information and its impact on the movement of asset prices, which is used together with the asset time series data to predict the volatility of asset price returns. Comprehensive numerical experiments demonstrate that the new proposed volatility models provide superior prediction than the "plain vanilla" GARCH, TGARCH and EGARCH models. This research presents evidence that including news sentiment term as an exogenous variable in the GARCH framework improves the prediction power of the model. The analysis of this study suggested that the use of an exponential decay function is good when the news flow is frequent, whereas the Hill decay function is good only when there are scheduled announcements. The numerical results vindicate some recent findings regarding the utility of news sentiment as a predictor of volatility, and also vindicate the utility of the new models combining the proxies for past news sentiments and the past asset price returns. The empirical analysis suggested that news augmented GARCH models can be very useful in estimating VaR and implementing risk management strategies. Another direction of my research is introducing a new approach to construct a commodity futures pricing model. This study proposed a new method of incorporating macroeconomic news into a predictive model for forecasting prices of crude oil futures contracts. Since these futures contracts are iii iv more liquid than the underlying commodity itself, accurate forecasting of their prices is of great value to multiple categories of market participants. The Kalman filtering framework for forecasting arbitrage-free (futures) prices was utilized, and it is assumed that the volatility of oil (futures) price is influenced by macroeconomic news. The impact of quantified news sentiment on the price volatility is modelled through a parametrized, nonlinear functional map. This approach is motivated by the successful use of a similar model structure in my earlier work, for predicting individual stock volatility using stock-specific news. Numerical experiments with real data illustrate that this new model performs better than the one factor model in terms of accuracy of predictive power as well as goodness of fit to the data. The proposed model structure for incorporating macroeconomic news together with historical (market) data is novel and improves the accuracy of price prediction quite significantly.

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Novelli, Pier Augusto. "The interaction between foreign exchange volatility and price." Thesis, Massachusetts Institute of Technology, 1993. http://hdl.handle.net/1721.1/12379.

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Wohlenberg, Emerson. "Brazil farmland price volatility in distinct production regions." Thesis, Kansas State University, 2014. http://hdl.handle.net/2097/17644.

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Master of Agribusiness
Department of Agricultural Economics
Allen M. Featherstone
Land is a fundamental input in agricultural production and the factors affecting land prices are an important topic in agricultural economics research. The farmland market has several unique characteristics. Land price volatility can be a source of problems for farmers and investors, especially in periods of falling prices in locations far from markets where the impact of land price reductions is higher than in other locations. This study analyzes land price volatility in different geographical regions of Brazil. The hypothesis is that variation in land price increases with the distance to the market, indicating that land price changes will be more pronounced in areas far from markets and the effects of price cycles in land markets will increase as distance from the market increases. The results obtained in this research support the hypothesis that areas far from end markets are exposed to greater changes in land prices and those same areas are more susceptible to price cycles. The effect on price volatility was also stronger in periods of land price declines. These regions have greater incentives for expansion and investment in periods of land price increase and greater risks of disinvestment and failure in periods of land price contraction. It is difficult to predict when a cycle of expansion or crisis will start or finish, but the present study helps to understand the effects of increases or decreases in land prices when such an event occurs.

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Zoi, Patrick <1981&gt. "Price and volatility jumps in the stock market." Doctoral thesis, Università Ca' Foscari Venezia, 2016. http://hdl.handle.net/10579/10252.

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Chapter1: We study the bivariate jump process involving the S&P 500 and the Euro Stoxx 50 index with jumps extracted from high frequency data using non-parametric methods. Our analysis, based on the generalized Hawkes process, reveals the presence of self excitation in the jump activity which is responsible for jump clustering but has a very small persistence in time. Concerning cross-market effects, we find statistically significant co-jumps occurring when both markets are simultaneously operating but no evidence of contagion in the jump activity, suggesting that the role of jumps in volatility transmission is negligible. Moreover, we find a negative relationship between the jump activity and the continuous volatility indicating that jumps are mostly detected during tranquil market conditions rather than in periods of stress. Importantly, our empirical results are robust under different jump detection methods. Chapter2:We construct new nonparametric robust to jumps estimators for the realized volatility combining multiple measures applied to high frequency data. Collecting information from several estimators, this method provides a higher asymptotic efficiency and allows to improve finite sample properties. We use the new estimators to construct nonparametric tests for the detection of jumps in asset prices: our Monte Carlo study shows that such tests can achieve substantially more power compared to other common tests. Chapter3:We introduce a new stochastic process generalizing the Autoregressive Gamma (ARG ) of [Gourieroux_Jasiak_2006]. This process is based on a new and more flexible specification of the conditional distribution which extends the non-central gamma while preserving the same analytical tractability. We propose an empirical a application to the realized volatility measured from high frequency data. The period of our analysis includes the sub-prime and the Euro Sovereign crisis. Our results highlight the superior performances of the new process compared the standard ARG and confirm the need of at least two stochastic factors for a satisfactory description of the volatility dynamics: one factor is responsible for small volatility fluctuations while the second factor generates large upward shocks featuring volatility jumps.

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Li, Rong-Jen. "Combined Leverage and the Volatility of Stock Prices." Thesis, North Texas State University, 1985. https://digital.library.unt.edu/ark:/67531/metadc331340/.

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Much has been written during the past decade to explain the relationship between financial and operating leverage and stock-price volatility. However, the relationship between combined leverage and stock-price volatility has yet to be fully explored. Mandelker and Rhee's (MR) recent study uses both operating and financial leverage in a regression (equivalent to the traditional total leverage—DTL) and shows that both types of leverage are positively associated with common stock betas. Huffman recently demonstrated that there are interactions between operating leverage and financial leverage. Therefore, MR's model could be oversimplified. This study examines the relationship between firms' combined leverage and their stock-price volatility. The study also examines industry and industry growth to see if the relationship is influenced by these factors. The question is whether DOCL is a better risk measure than DTL and whether there is an interaction between operating and financial leverage. The inferences that can be drawn from the study's results are as follows: (a) Stock risk is a function of combined leverage; (b) Industry significantly influences the relationship between stock risk and DOCL; (c) High growth increases the relationship between stock risk and DOCL; (d) Combined leverage (DOCL) is a better risk measure than total leverage (DTL). Further, the problem with the traditional total leverage measure is the omission of the interaction between DOL and DFL. This is consistent with Huffman's theory and suggests Mandelker and Rhee's model is oversimplified.

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Tsakou, Katina. "Essays on financial volatility forecasting." Thesis, University of Stirling, 2016. http://hdl.handle.net/1893/25403.

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The accurate estimation and forecasting of volatility is of utmost importance for anyone who participates in the financial market as it affects the whole financial system and, consequently, the whole economy. It has been a popular subject of research with no general conclusion as to which model provides the most accurate forecasts. This thesis enters the ongoing debate by assessing and comparing the forecasting performance of popular volatility models. Moreover, the role of key parameters of volatility is evaluated in improving the forecast accuracy of the models. For these purposes a number of US and European stock indices is used. The main contributions are four. First, I find that implied volatility can be per se forecasted and combining the information of implied volatility and GARCH models predict better the future volatility. Second, the GARCH class of models are superior to the stochastic volatility models in forecasting the one-, five- and twenty two-days ahead volatility. Third, when the realised volatility is modelled and forecast directly using time series, I find that the HAR model performs better than the ARFIMA. Finally, I find that the leverage effect and implied volatility significantly improve the fit and forecasting performance of all the models.

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Cheng, Xin. "Three essays on volatility forecasting." HKBU Institutional Repository, 2010. http://repository.hkbu.edu.hk/etd_ra/1183.

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Zhang, Yuzhao. "Essays on return predictability and volatility estimation." Diss., Restricted to subscribing institutions, 2008. http://proquest.umi.com/pqdweb?did=1666139151&sid=3&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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20

Rikter-Svendsen, Torstein, Cecilie Nilsen Kielland, and Bjørn Heineman. "Price-Volatility Modeling in the US Natural Gas Market." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for industriell økonomi og teknologiledelse, 2012. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-21064.

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Understanding price-volatility in the natural gas market is important as it affects new investments and the behavior of market participants. In this paper the volatility of US natural gas prices is investigated using daily Henry Hub futures data for the period 1996 to 2011. The purpose is to determine the best conditional volatility model for forecasting and modeling, and to investigate the fundamental drivers of volatility. Several models are applied and compared on the basis of explanatory power, post-estimation tests, as well as in- and out-of-sample one-day-ahead forecasting capabilities evaluated using the Dynamic Quantile Test and Kupiec LR test. Based on these evaluation criteria EGARCH is found superior to GARCH, GJR, IGARCH, RiskMetrics and APARCH. Additionally, EGARCH is found satisfactory when evaluating 5, 10 and 20-day-ahead forecasts using the Kupiec LR test on Monte Carlo simulated VaR levels. To investigate the drivers of volatility, proxies for each determinant are included in the conditional volatility models and in an OLS framework. Economic activity, seasonality and daily effects are found to be statistical significant, with the daily effects having the largest influence, while oil volatility, changes in temperature, production and storage levels are insignificant. From the results it can be concluded that if the aim of the conditional volatility modeling is short-term forecasting, the determinants should be excluded as they do not improve forecasting accuracy. Conversely, if the aim is to explain the causes of volatility, the in-sample evaluation indicate that the inclusion of determinants is a reasonable approach, and a good foundation for scenario analyses. Our findings are useful for producers, traders, risk managers and other market participants as they provide an accurate measure of price risk, and can be used to understand the causes of volatility.

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Chang, Yuanchen. "Modelling intraday foreign exchange rates : price patterns and volatility." Thesis, Lancaster University, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.364367.

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22

Dodd, Olga. "Price, liquidity, volatility, and volume of cross-listed stocks." Thesis, Durham University, 2011. http://etheses.dur.ac.uk/867/.

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This thesis examines the possible implications of international cross-listings for the wealth of shareholders, for stock liquidity and volatility, and for the distribution of trading volumes across both the domestic and foreign stock markets where the shares are traded. For the purpose of clarity, these three issues are analysed in three empirical chapters in the thesis. The first empirical issue examined in this thesis is the effects of international cross-listings on shareholders’ wealth. This is discussed in chapter 2. The chapter compares the gains in shareholders’ wealth that result from cross-listing in the American, British, and European stock exchanges and then evaluates their determinants by applying various theories on the wealth effects of cross-listing. Moreover, it evaluates how the wealth effect of cross-listing has changed over time reflecting the implications of the significant developments in capital markets that have taken place in recent years. In particular, the effects of the introduction of the Euro in Europe and the adoption of the Sarbanes-Oxley Act in the US are analysed. The findings suggest that, on average, cross-listing of stocks enhances shareholders’ wealth but the gains are dependent on the destination market. In addition, the regulatory and economic changes in the listing environment not only alter the wealth effects of cross-listings, but also affect the sources of value creation. Overall, this chapter provides in-depth insights into the motivations for, and the benefits of, cross-listings across different host markets in changing market conditions. The second empirical issue examined is the impact of cross-listing and multimarket trading on stock liquidity and volatility (chapter 3). Cross-listing leads to additional mandatory disclosure in order to comply with the requirements of the host market. Such requirements are expected to reduce information asymmetry among various market participants (corporate managers, stock dealers, and investors). An enhanced information environment, in turn, should increase stock liquidity and reduce stock return volatility. The findings of this study suggest that the stock liquidity and volatility improves after cross-listing on a foreign stock exchange. Moreover, this study distinguishes between cross-listing and cross-trading. The distinction is important because cross-trading, unlike cross-listing, does not require the disclosing of additional information. Although such a distinction means there is a variation in the information environment of cross-listed and cross-traded stocks, the results do not reveal any significant difference in the liquidity and volatility of the stocks that are cross-listed and cross-traded. This evidence suggests that the improvement in the liquidity and volatility of cross-listed/traded stocks comes primarily from the intensified competition among traders rather than from mandatory disclosure requirements. The final empirical issue investigated in this thesis (chapter 4) is the identification of the determinants of the distribution of equity trading volume from both stock exchange and firm specific perspectives. From a stock exchange perspective, exchange level analysis focuses on the stock exchange characteristics that determine the ability of a stock exchange to attract trading of foreign stocks. While from a firm perspective, firm level analysis focuses on firm specific characteristics that affect the distribution of foreign trading. The results show that a stock exchange’s ability to attract trading volumes of foreign equity is positively associated with a stock exchange’s organizational efficiency, market liquidity, and also the quality of investor protection and insider trading regulations. Analysis also reveals the superior ability of American stock exchanges to attract trading of European stocks. Moreover, there is strong evidence suggesting that regulated stock exchanges are more successful in attracting trading of foreign stocks than non-regulated markets, such as OTC and alternative markets and trading platforms. From a firm perspective, the proportion of trading on a foreign exchange is higher for smaller and riskier companies, and for companies that exhibit lower correlation of returns with market index returns in the host market. Also this proportion is higher when foreign trading takes place in the same currency as trading in the firm’s home market and increases with the duration of a listing. Finally, the study provides separate evidence on the expected levels of trading activity on various stock exchanges for a stock with particular characteristics. Overall, the findings of this thesis suggest that international cross-listing is beneficial for both firms and their shareholders but the findings also suggest that there are significant variations in the implications of cross-listings for different firms and from listing in different destination foreign markets. Finally, these implications are not static and respond to changes and reforms in listing and trading conditions.

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23

Foster, Andrew J. "Information, volatility and price discovery in oil futures markets." Thesis, Brunel University, 1994. http://bura.brunel.ac.uk/handle/2438/5871.

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This thesis presents four related empirical essays which investigate the role of information in crude oil futures markets. The first line of investigation examines the impact of futures trading on spot price volatility and finds that the nature of spot price volatility is affected by derivative trading and the improvements in information discovery which such trading brings. Second, the efficiency of futures markets is examined with respect to their ability to provide unbiased estimates of future spot prices. Here it is concluded that while unbiased estimates are generally provided in the long-term, they tend to be largely biased over the short-term. The third area of investigation looks at the relative ability of contemporaneous spot and futures prices to discover information, where it is found that futures generally exhibit price discovery over spot markets but that the relationship can vary considerably over time and in relation to market conditions. In addition, the investigation suggests that previous studies into such relationships have failed to account for all routes through which information passes between spot and futures markets. Finally the thesis probes the question of the relationship within futures markets between volume, volatility and information. The finding is' that futures markets' prices and trading volume exhibit a positive relation and are jointly driven by the rate of information arrival. The results further suggest that the widely held expectation that volume statistics can improve forecasts of future price change does not hold in the case of oil futures. The overall finding of the thesis is that oil futures markets are well-functioning and in general are of benefit to the underlying spot market.

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Wong, Mei Wa. "Price and volatility behaviour of four Asian stock markets." Thesis, Durham University, 1999. http://etheses.dur.ac.uk/4306/.

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The past ten years have witnessed many changes in the Asian economies and stock markets, particularly in the Four Tigers, Hong Kong, Singapore, South Korea and Taiwan. They enjoyed economic growth well above the world average during the late 1980s and early 1990s. There were sharp increases in their stock market capitalisations against the background of low growth and low interest rates in the US and European countries in the early 1990s. This coincided with the time when measures to liberalise these markets were implemented to allow or attract foreign direct investments in their stock markets. Then by mid 1997, both their economies and stock markets began to slump. This ten year time period thus provides a good opportunity to examine how such economic and institutional changes affected the price and volatility behaviour of the Four Tigers and their relationships with other markets. Overall, the findings of the thesis suggest that with the increase in foreign participation in the four individual markets, the influence of noise trading activities has been reduced through more and better informed trading. However, their relationships with three world major markets, the US, the UK and Japan, are not getting much stronger. There is no evidence to suggest that their prices are being increasingly led by the world markets, nor is their volatility becoming more sensitive to foreign news. Their price and volatility relationships with three regional markets, Thailand, Malaysia and Indonesia, were not particularly strong either, until recently, when the Asian financial crisis has made them more responsive to shocks from one another. The message to the governments of the Four Tigers is clear. Foreign direct equity investments have not destabilised their stock markets. Instead, the mismanagement of their own and/or their trading partners' economies should be held more responsible.

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Jakobsson, Robin Jari Mattias, and Leo Lundberg. "The Effect of ESG Performance on Share Price Volatility." Thesis, Umeå universitet, Företagsekonomi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-149982.

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Environmental, Social, and Governance (ESG) investing is growing rapidly. Previous research in the area, has mostly been centered around ESG/CSR and its link to corporate financial performance, cost of capital and idiosyncratic risk. Furthermore, relevant previous research is presented that in part challenges the traditional market models and suggests that total risk is a relevant risk factor, instead of only the systematic risk, as proposed by normative theory. In this study, we develop two separate panel regression models, with separate dependent variables. Realized volatility and a GARCH (1,1) estimate of volatility. This is done in order to gain insight into if there is, as propositioned, a negative relation between high ESG/CSR performance and volatility of the shares, i.e. the total risk of the shares. The study uses ESG and financial data from Thomson Reuters Eikon database. The sample size is 481 firms from the S&P 500 Index, for the years 2009-2016. The results of this study indicate that there is a statistically significant negative relationship between high ESG/CSR performance and share price volatility. This result adds to the discussion that challenges existing theory.

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Sörensen, William, and Olena Deboi. "Stock price volatility and dividend yield: Evidence from Sweden." Thesis, Jönköping University, IHH, Nationalekonomi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-51338.

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This research aims to examine if a negative relationship exists between the dividend yield and stock price volatility of firms listed on the Swedish Stock exchange market, which is of utter interest and intrinsic for investors and financial analyst in the process of valuing a security’s and a stock portfolio's risk and return. The data that was utilized for this study consists of 52 companies for the period of 2010 to 2019 which makes up for 520 observations. A pooled regression model and a multiple ordinary least squares model was applied to test the relationship. The results show a negative relationship between the dividend yield and stock price volatility. On the other hand, the results indicate that there is a significant positive relationship between earnings volatility and stock price volatility. However, there is a negative relationship for leverage, market value and asset growth with stock price volatility.

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Higgs, Helen. "Price and volatility relationships in the Australian electricity market." Thesis, Queensland University of Technology, 2006. https://eprints.qut.edu.au/16404/1/Helen_Higgs_Thesis.pdf.

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This thesis presents a collection of papers that has been published, accepted or submitted for publication. They assess price, volatility and market relationships in the five regional electricity markets in the Australian National Electricity Market (NEM): namely, New South Wales (NSW), Queensland (QLD), South Australia (SA), the Snowy Mountains Hydroelectric Scheme (SNO) and Victoria (VIC). The transmission networks that link regional systems via interconnectors across the eastern states have played an important role in the connection of the regional markets into an efficient national electricity market. During peak periods, the interconnectors become congested and the NEM separates into its regions, promoting price differences across the market and exacerbating reliability problems in regional utilities. This thesis is motivated in part by the fact that assessment of these prices and volatility within and between regional markets allows for better forecasts by electricity producers, transmitters and retailers and the efficient distribution of energy on a national level. The first two papers explore whether the lagged price and volatility information flows of the connected spot electricity markets can be used to forecast the pricing behaviour of individual markets. A multivariate generalised autoregressive conditional heteroskedasticity (MGARCH) model is used to identify the source and magnitude of price and volatility spillovers within (intra-relationship) and across (inter-relationship) the various spot markets. The results show evidence of the fact that prices in one market can be explained by their own price lagged one-period and are independent of lagged spot prices of any other markets when daily data is employed. This implies that the regional spot electricity markets are not fully integrated. However, there is also evidence of a large number of significant ownvolatility and cross-volatility spillovers in all five markets indicating that shocks in some markets will affect price volatility in others. Similar conclusions are obtained when the daily data are disaggregated into peak and off-peak periods, suggesting that the spot electricity markets are still rather isolated. These results inspired the research underlying the third paper of the thesis on modelling the dynamics of spot electricity prices in each regional market. A family of generalised autoregressive conditional heteroskedasticity (GARCH), RiskMetrics, normal Asymmetric Power ARCH (APARCH), Student APARCH and skewed Student APARCH is used to model the time-varying variance in prices with the inclusion of news arrival as proxied by the contemporaneous volume of demand, time-of-day, day-of-week and month-of-year effects as exogenous explanatory variables. The important contribution in this paper lies in the use of two latter methodologies, namely, the Student APARCH and skewed Student APARCH which take account of the skewness and fat tailed characteristics of the electricity spot price series. The results indicate significant innovation spillovers (ARCH effects) and volatility spillovers (GARCH effects) in the conditional standard deviation equation, even with market and calendar effects included. Intraday prices also exhibit significant asymmetric responses of volatility to the flow of information (that is, positive shocks or good news are associated with higher volatility than negative shocks or bad news). The fourth research paper attempts to capture salient feature of price hikes or spikes in wholesale electricity markets. The results show that electricity prices exhibit stronger mean-reversion after a price spike than the mean-reversion in the normal period, suggesting the electricity price quickly returns from some extreme position (such as a price spike) to equilibrium; this is, extreme price spikes are shortlived. Mean-reversion can be measured in a separate regime from the normal regime using Markov probability transition to identify the different regimes. The fifth and final paper investigates whether interstate/regional trade has enhanced the efficiency of each spot electricity market. Multiple variance ratio tests are used to determine if Australian spot electricity markets follow a random walk; that is, if they are informationally efficient. The results indicate that despite the presence of a national market only the Victorian market during the off-peak period is informationally (or market) efficient and follows a random walk. This thesis makes a significant contribution in estimating the volatility and the efficiency of the wholesale electricity prices by employing four advanced time series techniques that have not been previously explored in the Australian context. An understanding of the modelling and forecastability of electricity spot price volatility across and within the Australian spot markets is vital for generators, distributors and market regulators. Such an understanding influences the pricing of derivative contracts traded on the electricity markets and enables market participants to better manage their financial risks.

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Higgs, Helen. "Price and volatility relationships in the Australian electricity market." Queensland University of Technology, 2006. http://eprints.qut.edu.au/16404/.

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This thesis presents a collection of papers that has been published, accepted or submitted for publication. They assess price, volatility and market relationships in the five regional electricity markets in the Australian National Electricity Market (NEM): namely, New South Wales (NSW), Queensland (QLD), South Australia (SA), the Snowy Mountains Hydroelectric Scheme (SNO) and Victoria (VIC). The transmission networks that link regional systems via interconnectors across the eastern states have played an important role in the connection of the regional markets into an efficient national electricity market. During peak periods, the interconnectors become congested and the NEM separates into its regions, promoting price differences across the market and exacerbating reliability problems in regional utilities. This thesis is motivated in part by the fact that assessment of these prices and volatility within and between regional markets allows for better forecasts by electricity producers, transmitters and retailers and the efficient distribution of energy on a national level. The first two papers explore whether the lagged price and volatility information flows of the connected spot electricity markets can be used to forecast the pricing behaviour of individual markets. A multivariate generalised autoregressive conditional heteroskedasticity (MGARCH) model is used to identify the source and magnitude of price and volatility spillovers within (intra-relationship) and across (inter-relationship) the various spot markets. The results show evidence of the fact that prices in one market can be explained by their own price lagged one-period and are independent of lagged spot prices of any other markets when daily data is employed. This implies that the regional spot electricity markets are not fully integrated. However, there is also evidence of a large number of significant ownvolatility and cross-volatility spillovers in all five markets indicating that shocks in some markets will affect price volatility in others. Similar conclusions are obtained when the daily data are disaggregated into peak and off-peak periods, suggesting that the spot electricity markets are still rather isolated. These results inspired the research underlying the third paper of the thesis on modelling the dynamics of spot electricity prices in each regional market. A family of generalised autoregressive conditional heteroskedasticity (GARCH), RiskMetrics, normal Asymmetric Power ARCH (APARCH), Student APARCH and skewed Student APARCH is used to model the time-varying variance in prices with the inclusion of news arrival as proxied by the contemporaneous volume of demand, time-of-day, day-of-week and month-of-year effects as exogenous explanatory variables. The important contribution in this paper lies in the use of two latter methodologies, namely, the Student APARCH and skewed Student APARCH which take account of the skewness and fat tailed characteristics of the electricity spot price series. The results indicate significant innovation spillovers (ARCH effects) and volatility spillovers (GARCH effects) in the conditional standard deviation equation, even with market and calendar effects included. Intraday prices also exhibit significant asymmetric responses of volatility to the flow of information (that is, positive shocks or good news are associated with higher volatility than negative shocks or bad news). The fourth research paper attempts to capture salient feature of price hikes or spikes in wholesale electricity markets. The results show that electricity prices exhibit stronger mean-reversion after a price spike than the mean-reversion in the normal period, suggesting the electricity price quickly returns from some extreme position (such as a price spike) to equilibrium; this is, extreme price spikes are shortlived. Mean-reversion can be measured in a separate regime from the normal regime using Markov probability transition to identify the different regimes. The fifth and final paper investigates whether interstate/regional trade has enhanced the efficiency of each spot electricity market. Multiple variance ratio tests are used to determine if Australian spot electricity markets follow a random walk; that is, if they are informationally efficient. The results indicate that despite the presence of a national market only the Victorian market during the off-peak period is informationally (or market) efficient and follows a random walk. This thesis makes a significant contribution in estimating the volatility and the efficiency of the wholesale electricity prices by employing four advanced time series techniques that have not been previously explored in the Australian context. An understanding of the modelling and forecastability of electricity spot price volatility across and within the Australian spot markets is vital for generators, distributors and market regulators. Such an understanding influences the pricing of derivative contracts traded on the electricity markets and enables market participants to better manage their financial risks.

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Fleming, Nathan Richard. "Metal price volatility : a study of informative metrics and the volatility mitigating effects of recycling." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/66481.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; and, (S.M. in Technology and Policy)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2011.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 97-101).
Metal price volatility is undesirable for firms that use metals as raw materials, because price volatility can translate into volatility of material costs. Volatile material costs and can erode the profitability of the firm, and limit material selection decisions. The undesirability of volatility gives firms an incentive to try to gather advanced information on fluctuations in price, and to manage-or at least control their exposure to-price volatility. It was hypothesized that since price can be a measure of the scarcity of a metal, that other metrics of scarcity risk might correlate with price. A system dynamics simulation of the aluminum supply chain was run to determine how well some commonly used metrics of scarcity correlated with future changes in price, and to explore some conditions that strengthened or weakened those correlations. Additionally, prior work has suggested that increased recycling rates can lower price volatility. The study of the correlation of scarcity risk metrics with price is accompanied by a study on how the technical substitutability of secondary metal for primary, termed secondary substitutability, affects the price volatility. The results show that some scarcity risk metrics modeled (alumina price, primary marginal cost, recycling efficiency, and the static depletion index) weakly correlate with future primary metal price, and hence volatility. Other metrics examined (recycling rate, mining industry Herfindahl Index, the acceleration of the mining rate, and the alumina producer's marginal cost) did not correlate with the future primary price. Correlations were stronger when the demand elasticity was high, the secondary substitutability was high, or the delays in adding primary capacity were low. Regarding managing price volatility, greater secondary substitutability lowers price volatility; likely because it increases the elasticity of substitution of secondary for primary metal-this result is explored mathematically. The model results show that some scarcity risk metrics do weakly correlate with future primary price, but the strength of the correlation depends on certain market conditions. Moreover, firms may have some ability to manage price volatility by increasing the limit for how much secondary metal they can use in their product.
by Nathan Richard Fleming.
S.M.in Technology and Policy
S.M.

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30

Law, Ka-chung, and 羅家聰. "A comparison of volatility predictions in the HK stock market." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1999. http://hub.hku.hk/bib/B30163535.

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31

Du, Yuchen. "Modelling and Forecasting Volatility of Gold Price with Other Precious Metals Prices by Univariate GARCH Models." Thesis, Uppsala universitet, Statistiska institutionen, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-187914.

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This paper aims to model and forecast the volatility of gold price with the help of other precious metals. The data applied for application part in the article involves three financial time series which are gold, silver and platinum daily spot prices. The volatility is modeled by univariate Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models including GARCH and EGARCH with different distributions such as normal distribution and student-t distribution. At the same time, comparisons of estimation and forecasting the volatility between GARCH family models have been done.

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32

Ellul, Andrew. "Trading behaviour, price discovery and volatility in competing market microstructures." Thesis, London School of Economics and Political Science (University of London), 2001. http://etheses.lse.ac.uk/2102/.

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The first chapter investigates the price and volatility impacts produced by block trades in an inter-market environment with different microstructures. A sample of European cross-traded securities is employed to investigate whether large trades executed on the foreign market (London Stock Exchange's SEAQ-I market) produce any impacts on the securities' home markets and analyse whether different market microstructures matter. The price impact in the home markets is detected before the large trade is executed on SEAQ-I and proceeds in a protracted fashion, implying that substantial pre- and post-positioning is undertaken by London market makers through the home markets. The new equilibrium price on the home market is reached before the trade information is published on SEAQ-I. Large trades are also found to cause higher price volatility in auction trading systems than in a hybrid market microstructure. The second and third chapters analyse the formation of quoted and effective spreads and their components in three different market microstructures. The results show that quoted and effective spreads generated by a hybrid system (Deutsche Borse's IBIS system) are lower than those generated by both the pure auction system (Paris Bourse's CAC system) and the dealership system (London Stock Exchange SEAQ market). Traders on a hybrid mechanism face the lowest costs and this result holds even when we control for (a) the level of market concentration in liquidity provision, and (b) company-specific news. However, the adverse selection component of the spread is significantly higher in an auction trading system compared to both the dealership and the hybrid trading system. This fifth chapter investigates (a) whether, in a hybrid trading mechanism, voluntary market makers provide a higher level of price stabilisation than limit order traders even if they do not have any obligation to keep orderly markets, (b) the strategic interactions between the limit order book and market makers, and (c) the behaviour of the order flow at times of price uncertainty. We analyse these issues using high frequency data from the London Stock Exchange which has adopted a hybrid market microstructure. We find that prices on the dealership system track the security's true value more efficiently. The dealership system can transact higher volumes with lower price volatility. This evidence suggests that market makers provide price stabilisation, even if they have no binding obligation to do so, thus improving the market's quality. In terms of trading behaviour, we find that in a hybrid trading mechanism, traders are not encouraged to provide liquidity on the order book through limit orders as price uncertainty increases. Instead orders migrate to the dealership system for execution.

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33

Kim, Eun Hie, and Michael Nsiah-Gyimah. "The impact of fuel price volatility on transportation mode choice." Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/53542.

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Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2009.
Includes bibliographical references (leaves 43-45).
In recent years, the price of oil has driven large fluctuations in the price of diesel fuel, which is an important cost component in freight logistics. This thesis explores the impact of fuel price volatility on supply chains by examining the sensitivity of decisions under various scenarios. Specifically, we analyze the transportation mode choice decision between truckload and intermodal (truck combined with rail) transportation using a model to calculate the total relevant cost, consisting of transportation cost and inventory holding cost. We use input from the North American operations for a global retail company regarding annual demand, product characteristics, load size, lead time, transportation rates, fuel surcharges, inventory policies and holding cost to perform sensitivity analysis of the mode choice decision to fuel price and the value density of the product. For several origin-destination pairs we identify the diesel price at which intermodal offers lower total cost than truckload as well as the magnitude of savings that can be achieved by switching modes. We then generalize the insights from this case by providing an equation to calculate the fuel price for this mode choice tradeoff.
by Eun Hie Kim [and] Michael Nsiah-Gyimah.
M.Eng.in Logistics

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Kim, Jae Hyun S. B. Massachusetts Institute of Technology. "Analysis of historical trends in material production and price volatility." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/119064.

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Thesis: S.B., Massachusetts Institute of Technology, Department of Materials Science and Engineering, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 42-44).
Volatilities generate uncertainties in the market that critically impact the decisions of producers, consumers, and speculators alike. Historical trends in volatility can be studied as a means of better understanding current volatilities and predicting future ones in the industry. This study used the coefficient of variation (CV) as a relative metric to compare the historical production and price volatilities of various materials - 12 metals, cement, and steel - from 1900 through 2015. The long-term (1900-2015) and short-term (1995-2015) volatilities of these materials were quantified, and decades corresponding to periods of warfare and/or economic recession were shown to exhibit highest volatility. To complement the breadth of this approach, aluminum and steel were used as case studies to determine which factors - amongst production, consumption, energy price, and raw material price - drive trends in U.S. material price volatility. Volatility comparison graphs of material price and the factor in question were generated, and the root mean square (RMS) error between the volatilities was taken as a measure of their correlation. Volatilities in both aluminum and steel price were shown to correlate strongest with volatilities in raw material (bauxite and iron ore) price, with volatilities in steel also correlating comparatively with production and consumption dynamics. Overall, this study demonstrated the effectiveness of CV as a quantitative metric to assess historical volatilities and identified key market forces driving these volatilities for the aluminum and steel industries.
by Jae Hyun Kim.
S.B.

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35

Wilks, Megan. "Spread, inventory and spot price volatility in the platinum market." Master's thesis, University of Cape Town, 2011. http://hdl.handle.net/11427/12453.

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Includes bibliographical references
The central idea of the theory of storage is that the level of inventory influences the effect that changes in the demand-and-supply conditions have on spot and futures prices. With the use of monthly data for the period January 1992 to January 2010, I find that the predictions of the theory of storage do not always hold in the platinum market. In conflict with the theoretical predictions, I find that: i) demand-and-supply shocks will have the same effect on spot and futures prices, regardless of the level of inventory; and ii) changes in spot prices have very similar effects on the changes in futures prices when inventory is high and when it is low. In support of the theory of storage, I find a significant negative correlation between the volatility of spot prices and inventory throughout the sample period. Thereafter, I test the forecasting ability of the spot price volatility by employing a GARCH-t(1,1) model and find that volatility can be forecast fairly accurately for short periods, during which the spot prices are somewhat stable.

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Karlsson, Christopher, and Renteln Alexander von. "Stock price volatility and dividend policy: The German stock exchange." Thesis, Jönköping University, IHH, Nationalekonomi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-53018.

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The objective of this research is to analyse if there is a negative relationship between dividend policy and stock price volatility in the German stock market. The data that was collected for this research consists of the 30 biggest companies listed on the German stock exchange Deutscher Aktienindex known as DAX 30 for the period 2000-2020. Fixed effect model estimated by panel data was applied to find the results of this research. The findings showed that the main variables of dividend policy (dividend yield and payout ratio) were negatively significant correlated with stock price volatility which provides evidence for our hypothesis. The results showed that the control variable earnings volatility had a positive significant relationship with stock price volatility. However, asset growth resulted in an insignificant relationship but the rest of the control variables such as leverage, market value and free float percentage showed a significant negative relationship with stock price volatility.

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Zwane, Reuben Mabutho. "Housing price volatility: exploring metropolitan property markets in South Africa." Thesis, Nelson Mandela Metropolitan University, 2018. http://hdl.handle.net/10948/21560.

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This study analyses the housing price volatility in metropolitan areas in South Africa, particularly Port Elizabeth and East London residential housing markets. This study uses secondary statistical data, obtained from secondary sources. The study uses quarterly time series data for the period 1981:1 to 2015:3 giving 139 observations. The data will be collected from different sources. The main sources of data are real estate agencies (Trafalgar, Harcourts and Property24), the South African Department of Trade and Industry (dti) and supplemented by the South African Reserve Bank (SARB) and Statistics South Africa (Stats SA). The study shall use the ordinary least squares (OLS) method to estimate its results. Ordinarily, this is a generalised linear modelling technique that may be used to model a single response variable which has been recorded on at least an interval scale. This method requires that the underlying stochastic processes of the variables are stationary. That is, explanatory variables should exhibit constant means and variances over time. If the stochastic processes are not stationary, OLS produces unreliably significant coefficients. Results showed that household savings, household income and total growth in household buildings (TGH) are statistically significant in explaining changes in house prices. Jointly, all the explanatory variables can account for almost 52% of the changes in the dependent variable. The Durbin Watson statistic showed that there is no autocorrelation in the model. This shows that the model is good. Results from the regression show that there is a negative relationship between house prices and household savings. A one-unit increase in household savings leads to a 0.407 decrease in house prices. This relationship makes economic sense because when households save, there is less income available to buy houses. When there is less income available to buy houses, it would mean there is less demand for houses.

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Zhang, Siyu. "Pricing caps and swaptions when bond prices follow jump-diffusion processes and have log-price volatility." [Bloomington, Ind.] : Indiana University, 2008. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3307569.

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Thesis (Ph.D.)--Indiana University, Dept. of Mathematics, 2008.
Title from PDF t.p. (viewed Dec. 9, 2008). Source: Dissertation Abstracts International, Volume: 69-05, Section: B, page: 3039. Adviser: Victor Goodman.

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Merino, Fernández Raúl. "Option Price Decomposition for Local and Stochastic Volatility Jump Diffusion Models." Doctoral thesis, Universitat de Barcelona, 2021. http://hdl.handle.net/10803/671682.

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In this thesis, an option price decomposition for local and stochastic volatility jump diffusion models is studied. On the one hand, we generalise and extend the Alòs decomposition to be used in a wide variety of models such as a general stochastic volatility model, a stochastic volatility jump dffusion model with finite activity or a rough volatility model. Furthermore, we note that in the case of local volatility models, speci_cally, spot-dependent models, a new decomposition formula must be used to obtain good numerical results. In particular, we study the CEV model. On the other hand, we observe that the approximation formula can be improved by using the decomposition formula recursively. Using this decomposition method, the call price can be transformed into a Taylor type formula containing an infinite series with stochastic terms. New approximation formulae are obtained in the Heston model case, finding better approximations.
En aquesta tesi, s'estudia una descomposició del preu d'una opció per a models de volatilitat local i volatilitat estocàstica amb salts. D'una banda, generalitzem i estenem la descomposició d'Alòs per a ser utilitzada en una àmplia varietat de models com, per exemple, un model de volatilitat estocàstica general, un model de volatilitat estocàstica amb salts d'activitat finita o un model de volatilitat 'rough'. A més a més, veiern que en el cas dels models de volatilitat local, en particular, els models dependents del 'spot' s'ha d'utilitzar una nova fórmula de descomposició per a obtenir bons resultats numèrics. En particular, estudiem el model CEV. D'altra banda, observem que la fórmula d'aproximació es pot millorar utilitzant la formula de descomposició de forma recursiva. Mitjançant aquesta tècnica de descomposició, el preu d'una opció de compra es pot transformar en una formula tipus Taylor que conté una sèrie infinita de termes estocàstics. S'obtenen noves fórmules d'aproximació en el cas del model de Heston, trobant una millor aproximació.
En esta tesis, se estudia una descomposición del precio de una opción para los modelos de volatilidad local y volatilidad estocástica con saltos. Por un lado, generalizamos y ampliamos la descomposición de Alòs para ser utilizada en una amplia variedad de modelos como, por ejemplo, un modelo de volatilidad estocástica general, un modelo de volatilidad estocástica con saltos de actividad finita o un modelo de volatilidad 'rough'. Además, vemos que en el caso de los modelos de volatilidad local, en particular, los modelos dependientes del 'spot', se debe utilizar una nueva fórmula de descomposición para obtener buenos resultados numéricos. En particular, estudiamos el modelo CEV. Por otro lado, observamos que la fórmula de aproximación se puede mejorar utilizando la fórmula de descomposición de forma recursiva. Mediante esta técnica de descomposición, el precio de una opción de compra se puede transformar en una fórmula tipo Taylor que contiene una serie infinita de términos estocásticos. Se obtienen nuevas fórmulas de aproximación en el caso del modelo de Heston, encontrando una mejor aproximación.

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Soffronow, Pagonidis Alexander Ivan. "Short Sale Constraints: Effects on Crashes, Price Discovery, and Market Volatility." Thesis, Jönköping University, Jönköping International Business School, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-9063.

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The recent SEC ban on short selling has presented an unrivaled opportunity to explore the effects of short selling constraints on crashes, market efficiency, and volatility. In this paper I carry out two groups of empirical tests on the individual banned stocks and a series of portfolios created from them: the first tests the hypothesis that short sale constraints increase the frequency and magnitude of crashes, by testing Hong & Stein’s (2003) model of market crashes. The second tests the hypothesis that short sale constraints reduce market efficiency, by testing Miller’s (1977) model in which stocks that are hard (or impossible) to short tend to exhibit overpricing. In regards to the first group of tests, the results are ambiguous: the frequency and magnitude of crashes increased during the ban period, while the skewness of the returns distribution of the portfolios became more negative, as expected, but these changes hold for the market as a whole, as well. On the other hand, the skewness of the returns distribution of the individual banned stocks became more positive. The second group of tests provides ample support for Miller’s model, as the results coincide with the models predictions: banning short selling leads to positive abnormal returns (overpricing) in the affected stocks. The ban is also related with a decrease in volatility relative to the market, an important result from a policy perspective.

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Doroudian, Ali. "Speculation and price volatility : the case of rice in United States." Thesis, University of British Columbia, 2011. http://hdl.handle.net/2429/36925.

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In response to the rampant and high volatility in rice prices relative to other grains over the past few decades and calls by governments for tighter control and regulation on futures trading to limit speculation and curtail volatility, this work evaluates the performance of the rice futures market in United State in terms of its impact on the nation’s rice cash price volatility. This study presents a refined form of Milton Friedman’s original theory (1953) that speculation leads to less volatility unless it is carried out by irrational speculators. It will test this theory empirically using time series econometrics. Generalized autoregressive conditional heteroskedasticity (GARCH) is used to measure volatility of the price of rice. Vector autoregressive (VAR) models are deployed to measure the impact of trading activity on cash price volatility through Granger Causality test, forecast error variance decomposition (FEVD), and impulse response (IR) methods. Results show that rice cash price volatility after the introduction of the rice futures market on the Chicago Board of Trade is lowered by 51%. The Granger Causality test also indicates that sudden changes in the futures market trading activity (proxy for the presence of irrational speculators) cause higher volatility in the cash market. The FEVD, and IR methods indicate that a sudden rise in non-commercial open interest has a larger impact on cash price volatility than changes in trading volume.

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Hammad, Rayan Salem. "Modelling the impact of oil price volatility on investment decision-making." Thesis, University of Hull, 2011. http://hydra.hull.ac.uk/resources/hull:5379.

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The energy industry is transforming from the old, vertically integrated model into a more competitive model in which most companies are exposed to different types of risk. One of the major challenges facing energy companies is making investment decision-making associated with the prices of crude oils. Since 1973, crude oil price behaviour has become more volatile, which suggested that different forces were driving crude oil prices. One of the main factors in generating the behaviour of crude oil prices is the role performed by OPEC and non-OPEC crude oil producers. Several theoretical and empirical analyses suggested that the economics behind OPEC’s supply of crude oil is different than those of non-OPEC supply. This study investigates whether prices of OPEC crude oils and prices of non-OPEC crude oils share a common data-generating process. The study empirically tests oil price volatility of OPEC and non-OPEC crude oil prices using GARCH models. It also applies the Johansen Cointegration Model and the Engle-Granger Error Correlation Model (ECM) model to test the long – and short-term relationship between crude prices (OPEC and non-OPEC) and stock prices of different oil companies. Finally, a panel data approach using fixed and random effects is used to estimate the reaction of OPEC and non-OPEC crude oil prices to events and news items that could possibly affect oil supply and prices. The results obtained suggest that the behaviour of crude oil prices is not affected by OPEC or non-OPEC affiliation. This finding suggests that the international oil market is globally integrated market that is able to factor in any possible changes to supply behaviour of OPEC or non-OPEC producers.

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Kornher, Lukas [Verfasser]. "Food price volatility: the role of stocks and trade / Lukas Kornher." Bonn : Universitäts- und Landesbibliothek Bonn, 2015. http://d-nb.info/1079323821/34.

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44

Rottenberg, Boaz. "The effect of financial leverage on asset price volatility in JapaneseKeiretsu." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2003. http://hub.hku.hk/bib/B31954625.

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Lahouiri, Elia. "Volatility surfacef and market price uncertainty." Master's thesis, 2018. http://hdl.handle.net/10362/49536.

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Volatility surface is a major factor in the valuation of several instruments. The models behind it are many. In this work project, we are going to discuss the major stochastic models used in practice, the hypotheses of these models, how to construct them and their main drawbacks. These drawbacks lead sometimes to valuation uncertainty in the market which is an important risk factor in different fields in finance. In this work we are going to focus on risk management. The aim of this analysis is to understand the motivation under which the European Bank Authority (EBA) creates a prudent valuation framework and the risk management solution to assess this risk.

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Vathitphund, Kwanchai, and 陳浩天. "Export Price Volatility of Thailand Rice." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/69223707519524112943.

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碩士
國立中興大學
應用經濟學系所
105
The aim of this study to find out the most appropriate GARCH model with export price volatility of Thailand rice by using the daily data. The data come from Official of Agricultural Economics of Thailand and starting from 1st January 2008 until 19th January 2016. The empirical analysis base on GARCH (1,1), EGARCH, and GJR-GARCH models. From the Akaike information criterion (AIC) and Schwartz criterion (SBC) suggest that GJR-GARCH model is the most appropriate model with export price volatility of Thailand rice. From the empirical result explains that there are statistically significant in ARCH and GARCH terms. The both results mean that export price volatility of Thailand rice in previous period can influence present period export price volatility of Thailand rice. Finally, this study discover over supply of rice in Thailand during that period because there is negative shock (bad news:  0) on volatility of export price of Thailand rice.

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Troy, IV William. "Wholesale electricity price volatility and price bounds: a market comparison." Master's thesis, 2017. http://hdl.handle.net/10362/22255.

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Due to high volatility and frequent price spikes in wholesale electricity market prices, market regulators often impose price bounds on auction and final market prices. This paper applies a model-free intraday-range measure and ARMA-EGARCH(1,1) models to wholesale electricity price data collected from seven markets in the United States and Europe to measure and compare volatilities across the seven markets and the effects of exogenous amendments to price bounds in a subsample of three markets. The paper concludes that the wider a market’s imposed price bounds, the higher the price volatility. Conclusions also suggest that exogenous price bound changes have more significant effects in markets with tighter imposed bounds and that changes made to locational marginal price bounds have greater effects on price behavior than do changes made to energy offer price bounds. Conclusions add to emerging research about the effects of price bounds on electricity price volatility and are relevant for policy makers and market participants concerned with price volatility.

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"Application of neural network to study share price volatility." 1999. http://library.cuhk.edu.hk/record=b5896263.

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by Lam King Wan.
Thesis (M.B.A.)--Chinese University of Hong Kong, 1999.
Includes bibliographical references (leaves 72-73).
ABSTRACT --- p.ii.
TABLE OF CONTENTS --- p.iv.
Section
Chapter I. --- OBJECTIVE --- p.1
Chapter II. --- INTRODUCTION --- p.3
The principal investment risk --- p.3
Effect of risk on investment --- p.4
Investors' concern for investment risk --- p.6
Chapter III. --- THE INPUT PARAMETERS --- p.9
Chapter IV. --- LITERATURE REVIEW --- p.15
What is an artificial neural network? --- p.15
What is a neuron? --- p.16
Biological versus artificial neuron --- p.16
Operation of a neural network --- p.17
Neural network paradigm --- p.20
Feedforward as the most suitable form of neural network --- p.22
Capability of neural network --- p.23
The learning process --- p.25
Testing the network --- p.29
Neural network computing --- p.29
Neural network versus conventional computer --- p.30
Neural network versus a knowledge based system --- p.32
Strength of neural network --- p.34
Weaknesses of neural network --- p.35
Chapter V. --- NEURAL NETWORK AS A TOOL FOR INVESTMENT ANALYSIS --- p.38
Neural network in financial applications --- p.38
Trading in the stock market --- p.41
Why neural network could outperform in the stock market? --- p.43
Applications of neural network --- p.45
Chapter VI. --- BUILDING THE NEURAL NETWORK MODEL --- p.47
Implementation process --- p.48
Step 1´ؤ Problem specification --- p.49
Step 2 ´ؤ Data collection --- p.51
Step 3 ´ؤ Data analysis and transformation --- p.55
Step 4 ´ؤ Training data set extraction --- p.58
Step 5 ´ؤ Selection of network architecture --- p.60
Step 6 ´ؤ Selection of training algorithm --- p.62
Step 7 ´ؤ Training the network --- p.64
Step 8 ´ؤ Model deployment --- p.65
Chapter 7 --- RESULT AND CONCLUSION --- p.67
Result --- p.67
Conclusion --- p.69
BIBLIOGRAPHY --- p.72

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Liu, Cheng-Rui, and 劉程睿. "The Relationship among Turnover Ratio, Trading Volume Volatility and Stock Price Volatility." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/99179065514691273066.

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碩士
淡江大學
管理科學研究所碩士班
96
Most domestic and foreign literatures involve the behavior between quantity and price volatilities. This research investigates the relationships between price volatilities trading volume volatilities instead of quantity in order to expand the scope of this research. In addition, high turnover ratio is the characteristic of Taiwan stock market, and it means that investors prefer short term investment instead of holding stocks in the long run. Thus, whether the high turnover ratio will cause stock price volatilities is another issue we concern. By employing Fubon ETF underlying stocks from the data period form 2006/09/29 to 7007/09/29, the following empirical results are found as follow: 1.The turnover ratio Granger-cause stock price volatilities positively. It means that high turnover ratio means investors change stocks very often, and then it might lift up the volatilities of share price. 2.Trading volume volatilities will Granger-cause stock price volatilities positively. It means that while trading volume is going up, the stock price volatilities will rise up later. Investors might be careful to trade stocks with higher turnover ratio, since higher trading volume might be involved by huge trading of investment institution, and investors with lots of money. The possible reasons of this kind involving are inside information, and speculation trading, investors should careful in trading higher turnover stocks in order to prevent loss by asymmetric information be.

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Doran, James Stephen Ronn Ehud I. "On the market price of volatility risk." 2004. http://repositories.lib.utexas.edu/bitstream/handle/2152/1951/doranjs042.pdf.

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Dissertations / Theses on the topic 'Price volatility'

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