Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

This thesis provides evidence of how macroeconomic surprises, constructed as deviations from market expectations, impact daily spread changes of Czech, Polish and Hungarian (CEEC-3) government bonds and sovereign credit default swaps. Firstly, we carried out series of event studies that inspect the spreads' reactions to the announcements. Subsequently, we employed the general-to-specific modeling approach and arrived at thirty GARCH-type models that consider surprises' impact on both conditional mean and variance. We have found significant impacts on the mean, yet in terms of magnitude, the impact of macroeconomic surprises has not been superior to that of broad financial factors. The impact on spreads' volatility appears more consequential though it lacks a clear pattern: Both good and bad news have been found to affect the volatility in either direction. Our findings suggest that with respect to macroeconomic news, daily changes of the bond spreads are driven rather by inflation expectations than by credit risk considerations. Foreign news proxied by the German surprises seems to affect the CEEC-3 bond spreads mainly through the risk-free proxy - the German Bund yield. Contrary to studies using low-frequency macroeconomic data, we have found no evidence for the "wake-up call" hypothesis.

This thesis provides an analysis of systemic risk in the US banking sector. We use conditional value at risk (∆CoVaR), marginal expected shortfall (MES) and cross-quantilogram (CQ) to statistically measure tail-dependence in return series of individual institutions and the system as a whole. Wavelet multireso- lution analysis is used to study systemic risk in the time-frequency domain. De- composition of returns on different scales allows us to isolate cycles of 2-8 days, 8-32 days and 32-64 days and analyze co-movement patterns which would oth- erwise stay hidden. Empirical results demonstrate that filtering out short-term noise from the return series improves the forecast power of ∆CoVaR. Eventu- ally, we investigate the connection between statistical measures of systemic risk and fundamental characteristics of institutions (size, leverage, market to book ratio) and conclude that size is the most robust determinant of systemic risk.

This thesis examines the output-variability relationship and causal relationships among the inflation, the output growth and their uncertainties for the Central and Eastern European region during the period of time that covers the economic crisis of 2008. We apply the bivariate GARCH(1,1) model with the constant conditional correlation covariance matrix to obtain conditional variances that proxy the two uncertainties and use Granger causality test to determine the causal effects among four variables. We come up with a number of interesting results. First, we did not find statistical evidence neither for the inflation-output variability relationship nor for the Phillips curve. Second, we uncovered support for the positive causal effect of the inflation on its uncertainty and negative causal effect for the reverse direction. Additionally, we also found some support for the indirect negative causal effect of the inflation on the output growth. These results support the policy of low and stable inflation in the countries. Finally, we showed that crisis has a significant impact on the results, changing the behaviour of conditional variances and causal effects among the variables. Powered by TCPDF (www.tcpdf.org)

The efficient market hypothesis has been around since 1962, the theory based on a simple rule that states the price of any asset must fully reflect all available information. Yet there is empirical evidence suggesting that markets are too volatile to be efficient. In essence, this evidence seems to suggest that the reaction of the market participants to the information or events that is the crucial factor, rather than the actual information. This highlights the need to include the behavioural finance theory in the pricing of assets. Essentially, the research aims to analyse the efficiency of six key sovereign debt markets during a period of changing volatility including the recent global financial and sovereign debt crises. We analyse the markets in the pre-crisis period and during the financial and sovereign debt crises to determine the impact of the crises on the efficiency of these financial markets. We use two GARCH-based variance bound tests to test the null hypothesis of the market being too volatile to be efficient. Proposing a GJR-GARCH variant of the variance bound test to account for variation in the asymmetrical effect. This leads to an analysis of the changing behaviour of price volatility to identify what makes the market efficient or inefficient. In general, our EMH tests resulted in mixed results, hinting at the acceptance of the null hypothesis of the market being too volatile to be efficient. However, interestingly a number of 2017 observations under both models seem to be hinting at the rejection of the null hypothesis. Furthermore, our proposed GJR-GARCH variant of the variance bound test seems to be more likely to accept the EMH than the GARCH variant of the test.

There has been an on-going debate about choices of the most suitable model amongst a variety of model specifications and parameterizations. The first dissertation essay investigates whether asymmetric leptokurtic return distributions such as Hansen's (1994) skewed tdistribution combined with GARCH specifications can outperform mixed GARCH-jump models such as Maheu and McCurdy's (2004) GARJI model incorporating the autoregressive conditional jump intensity parameterization in the discrete-time framework. I find that the more parsimonious GJR-HT model is superior to mixed GARCH-jump models. Likelihood-ratio (LR) tests, information criteria such as AIC, SC, and HQ and Value-at-Risk (VaR) analysis confirm that GJR-HT is one of the most suitable model specifications which gives us both better fit to the data and parsimony of parameterization. The benefits of estimating GARCH models using asymmetric leptokurtic distributions are more substantial for highly volatile series such as emerging stock markets, which have a higher degree of non-normality. Furthermore, Hansen's skewed t-distribution also provides us with an excellent risk management tool evidenced by VaR analysis. The second dissertation essay provides a variety of empirical evidences to support redundancy of stochastic volatility for SP500 index returns when stochastic volatility is taken into account with infinite activity pure Lévy jumps models and the importance of stochastic volatility to reduce pricing errors for SP500 index options without regard to jumps specifications. This finding is important because recent studies have shown that stochastic volatility in a continuous-time framework provides an excellent fit for financial asset returns when combined with finite-activity Merton's type compound Poisson jump-diffusion models. The second essay also shows that stochastic volatility with jumps (SVJ) and extended variance-gamma with stochastic volatility (EVGSV) models perform almost equally well for option pricing, which strongly imply that the type of Lévy jumps specifications is not important factors to enhance model performances once stochastic volatility is incorporated. In the second essay, I compute option prices via improved Fast Fourier Transform (FFT) algorithm using characteristic functions to match arbitrary log-strike grids with equal intervals with each moneyness and maturity of actual market option prices.

In chapter 1, I investigate the return links and dynamic conditional correlations between the equity and commodity returns for G7 countries from 2000:01 to 2014:10. The commodity futures include BCOM Index which contains the futures and spot price of 22 commodities, Brent and Crude oil futures, gold and silver futures, Wheat, Corn and Soybean futures and CRB index. The finding indicates that during the full sample period GOLD, WHEAT and CORN have the smallest dynamic conditional correlations with all the Equity indexes. In addition, the correlations between the GOLD/Equity pairs are negative during the financial crisis. This fact indicates the benefit of hedging the stock portfolios with gold futures while we have stress in the financial markets. The results from hedging effectiveness suggest that all the commodity/stock portfolios provide better diversification benefits than the stock portfolios. In average, including CRB, BCOM and GOLD futures to the stock portfolios have the highest hedging effectiveness ratios. Chapter 2 investigates the impact of global and local variables on the Sovereign bond spreads for 22 developed countries in North America, Europe and Pacific Rim Regions, using monthly data from January 2010 to March 2015. There are a few main findings of this chaper. First, the global factors are considerably more important in déterminant the sovereign bond spreads for all the regions. Second, for the bond spread of each region over its local government bond, the countries’ domestic fundamentals are found to be more influential determinants of the spreads, compared to the spread over US government bond as a safe haven government bond. Third, the bond spreads in the Eurozone area is less influenced by the global factors compared to the other regions. Fourth, the sovereign bond spreads of all regions are positively related to the US corporate high yield spreads as a proxy of market sentiment and the log of VIX index as measurement for the investor risk aversion. The coefficient of the log of VIX index shows the strong power of the stock market implied volatility on determining the yield spreads in the fixed income market.

This dissertation comprises two essays; the first of which investigates sovereign credit risk interdependencies, while the second examines the reaction of corporate credit risk to sovereign credit risk events. The first essay titled, Characterizing Sovereign Credit Risk Interdependencies: Evidence from the Credit Default Swap Market, investigates the relationships that exist among disparate sovereign credit default swaps (CDS) and the implications on sovereign creditworthiness. We exploit emerging market sovereign CDS spreads to examine the reaction of sovereign credit risk to changes in country-specific and global financial factors. Utilizing aVAR model fitted with DCC GARCH, we find that comovements of spreads generally exhibit significant time-varying correlations, suggesting that spreads are commonly affected by global financial factors. We construct 19 country-specific commodity price indexes to instrument for country terms of trade, obtaining significant results. Our commodity price indexes account for significant variation in CDS spreads, controlling for global financial factors. In addition, sovereign spreads are found to be related to U.S. stock market returns and the VIX volatility risk premium global factors. Notwithstanding, our results suggest that terms of trade and commodity prices have a statistically and economically significant effect on the sovereign credit risk of emerging economies. Our results apply broadly to investors, financial institutions and policy makers motivated to utilize profitable factors in global portfolios. The second essay is titled, Differential Stock Market Returns and Corporate Credit Risk of Listed Firms. This essay explores the information transfer effect of shocks to sovereign credit risk as captured in the CDS and stock market returns of cross-listed and local stock exchange listed firms. Based on changes in sovereign credit ratings and outlooks, we find that widening CDS spreads of firms imply that negative credit events dominate, whereas tightening spreads indicate positive events. Grouping firms into companies with cross-listings and those without, we compare the spillover effects and find strong evidence of contagion across equity and CDS markets in both company groupings. Our findings suggest that the sensitivity of corporate CDS prices to sovereign credit events is significantly larger for non-cross-listed firms. Possible reasons for this finding could in fact be due to cross-listed firms’ better access to external capital and less degree of asymmetric information, relative to non-cross-listed peers with lower level of investor recognition. Our results provide new evidence relevant to investors and financial institutions in determining sovereign credit risk germane to corporate financial risk, for the construction of debt and equity portfolios, and hedging considerations in today’s dynamic environment.

This paper focuses on analysing and modelling inflation and its dynamics in Czech Republic applying a special kind of econometric models. Firstly economic theory of inflation is mentioned - fundamental terms, measuring methods of inflation, the way Czech national bank is monitoring the inflation and obviously a short summary of historical evolution of inflation in Czech economy. In the second part of this paper two econometric concepts of modelling time series are introduced - vector autoregression models (VAR models) and volatility models, concretely ARCH and GARCH models. In connection with the VAR models, Granger causality, impulse response functions, cointegration and error correction models are described. The empirical part includes application of selected models on real time series of chosen macroeconomic indicators. The estimation outputs are interpreted and forecasts are implemented. The quality of chosen econometric models for modelling inflation in Czech Republic is discussed.