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Econometric Analysis of Bulk Shipping Markets Implications for Investment Strategies and Financial Decision-Making

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Econometric Analysis of Bulk Shipping Markets Implications for Investment Strategies and Financial Decision-Making Econometric Analysis of Bulk Shipping Markets Implications for Investment Strategies and Financial Decision-Making Econometrische analyse van de maritieme vervoersmarkten voor bulkgoederen implicaties voor scheepvaartinvesteringen en financiële besluit vorming Thesis to obtain the degree of Doctor from the Erasmus University Rotterdam by command of the Rector Magnificus Prof.dr. S.W.J. Lamberts and in accordance with the decision of the Doctorate Board The public defence shall be held on Thursday 9th of June 2005 at 11.00 hrs by Stavros Tsolakis Born at Katerini Pierias, Greece Doctoral Committee Promotors: Prof.dr. H.E. Haralambides Prof.dr. P.H.B.F. Franses Other Members: Prof.dr.ir. R. Dekker Prof.dr. R. Mariano Prof.dr. S.P. Strandenes Executive Summary This thesis provides an econometric analysis of the bulk shipping markets and the implications for shipping investment and financial decision making. Chapter 1 sets the scene by providing a historic analysis of bulk shipping markets over the last 55 years. From this analysis, four shipping markets (freight, newbuilding, second-hand and demolition) are distinguished as well as a fifth one (ship finance) that acts as a facilitator to the other four. Also, with the help of correlation analysis, the factors influencing these markets are identified. The chapter then considers five critical interdependent forces (economic structure, ship supply and demand capital flows expressed by investor preferences and investment performance) that comprise the shipping market and move in cyclical patterns. This way, the chapter explains the role of the shipping cycle in devising investment strategies. Based on this analysis, Chapter 1 ends by defining the thesis aim and objectives. Chapter 2 presents the thesis methodology. It critically analyses the methods used in the collection of data and the interpretation of it, as well as the problems experienced while collecting it. The four subsequent chapters present the results from the analysis of the four shipping markets (freight, newbuilding, second-hand and demolition). Based on theory, Error Correction Models describing and quantifying the relationships between the variables are developed for all four markets. This way the thesis fills a gap in maritime economics literature by estimating models where none of the CLRM assumptions are violated. Consequently, statistical inferences from these models can be made safely. Furthermore, by disaggregating into the different ship types according to size, the thesis finds that different variables have different effects on each type, thus proving that each ship type has its own distinctive characteristics. Finally, chapters 4 to 7 compare different econometric methods, the theoretical Error Correction and the atheoretical family of Auto Regressive Moving Average (ARMA) models. It is found that theoretical models, are still to be preferred if one wants to achieve the classical objectives of Econometric Business Cycle Research simultaneously (to describe and forecast cycles and to evaluate policies and test economic theories). However, if not all goals have to be met with a single vehicle, other methods might serve the purpose equally well or even better as is the case with the Auto Regressive Moving Average method whose forecasts outperform those of the ECM method on many occasions. With respect to the period or time charter market, the thesis finds that spot rates are the major determinant for period ones. This indicates the validity of the pure expectation hypothesis of the term structure relationship between spot and period rates. However, this hypothesis is not always valid since on two occasions (Panamax bulk carriers and Aframax tankers), fleet changes, a variable incorporated in the model to depict market changes and risks, is found to be statistically significant. This leads to inconclusive evidence regarding the validity of the pure expectation hypothesis of the term structure relationship and needs further investigation. Finally, it is found that the forecasting ability of the models for the timecharter market is superior to that for the freight market. This can be attributed to the dominance of the stochastic component of the spot rates over the deterministic one, which makes their accurate forecasting a very difficult task. As far as the econometric analysis of new vessel prices is concerned, shipbuilding costs are found to have the most significant effect on the determination of newbuilding prices for all ship types. Time charter rates have an effect only on few ship segments. This is in line with theory that newbuilding prices are cost driven i rather than market driven as second-hand ship prices are. It is also found that actual exchange rates do not affect shipbuilding prices but cost variations due to exchange rate fluctuations do. Orderbook as a percentage of the fleet, used as a proxy for shipyard capacity due to data discrepancies and lack of long enough time series for the later, is found significant only for tankers indicating that shipyards' expansion policy is aimed at high value ships like tankers rather than bulk carriers. Finally, newbuilding prices for some ship types may be driven to a certain extent by asset pricing and speculation. Newbuilding and timecharter rates have the greatest effect of all variables on the determination of second-hand prices, in most cases both in the short and the long run. The cost of capital is only significant for bulk carrier owners. The only exception is the Suezmax segment. Suezmax prices have been closely pegged to VLCCs with a discount but not proportional to the size. In other words Suezmaxes are rarely bargain vessels. Second-hand prices of Suezmaxes could therefore be more closely tied to newbuilding prices than for other tanker sizes. Finally, orderbook as a percentage of the fleet has a negative effect on the prices of second-hand vessels only in the long run and only in large and Panamax tankers. The thesis also finds that demolition prices are primarily driven by market conditions and expectations. In addition, the price of scrap steel is also found to have a significant effect on VLCCs due to increasing demand for scrap steel that makes demolition traders eager to offer higher prices for larger tankers to satisfy demand. Finally, it is found that the volume of scrapped ships has a negative effect on the demolition price of medium and large tankers. This is due to new legislation usually stemming from an accident or environmental campaigns that may force shipowners to scrap their ships earlier than they had originally anticipated. Shipowners invest in different ship markets and vessel sizes in the expectation of achieving a reduction in risk via the resulting diversification in their income. However, it is frequently observed that shipping companies focusing on a particular ship type achieve equally good or even better risk levels than those investing in various ship types and size. A question therefore arises whether such diversification strategies really reduce the investor's risk. This thesis investigates the potential of risk reduction benefits for a bulk shipping investor through diversification. It first analyses the traditional risk reduction approach of calculating the variance and the standard deviation of a portfolio. Results show that risk reduction benefits are achieved through diversification. Then, the thesis builds upon the shortcomings of correlation, namely the fact that while markets may tend to diverge considerably in the short-run, like periods of up to a year, they may actually be integrated over longer periods. If the income, expressed in time charter equivalent rates, of the various ship types or sizes is very strongly correlated in the long run, diversification will be less effective than if the ship markets or segments operated independently of one another. An important indication of the degree to which long run diversification is available to shipping investors is given by determining whether the markets are cointegrated. The thesis employs the Johansen method on 247 different combinations of investment in the dry and wet bulk markets. It finds that investing in more than one type of bulk carrier nullifies any risk reduction benefits. Furthermore, risk reduction benefits decrease as diversification increases with no risk reduction benefits obtained when investment involves more than five different ship types/sizes. These results initially seem to be in contrast with portfolio theory which claims that risk reduction benefits increase with higher diversification. However, the reason behind this difference lies with time horizon and the results actually ii supplement the theory of risk reduction through diversification by showing that the benefits of diversification in most cases may exist in the short run but disappear in the long run. Finally, finding such long run relationships supports the existence of inefficiencies in the shipping freight market, a finding in line with previous research. This thesis also develops an analytical tool for shipmanagers to measure the possible losses, within a specified time horizon and confidence interval, of their portfolios by calculating Value at Risk with the variance-covariance, historical and Monte Carlo simulation methods. This tool allows managers to identify the extent to which each asset contributes to these possible losses, as well as get an idea of the maximum possible losses should the worst case scenario occur. Based on this framework, shipping firms can
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