Over the past decade, numerous engineered credit events and cases of market participants manipulating bond prices to influence Credit Default Swap (CDS) auction payouts have occurred. These cases have become increasingly common, and the CFTC has stated they may constitute market manipulation and undermine not only the CDS market but also the credit derivative and default markets. Although there is a plethora of news and media coverage on publicized cases, there is no previous empirical research on evidence of these practices. This paper is motivated by the desire to determine if there is indirect evidence of bond price manipulation around default and of market participants’ attempts to favorably move CDS’s underlying bond prices to achieve more profitable positions around default and emerging from CDS auctions. The analysis is performed by analyzing the effect of a bonds’ inclusion in CDS auctions on bond return volatility around the time of default while controlling for credit risk, illiquidity, firm fundamentals, and other bond-level controls. I find that bond return volatility around default is much higher as a result of a bond’s inclusion in a CDS auction, which serves as indirect evidence of bond price manipulation around default as market participants strive for more profitable CDS auction outcomes and possibly of manufactured credit events. Consistent with previous literature, I also find that bond illiquidity significantly impacts bond return volatility. My results are robust to propensity score matching, implementing double-robust estimators, and controlling for any time-varying cross-sectionally-invariant fluctuations in bond return volatility.

Uma das informações mais importantes no mercado financeiro é a variabilidade de um ativo. Diversos modelos foram propostos na literatura com o intuito de avaliar este fenômeno. Dentre eles podemos destacar os modelos GARCH. Este trabalho propõe o uso do método Monte Carlo Hamiltoniano (HMC) para a estimação dos parâmetros do modelo GARCH univariado e multivariado. Estudos de simulação são realizados e as estimativas comparadas com o método de estimação Metropolis-Hastings presente no pacote BayesDccGarch. Além disso, compara-se os resultados do método HMC com a metodologia adotada no pacote rstan. Por fim, é realizado uma aplicação a dados reais utilizando o DCC-GARCH bivariado e os métodos de estimação HMC e Metropolis-Hastings. / One of the most important informations in financial market is variability of an asset. Several models have been proposed in literature with a view of to evaluate this phenomenon. Among them we have the GARCH models. This paper use Hamiltonian Monte Carlo (HMC) methods for estimation of parameters univariate and multivariate GARCH models. Simulation studies are performed and the estimatives compared with Metropolis-Hastings methods of the BayesDcc- Garch package. Also, we compared the results of HMC method with the methodology present in rstan package. Finally, a application with real data is performed using bivariate DCC-GARCH and the methods of estimation HMC and Metropolis-Hastings.

Derivative pricing, model calibration, and sensitivity analysis are the three main problems in financial modeling. The purpose of this study is to present an algorithm to improve the pricing process, the calibration process, and the sensitivity analysis of the double Heston model, in the sense of accuracy and efficiency. Using the optimized caching technique, our study reduces the pricing computation time by about 15%. Another contribution of this thesis is: a novel application of the Automatic Differentiation (AD) algorithms in order to achieve a more stable, more accurate, and faster sensitivity analysis for the double Heston model (compared to the classical finite difference methods). This thesis also presents a novel hybrid model by combing the heuristic method Differentiation Evolution, and the gradient method Levenberg--Marquardt algorithm. Our new hybrid model significantly accelerates the calibration process.

[pt] O presente trabalho visa generalizar a modelagem do tempo entre os negócios ocorridos no mercado financeiro, doravante chamado duração, e estudar os impactos destas duraçõoes sobre a volatilidade instântanea. O estudo foi realizado por meio do modelo linear ACD (autoregression conditional duration) proposto por Engel e Russel[3], os quais usaram a distribuição Exponencial e Weibull para as inovações, e o modelo GARCH-t para dados com alta freqüência para modelar a volatilidade instântanea, também usando a proposição de Engel e Russel[3]. A generalização faz uso da Gama Generalizada proposta em Zhang, Russel & Tsay[9] em um modelo de duração não linear conhecido como TACD (threshold autoregressive conditional duration). A justificativa para o estudo das durações com a Gama Generalizada é obter uma modelo mais flexível que o proposto por Engel e Russel[3]. Os resultados do modelo ACD com as inovações seguindo uma Gama Generalizada se mostrou mais adequado capturando a sub-dispersão dos dados. A seguir estimamos o modelo de volatilidade instantânea usando as durações estimadas como variáveis explicativas encontrando resultados compatíveis com a literatura. / [en] This work generalizes the duration model, the time elapsed between two consecutive transactions, such as financial transactions data; and explores the consequences of durations in the instantaneous volatility. The approach have been motivated by Engel and Russel[3], that proposed an autoregressive conditional duration (ACD) model to explain the variation of volatility, where the innovations proposes were Exponential andWeibull distributions. Besides they used the GARCH-t to modeling the instantaneous volatility in high frequency data. This work uses the Generalized Gamma to the innovations in order to generalize the ACD model, this distribution has been first suggested by Zhang, Russel and Tsay[9], in the threshold ACD (TACD) framework. We justify the generalized Gamma specification in order to allow for more flexibility than the ACD model of Engel and Russel[3]. We find evidences that the ACD model with this specification was better to captur the behavior such as sub- dispersion.

This thesis examines the empirical performance of four Affine Jump Diffusion models in pricing and hedging S&P 500 Index options: the Black Scholes (BS) model, Heston???s Stochastic Volatility (SV) model, a Stochastic Volatility Price Jump (SVJ) model and a Stochastic Volatility Price-Volatility Jump (SVJJ) model. The SVJJ model structure allows for simultaneous jumps in price and volatility processes, with correlated jump size distributions. To the best of our knowledge this is the first empirical study to test the hedging performance of the SVJJ model. As part of our research we derive the SVJJ model minimum variance hedge ratio. We find the SVJ model displays the best price prediction. The SV model lacks the structural complexity to eliminate Black Scholes pricing biases, whereas our results indicate the SVJJ model suffers from overfitting. Despite significant evidence from in and out-of-sample pricing that the SV and SVJ models were better specified than the BS model, this did not result in an improvement in dynamic hedging performance. Overall the BS delta hedge and SV minimum variance hedge produced the lowest errors, although their performance across moneyness-maturity categories differed greatly. The SVJ model???s results were surprisingly poor given its superior performance in out-of-sample pricing. We attribute the inadequate performance of the jump models to the lower hedging ratios these models provided, which may be a result of the negative expected jump sizes.

期望波動度在投資組合的選擇、避險策略、資產管理，以及金融資產的評價上是關鍵性因素，因此，在波動度變化甚巨的金融市場中，找出具有良好預測波動度能力的模型，是絕對必要的。過去從事資產價格行為的相關研究都假設資產的價格過程是隨機的，且呈對數常態分配、變異數固定。然而實證結果一再顯示：變異數是隨時間而變動的（如 Mandelbrot(1963)、 Fama(1965)）。為預測波動度（或變異數），Eagle(1982)首先提出了 ARCH 模型，允許預期條件變異數作為過去殘差的函數，因此變異數能隨時間而改變。此後 Bollerslve(1986)提出 GARCH 模型，修正ARCH 模型線性遞減遞延結構，將過去的殘差及變異數同時納入條件變異數方程式中。 Nelson(1991)則提出 EGARCH 模型以改進 GARCH 模型的三大缺點，此模型對具有高度波動性的金融資產提供更成功的另一估計模式。除上列之 ARCH-type 模型外，Hull and White(1987)提出連續型隨機波動模型(continuous time stochastic volatility model)，用以評價股價選擇權，此模型不僅將過去的變異數納入條件變異數的方程式中，同時該條件變異數也會因隨機噪音(random noise)而變動。近年來，上述模型均被廣泛運用在模擬金融資產的波動性，均是相當實用的模型。 本文以隨機漫步(random walk)、GARCH(1,1)、EGARCH(1,1)及隨機波動模型(stochastic volatility)進行不同期間下，股價指數與外匯波動度之預測，並以實證結果判斷上述四種模型在預測外匯及股價指數波動度的能力表現。實證結果顯示：隨機波動模型不論在股價指數或外匯、長期或短期的波動度預測上，都是最佳的波動度預測模型，因此建議各大金融機構可採隨機波動模型預測金融資產未來的波動度。 / Volatility forecast is extremely important factor in portfolio chice, hedging strategies, asset management, asset pricing and option pricing. Identifying a good forecast model of volatility is absolutely necessary, especially for the highly volatile Taiwan stock marek. Due to increasing attention to the impact of marke risk on asset returns, academic researchers and practicians have developed ways to control risk and methodologies to forecast return volatility. Past researches on asset price behavior usually assumed that asset price behavior follows random walk, and its probability distribution is a log-normal distribution with a constant variance (or constant volatility). This assumption is in fact in violation of empirical evidence showing that volatility tends to vary over time (e.g., Mandelbrot﹝1963﹞ and Fama﹝1965﹞). To forecast volatility (or variance), Engle(1982) is the first scholar to propose a forecast model, now well-known as ARCH, whose conditional variance is a funtion of past squared returns residuals. Accordingly, the forecast variance(or volatility) varies over time. Bollerslev(1986) proposed a generalized model, called GARCH, which allows the current conditional variance depends not only on past squared residuals, but also on past conditional variances. However, Nelson(1991) has recently proposed a new model, called EGARCH, which attempts to remove the weakness of the GARCH model. The EGARCH model has been shown to be successful to forecast volatility and to describe successful stock price behavior. In addition, Hull and white(1987) employed a continuous-time stochastic volatility model to develop in option pricing model. Their stochastic volatility model not only admits the past variance, but also depends on random noise of volatility. The above-mentioned models have been widely implemented in practice to simulate and to forecast asset return volatility. This thesis investigates whether random walk, GARCH(1,1), EGARCH(1,1) and stochastic volatility model differ in their ability to predict the volatility of stock index and currency returns over short-term and long-term horizons. The results strongly support that the best volatility predictions are generated by the stochasic volatility model. Therefore, it is recommended that financial institutions may adopt stochastic volatility model to predict asset return volatility.

This dissertation consists of 3 essays that examine the impact of electronic screen trading in futures markets. The research provides empirical evidence on increasingly significant issues given the rapid global advances in technology used in securities markets. Each essay addresses the scarcity of conclusive research in order to aid researchers, regulators, exchange policy makers and systems builders as they confront issues related to electronic trading systems.

<p>The quality of software systems depends on early activities in the software development process, of which the management of requirements is one. When requirements are not managed well, a project can fail or become more costly than intended, and the quality of the software developed can decrease. Among the requirements management practices, it is particularly important to quantify and predict requirements volatility, i.e., how much the requirements are likely to change over time. Software measures can help in quantifying and predicting requirements attributes like volatility. However, few measures have yet been defined, due to the fact that the early phases are hard to formalise. Furthermore, very few requirements measures have been validated, which would be needed in order to demonstrate that they are useful. The approach to requirements management in this thesis is quantitative, i.e. to monitor the requirements management activities and requirements volatility through software measurement. In this thesis, a set of 45 requirements management measures is presented. The measures were defined using the goal question metrics framework for the two predefined goals of the requirements management key process area of the capability maturity model for software. A subset of these measures was validated theoretically and empirically in four case studies. Furthermore, an analysis of validated measures in the literature was performed, showing that there is a lack of validated process, project, and requirements measures in software engineering. The studies presented in this thesis show that size measures are good estimators of requirements volatility. The important result is that size is relevant: increasing the size of a requirements document implies that the number of changes to requirements increases as well. Furthermore, subjective estimations of volatility were found to be inaccurate assessors of requirements volatility. These results suggest that practitioners should complement the subjective estimations for assessing volatility with the objective ones. Requirements engineers and project managers will benefit from the research presented in this thesis because the measures defined, proved to be predictors of volatility, can help in understanding how much requirements will change. By deploying the measures, the practitioners would be prepared for possible changes in the schedule and cost of a project, giving them the possibility of creating alternative plans, new cost estimates, and new software development schedules.</p>

<p>Background: An evaluation of analysts´ forecasting ability is interesting since their estimates constitute an important part in stock valuation and investment decisions. The recent years´ development in the stock market has lead to criticism of analysts’ deficient forecasts. </p><p>Purpose: The purpose of this thesis is to evaluate analysts´ forecasting ability concerning companies quoted at Stockholmsbörsen between 1987 and 2002. We also intend to discuss possible explanations for analysts’ behavior in case of deficient accuracy. </p><p>Method: Regression analysis is used to compare consensus estimates of earnings per share to actual earnings per share. We attempt to investigate the existence of a relation between forecasting ability and forecast horizon, the volatility at Stockholmsbörsen and the industry in which the firm operates. Behavioral finance and economic incentives is used to discuss the most convincing explanations to analysts´ behavior in cases of deficient accuracy. </p><p>Result: The study indicates over optimistic forecasts and overreaction to earnings information. Analysts tend to give more accurate forecasts closer to earnings announcement. We believe that herding, economic incentives and the fact that analysts get information from the company explains a significant part of analysts’ behavior. In addition, the study shows a possible relation between more accurate forecasts and lower volatility. Concerning industries we find stronger overreaction in healthcare and heavy industry. The study shows the most exceptional optimism in consumer goods/services and IT/telecom.</p>

<p>Allteftersom svenska företag utökar sina verksamheter på den globala marknaden uppstår nya möjligheter men även nya risker. De flesta länder har nu ett rörligt växelkurssystem vilket lett till att företagens valutarisker ökat. Volatiliteten på valutamarknaden har under de senaste åren ökat i omfattning vilket ökar betydelsen av fungerande valutariskhantering.</p><p>Syftet med denna uppsats är att undersöka hur vissa svenska multinationella företag hanterar sina valutarisker och om det har förändrats i tider av hög volatilitet på valutamarknaden och förändrat konjunktursläge.</p><ul><li>Hur identifierar och hanterar företag sina valutaexponeringar?</li><li>Vilka faktorer inverkar på ett företags valutariskhantering?</li><li>Förändras valutariskhanteringen vid ökad volatilitet på valutamarknaden och förändrat konjunkturläge?</li></ul><p><strong></strong></p><p>I uppsatsen har vi använt oss utav en kvalitativ metod med ett hermeneutiskt synsätt för att uppnå en djupare förståelse av ämnet och på grund utav att uppsatsens syfte kräver en metod som möjliggör för oss författare att förstå tankesättet bakom handlingarna. Vi startade med att samla in sekundärdata för att skapa en teoretisk referensram att använda som bas att utgå våra intervjuer ifrån och analysera datan.</p><p>Slutsatserna vi som uppsatsskrivare kommit fram till av studien är att den ökade volatiliteten påverkat valutariskhanteringen och intresset av valutariskhantering ute på operativ nivå i företagen ökat. Uppsatsen visar även på att det osäkra marknadsläget lett till att företagen minskat säkringsnivåerna på deras exponeringar för att undvika att bli översäkrad.</p><p>Vi anser att det vore intressant att använda sig av ett större urval företag (alternativt att fokusera branschvis) ur en längre tidsperiod. Det har även uppkommit frågor under uppsatsen gång som vi inte kunnat gå in närmare på, exempelvis hur företagen arbetar med den ekonomiska exponeringen. Även en studie som närmare undersöker IAS 39s påverkan på företagens valutariskhantering vore intressant.</p><p>Uppsatsen har bidragit till ökad kunskap om vilka faktorer som påverkar valutariskhanteringsarbetet och hur valutariskhanteringen förändras under volatila och mer osäkra förhållanden.</p><p> </p> / <p>As multinational Swedish companies extend their international operations they encounter new opportunities as well as new risks. Since most economies today has floating currency systems the currency risk for the firms also increases. During the last years substantially increased volatility on the currency market has lead to an increased importance of a functioning currency risk management.</p><p>The purpose of this bachelor thesis is to investigate how some Swedish multinational firms manage their currency risks and how they have become affected of the increased market volatility and an uncertain economic situation.</p><ul><li>How do firms measure and manage their currency exposure?</li><li>Which variables affect firms' currency risk management?</li><li>Do the firms' currencies risk management change during an increased volatility and uncertain economic situation?</li></ul><p> </p><p>In this thesis we have chosen to use a qualitative method with a hermeneutic approach to gain a deeper knowledge in the subject since our purpose demands a greater depth to understand the firms' way of thinking. We started off with gathering secondary data to create a theoretical frame of reference. The framework was later used a as support for the interviews and as well for the analysis.</p><p><strong></strong></p><p>The conclusions we as writers made of this thesis was that the increased volatility affected the currency risk management and the interest to manage currency risks has risen on an operative levels. The thesis shows that the uncertain economic situation has lead to the firms have reduced their hedging levels to avoid become over hedged.</p><p>We would find it interesting to gather data from a greater amount of firms (or focus on specific industries) during a longer period of time. Because of our limited time we couldn't explore all the questions that have come up. For an example: a study on how firms manage their economic exposure. We would also like to see a study on how IAS 39 affects firms' currency risk management.</p><p>This thesis has contributed to increased knowledge about what variables influences firms' currency risk management and how the currency risk management changes in volatile and uncertain times.</p><p> </p>