In this thesis, we analyze volatility spillovers between crude oil and food commodities. The principal hypothesis assumes crude oil to behave as a production factor of the agricultural food commodities, thence we are looking for appropriate price effects. We mainly employ wavelet coherence and partial wavelet coherence, which provide us with valuable insight into the commodities nexus, without any strict restraints and assumptions levied on our data. Secondly, we build a DCC-GARCH model in order to model the presumed volatility spillovers. We also perform several simple benchmark analyses, in particular we test for Granger causality and we compute the Pearson correlation coefficients. Our data sample, including 10 commodities and 2 indices, covers the latest decade, significantly widening the existing contextual literature. Our results are mostly compliant with related literature, especially regarding the crude oil-fuels bundle and food commodities bundle, respectively. Considering the main research question of volatility spillovers between food commodities and crude oil, our results are indicating reasonably strong relationships with crude oil for soybeans and corn, leaving cotton and wheat rather on the verge of strong relationship and finding cattle to be completely unrelated. Main merits of the thesis...

Financialization of crude oil and its frequent inclusion into investment portfo- lios raise the demand for proper correlation estimates of this commodity and other financial assets. This thesis particularly examines the co-movement of crude oil price with prices of four other representatives of commodity market (gasoline, natural gas, gold and Industrials Index). It contributes to the exist- ing literature by the results obtained from application of wavelet coherence, which allows uncovering dynamics of interconnection between commodity prices in time as well as over different frequencies. Analysis brings many in- teresting findings and practical implications. Among others, it specifies the investment horizons that should be considered to maximize diversification properties of studied commodities. 1

This thesis examines an impact of high frequency trading on equity market qualities. As an indicator of market quality, stock prices realized volatility is used. To estimate the high frequency trading activity, we implement a special method of identification of high frequency orders from quote data. Study of relation between high frequency trading and market qualities is incited by growing concerns about the welfare impacts of high frequency trading and connected activities. In order to test the dependence and causality between high frequency trading activity and volatility, we implement time-scale estimation techniques. Wavelet coherence is used to study localized dependence. The analysis is amended by a robustness check, using wavelet correlation. Results show inconsistent dependence at short trading horizons and regions of significant continuous dependence at trading horizons within hours. Powered by TCPDF (www.tcpdf.org)

Twelve years after Satoshi Nakamoto published the paper describing the functioning mechanism and principals of cryptocurrency that maintains secure and anonymous digital transactions beyond any banks, cryptocurrencies have become a multi-billion-dollar industry comprising millions of investors, miners, developers and profiteers. However, the actual price determinants and ways to forecast future price changes remain an open question yet to discover the answer for. This study attempts to figure out whether media hype exerts that much influence upon cryptocurrencies price movements and whether it can be used as the basis for future movements prediction. Two cryptocurrencies, Bitcoin and Tezos, and 7 mass and social media factors for each of them were considered on daily basis from 08-01-2018 to 10-31-2020. To explore the interdependence between media drivers and cryptocurrencies' prices in short, medium and long timespan, this study deploys wavelet coherence approach. There was found, that price changes turn to be the supreme prior to hype, even though the growing ado may push the prices even higher. Thus, hype is failing to prove itself as a reliable cryptocurrency price predictor. Crypto investors, though, should anyways take the news background into account while building trading strategies,...

This thesis studies the relationship between the first generation biofuels and selected commodities and assets in the USA, Europe, and Brazil. It is the first attempt to combine the taxonomy and wavelet analyses in a single research application. Our unique dataset comprises 32 weekly price series covering the 2003--2015 time period. First, we employ a method of minimum spanning trees and hierarchical trees to model a biofuel-related price network. We demonstrate a development phase shift between Brazilian and the US/EU biofuel industries. We reveal a strong and stable connection between Brazilian ethanol and its main production factor, local sugarcane. We further find that US ethanol is closely linked to corn. In the contrary, European biodiesel exhibits only moderate ties to its production factors. Subsequent wavelet analysis scrutinizes the identified price connections both in time and frequency domains. Both Brazilian and US ethanols are found to be positively related to their respective feedstock commodities. In particular, feedstock proves to lead the price of the biofuel and not vice versa. Moreover, the dynamics remains qualitatively unchanged when controlled for the influence of crude oil.

Ce travail consiste à caractériser la variabilité temporelle et spatiale des séries chronologiques de paramètres hydroclimatiques (pluies, débits) au niveau de trois grand bassins au Maroc ; (bassins de la Moulouya, du Sebou et du Tensift) et à chercher les liens entre cette variabilité hydrologique et les fluctuations climatiques matérialisées par différents indices climatiques, NAO, SOI, WMOI. L’approche d’étude est basée le traitement statistique des séries temporelles, liée aux dimensions temps et espace.Les grands bassins versants d'échelle continentale comme le Tensift, le Sebou et la Moulouya en climat méditerranéen sous influence océanique, intègrent sur des grandes surfaces la réponse hydrologique aux changements climatiques et environnementaux (fluctuations du climat, précipitations, débits) à de larges échelles spatiales et temporelles, mais également les modifications du milieu physique d’origine anthropique (changements d’occupation des sols, aménagements…), ce qui rend parfois difficile l’identification des liens entre la variabilité hydrologique et la variabilité climatique. Les principaux objectifs de ce travail sont de déterminer et de quantifier les relations entre la variabilité hydroclimatique et les fluctuations du climat à l’échelle de chaque bassin étudié et de ses principaux sous-bassins, via l'utilisation de méthodes d’analyses spectrales adaptées à l’étude des processus non stationnaires (analyse en ondelettes continues, analyse de la cohérence par ondelettes). Plusieurs modes de variabilités sont identifiés à partir de l’analyse par station (pluies et débits), du cycle annuel au mode 16-22 ans, cette analyse sera complétée par une analyse par maille, dont les données sont issues d’un fichier (SIEREM) couvrant la période 1940-1999, où on identifie des fréquences de 1an au 8-16 ans, distinguées sur des périodes différentes au niveau de chaque bassin, permettant ainsi une décomposition de la variabilité spatiale des signaux mis en évidence. Trois principales discontinuités sont identifiées en 1970, 1980 et 2000. La contribution des indices climatiques est assez importante elle est entre 55% et 80%. / This work is to characterize the temporal and spatial variability of hydroclimatic time series (rainfall, flow) at three large basins in Morocco; (basins of the Sebou and Moulouya Tensift) and look links between the hydrologic variability and climate fluctuation materialized by various climate indices, NAO, SOI, WMOI. The approach to study is based on statistical analysis of time series, related to time and space dimensions.The great watershed of continental scale as Tensift, Sebou and Moulouya in Mediterranean climate under oceanic influence, integrate over large areas the hydrological response to climate and environmental changes (climate fluctuations, precipitation, flows) not only to large spatial and temporal scales, but also to changes in the physical environment anthropogenic (land use changes, developments ...), which sometimes makes difficult to identify the links between hydrological variability and climate variability. The main objective of this work is to determine and quantify the relationships between hydrological variability and climate fluctuations (regionalised precipitation, climate change indexes) across each studied basin and its main sub-basins, via using spectral analysis methods adapted to the study of non-stationary processes (continuous wavelet analysis, coherence analysis wavelet). Many modes of variability are identified from the station analysis (rainfall and flow rates), the annual cycle to 16-22 years, this analysis will be complemented by a grid analysis, the data come from a (SIEREM) file covering the period from 1940 to 1999, which will allow a better understanding of the spatial variability of signals set highlighted. Which is identified frequencies the 1 year 8-16 years, distinguished different time periods at each basin, three main discontinuities identified in 1970, 1980 and 2000. The contribution of climatic indices is important enough it is between 55% and 80%.

This thesis studies the impact of shale gas on commodity and stock markets in the U.S. by employing wavelet approach and conducting a time-frequency analysis of dynamic correlations between natural gas and important representatives of commodity markets: crude oil, coal, corn, wheat, and several indices. It covers the period from 2006 to 2015 and is performed on daily data. Our thesis enlarges existing literature on comovement between natural gas with other energy commodities and stocks using wavelet coherence - a methodology which allows analyzing comovement among assets not only from a time series perspective but also over different frequencies. Financialization of natural gas and its involvement in investment portfolios under changing conditions on the U.S. gas market provide space for examination of gas proper correlation estimates in respect to other financial assets. Our results reveal natural gas comovement behaviour with examined commodities during the Financial Crisis. They show gradual decoupling between gas and crude oil prices in time. To the best of our knowledge we are the first to address natural gas using wavelet coherence in connection to agricultural commodities corn and wheat. These commodities together with natural gas are primary sources for bioethanol production being used in...

Since Galileo Galilei invented the first thermometer, researchers have tried to understand the complex dynamics of ocean and atmosphere by means of scientific methods. They observe nature and formulate theories about the climate system. Since some decades powerful computers are capable to simulate the past and future evolution of climate.<br><br> Time series analysis tries to link the observed data to the computer models: Using statistical methods, one estimates characteristic properties of the underlying climatological processes that in turn can enter the models. The quality of an estimation is evaluated by means of error bars and significance testing. On the one hand, such a test should be capable to detect interesting features, i.e. be sensitive. On the other hand, it should be robust and sort out false positive results, i.e. be specific. <br><br> This thesis mainly aims to contribute to methodological questions of time series analysis with a focus on sensitivity and specificity and to apply the investigated methods to recent climatological problems. <br><br> First, the inference of long-range correlations by means of Detrended Fluctuation Analysis (DFA) is studied. It is argued that power-law scaling of the fluctuation function and thus long-memory may not be assumed a priori but have to be established. This requires to investigate the local slopes of the fluctuation function. The variability characteristic for stochastic processes is accounted for by calculating empirical confidence regions. The comparison of a long-memory with a short-memory model shows that the inference of long-range correlations from a finite amount of data by means of DFA is not specific. When aiming to infer short memory by means of DFA, a local slope larger than $alpha=0.5$ for large scales does not necessarily imply long-memory. Also, a finite scaling of the autocorrelation function is shifted to larger scales in the fluctuation function. It turns out that long-range correlations cannot be concluded unambiguously from the DFA results for the Prague temperature data set. <br><br> In the second part of the thesis, an equivalence class of nonstationary Gaussian stochastic processes is defined in the wavelet domain. These processes are characterized by means of wavelet multipliers and exhibit well defined time dependent spectral properties; they allow one to generate realizations of any nonstationary Gaussian process. The dependency of the realizations on the wavelets used for the generation is studied, bias and variance of the wavelet sample spectrum are calculated. To overcome the difficulties of multiple testing, an areawise significance test is developed and compared to the conventional pointwise test in terms of sensitivity and specificity. Applications to Climatological and Hydrological questions are presented. The thesis at hand mainly aims to contribute to methodological questions of time series analysis and to apply the investigated methods to recent climatological problems. <br><br> In the last part, the coupling between El Nino/Southern Oscillation (ENSO) and the Indian Monsoon on inter-annual time scales is studied by means of Hilbert transformation and a curvature defined phase. This method allows one to investigate the relation of two oscillating systems with respect to their phases, independently of their amplitudes. The performance of the technique is evaluated using a toy model. From the data, distinct epochs are identified, especially two intervals of phase coherence, 1886-1908 and 1964-1980, confirming earlier findings from a new point of view. A significance test of high specificity corroborates these results. Also so far unknown periods of coupling invisible to linear methods are detected. These findings suggest that the decreasing correlation during the last decades might be partly inherent to the ENSO/Monsoon system. Finally, a possible interpretation of how volcanic radiative forcing could cause the coupling is outlined. / Seit der Erfindung des Thermometers durch Galileo Galilei versuchen Forscher mit naturwissenschaftlichen Methoden die komplexen Zusammenhänge in der Atmosphäre und den Ozeanen zu entschlüsseln. Sie beobachten die Natur und stellen Theorien über das Klimasystem auf. Seit wenigen Jahrzehnten werden sie dabei von immer leistungsfähigeren Computern unterstützt, die das Klima der Erdgeschichte und der nahen Zukunft simulieren. <br><br> Die Verbindung aus den Beobachtungen und den Modellen versucht die Zeitreihen­analyse herzustellen: Aus den Daten werden mit statistischen Methoden charak­teristische Eigenschaften der zugrundeliegenden klimatologischen Prozesse geschätzt, die dann in die Modelle einfliessen können. Die Bewertung solch einer Schätzung, die stets Messfehlern und Vereinfachungen des Modells unterworfen ist, erfolgt statistisch entweder mittels Konfidenzintervallen oder Signifikanztests. Solche Tests sollen auf der einen Seite charakteristische Eigenschaften in den Daten erkennen können, d.h. sie sollen sensitiv sein. Auf der anderen Seite sollen sie jedoch auch keine Eigenschaften vortäuschen, d.h. sie sollen spezifisch sein. Für die vertrauenswürdige Untermauerung einer Hypothese ist also ein spezifischer Test erforderlich. <br><br> Die vorliegende Arbeit untersucht verschiedene Methoden der Zeitreihenanalyse, erweitert sie gegebenenfalls und wendet sie auf typische klimatologische Frage­stellungen an. Besonderes Augenmerk wird dabei auf die Spezifizität der jeweiligen Methode gelegt; die Grenzen möglicher Folgerungen mittels Datenanalyse werden diskutiert.<br><br> Im ersten Teil der Arbeit wird studiert, wie und ob sich mithilfe der sogenannten trendbereinigenden Fluktuationsanalyse aus Temperaturzeitreihen ein sogenanntes langes Gedächtnis der zugrundeliegenden Prozesse herleiten lässt. Solch ein Gedächtnis bedeutet, dass der Prozess seine Vergangenheit nie vergisst, mit fundamentalen Auswirkungen auf die gesamte statistische Beurteilung des Klimasystems. Diese Arbeit konnte jedoch zeigen, dass die Analysemethode vollkommen unspezifisch ist und die Hypothese “Langes Gedächtnis” gar nicht abgelehnt werden kann. <br><br> Im zweiten Teil werden zunächst Mängel einer sehr populären Analysemethode, der sogenannten kontinuierlichen Waveletspetralanalyse diskutiert. Diese Methode schätzt die Variabilität eines Prozesses auf verschiedenen Schwingungsperioden zu bestimm­ten Zeiten. Ein wichtiger Nachteil der bisherigen Methodik sind auch hier unspezi­fische Signifikanztests. Ausgehend von der Diskussion wird eine Theorie der Wavelet­spektralanalyse entwickelt, die ein breites Feld an neuen Anwendungen öffnet. Darauf basierend werden spezifische Signifikanztests konstruiert.<br><br> Im letzten Teil der Arbeit wird der Einfluss des El Niño/Southern Oscillation Phäno­mens auf den Indischen Sommermonsun analysiert. Es wird untersucht, ob und wann die Oszillationen beider Phänomene synchron ablaufen. Dazu wird eine etablierte Methode für die speziellen Bedürfnisse der Analyse von typischerweise sehr unregel­mäßigen Klimadaten erweitert. Mittels eines spezifischen Signifikanztests konnten bisherige Ergebnisse mit erhöhter Genauigkeit bestätigt werden. Zusätzlich konnte diese Methode jedoch auch neue Kopplungsintervalle feststellen, die die Hypothese entkräften konnten, dass ein neuerliches Verschwinden der Kopplung ein beisspielloser Vorgang sei. Schliesslich wird eine Hypothese vorgestellt, wie vulkanische Aerosole die Kopplung beeinflussen könnten.

Gouvernée par un socle juridique d’inspiration religieuse, le fonctionnement de la banque islamique est, sur le plan théorique, différent de celui de la banque conventionnelle. Bien que la littérature portant sur les mécanismes de transmission de la politique monétaire dans un cadre conventionnel soit abondante, rares sont les travaux, théoriques et empiriques, qui examinent le rôle des banques islamiques dans cette transmission. En effet, la littérature existante ne présente pas de schéma analytique complet permettant d’appréhender clairement le rôle des banques islamiques dans la transmission de la politique monétaire, et d'identifier et spécifier la nature des interactions entre banques islamiques et banques conventionnelles. L’ambition de la présente thèse, structurée en trois chapitres, consiste donc à étudier par quels mécanismes et dans quelles mesures la banque centrale est susceptible de réguler l’activité économique en présence de banques islamiques. / Governed by a religiously inspired legal framework, Islamic banking is, in theory, different from conventional banking. While the literature on the transmission mechanisms of monetary policy in a conventional framework is abundant, very little research, theoretical and empirical, has been focused directly at the role of Islamic banks in this transmission. Indeed, the existing literature does not present a complete analytical framework allowing a full and clear understanding of the role of Islamic banks in the transmission of monetary policy, and to identify and specify the nature of the interactions between Islamic and conventional banks. The aim of this thesis, made up of three chapters, is to study by which mechanisms and to what extent the central bank is likely to regulate the economic activity in the presence of Islamic banks.