1,721,038 research outputs found
Global Integration of Central and Eastern European Financial Markets-The Role of Economic Sentiments
No full textThis paper examines the importance of different economic sentiments for the Central and Eastern European countries (CEECs) during the transition process. We first analyze the importance of economic confidence with respect to the CEECs' financial markets. Since the integration of formerly strongly-regulated markets into global markets can also lead to an increase in the dependence of the CEECs' economies on global sentiments, we also investigate the relationship between global economic sentiments, domestic income, and share prices. Applying a restricted cointegrating VAR (CVAR) framework, which allows us to distinguish between the long-run and the short-run dynamics, our results for the short run suggest that economic sentiments are influenced by share prices but also offer some predictive power with respect to the latter. What is more, European sentiments play an important role in particular for the CEECs' income and sentiments
Drivers of Government Activity in European Countries: Do Partisan Politics Still Divide East and West?
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This article takes a novel look at the relationship between government activity, partisan preferences and varieties of capitalism. Evidence from panel regressions for 25 EU countries from 1990 to 2014 suggests that there are major divides among European countries in terms of the drivers of government activity, that is, government spending and government regulation. The European divide appears to be even more pronounced between liberal and coordinated economic systems than between the classical geographical divide of east and west, which is typically used in most contributions. While both divides apply to the determinants of government activity in general, a reversal of the classical partisan effect for the east is to be found only in specific cases and, is most likely in government spending in liberal eastern countries
Die Bedeutung von Erwartungen und medienbasiertem Sentiment für das individuelle Verhalten, Energiepreise und Renditen grüner Anlagen
Get PDFThis cumulative dissertation examines the extent to which media-based sentiment and information influence individual expectations and behavior as well as economic developments and market prices. Of particular interest is the question whether sentiment can be regarded as relevant information that leads to behavioral changes and market adjustments, or whether it can be regarded as noise that leads to little or no behavioral and market changes. The role of sentiment and information in the economy is considered in particular in the context of sustainable investments, green asset returns, energy markets, and environmental, social and governance (ESG) indices. The work comprises a total of five empirical studies. Four of the studies were written jointly with co-authors, while one study was authored solely. Three of the studies were published in peer-reviewed journals, while the other two studies were published as working papers and are currently in the review process for peer-reviewed journals
Relevance of Sentiment Indicators for Expectations and Uncertainty in Foreign Exchange and Energy Markets
Get PDFThe foreign exchange (FX) and energy markets have undergone significant changes due to increased trading activity and global financial shifts. Foreign exchange markets, in particular, are seeing increasing daily trading volumes. Oil markets are influenced by geopolitical and production events, which impact expectations, uncertainties, and overall market dynamics. This cumulative dissertation examines how media sentiment influences the FX and oil markets, focusing on expectation formation and uncertainty. Building on traditional models such as the rational expectations hypothesis, the study emphasizes the role of media coverage as a public signal that shapes expectations and uncertainties. The dissertation consists of six empirical studies. It finds that expectations about future exchange rates and oil prices are affected by the intensity and tonality of media coverage. In addition, the study illustrates the effects on uncertainties, including forecast errors and disagreements among professionals. Furthermore, media coverage is more significant for information rigidities in the FX market compared to order flow and is valuable for understanding the weak link between FX and fundamentals through scapegoat effects. The implications of the dissertation show that media coverage and tonality, as sources of public information, capture a substantial part of the market, providing an important channel through which information is processed and potentially influencing expectation formations and uncertainties in the FX and oil markets
Urbanization, Remittances, Energy: An Impact Assessment on Economic Development: Analysis in Three Essays
No full textEssays in Financial Econometrics
Get PDFThe analysis of financial time series with econometric methods is an important part of understanding risk and return characteristics of assets and portfolios, it is essential for making and evaluating forecasts and generally, it is obligatory for macroeconomic decision making. This dissertation consists of five essays of different but related topics out of the financial econometrics cosmos. They all have in common that they provide insights into the financial markets. While the first two projects focus on explosive financial periods, the third is about exchange rates, and the fourth is about improving the equity premium prediction. The last project deals with convergence behaviour of ESG stock market indices. Chapter 2 comprises the analysis of financial exuberance periods which is done together with Robinson Kruse-Becher and Christoph Wegener. We identify over 170 financial exuberance periods based on a data set consisting of stock market indices by applying the financial exuberance detection procedure of Phillips, Shi, and Yu (2015). Based on these, we investigate the stylized facts of exuberance periods, propose a new data generating process (DGP) based on an autoregressive process and propose specific parameter settings for different kinds of exuberance periods. Our main findings suggest that the often made parameter assumptions in the literature, e.g. by Evans (1991) are not confirmed by empirical evidence. Chapter 3 is my single author project. In contrast to Chapter 2, it takes on a multivariate perspective and analyses the co-explosiveness of corporate credit spreads - a situation in which two temporary explosive time series share the same autoregressive process and thus, their linear combination is integrated of order zero. The analysis of corporate credit spreads for six major markets shows that there is no static co-explosiveness within the full sample but co-explosiveness is identified at the local level. For different sub-periods like the GFC and COVID-19, there is some co-explosiveness between different spreads. After the GFC, the percentage of co-explosive credit spread pairs went down which can be interpreted as more successful financial regulation efforts. Another finding is that the lead/lag relationship between credit spreads changes over time rather than being constant. Chapter 4 deals with exchange rate prediction. Joscha Beckmann, Robinson Kruse-Becher and I investigate if there are different regimes in predictability of six major exchange rates with respect to USD (G7 currencies). This is done by applying the IVX-approach of Gonzalo and Pitarakis (2017) with transition variables linked to uncertainty and sentiment data. We majorly find that predictability regimes are triggered by increased media coverage and high uncertainty. Based on them, a predictability regime can be differentiated from a regime of low/no-predictability. Most successful predictors are linked to interest-rates and chosen transition variables are mainly buzz and sentiment indicators. Chapter 5 is joined work with Rainer Schüssler and Norbert Fay. It deals with forecasting the equity premium but in contrast to the majority of literature in this field, we focus on forecasting the predictive density of the equity premium. We show that the predictive power of Bayesian predictive densities can be significantly increased by restricting the first three moments of the distribution. This is done by using a technique called entropic tilting. With this, we take forwardlooking information from option prices into account. Chapter 6 contains joint work with Robinson Kruse-Becher about the convergence behaviour of MSCI ESG (’environmental, social, governmental’) stock market indices. For a sample of 18 different stock markets we show that there are different convergence clusters prior to a structural break identified in May 2019. After this break – which is linked to the increased ESG attention of investors – all considered stock markets are in one single cluster and show level convergence, the strongest form of convergence.Die Analyse von Finanzzeitreihen mit Hilfe ökonometrischer Methoden ist ein wichtiger Bestandteil zum Verständnis von Risiko- und Renditeeigenschaften von Vermögenswerten und Portfolios, sie ist essenziell um Prognosen durchzuführen und zu evaluieren und im Allgemeinen ist sie zum Treffen makroökonomischer Entscheidungen obligatorisch. Diese Dissertation besteht aus fünf verschiedenen Forschungsarbeiten, welche allesamt aus dem Bereich Finanzökonometrie stammen. Sie haben alle gemeinsam, dass sie neue Erkenntnisse für Finanzmärkte bereitstellen. Während die ersten beiden Projekte einen Fokus auf explosive finanzielle Prozesse legen, beschäftigt sich Projekt drei mit Wechselkursen. Das vierte Projekte beschäftigt sich mit der Verbesserung der Vorhersage des Equity Premiums und das letzte Projekt behandelt das Konvergenzverhalten von ESG Aktienmarktindizes. Kapitel 2 behandelt die Analyse von explosiven Finanzperioden und wurde zusammen mit Robinson Kruse-Becher und Christoph Wegener durchgeführt. Wir identifizieren über 170 explosive Perioden auf Basis von diversen Aktienmarktindizes, indem wir das Verfahren von Phillips, Shi und Yu (2015a) zur Identifikation von explosiven Finanzmarktphasen anwenden. Auf Basis dieser Datengrundlage analysieren wir die Stylized Facts von explosiven Perioden, schlagen einen neuen datengenerierenden Prozess auf Basis autoregressiver Prozesse vor und bieten spezifische Parametrisierungen für verschiedene explosive Phasen an. Unsere Haupterkenntnisse zeigen, dass die häufig in der Literatur gemachten Parameterannahmen (u.a. in Evans (1991)) nicht durch empirische Evidenz gestützt werden. Kapitel 3 ist mein alleiniges Projekt. Im Gegensatz zu Kapitel 2 wird eine multivariate Perspektive eingenommen und es wird die Co-Explosivität zwischen Kreditrisikoprämien für Unternehmensanleihen analysiert. Hierbei handelt es sich um eine Situation, in der zwei temporär explosive Zeitreihen den gleichen autoregressiven Prozess teilen und somit deren Linearkombination integriert vom Grad 0 ist. Die Analyse verschiedener Kreditrisikoprämien für sechs bedeutende Märkte zeigt, dass es keine statische Co-Explosivität über den kompletten Zeitraum gibt. Es wird jedoch Co-Explosivität im lokalen Bereich identifiziert. Für verschiedene Perioden, wie die globale Finanzkrise 2007/09 und COVID-19, werden einige Co-Explosivitäten zwischen Spreads identifiziert. Nach der GFC verringert sich der Anteil co-explosiver Spread Paare, was durch adäquatere Regulierungsbemühungen im Finanzbereich erklärt werden kann. Darüber hinaus wird herausgestellt, dass die Beziehung zwischen Kreditrisikoprämien nicht konstant, sondern zeitvariierend ist. Kapitel 4 behandelt die Vorhersage von Wechselkursen. Joscha Beckmann, Robinson Kruse-Becher und ich untersuchen, ob es verschiedene Vorhersageregime für sechs bedeutende Wechselkurse in Bezug auf den US-Dollar (G7-Währungen) gibt. Dies wird gemacht, indem der IVX-Ansatz von Gonzalo und Pitarakis (2017) mit Transitionsvariablen, die einen Bezug zu Unsicherheit und Sentiment Daten aufweisen, angewendet wird. Unsere Haupterkenntnisse sind, dass Vorhersageregime durch erhöhte Medienberichterstattungen und hohe Unsicherheit ausgelöst werden. Auf deren Basis lassen sich ein Vorhersageregime von einem Regime mit geringer bzw. keiner Vorhersagekraft unterscheiden. Die erfolgreichsten Prädiktoren weisen einen Bezug zu Zinssätzen auf und die gewählten Transitionsvariablen sind hauptsächlich dem Bereich Buzz und Sentiments zuzuordnen. Kapitel 5 ist ein gemeinsames Projekt mit Rainer Schüssler und Norbert Fay. Es beschäftigt sich mit der Vorhersage des Equity Premiums. Im Gegensatz zum Großteil der Literatur in diesem Gebiet beschäftigen wir uns mit der Prognose der Vorhersagedichte des Equity Premiums. Wir zeigen, dass die Vorhersagegüte von Bayesianischen Vorhersagedichten signifikant verbessert werden kann, indem die ersten drei Momente der Verteilung beschränkt werden. Dies wird gemacht, indem eine Methodik namens Entropic Tilting verwendet wird. Hiermit werden nach vorne schauende (zukünftige) Informationen aus Optionspreisen mit berücksichtigt. Kapitel 6 enthält eine gemeinsame Arbeit mit Robinson Kruse-Becher über das Konvergenzverhalten von MSCI ESG Aktienmarktindizes. Für einen Datensatz von 18 verschiedenen Aktienmärkten zeigen wir, dass es verschiedene Konvergenzcluster bis zu einem Strukturbruch im Mai 2019 gibt. Nach diesem Bruch, welcher in Bezug zu der höheren Aufmerksamkeit von Investoren für die ESG Thematik steht, befinden sich alle betrachteten Aktienmärkte in einem einzigen Cluster. Dieses Cluster weißt Level-Konvergenz auf, welches die stärkte Form der Konvergenz ist
Essays on the estimation and forecasting of financial volatility
Get PDFThe Great Financial Crisis of 2008 highlighted the fragility of the modern financial system. The bankruptcy and bailout of financial institutions captured global media attention and significantly impacted daily life worldwide. The crisis affected both national economies and individuals, with the US GDP growth rate in 2009 falling to -2.6% and the EU's to -4.3%. Unemployment in the US surged from 5.1% in March 2008 to 9.4% in May 2009, while the euro area's rate rose from 7.2% to 9.5%. This crisis raised crucial questions: How did it happen? How can future crises be predicted? What actions should be taken when a crisis occurs? Extensive research has since aimed to answer these questions, particularly focusing on financial volatility, which reveals risk dynamics and helps predict future risks. Volatility, expressed through the variance of financial returns, is crucial for understanding market behavior and making investment decisions. The development of econometric models like the generalized autoregressive conditional heteroskedasticity (GARCH) model has significantly advanced volatility research. This thesis comprises three essays on volatility estimation and prediction, utilizing various information sets to enhance accuracy. Each chapter explores different data sources, from current stock market observations to macroeconomic indicators and high-frequency trading data, to improve volatility prediction
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Speculation driven overreaction and momentum effects in cryptocurrency and commodity markets
No full textThe present thesis is focused on speculative behavior of investors in financial markets. More precisely, the thesis consists of five papers and takes a closer look at two speculation driven financial market anomalies, the overreaction hypothesis and the momentum effect, and considers them in two financial markets, cryptocurrency and commodity markets
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