Thèses sur le sujet « VOLATILITY MEASUREMENT »

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

This study comprises of three essays on the subject of financial risk management with applications in the fields of portfolio optimization, continuous and discrete time stochastic volatility (SV) modelling. We jointly consider two risk measures: Value-at-Risk (VaR) and conditional Value-at-Risk (CVaR) to measure the financial market risk. In order to model the distribution of financial asset returns which is characterized by skewness, heavy tails and leptokurtosis, we employ the Asymmetric Laplace distribution (ALD) in the first and third essay while constructing the risk model on the basis of the Heston stochastic volatility (SV) model in the second essay. Specifically, in the first essay, we provide a comprehensive empirical examination of the viability of the new proposed Mean-CVaR-Skewness optimization model under ALD by Zhao et al. (2015). In addition, we propose the Mean-VaR-Skewness model under ALD by employing VaR as risk measure. The closed-form solution of the two optimization models is shown to be consistent and is obtainable by using the Lagrange Multiplier approach. In the second essay, we construct the VaR and CVaR models for the financial dynamics that do not have a closed-form probability density function. The only input required in our approach is the knowledge of the characteristic function of the underlying asset. In the numerical analysis, we investigate the elements that could impact the VaR and CVaR approximations in the Heston model. The third essay contributes to the existing literature by extending the ALD (Kotz et al., 2001) to the return error term of a standard discrete time SV model. We give the closed-form VaR and CVaR formulas for oil supply and demand. As additional contribution, we propose a new scale mixture of uniform (SMU) representation for the AL density so that the model can be implemented efficiently within the Bayesian Markov Chain Monte Carlo framework.

Exchange rate movements play substantial role in risk measurement and their effective management. Volatility in exchange rates has been quite large and it has affected sales as well as profit margins of multinationals in India. Based on statistic analysis, some suggestion have been drawn for improving functioning of forex exchange market in India.
1. Most hedging instruments are required to cope up extreme volatility of INR against all major currencies of the world. 2. Steady liberalization of financial markets is need more attention on business who invest back in India. 3. Promotion of invoicing of trade in domestic currency will be extremely helpful and beneficial to cope up with extreme volatility. 4. There has been wide progress and enhancement of INR market across globe especially in Dubai, Singapore, London and New York, so it is need to try relocate of offshore activities on shore. 5. RBI has taken a number of steps in the recent past to liberalize currency futures market to obviate/reduce the need for the NDF market. 6. There is need for effective coalition between OTC and exchange traded markets for currency futures. 7. More focus should be to advocate the importance and practicability of risk management techniques in particular using options. 8. There is need to develop strict monitoring mechanism by liberalizing open position limits of banks.

The focus of this thesis is on the employment of theoretical and practical quantile methods in addressing prediction, risk measurement and inference problems. From a prediction perspective, a problem of creating model-free prediction intervals for a future unobserved value of a random variable drawn from a sample distribution is considered. With the objective of reducing prediction coverage error, two common distribution transformation methods based on the normal and exponential distributions are presented and they are theoretically demonstrated to attain exact and error-free prediction intervals respectively. The second problem studied is that of estimation of expected shortfall via kernel smoothing. The goal here is to introduce methods that will reduce the estimation bias of expected shortfall. To this end, several one-step bias correction expected shortfall estimators are presented and investigated via simulation studies and compared with one-step estimators. The third problem is that of constructing simultaneous confidence bands for quantile regression functions when the predictor variables are constrained within a region is considered. In this context, a method is introduced that makes use of the asymmetric Laplace errors in conjunction with a simulation based algorithm to create confidence bands for quantile and interquantile regression functions. Furthermore, the simulation approach is extended to an ordinary least square framework to build simultaneous bands for quantiles functions of the classical regression model when the model errors are normally distributed and when this assumption is not fulfilled. Finally, attention is directed towards the construction of prediction intervals for realised volatility exploiting an alternative volatility estimator based on the difference of two extreme quantiles. The proposed approach makes use of AR-GARCH procedure in order to model time series of intraday quantiles and forecast intraday returns predictive distribution. Moreover, two simple adaptations of an existing model are also presented.

Thesis: Ph. D. in Environmental Chemistry, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references.
Organic aerosol is a central topic in environmental science due to its role in climate forcing and negative health effects. The transformation of organic species from primary gas phase emissions to secondary organic aerosol (SOA) is highly complex and poorly understood, proving difficult for even stateof- the-art computational models to predict. This thesis describes the in-depth characterization and redesign of a previously developed technique for the quantification of intermediate volatility organic compounds (IVOCs), which are compounds with saturation vapor pressures of 10³-10⁷ [mu]g/m³. This analytical technique, the thermal-desorption electron ionization mass spectrometer (TD-EIMS) provides a volatility separated, bulk measurement of IVOCs and will be used to investigate the primary emissions as well as production and evolution of IVOCs in a series of experiments described in this thesis. Primary emissions of IVOCs have been previously measured in vehicle exhaust and have been theorized as a significant precursor to secondary organic aerosol (SOA) in urban atmospheres. IVOCs are predominately emitted during cold start periods, but maintain a similar chemical composition across all engine states. As emissions controls have tightened, emissions of non-methane hydrocarbons and primary particulate matter have decreased, however emissions of IVOCs have only decreased significantly (as much as 80%) between the newest ULEV and SULEV emissions control tiers. Laboratory studies examining the atmospheric oxidation of common biogenic and anthropogenic SOA precursors in environmental "smog" chambers show different production and evolution profiles of IVOCs. The comparison of IVOCs measured by the TD-EIMS with other analytical techniques sampling in parallel show the TD-EIMS may detect a previously characterized fraction of carbon. Production of secondary low volatility organic compounds can also occur in low oxygen systems, such as in planetary atmospheres or in the process of soot formation. Ultraviolet light or heat can form radical hydrocarbon species, which, in low oxygen environments, will react with other hydrocarbon or radical species, undergoing oxidation by molecular growth. Particles made from ethane and ethylene are composed of very saturated compounds. The particles produced from the photolysis of acetylene are fundamentally different showing significantly larger molecule sizes and substantially higher degrees of unsaturation. The results from this thesis demonstrate measurements of the production and evolution of primary and secondary low volatility organic gases by new analytical techniques and provide a new insight to the complex chemical processes in the atmosphere leading to the production of secondary organic aerosol.
by Jonathan Pfeil Franklin.
Ph. D. in Environmental Chemistry

Diese Arbeit konzentriert sich auf die Lösung des Problems der Unsicherheitsmessung und ihrer Auswirkungen auf Geschäftsentscheidungen, wobei zwei Ziele verfolgt werden: Erstens die Entwicklung und Validierung robuster Modelle zur Quantifizierung der Unsicherheit, wobei insbesondere sowohl die etablierten statistischen Modelle als auch neu entwickelte maschinelle Lernwerkzeuge zum Einsatz kommen. Das zweite Ziel dreht sich um die industrielle Anwendung der vorgeschlagenen Modelle. Die Anwendung auf reale Fälle bei der Messung der Volatilität oder bei einer riskanten Entscheidung ist mit einem direkten und erheblichen Gewinn oder Verlust verbunden. Diese These begann mit der Untersuchung der impliziten Volatilität (IV) als Proxy für die Wahrnehmung der Unsicherheit von Anlegern für eine neue Klasse von Vermögenswerten - Kryptowährungen. Das zweite Papier konzentriert sich auf Methoden zur Identifizierung risikofreudiger Händler und nutzt die DNN-Infrastruktur, um das Risikoverhalten von Marktakteuren, das auf Unsicherheit beruht und diese aufrechterhält, weiter zu untersuchen. Das dritte Papier befasste sich mit dem herausfordernden Bestreben der Betrugserkennung 3 und bot das Entscheidungshilfe-modell, das eine genauere und interpretierbarere Bewertung der zur Prüfung eingereichten Finanzberichte ermöglichte. Angesichts der Bedeutung der Risikobewertung und der Erwartungen der Agenten für die wirtschaftliche Entwicklung und des Aufbaus der bestehenden Arbeiten von Baker (2016) bot das vierte Papier eine neuartige DL-NLP-basierte Methode zur Quantifizierung der wirtschaftspolitischen Unsicherheit. Die neuen Deep-Learning-basierten Lösungen bieten eine überlegene Leistung gegenüber bestehenden Ansätzen zur Quantifizierung und Erklärung wirtschaftlicher Unsicherheiten und ermöglichen genauere Prognosen, verbesserte Planungskapazitäten und geringere Risiken. Die angebotenen Anwendungsfälle bilden eine Plattform für die weitere Forschung.
This thesis focuses on solving the problem of uncertainty measurement and its impact on business decisions while pursuing two goals: first, develop and validate accurate and robust models for uncertainty quantification, employing both the well established statistical models and newly developed machine learning tools, with particular focus on deep learning. The second goal revolves around the industrial application of proposed models, applying them to real-world cases when measuring volatility or making a risky decision entails a direct and substantial gain or loss. This thesis started with the exploration of implied volatility (IV) as a proxy for investors' perception of uncertainty for a new class of assets - crypto-currencies. The second paper focused on methods to identify risk-loving traders and employed the DNN infrastructure for it to investigate further the risk-taking behavior of market actors that both stems from and perpetuates uncertainty. The third paper addressed the challenging endeavor of fraud detection and offered the decision support model that allowed a more accurate and interpretable evaluation of financial reports submitted for audit. Following the importance of risk assessment and agents' expectations in economic development and building on the existing works of Baker (2016) and their economic policy uncertainty (EPU) index, it offered a novel DL-NLP-based method for the quantification of economic policy uncertainty. In summary, this thesis offers insights that are highly relevant to both researchers and practitioners. The new deep learning-based solutions exhibit superior performance to existing approaches to quantify and explain economic uncertainty, allowing for more accurate forecasting, enhanced planning capacities, and mitigated risks. The offered use-cases provide a road-map for further development of the DL tools in practice and constitute a platform for further research.

The research presented in this thesis addresses different aspects of dynamic portfolio construction and portfolio risk measurement. It brings the research on dynamic portfolio optimization, replicating portfolio construction, dynamic portfolio risk measurement and volatility forecast together. The overall aim of this research is threefold. First, it is aimed to examine the portfolio construction and risk measurement performance of a broad set of volatility forecast and portfolio optimization model. Second, in an effort to improve their forecast accuracy and portfolio construction performance, it is aimed to propose new models or new formulations to the available models. Third, in order to enhance the replication performance of hedge fund returns, it is aimed to introduce a replication approach that has the potential to be used in numerous applications, in investment management. In order to achieve these aims, Chapter 2 addresses risk measurement in dynamic portfolio construction. In this chapter, further evidence on the use of multivariate conditional volatility models in hedge fund risk measurement and portfolio allocation is provided by using monthly returns of hedge fund strategy indices for the period 1990 to 2009. Building on Giamouridis and Vrontos (2007), a broad set of multivariate GARCH models, as well as, the simpler exponentially weighted moving average (EWMA) estimator of RiskMetrics (1996) are considered. It is found that, while multivariate GARCH models provide some improvements in portfolio performance over static models, they are generally dominated by the EWMA model. In particular, in addition to providing a better risk-adjusted performance, the EWMA model leads to dynamic allocation strategies that have a substantially lower turnover and could therefore be expected to involve lower transaction costs. Moreover, it is shown that these results are robust across the low - volatility and high-volatility sub-periods. Chapter 3 addresses optimization in dynamic portfolio construction. In this chapter, the advantages of introducing alternative optimization frameworks over the mean-variance framework in constructing hedge fund portfolios for a fund of funds. Using monthly return data of hedge fund strategy indices for the period 1990 to 2011, the standard mean-variance approach is compared with approaches based on CVaR, CDaR and Omega, for both conservative and aggressive hedge fund investors. In order to estimate portfolio CVaR, CDaR and Omega, a semi-parametric approach is proposed, in which first the marginal density of each hedge fund index is modelled using extreme value theory and the joint density of hedge fund index returns is constructed using a copula-based approach. Then hedge fund returns from this joint density are simulated in order to compute CVaR, CDaR and Omega. The semi-parametric approach is compared with the standard, non-parametric approach, in which the quantiles of the marginal density of portfolio returns are estimated empirically and used to compute CVaR, CDaR and Omega. Two main findings are reported. The first is that CVaR-, CDaR- and Omega-based optimization offers a significant improvement in terms of risk-adjusted portfolio performance over mean-variance optimization. The second is that, for all three risk measures, semi-parametric estimation of the optimal portfolio offers a very significant improvement over non-parametric estimation. The results are robust to as the choice of target return and the estimation period. Chapter 4 searches for improvements in portfolio risk measurement by addressing volatility forecast. In this chapter, two new univariate Markov regime switching models based on intraday range are introduced. A regime switching conditional volatility model is combined with a robust measure of volatility based on intraday range, in a framework for volatility forecasting. This chapter proposes a one-factor and a two-factor model that combine useful properties of range, regime switching, nonlinear filtration, and GARCH frameworks. Any incremental improvement in the performance of volatility forecasting is searched for by employing regime switching in a conditional volatility setting with enhanced information content on true volatility. Weekly S&P500 index data for 1982-2010 is used. Models are evaluated by using a number of volatility proxies, which approximate true integrated volatility. Forecast performance of the proposed models is compared to renowned return-based and range-based models, namely EWMA of Riskmetrics, hybrid EWMA of Harris and Yilmaz (2009), GARCH of Bollerslev (1988), CARR of Chou (2005), FIGARCH of Baillie et al. (1996) and MRSGARCH of Klaassen (2002). It is found that the proposed models produce more accurate out of sample forecasts, contain more information about true volatility and exhibit similar or better performance when used for value at risk comparison. Chapter 5 searches for improvements in risk measurement for a better dynamic portfolio construction. This chapter proposes multivariate versions of one and two factor MRSACR models introduced in the fourth chapter. In these models, useful properties of regime switching models, nonlinear filtration and range-based estimator are combined with a multivariate setting, based on static and dynamic correlation estimates. In comparing the out-of-sample forecast performance of these models, eminent return and range-based volatility models are employed as benchmark models. A hedge fund portfolio construction is conducted in order to investigate the out-of-sample portfolio performance of the proposed models. Also, the out-of-sample performance of each model is tested by using a number of statistical tests. In particular, a broad range of statistical tests and loss functions are utilized in evaluating the forecast performance of the variance covariance matrix of each portfolio. It is found that, in terms statistical test results, proposed models offer significant improvements in forecasting true volatility process, and, in terms of risk and return criteria employed, proposed models perform better than benchmark models. Proposed models construct hedge fund portfolios with higher risk-adjusted returns, lower tail risks, offer superior risk-return tradeoffs and better active management ratios. However, in most cases these improvements come at the expense of higher portfolio turnover and rebalancing expenses. Chapter 6 addresses the dynamic portfolio construction for a better hedge fund return replication and proposes a new approach. In this chapter, a method for hedge fund replication is proposed that uses a factor-based model supplemented with a series of risk and return constraints that implicitly target all the moments of the hedge fund return distribution. The approach is used to replicate the monthly returns of ten broad hedge fund strategy indices, using long-only positions in ten equity, bond, foreign exchange, and commodity indices, all of which can be traded using liquid, investible instruments such as futures, options and exchange traded funds. In out-of-sample tests, proposed approach provides an improvement over the pure factor-based model, offering a closer match to both the return performance and risk characteristics of the hedge fund strategy indices.

The drivers of human health and changing climate are important areas of environmental and atmospheric studies. Among many environmental factors present in our biosphere, small particles, also known as ultrafine particles or UFPs, have direct and indirect pathways to affect human health and climatic processes. The rapid change in their properties makes UFPs dynamic and often challenging to quantify their effect on health and radiative forcing. To reduce uncertainty in the climate effects of UFPs and to strengthen the evidence on health effects, accurate characterizations of physical and chemical properties of UFPs are needed. In this thesis, two broad aspects of UFPs were investigated: (1) the development of particle instrumentation to study particle properties; and (2) measurement of physical and chemical properties of UFPs relevant to human health and climate. These two broad aspects are divided into four specific aims in this thesis. The measurement of UFP concentration at different locations in an urban location, from roadside to various residential areas, can be improved by using a mobile particle counter. A TSI 3786 Condensation Particle Counter (CPC) was modified for mobile battery-power operation. This design provided high-frequency, one second time resolution measurements of particle number and carbon dioxide (CO2). An independent electric power system, a central controller and robust data acquisition system, and a GPS system are the major components of this mobile unit. These capabilities make the system remotely deployable, and also offer flexibility to integrate other analog and digital sensors. A Volatility Tandem Differential Mobility Analyzer (V-TDMA) system was designed and built to characterize the volatility behavior of UFPs. The physical and chemical properties of UFPs are often challenging to measure due to limited availability of instruments, detection limit in terms of particle size and concentration, and sampling frequency. Indirect methods such as V-TDMA are useful, for small mass (<1 µg/m3), and nuclei mode particles (<30nm). Another advantage of V-TDMA is its fast response in terms of sampling frequency. A secondary motivation for building a V-TDMA system was to improve instrumentation capability of our group, thus enabling study of kinetic and thermodynamic properties of novel aerosols. Chapter four describes the design detail of the built V-TDMA system, which measures the change in UFP size and concentration during heated and non-heated (or ambient) condition. The V-TDMA system has an acceptable penetration efficiency of 85% for 10 nm and maintains a uniform temperature profile in the heating system. Calibration of V-TDMA using ammonium sulfate particles indicated that the system produces comparable evaporation curves (in terms of volatilization temperature) or volatility profiles to other published V-TDMA designs. Additionally the system is fully programmable with respect to particle size, temperature and sampling frequency and can be run autonomously after initial set up. The thesis describes a part of yearlong study to provide a complete perspective on particle formation and growth in a rural and agricultural Midwestern site. Volatility characterizations of UFPs were conducted to enable inference about particle chemistry, and formation of low volatile core or evaporation resistant residue in the UFP in the Midwest. This study addresses identification of the volatility signature of particles in the UFP size range, quantification of physical differences of UFPs between NPF1 and non-NPF events and relation of evaporation resistant residue with particle size, seasonality and mixing state. K-means clustering was applied to determine three unique volatility clusters in 15, 30, 50 and 80 nm particle sizes. Based on the proposed average volatility, the identified volatility clusters were classified into high volatile, intermediate volatile and least volatile group. Although VFR alone is insufficient to establish chemical composition definitively, least volatile cluster based on average volatility may be characteristically similar to the pure ammonium sulfate. The amount of evaporation residue at 200 °C was positively correlated with particle size and showed significant correlation with ozone, sulfur dioxide and solar radiation. Residue also indicated the presence of external mixture, often during morning and night time. Air quality science and management of an accidental urban tire fire occurring in Iowa City in May and June of 2012 were investigated. Urban air quality emergencies near populated areas are difficult to evaluate without a proper air quality management and response system. To support the development of an appropriate air quality system, this thesis identified and created a rank for health-related acute and chronic compounds in the tire smoke. For health risk assessment, the study proposed an empirical equation for estimating multi-pollutant air quality index. Using mobile measurements and a dispersion model in conjunction with the proposed air quality index, smoke concentrations and likely health impact were evaluated for Iowa City and surrounding areas. It was concluded that the smoke levels reached unhealthy outdoor levels for sensitive groups out to distances of 3.1 km and 18 km at 24 h and 1h average times. Tire smoke characterization was another important aspect of this study which provided important and new information about tire smoke. Revised emission factors for coarse particle mass and aerosol-PAH and new emission factors and enhancement ratios values for a wide range of fine particulate mass, particle size (0.001-2.5 µm), and trace gas were estimated. Overall the thesis added new instrumentation in our research group to measure various physical properties such as size, concentration, and volatility UFP. The built instruments, data processing algorithm and visualization tools will be useful in estimation of accurate concentration and emission factors of UFP for health exposure studies, and generate a fast response measurement of kinetic and thermodynamics properties of ambient particles. This thesis also makes a strong case for the development of an air quality emergency system for accidental fires for urban location. It provides useful evaluation and estimation of many aspects of such system such as smoke characterization, method of air quality monitoring and impact assessment, and develops communicable method of exposure risk assessment.

The development of financial economics literature has been characterised by a continual dialogue between empirical and theoretical researchers. Often, this dialogue has taken the form of empirical observation prompting theoretical enquiry. This thesis follows this long tradition by investigating a number of emerging empirical facts, for which in most cases, simple theoretical explanations are suggested. Broadly speaking, this thesis investigates the manner in which the level of activity in an asset market influences the empirical features exhibited by the asset's returns. Motivated by these empirical observations reported in this thesis, theoretical models based on heterogeneous trader behaviour are suggested as explanations of these observations. A body of widely accepted empirical facts are first re-evaluated with reference to three representative equity indices. Features such as linear dependence in expected returns, dependence in the volatility of returns and negative correlation between returns and volatility innovations are found to be common characteristics of index returns. A number of authors have documented the emerging fact that the presence of non-linearity in returns is transitory in nature. A central issue of this thesis is to propose a rationale for this as yet unexplained phenomenon. Within a model of trader interaction, it is shown that the intensity of noise trading is critically important for the presence of nonlinear price outcomes. Increases in the intensity of noise trading are shown to extinguish non-linear structure in simulated returns. Analysis of index returns lends support to this notion in that periods of returns that exhibit more intense noise are associated with linearity. Issues relating to the accurate and efficient measurement of noise are discussed in detail. It is found that when dealing with stock returns, simple standard deviation of returns is a valid approximation to the intensity of noise in returns. As the presence of non-linearity in returns does not appear to be a persistent feature, the link between market activity and linear dependence in returns is also investigated. Using a similar model of trader interaction, it is shown that when the rate of news arrival is relatively low (high) strong (weak) positive autocorrelations are detected. Broadly consistent patterns are also detected in index returns, supporting the notion that news influences the behavioural patterns of investors and thus observed structure in returns. Another emerging empirical fact documented in this thesis is the manner in which the intensity of noise in returns influences dependence in the volatility of returns. An accepted feature of the dependence in volatility is that an asymmetry exists between returns and volatility innovations. It is shown here that during periods where the intensity of noise in returns is relatively high, this asymmetrical effect becomes more pronounced. While no formal explanation of this observation is suggested, this exercise has followed in the tradition of much research in investigating empirical phenomena as a first step in expanding our understanding of asset markets. The results reported throughout this thesis are important from two perspectives. First, they expand upon our knowledge of the empirical features of asset returns in that emerging facts are re-evaluated and new facts documented. Second, given the theoretical explanations proposed for these observations, insights into the behavioural mechanisms generating returns are also revealed.

Assignment (MComm)--Stellenbosch University, 2005.
ENGLISH ABSTRACT: Volatilty was originally seen to be constant and deterministic, but it was later realised that return series are non-stationary. Owing to this non-stationarity nature of returns, there were no reliable ex-post volatility measurements. Subsequently, researchers focussed on ex-ante volatility models. It was only then realised that before good volatility models can be created, reliable ex-post volatility measuremetns need to be defined. In this study we examine non-parametric ex-post volatility measurements in order to obtain approximations of the variances of non-stationary return series. A detailed mathematical derivation and discussion of the already developed volatility measurements, in particular the realised volatility- and DST measurements, are given In theory, the higher the sample frequency of returns is, the more accurate the measurements are. These volatility measurements referred to above, however, all have short-comings in that the realised volatility fails if the sample frequency becomes to high owing to microstructure effects. On the other hand, the DST measurement cannot handle changing instantaneous volatility. In this study we introduce a new volatility measurement, termed microstructure realised volatility, that overcomes these shortcomings. This measurement, as with realised volatility, is based on quadratic variation theory, but the underlying return model is more realistic.
AFRIKAANSE OPSOMMING: Volatiliteit is oorspronklik as konstant en deterministies beskou, dit was eers later dat besef is dat opbrengste nie-stasionêr is. Betroubare volatiliteits metings was nie beskikbaar nie weens die nie-stasionêre aard van opbrengste. Daarom het navorsers gefokus op vooruitskattingvolatiliteits modelle. Dit was eers op hierdie stadium dat navorsers besef het dat die definieering van betroubare volatiliteit metings 'n voorvereiste is vir die skepping van goeie vooruitskattings modelle. Nie-parametriese volatiliteit metings word in hierdie studie ondersoek om sodoende benaderings van die variansies van die nie-stasionêre opbrengste reeks te beraam. 'n Gedetaileerde wiskundige afleiding en bespreking van bestaande volatiliteits metings, spesifiek gerealiseerde volatiliteit en DST- metings, word gegee. In teorie salopbrengste wat meer dikwels waargeneem word tot beter akkuraatheid lei. Bogenoemde volatilitieits metings het egter tekortkominge aangesien gerealiseerde volatiliteit faal wanneer dit te hoog raak, weens mikrostruktuur effekte. Aan die ander kant kan die DST meting nie veranderlike oombliklike volatilitiet hanteer nie. Ons stel in hierdie studie 'n nuwe volatilitieits meting bekend, naamlik mikro-struktuur gerealiseerde volatiliteit, wat nie hierdie tekortkominge het nie. Net soos met gerealiseerde volatiliteit sal hierdie meting gebaseer wees op kwadratiese variasie teorie, maar die onderliggende opbrengste model is meer realisties.

Few studies have examined the impact of portfolio concentration upon the realised volatility of stock index portfolios, such as the FTSE 100. Instead, previous research has focused upon diversification across industries, across geographic regions and across different firms. The present study addresses this imbalance by calculating the daily time series of four concentration metrics for the FTSE 100 Index over the period from January 1984 through March 2003. In addition, the value weighted variance covariance matrix (VCM) of daily FTSE 100 Index constituent returns is decomposed into four sub-components: two from the diagonal elements and two from the off-diagonal elements of the VCM. These consist of the average variance of constituent returns, represented by the sum of diagonal elements in the VCM, and the average covariance represented by the sum of off-diagonal elements in the VCM. The value weighted average variance (VAV) and covariance (VAC) are each subdivided into the equally weighted average variance (EAV) the equally weighted average covariance (EAC) and incremental components that represent the difference between the respective value-weighted and equally weighted averages. These are referred to as the incremental average variance (IAV) and the incremental average covariance (IAC) respectively. The incremental average variance and the incremental average covariance are then combined, additively, to produce the incremental realised variance (IRV) of the FTSE 100 Index. The incremental average covariance and the incremental realised variance are found to be negative during the 1987 crash and the 1992 ERM crisis. They are also negative for a substantial part of the study period, even when concentration was at its highest level. Hence the findings of the study are consistent with the notion that the value weighted, and hence concentrated, FTSE 100 Index portfolio is generally less risky than a hypothetical equally weighted portfolio of FTSE 100 Index constituents. Furthermore, increases in concentration tend to precede decreases in incremental realised volatility and increases in the equally weighted components of the realised VCM. The results have important implications for portfolio managers concerned with the effect of changing portfolio weights upon portfolio volatility. They are also relevant to passive investors concerned about the effects of increased concentration upon their benchmark indices, and to providers of stock market indices.

Approved for public release; distribution is unlimited
Inappropriate and/or duplicate IT systems results in a severe drain on resources. Identifying the development of low utility and duplicate systems allows for the redirection of resources with higher and unique returns. Volatility measurements allow systems to be compared to determine the gains over prior iterations along with aiding in determining which options to exercise for future systems. The decision maker of an organization must be able to monitor how IT systems are functioning and hold program managers and developers accountable for improving efficiency, timeliness, and accuracy of the information being gather and processed. Volatility measurements take consideration of all factors and give a baseline from which the IT manager can make decisions across systems. The additional capabilities provided by volatility measurements will go a long way in strengthening IT investments, the performance review of those systems, and provides the additional information needed to forecast and compare systems in order to make better decisions.

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Este trabalho analisa o desempenho fora da amostra de carteiras de mínima variância e baixa volatilidade no mercado de ações brasileiro entre 2003 e 2013, comparativamente ao índice IBOVESPA e a uma carteira igualmente ponderada. As carteiras de mínima variância foram otimizadas com restrição de posições vendidas e limite de peso para os ativos. A matriz de covariância foi estimada pelo método amostral e método shrinkage proposto por Ledoit e Wolf (2003). A carteira de baixa volatilidade foi estruturada de forma similar ao método do índice S&P 500 Low Volatility. O período utilizado para o rebalanceamento das carteiras foi quadrimestral e os ativos elegíveis para as carteiras foram os componentes do IBOVESPA em cada quadrimestre analisado. A comparação das carteiras foi feita através dos indicadores de retorno, desvio padrão e índice de Sharpe anualizados, MVaR e maximum drawdown. Os resultados apontam para a importância na escolha do limite de pesos para os ativos das carteiras de mínima variância. As carteiras de menor risco obtiveram os melhores resultados em todos os indicadores testados.
This study analyzes the out-of-sample performance of minimum-variance and low volatility portfolios in the Brazilian stock market from 2003 to 2013, when compared to IBOVESPA index and an equally weighted portfolio. The minimum variance portfolios have been optimized with short selling restriction and weight limits for the assets. The covariance matrix was estimated by sample method and shrinkage method proposed by Ledoit & Wolf (2003). The low volatility portfolio was structured in a similar way to the S&P 500 Low Volatility index method. The portfolios rebalancing period were quarterly and the eligible assets for the portfolios were IBOVESPA components in each analyzed period. The portfolios performance was evaluated through indicators such return, standard deviation, Sharpe ratio, maximum drawdown and MVAR indicators. The results point to the importance in choosing the weight limits for the assets of minimum-variance portfolios. Lower risk portfolios delivered the best results in all tested indicators.

Thesis (Ph.D.)--Cleveland State University, 2008
Abstract. Includes bibliographical references (p. 110-111). Electronic full text release has been delayed at the author's request until December 31, 2010.

Cette thèse analyse, d’un point de vue empirique et théorique, la procyclicité des mesures de risque sur les données historiques, i.e. l'effet de surestimation du risque futur en temps de crise, et sa sous-estimation en temps normal. Nous développons une méthodologie pour évaluer empiriquement le degré de procyclicité, en introduisant un processus de quantiles (« Value-at-Risk ») historiques pour mesurer le risque. En appliquant cette procédure à 11 indices boursiers, nous identifions deux facteurs expliquant la procyclicité : le « clustering » et le retour à la moyenne de la volatilité (tel que modélisée par un GARCH(1,1)), mais aussi la façon intrinsèque d'estimer le risque sur des données historiques (même en l'absence de dynamique de la volatilité). Pour confirmer théoriquement ces arguments, nous procédons en deux étapes. Premièrement, nous démontrons des théorèmes bivariés (fonctionnels) de limite centrale pour les estimateurs de quantiles avec différents estimateurs de dispersion. Comme modèles de base, nous considérons les suites de variables aléatoires iid, ainsi que la classe des processus GARCH(p,q) augmentés. Enfin, ces résultats asymptotiques permettent de valider théoriquement la procyclicité observée empiriquement. Généralisant cette étude à d’autres mesures de risque et de dispersion, nous concluons que la procyclicité persistera quel que soit le choix de ces mesures
This thesis examines, empirically and theoretically, the pro-cyclicality of risk measurements made on historical data. Namely, the effect that risk measurements overestimate the future risk in times of crisis, while underestimating it in quiet times. As starting point, we lay down a methodology to empirically evaluate the amount of pro-cyclicality when using a sample quantile (Value-at-Risk) process to measure risk. Applying this procedure to 11 stock indices, we identify two factors explaining the pro-cyclical behavior: The clustering and return-to-the-mean of volatility (as modeled by a GARCH(1,1)) and the very way of estimating risk on historical data (even when no volatility dynamics are present). To confirm these claims theoretically, we proceed in two steps. First, we derive bivariate (functional) central limit theorems for quantile estimators with different measure of dispersion estimators. We establish them for sequences of iid random variables as well as for the class of augmented GARCH(p,q) processes. Then, we use these asymptotics to theoretically prove the pro-cyclicality observed empirically. Extending the setting of the empirical study, we show that no matter the choice of risk measure (estimator), measure of dispersion estimator or underlying model considered, pro-cyclicality will always exist

Cette thèse par essais a pour objectif de contribuer à une meilleure compréhension de la transmission au marché alimentaire des chocs provenant des marchés financier et énergétique. Le premier essai étudie l’efficience du marché alimentaire. Le deuxième essai examine les transmissions de rendements et de volatilités entre les trois marchés. Quant au troisième essai, il s’intéresse à l’analyse de la dépendance extrême entre ces marchés. Nos principaux résultats permettent de souligner l’impact de la crise financière de 2007-2008 et la financiarisation des marchés de commodités dans l’intensification aussi bien des transmissions de volatilités et de prix que des dépendances (notamment les dépendances de queue) entre ces marchés. Ils permettent également de souligner l’efficacité de la couverture du risque par la construction de portefeuilles diversifiés incluant les commodités alimentaires
The aim of this three essays thesis is to contribute to a better understanding of the transmission of shocks from energy and financial markets to food market commodities. The first essay investigates the efficiency of food market. The second essay studies returns and volatilities transmission between the three markets. Extreme dependence between these markets is analyzed in the third essay. Our main results underline the impact of the 2007-2008 financial crisis in the intensification of returns and volatilities spillovers between these markets as well as tail dependencies (namely tail dependencies). They allow also underlining hedge effectiveness by the construction of diversified portfolios including food commodities

Measurement of volatility spillovers and asymmetric connectedness on commodity and equity markets Tereza Malířová Master's Thesis, IES FSV UK, July 2017 We study volatility spillovers among commodity and equity markets by employing a recently developed approach based on realized measures and forecast error variance decomposition invariant to the variable ordering from vector-autoregressions. This enables us to measure total, directional and net volatility spillovers as well as the asymmetry of responses to positive and negative shocks. We exploit high-frequency data on the prices of Crude oil, Corn, Cotton and Gold futures, and the S&P 500 Index and use a sample which spans from January 2002 to December 2015 to cover the entire period around the global financial crisis of 2008. Our empirical analysis reveals that on average, the volatility shocks related to other markets account for around one fifth of the volatility forecast error variance. We find that shocks to the stock markets play the most important role as the S&P 500 Index dominates all commodities in terms of general volatility spillover transmission. Our results further suggest that volatility spillovers across the analyzed assets were rather limited before the global financial crisis, which then boosted the connectedness between commodity and stock...

This dissertation is a study on volatility measurement of Foreign exchange market in India using GARCH model. This study includes an overview of Indian Foreign exchange market and its position with respect to global Forex market .Regimes of Indian foreign exchange market have been studied to bring out the impact of high volatility on the foreign trade and economic growth in India .The periods of high volatility have causes a substantial decrease in foreign trade and economic activity in the country emphasizing the importance to forecast volatility so that the competent authority can take corrective measures to check high volatility. Different models that had been used to forecast volatility by researchers have been summarized in the literature review. Also in the literature review have been analyzed that GARCH model gives more accurate results in forecasting volatility than the other available models. The objectives of this study are to (a) Summarize different models available for forecasting volatility (b) Forecast volatility of Indian foreign exchange market using GARCH model Vast literature on the subject of volatility measurement of Forex have justified that volatility can be expressed as conditional variance and time series data modeling can be used to measure volatility. Some models use standard deviation to predict volatility that gives biased results. GARCH model use conditional variance and many researchers have studied the accuracy of volatility measurement using GARCH model in other foreign countries and found that it gives satisfactory results with the use of constraints of stationarity. A number of different types of GARCH models have been developed for improving the accuracy of volatility forecast. INR and USD currency pair data from January 2007-January 2017 is used for this study as it is the currency pair in which major part of foreign exchange trading in India is done. Analysis of volatility forecast by GARCH model shows that although the errors are not normally distributed but the estimators of volatility are consistent and GARCH model can be satisfactorily used for volatility forecast of Indian foreign exchange market

This dissertation studies volatility measurement and modeling issues when asset prices are subject to price limits based on Bayesian approaches. Two types of estimators are developed to consistently estimate integrated volatility in the presence of price limits. One is a realized volatility type estimator, but using both realized asset prices and simulated asset prices. The other is a discrete sample analogue of integrated volatility using posterior samples of the latent volatility states. These two types of estimators are first constructed based on the simple log-stochastic volatility model in Chapter 2. The simple log-stochastic volatility framework is extended in Chapter 3 to incorporate correlated innovations and further extended in Chapter 4 to accommodate jumps and fat-tailed innovations. For each framework, a MCMC algorithm is designed to simulate the unobserved asset prices, model parameters and latent states. Performances of both type estimators are also examined using simulations under each framework. Applications to Chinese stock markets are also provided.
Thesis (Ph.D, Economics) -- Queen's University, 2014-01-22 10:29:12.507

碩士
國立高雄第一科技大學
金融營運所
95
This study is using the model of implied volatility model of Chicago Board Option Exchange to construct the implied volatility index of Taiwan’s option market. We hope the implied volatility index of Taiwan’s option market can provide more information to analyze for the investor to trade. In order to make the accuracy better, we try to do some change on the underlying assets in the model. We Use Taiwan’s Future Index to be the underlying assets. According this, we construct the new implied volatility index of Taiwan’s option market. The results show that calculates the implied volatility of Taiwan’s option market that uses Taiwan’s Future Index to be the underlying assets is better than the TAIEX in the same model. The new implied volatility of Taiwan’s that uses Taiwan’s Future Index to be the underlying assets have a better ability to explain and forecast the change about the index in the future. In the recent years there is more and more major security markets in the world are developing in the implied volatility index area. How to use the method we use now and provide it or studying the new way to get better data of the implied volatility index to the inventors for trading will be the major subject in the market.

碩士
中國醫藥大學
職業安全與衛生學系碩士班
101
Ambient ultrafine particles (diameters < 100 nm) are chemically complex mixtures. Because of their small sizes, these particles have little mass and evolve rapidly in ambient air, thus making the measurements of their physicochemical properties a major technical challenge. Nevertheless, as different chemicals exhibit different volatility, direct measurements of the particle volatility could allow us to infer particle’s chemical composition and mixing state. With that in mind, the aims of this study were to develop a volatility tandem mobility analyzer (V-TDMA) system for measuring ultrafine particles’ volatility, to apply the system for assessing the size-dependent volatility as a function of time, and to identify the relative volume fractions of different volatile components. The developed V-TDMA system includes a TDMA that selects and measures the particle size, a thermodenuder that thermally desorbs volatile compounds from the particles at three different temperatures (26°C, 100°C and 320°C) and then removes them from the gas stream, and a scanning mobility particle sizer and condensation particle counter that measures the number size distribution of particles between 5.5-350 nm. The measurement results were subsequently used for the estimation of particle shrinkage factor (SF) and volatile volume fraction (VF). A series of quality assurance and quality control measures were taken to characterize the temperature profile, particle losses, sizing precision/accuracy, and volatile particle removal efficiency of the V-TDMA system. The test results suggest that the performance of the V-TDMA system is inline with earlier work. In the field application, the results show that the particle volatility under different temperature was strongly dependent on the particle size but showed little temporal patterns. Overall, the results indicate that ultrafine particles mainly consist of low-volatile compounds and the remaining of minor non-volatile and high-volatile compounds; however, the nucleation mode particles could consist a notable amount of high-volatile compounds.

This dissertation is based on the hypothesis that a third dimension, namely investment time horizon, can add value to the more conventional two-dimensional methodology of assessing the relative risk and return attributes of various assets and portfolios in order to enhance investment decisions. This study shows that time horizons should be considered in the investment decision making process and provides concrete evidence that a methodology that is not cognizant of investment time horizon is prone to extensive long-term opportunity cost risk. In addition to providing evidence of investment time horizon relevance, the study makes suggestions as to how time horizons could be incorporated into the risk return assessments of various asset classes and also presents a framework for the more holistic assessment of asset class properties while incorporating time horizons.
Business Management
Thesis (M. Com. (Business Management))

The Aerosol Mass Spectroscopy (AMS) is a recently developed method that provides on-line measurements of the chemical composition, mass spectrum and mass distributions of the atmospheric aerosol. Using the AMS with a thermodenuder in smog chamber experiments of ozonolysis of α-pinene, β-pinene and limonene, the mass spectrum of the secondary organic aerosols (SOA) is deconvoluted in low, medium and high volatility mass spectra. The spectrum of the surrogate component with the lower volatility for α-pinene and β-pinene is quite similar to that of ambient oxygenated organic aerosol (OOA). This could explain part of the difference between the AMS mass spectrum in the lab and the field. Combining an AMS and a Scanning Mobility Particle Sizer (SMPS) in smog chamber experiments of α-pinene, β-pinene and limonene ozonolysis, the density of the SOA is calculated and estimated between 1.4 and 1.65 g cm-3. This high density implies that the SOA is likely in a solid or a waxy state. The method is applied on field measurements at Finokalia, Crete during the FAME. For the summer campaign (FAME-08) the organic density is in the range of 0.8 and 1.8 g cm-3 with a mean value of 1.35±0.22 g cm-3¬, while for the winter (FAME-09) the average organic density is 1.14±0.36 g cm-3. This technique can also calculate the Collection Efficiency (CE) of the AMS, since AMS does not measure all the particles that enter the instrument. Applying the estimated CE, the AMS is in a good agreement with other instrumentation. The CE and the organic density of the thermodenuded samples are calculated as well. The CE and the organic density both for the ambient and the themodenuded samples are used as post corrections in the volatility estimation. For FAME-08 the organic aerosol is one order of magnitude less volatile than laboratory-generated α-pinene SOA. Furthermore they are highly oxidized due to the photochemistry conditions (especially in the summer) and the station location (away from detectable sources of pollution). Finally, modifying the steam-jet aerosol collector (SJAC) method both particulate and gas phase of the main inorganic species can be measured. Testing the approach at ambient conditions at the ICE-FORTH Institute, we were able to measure together with the inorganic aerosol composition the gas-phase concentrations of NH3, HONO and very low HNO¬3. The results are consistent with the predictions of the thermodynamic model ISORROPIA.
Τα αεροζόλ είναι σωματίδια που αιωρούνται στην ατμόσφαιρα. Η Φασματομετρία Μάζας Αεροζόλ (AMS) είναι μία νέα μέθοδος που μπορεί να δώσει ταυτόχρονα και σε πραγματικό χρόνο τη χημική σύσταση, το φάσμα μάζας και τις κατανομές μάζας των ατμοσφαιρικών σωματιδίων. Χρησιμοποιώντας το AMS με έναν θερμικό απογυμνωτή σε πειράματα οζονόλυσης α-πινενίου, β-πινενίου και λεμονενίου σε περιβαλλοντικό θάλαμο, το φάσμα μάζας των δευτερογενών οργανικών σωματιδίων (SOΑ) αναλύεται σε 3 επιμέρους φάσματα, ανάλογα με την πτητικότητα των οργανικών σωματιδίων. Το φάσμα που αντιστοιχεί στις ενώσεις με τη χαμηλότερη πτητικότητα για το α- και β-πινένιο είναι αρκετά όμοιο με αυτό των οξυγονωμένων οργανικών σωματιδίων (ΟΟΑ) από το περιβάλλον. Αυτό εξηγεί και μέρος της διαφοράς του φάσματος μάζας AMS μεταξύ εργαστηρίου και πεδίου. Συνδυάζοντας το AMS με ένα σαρωτή μεγέθους κινούμενων σωματιδίων (SMPS) υπολογίζεται η πυκνότητα των SOA από οζονόλυση α-πινενίου, β-πινενίου και λεμονενίου μεταξύ 1.4 και 1.65 g cm-3. Η σχετικά υψηλή τιμή της πυκνότητας μάλλον σημαίνει ότι τα παραγόμενα σωματίδια είναι στερεά ή κερώδη.Η παραπάνω μέθοδος εφαρμόζεται σε μετρήσεις πεδίου στη Φινοκαλιά, στην Κρήτη (FAME). Για το FAME-08 (καλοκαίρι) η πυκνότητα των οργανικών σωματιδίων είναι μεταξύ 0.8 και 1.8 g cm-3 με μέση τιμή 1.35±0.22 g cm-3, ενώ για το FAME-09 (χειμώνας) η μέση τιμή είναι 1.14±0.36 g cm-3. Η τεχνική αυτή υπολογίζει και το ποσοστό συλλογής (CE) σωματιδίων του AMS, καθώς το AMS μετράει ένα ποσοστό αυτών. Εφαρμόζοντας την CE που υπολογίζεται, η συμφωνία μεταξύ του AMS και άλλων οργάνων είναι αρκετά καλή. Υπολογίζεται επίσης η CE και η πυκνότητα των οργανικών για τα δείγματα που έχουν θερμανθεί στον θερμικό απογυμνωτή. Οι CE και οι οργανικές πυκνότητες χρησιμοποιούνται ως διορθώσεις για την αποφυγή υποεκτίμησης της πτητικότητας του οργανικού αεροζόλ. Για το FAME-08 οι οργανικές ενώσεις είναι περισσότερο από μία τάξη μεγέθους λιγότερο πτητικές από τα SOA που δημιουργούνται σε συνθήκες εργαστηρίου. Επίσης είναι υψηλά οξειδωμένες λόγω της φωτοχημείας (καλοκαίρι) και της τοποθεσίας της δειγματοληψίας (μακριά από πρωτογενείς ρύπους). Τέλος τροποποιώντας τη μέθοδο δειγματοληψίας υγροποιημένων σωματιδίων (SJAC) είναι δυνατό να μετρηθεί και η σωματιδιακή αλλά και η αέρια φάση των κυρίως ανόργανων ενώσεων. Πειράματα που έγιναν από δειγματοληψία στο ΕΙΧΗΜΥΘ δείχνουν την ύπαρξη ΝΗ3 αλλά σχεδόν μηδενικού ΗΝΟ3. Τα αποτελέσματα συγκρίνονται με ένα θερμοδυναμικό μοντέλο (ISΟRROPIA) και η συμφωνία είναι καλή.

A new experimental methodology was developed to measure the non-volatile particle number concentration, using a thermodenuder (TD). The TD was coupled with a high resolution time-of-flight aerosol mass spectrometer, measuring the chemical composition and mass size distribution of the submicrometer aerosol and a scanning mobility particle sizer (SMPS) that provided the number size distribution of the aerosol in the range from 10 to 500 nm. The method was evaluated with a set of smog chamber experiments and achieved almost complete evaporation (98 %) of secondary organic aerosol (SOA) as well as freshly nucleated particles, using the TD temperature of 400 C. This experimental approach was applied in a winter field campaign in Athens and provided a direct measurement of non-volatile particles from major pollution sources. During periods in which the contribution of biomass burning sources was dominant, more than 80% of the particles survived the intense heating, suggesting that nearly all biomass burning particles had a non-volatile core. These particles consisted mostly from black carbon (BC), while organic aerosol (OA) were responsible for another 40 %. Organics that survived through the TD were mostly biomass burning OA (BBOA) and oxygenated OA (OOA) that had not evaporated, contributing 90% of the organic mass concentration, while the other 10% was hydrocarbon-like OA (HOA) and cooking OA (COA). For periods that traffic contribution was dominant, mostly during the rush hour, 50-60% of the particles had a non-volatile core, while the rest evaporated at 400 0C. The remaining particles consisted mostly from BC, with an 80% contribution, while organics were responsible for another 15-20 %. Organics were mostly HOA and OOA, with a contribution of >95% to the organic mass concentration, while <5% was from BBOA and COA.
Μια νέα πειραματική μεθοδολογία αναπτύχθηκε για τη μέτρηση της συγκέντρωσης αριθμού μη πτητικών σωματιδίων, χρησιμοποιώντας εναν θερμοαπογυμνωτή. Ο θερμοαπογυμνωτής ήταν συζευγμένος με ένα υψηλής-ανάλυσης χρόνου-πτήσης φασματόμετρο μάζας (HR-ToF-AMS), το οποίο μετρούσε τη χημική σύσταση και τη κατανομή μεγέθους μάζας των υπο-μικρομέτρου αεροζόλ και ένα σαρωτή κινητικότητας μεγέθους σωματιδίων (SMPS) που παρείχε τη κατανομή μεγέθους αριθμού των αεροζόλ στο εύρος απο 10 έως 500 nm. Η μέθοδος αξιολογήθηκε με μια σειρά πειραμάτων σε θάλαμο προσομοίωσης ατμόσφαιρας και πέτυχε σχεδόν πλήρη εξάτμιση (98 %) των δευτερογενών οργανικών αεροζόλ (SOA), καθώς και φρέσκων σωματιδίων προερχόμενων απο πυρηνογένεση, χρησιμοποιώντας το θερμοαπογυμνωτή στη θερμοκρασία των 400 °C. Αυτή η πειραματική προσέγγιση εφαρμόστηκε σε μια χειμερινή καμπάνια πεδίου στην Αθήνα και παρείχε μια άμεση μέτρηση των μη πτητικών σωματιδίων απο τις κύριες πηγές ρύπανσης. Κατά τη διάρκεια περιόδων όπου η συνεισφορά των πηγών καύσης βιομάζας ήταν κυρίαρχη, περισσότερο απο 80 % των σωματιδίων επέζησαν απο την έντονη θέρμανση, γεγονός που υποδηλώνει ότι σχεδόν όλα τα σωματίδια καύσης βιομάζας είχαν μη πτητικό πυρήνα. Αυτά τα σωματίδια αποτελούνταν ως επί το πλείστον από μαύρο άνθρακα (BC), ενώ τα οργανικά αεροζόλ (ΟΑ) ήταν υπεύθυνα για το υπόλοιπο 40 %. Τα οργανικά που επιβίωσαν έπειτα απο τη διέλευση τους απο το θερμοαπογυμνωτή ήταν κυρίως απο καύση βιομάζας (ΒΒΟΑ) και οξυγωνομένα ΟΑ (ΟΟΑ), συμβάλλοντας στο 90 % της συγκέντρωσης οργανικής μάζας, ενώ το υπόλοιπο 10 % ήταν οργανικοί υδρογονάνθρακες (ΗΟΑ) και οργανικά αεροζόλ προερχόμενα από μαγείρεμα (COA). Για τις περιόδους όπου η συμβολή της κυκλοφορίας ήταν κυρίαρχη, κυρίως κατά τη διάρκεια ωρών αιχμής, 50 έως 60 % των σωματιδίων είχαν μη πτητικό πυρήνα, ενώ τα υπόλοιπα εξατμίστηκαν στους 400 °C. Τα υπολοίποντα σωματίδια αποτελούνταν κυρίως από BC, με 80 % συνεισφορά, ενώ τα οργανικά ήταν υπεύθυνα για το 15 με 20 % της συγκέντρωσης μάζας. Τα οργανικά αποτελούνταν από ΗΟΑ και OOA, με μια συμβολή > 95 % στη συγκέντρωση οργανικής μάζας, ενώ < 5 % ήταν από BBOA και COA.

The aim of this research is to show the effects of financial liberalisation on emerging market economies, how these economies removed restrictions on financial institutions so that they can be globally integrated, and to show the flow of international finance in and out of a country. This research also illustrates how the financial system in these economies moved from being government-led to being market-led. The main finding of this research is that many countries failed to reap the benefits of liberalisation because of weaknesses in the regulatory structure, undercapitalised banks, volatile markets and contagion effects. The research concludes that the long-term gains of liberalisation certainly supersede short-term instability of liberalisation. Thus, for financial liberalisation to have predominantly positive effects, attention should be drawn to the importance of a more prudent regulatory and supervisory environment. Furthermore, financial liberalisation must be accompanied by a sound institutional infrastructure, proper conduct of monetary and fiscal policies, a reduction in corruption, and an increase in transparency. In addition, liberalisation should be a gradual process whereby the right measures are taken in the right sequence.
Economics
M. Comm. (Economics)

La présente étude offre un panorama sur les interactions et les liens qui existent entre la volatilité des taux de change et les échanges internationaux. L’objectif de ce travail est donc de présenter théoriquement cette relation, puis d’examiner empiriquement l’existence de cette relation de causalité entre le commerce international et la variabilité des taux de change. La littérature portant sur la question se considère dans l'ensemble comme contradictoire et supporte plusieurs controverses qui ne nous permettent pas de conclure clairement quant à la relation en question. Nous essayerons de pousser ces recherches un peu plus loin en réexaminant cette évidence pour le canada et en offrant une investigation empirique sur l’existence éventuelle d'un impact significatif de la volatilité sur les flux désagrégées des exportations sectoriels du canada vers son partenaire, les États-Unis. Nous y examinons la réponse empirique de 5 secteurs d’exportations canadiennes aux variations du taux de change réel effectif entre le canada et les États- Unis. Toutefois, nos résultats obtenus ne nous permettent pas de conclure quant à la significativité relative d’un impact de volatilité de taux de change sur les exportations sectoriels désagrégées destinées aux États-Unis. Dans l’ensemble, même si on admet que les signe des coefficients estimés de la variable de risque dans chaque secteur est négatif, nous arrivons à la conclusion que la volatilité ne semble pas avoir un impact statistiquement significatif sur le volume réelle des exportations du Canada vers les États-Unis.
This study provides an overview on the interactions and linkages between the volatility of exchange rates and international trade. The objective of this work is to present this relationship theoretically and examine, empirically the existence of this causal relationship between international trade and exchange rate variability. The literature on the subject considers himself across as contradictory and supports several controversies that do not allow the clear conclusion about the relationship in question. We try to push this research a step further by reviewing the evidence for Canada and providing an empirical investigation on the possible existence of a significant impact of volatility on sectoral disaggregated flows of Canadian exports to its trading partner, the United States. We empirically examine the response of five sectors of Canadian exports to changes in real effective exchange rate between Canada and the United States. However, our results do not allow us to conclude about the significance of an impact on volatility of exchange rates on disaggregated sectoral exports to United States. Overall, even if we admit that the sign of the estimated coefficients of the exchange risk variable in each sector is negative, we reach the conclusion that the volatility does not seem to have a statistically significant impact on the real volume of exports from Canada to the United States.