Notice bibliographique
Résumé
This dissertation consists of four self-contained chapters in the form of papers. The first chapter investigates the volatility spillover effects and the contagion to sovereign CDS spread returns for Germany, France, China and Japan against USA. To the best of our knowledge, this is the first empirical research in the literature, which investigates potential spillovers and contagion effects among sovereign CDS markets. We use daily data from October 2011 to February 2018. Employing a fourvariate cDCC-AR-FIGARCH model, we find evidence of spillover effects for all the pairs of markets. Furthermore, we find empirical evidence of contagion for the pairs of markets: Germany – France, Germany – Japan and France – Japan. Regarding China’s CDS market we obtain little empirical support for contagion with the rest of the countries. The results are of interest to policymakers, who provide regulations for the CDS markets, as well as to market-makers. The second chapter investigates the spillover effects and the contagion to major equity and FOREX markets of G20. The financial markets under scrutiny are those of USA, Brazil, Italy, Germany and Canada. The frequency of the data is daily. We set the sample period from April 2010 to April 2018, namely after the GFC. Other related empirical work include Kanas (2000), who investigated the existence of spillovers between national equity and FOREX markets, by employing a trivariate AR-diagonal BEKK model for S&P 500, national equity markets and the respective FOREX markets. Our empirical results find evidence of spillovers and contagion effects for the pairs of markets: S&P500-BOVESPA, S&P500-FTSEMIB, S&P500-DAX30 and S&P500-S&PTSX. Moreover, the pairs of markets S&P 500-CAD/USD, S&P 5000BRL/USD and BOVESPA-BRL/USD present no contagion. The resultsare of interest to individual investors, who want to diversify their portfolios through international financial market investments. The third chapter investigates the spillovers and the financial contagion of four major FOREX markets. The FOREX markets are those of EUR/USD, JPY/USD, CHW/USD and GBP/USD. Lee (2010) investigates ten FOREX markets in Asia and Latin America to USD, among others and finds evidence of spillover effects from JPY/USD on Asian currency markets. A fourvariate dynamic Conditional Correlation Generalized ARCH (DCC-GARCH) model is employed for the period April 2011 to February 2018. The empirical results suggest contagion for all the pairs of markets. Additionally, we find that EUR/USD and GBP/USD present the strongest contagion effects, while CHW/USD show the lowest contagion levels with the rest of the markets.The fourth chapter analyses the spillover and the contagion effects of MSCI (global index), NIKKEI 400 (Japan), CSI 300 (China) and S&P 500 (USA). We consider a portofolio analysis in order to produce the standardized residuals using in a trivariate cDCC-GARCH framework. Other research work include Miyakoshi (2003), who suggests the existence of spillover effects between USA and Asian national equity markets. We extend the above analysis by taking into consideration the individual effects of MSCI on three of the most important national equity markets. We use daily data for the period 2008-2018. The main empirical results are the following: (1) portfolio analysis results suggest that MSCI has a significant positive influence on all equity market returns, (2) we find empirical evidence of spillovers on all pairs and (2) we find contagion for the pairs of markets: NIKKEI 400-CSI 300, NIKKEI 400-S&P 500 and S&P 500-CSI 300 that indicate risky positive correlations from an investor’s perspective.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».