| In recent years, as influenced by the international financial crisis and the elapse in global trade, we have witnessed that the international dry bulk shipping industry reached its historical boom and its collapse soon after. As the upstream industry to dry bulk shipping industry, the world dry bulk vessel market also went through a roller coaster—vessel prices rose gradually and dropped suddenly. The scenarios happened more than once in the past decade. Till now, the world dry bulk vessel market is still in the market downturn, oversupply pervades in the industry, and vessel prices are always in the low level. Under this circumstance, vessel prices are very volatile, hard for practitioners to capture its characteristics. However, it is crucial to detect the real price volatility characteristics and understand the volatility mechanism, as the inherent volatility rules could guide investors and researchers for making investing decisions and better knowing the market. For such purpose, this dissertation will try to explore the reasons causing vessel price volatility and price volatility mechanism, as based on the fact of the time-varying external economic environment.This dissertation first did the literature review in the research areas of shipping economics, shipping finance, vessel economics and vessel finance. Some preliminary conclusions could be summarized that the past research was mainly focused on dry bulk shipping freight rate volatility modeling, vessel price formation and vessel price valuation, etc. Little attention has been paid on the areas of vessel price volatility mechanism analysis, volatility characteristics modeling under certain circumstances and cross-market volatility time-lag effect identification. Hence, targeting on the aforementioned ―neglected research areas‖, this dissertation will conduct a relatively thorough study to investigate those issues.According to the assumptions, this dissertation conducted the 1ststage study from the perspective of causes of vessel price volatility, by designing econometric volatility models to investigate the dynamics between vessel price volatility and other factors, especially the freight rate volatility. A model based on GARCH(1, 1) has been proposed and key factors such as freight rate volatility, shipbuilding cost volatility, the percentage of order to fleet size volatility and exchange rate volatility has been selected to be incorporated into this model. Then the newbuilding vessel price volatility was applied as an example of vessel price volatility to test the dynamic interactions. Using the sample data from 2001.01 to 2012.11, empirical analysis has been conducted. The results revealed that undoubtedly, freight rate volatility was the most important causing factor to vessel price volatility, and freight rate volatility affects vessel price volatility positively significantly. That means, an increase in the volatility degree of freight rate could induce a more volatile vessel price. Besides, the results also revealed that the percentage of order to fleet size volatility was another important positive factor to vessel price volatility. Generally, through this empirical analysis, it could be found that for every vessel type, except the critical cause factors—freight rate volatility and percentage of order to fleet size volatility, exchange rate volatility and shipbuilding cost volatility are conditional important cause factors, that is, only for some certain vessel types, they could impose significant influences on vessel price volatility, or they could only be normal factors. Another interesting phenomenon could be read from the empirical results: newbuilding and secondhand vessel price volatilities were not significantly affected, and this revealed that there may exist time-lag effects between the 2 volatilities, which derive the subsequent study for this dissertation.Then after examining the influences between the vessel market and other markets, especially the freight market, the dissertation turned its focus to the 2ndstage study: intra-market volatility modeling. Concerning the fact that during the sample period(2001.01-2012.11), the world has witnessed a certain number of global economic, political and financial events, such as 2008 world financial crisis, the world dry bulk vessel market is believed to suffer structural changes due to drastic external shocks. Structural changes to dry bulk vessel market may lead to structural breaks in the price volatility time series. In this section, this dissertation first applied the Bai & Perron method and modified ICSS algorithm to examine the structural break effects in the price volatility mean equation and variance equation. Empirical results show that there exist mean structural break points and variance structural break points for all types in both newbuilding and secondhand vessels. This finding confirmed my hypothesis that structural breaks did happen in the dry bulk vessel market. Then, a modified GARCH model with dummy variables both in the mean equation and variance equation based on the classic GARCH(1, 1) model has been proposed to re-examine the vessel price volatility characteristics. Empirical results show that when considering the structural break effects, the volatility properties present significant difference to the scenarios when neglecting structural break effects. See, for all vessel types, the volatility persistence of vessel price has declined significantly with structural break effects, meaning that there was pseudo-volatility persistence in the world dry bulk vessel market when structural break effects are not taken into consideration. Besides, for each vessel type, the volatility clustering effect also declines when taking structural break effects into account. These findings could help to fill the bridge in the current research in the vessel price volatility modeling.At last, with the findings in the above 2 stage study, on the 3rdstage, this dissertation explored the time-lag effect between the newbuilding and secondhand vessel price volatilities. The study started from the perspective of volatility spillover to detect the lead-lag effect(time-lag effect). To detect the volatility spillover direction, a multivariate GARCH model—BEKK-GARCH model was applied in this section. The preliminary empirical results show that for most vessel types(Capesize, Panamax, Handymax), the volatility spillover is from newbuilding market to secondhand market, that means the newbuilding vessel price volatility leads the secondhand vessel price volatility. Only in the Handysize market, the volatility transmission direction is from secondhand market to newbuilding market. However, as concerned in the 2nd stage, under the structural break effects, the price volatility properties have greatly changed. Hence, the study for volatility spillover should also be conducted in the framework of structural break effects. Considering the structural break effects, a structural break volatility spillover model has been proposed in this dissertation as dummy variables of structural break points has been incorporated in both the mean equation and variance equation. The further empirical results reveal that under the structural break framework, the volatility spillover mechanism has greatly changed. For Capesize and Panamax types, the price volatility spillover effects are still from newbuilding market to secondhand market, however for Handymax and Handysize types, the volatility transmission is from secondhand market to newbuilding market. Besides, structural changes could change the sensitivity of vessel price volatility(newbuilding and secondhand) to external shocks.In this dissertation, thestudy on dry bulk vessel price volatility characteristics is conducted. The findings may help to bridge the gap in the current literature on shipping finance, especially on vessel finance. Besides, the conclusions of this dissertation may help practitioners, investors and researchers better understand the world dry bulk vessel market in making investing decisions or doing risk management.
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