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In this paper, we study on the stock indexes return¡¦s dependence structure of the U.S. versus other G5 members during the 2008 subprime mortgage financial crisis. The sample series are weekly returns of the MSCI stock price indexes from 2003 to 2011. The model structure is combined with marginal model and copula model. We model the marginal distributions of our returns using the univariate skewed Student t AR¡]1¡^-GARCH model of Hansen¡]1994¡^, and we model the time-varying copula of Patton¡]2006¡^to measure the dependence structure between stock indexes returns. By analyzing the time series behavior of the dynamic copula parameters, we find that,¡]1¡^the dependence of stock indexes returns increased significantly between U.S. and other G5 members in early subprime mortgage financial crisis, which means the dependence structure has contagion effect.¡]2¡^Except the dependence structure between U.S. and Japan, the other dependence structure between U.S. and other G5 members in later subprime mortgage financial crisis have the phenomenon of interdependence, and their average tail dependence increased significantly.¡]3¡^By the above, international portfolio constructed by correlation coefficient will failed to diversify the downside risk and the systematic risk will be increased in financial crisis period, which is similar with the 2008 subprime mortgage financial crisis. Therefore, the construction of an international portfolio must consider the asymmetric dependence structure between the stock indexes returns.

This dissertation consists of two papers. The first paper examines the propagation of firm-specific shocks as well as market-wide shocks between 1995-2003 using Treasury and corporate bond market data. It then tests the implications of previously proposed models of contagion. I find little support for the industry and counterparty structure hypothesis, suggesting that fundamentals do not generate contagion. Consistent with the information transmission, rebalancing, and liquidity-shock hypotheses, I find evidence of flight to quality during the event periods. However, in contrast to the prediction of the liquidity-shock channel, the corporate bond market, on average, seems to be more liquid during event periods (evidenced by higher trading volume, trading frequency, and mean bond age). Furthermore, there are no significant changes in the trading of assets with the low transaction costs, which is contrary to the rebalancing theory. These findings are more in favor of the correlated information channel as a means of inducing contagion.The second paper examines the effect of liquidity on corporate bond prices using the newly formed TRACE data set. In the spirit of Acharya and Pedersen's (2005) liquidity-adjusted capital asset pricing model (LCAPM), I examine the impact of multiple sources of risk on corporate bond prices. The results do not lend strong support for the existence of liquidity risk in the corporate bond market or for the LCAPM, especially when liquidity is captured using the trading frequency, trading volume, and turnover. Contrary to the predictions of the LCAPM, more illiquid portfolios do not have higher values for the three liquidity betas; betas that capture the commonality in liquidity with the market, the sensitivity in returns with the market-wide liquidity, and the liquidity sensitivity with the market returns. Furthermore, after running cross-sectional regressions I do not find strong evidence either for the validity of the model or that liquidity risk does matter for the corporate bond prices.

Thesis (Ph. D. in Management)--Vanderbilt University, May 2007. / Title from title screen. Includes bibliographical references.

We study systemic risk in a network model of the interbank market where the asset returns of the banks in the network are correlated. In this way we can study the interaction of two important channels for systemic risk (correlation of asset returns and contagion due direct financial linkages). We carry out a simulation study that determins the probability of a systemic crisis in the banking network as a function of both the asset correlation, and the connectivity and structure of the financial network. An important observation is the fact that the relation between asset correlation and the probalility of a systemic crisis is hump-sharped; in particular, lowering the correlation between the assets returns of different banks does not always imply a lower probability of a systemic crisis.

This thesis contributes to the literature of asset comovement and crisis contagion in several aspects. First, it extends the study of contagion using an asset pricing framework to the two recent crises: the Global Financial crisis and the European debt crisis, and to a wider set of markets, including both developed and developing markets in order to compare and contrast the effects of different crises on different markets. Second, the thesis studies in detail the time-varying patterns of integration during crisis episodes. An interesting finding is that markets tend to become segmented during the latter half of a severe crisis. In other words, if a crisis is strong enough it can hamper the integration process. Such behaviours are observed in both developed and developing markets. Third, the thesis investigates the comovement and contagion of style portfolios in response to increasing interest in style investing. More specifically, it examines if portfolios sorted based on different firm characteristics exhibit different integration and contagion behaviours during different crises and finds distinct differences in the impact on integration and level of contagion from each crisis. The estimated results indicate complex integration patterns which have strong impacts on diversification. Similar to country portfolios, style portfolios also become segmented during the crises. Although contagion signals are detected, there is no clear evidence regarding which portfolios are more prone to contagion. Finally the thesis studies the behaviours of both time-varying global and regional integration patterns of each industry sector overtime and during each financial crisis and examines cross-region contagion for all the industries in the world. Empirical results provide evidence that contagion can occur in the same industry across region. Hence the result supports diversification across different industries across different regions rather than holding stocks of the same industry across regions.

This thesis studies the time evolution of a computer mediated community called FidoNet. The introduction explains what FidoNet is, briefly details its history and sociological significance and sets out research goals for the thesis as a whole. The second chapter-covering background and relevant literature-relates FidoNet to other social phenomena and reviews relevant sections of work on dynamic approaches to social systems. It also describes how FidoNet Nodelists were combined with geographic data on US telephone lines and 1990 Census data so that the geographic growth and decline of FidoNet could be mapped and analysed. The third through fifth chapters are substantive starting with an empirical analysis on the spatial growth of FidoNet in the United States, covering a variety of different ways in which distance could have mediated the contagiousness of FidoNet as a system. The fourth considers decline as a similarly contagious process, demonstrating that FidoNet's most obvious competitor-the internet-may in fact have discouraged its decline while the short-term influence of leaving events on current sysops fits the data far better as an explanation. The other explanatory variable of this section-long-term social influence-exhibits an unexpected sign, suggesting that perhaps there were incentives to maintain FidoNet that were most prevalent in the long-term. The fifth chapter attempts to tease out which different mechanisms may have been at work during decline, using an Agent-Based Modelling (ABM) approach and specifically considering individual rather than aggregated behaviour. The 6th and final chapter summarises the findings.

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The problem of influence maximization has been studied extensively with applications that include viral marketing, recommendations, and feed ranking. The optimization problem, first formulated by Kempe, Kleinberg and Tardos, is known to be NP-hard. Thus, several heuristics have been proposed to solve this problem. This thesis studies the problem of influence maximization under the deterministic linear threshold model and presents a novel heuristic for finding influential nodes in a graph with the goal of maximizing contagion spread that emanates from these influential nodes. Inputs to our algorithm include edge weights and vertex thresholds. The threshold difference greedy algorithm presented in this thesis takes into account both the edge weights as well as vertex thresholds in computing influence of a node. The threshold difference greedy algorithm is evaluated on 14 real-world networks. Results demonstrate that the new algorithm performs consistently better than the seven other heuristics that we evaluated in terms of final spread size. The threshold difference greedy algorithm has tuneable parameters which can make the algorithm run faster. As a part of the approach, the algorithm also computes the infected nodes in the graph. This eliminates the need for running simulations to determine the spread size from the influential nodes. We also study the target set selection problem with our algorithm. In this problem, the final spread size is specified and a seed (or influential) set is computed that will generate the required spread size. / Master of Science