DETERMINANTS OF RAIL ROLLING STOCK VALUE AN ANALYSIS OF THE DETERMINANTS OF LOCOMOTIVE AND FREIGHT WAGON VALUE IN THE EUROPEAN MARKET MAXIME BONNIER DELFT, 14 JANUARY 2019 MASTER THESIS TRANSPORT, INFRASTRUCTURE AND LOGISTICS i DELFT UNIVERSITY OF TECHNOLOGY ii DETERMINANTS OF RAIL ROLLING STOCK VALUE AN ANALYSIS OF THE DETERMINANTS OF LOCOMOTIVE AND FREIGHT WAGON VALUE IN THE EUROPEAN MARKET FRONT COVER LOCON 9905 in the evening sun at the temporary container terminal in Almelo on March 21, 2012. This locomotive started its second life through a second-hand transaction, 29 years after the manufacturer completed it. Built by Alsthom for Dutch national operator NS in 1982, locomotive 1836 was sold to private rail freight operator LOCON Benelux B.V. in October 2011. Subsequently, the locomotive was repainted and renumbered in 9905. In September 2017, when LOCON Benelux B.V. faced bankruptcy, Rotterdam-based rail fleet management company RailReLease B.V. acquired it. At that time, locomotive 9905 was still going strong at an age of 35 years, showing the potential of second-hand rail vehicles. PHOTO COURTESY Henk Zwoferink Fotografie iii iv DETERMINANTS OF RAIL ROLLING STOCK VALUE AN ANALYSIS OF THE DETERMINANTS OF LOCOMOTIVE AND FREIGHT WAGON VALUE IN THE EUROPEAN MARKET MAXIME BONNIER BSC DELFT, 14 JANUARY 2019 IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN TRANSPORT, INFRASTRUCTURE AND LOGISTICS AT DELFT UNIVERSITY OF TECHNOLOGY v vi ABOUT THE STUDENT Maxime Bonnier Master Programme: Transport, Infrastructure and Logistics Student Number: 4006100 Contact: maximebonnier(a)gmail.com CHAIR ASSESSMENT COMMITTEE Prof.Dr. G.P. (Bert) Van Wee Section: Transport and Logistics Department: Engineering Systems and Services Faculty: Technology, Policy and Management Organization: Delft University of Technology 1ST SUPERVISOR Dr. E.J.E. (Eric) Molin Section: Transport and Logistics Department: Engineering Systems and Services Faculty: Technology, Policy and Management Organization: Delft University of Technology 2ND SUPERVISOR Prof.Dr.Ir. Z. (Zili) Li Section: Railway Engineering Department: Structural Engineering Faculty: Civil Engineering and Geosciences Organization: Delft University of Technology Electronic copy available at: http://repository.tudelft.nl Copyright ©2019 Maxime Bonnier vii viii PREFACE The completion of this thesis marks the end of an important chapter in my life, as it is the end of my time as a student at the Delft University of Technology. At the same time, the page is turned to a new exciting chapter, as it flags the start of a professional career. It would never have been possible for me to write this thesis without the encouraging support, guidance and advice from others. First, I would like to express my gratitude to Wouter Radstake from DVB Bank SE and Bernd Wagner from Beacon Rail Leasing Ltd. for their time and willingness to support by giving insight in some general aspects of the practice of rail vehicle valuation. Finally, I would like to thank my supervisors for their time, constructive feedback and advice. On a more personal note, I would especially like to express my gratitude to my parents Hans and Marianne Bonnier for the at times much needed motivation, their trust, tips and tremendous support. Special thanks also go out to Dr. Lee Bouwman and Vivian Bouwman for their motivational speeches and advice. Furthermore, I must thank Denisa Krechlerová for her help with the translation of Czech documents containing rolling stock data that proved difficult to translate using digital tools alone and Henk Zwoferink for making a cover photo available. Finally yet importantly, I would like to thank all other family members and friends that have supported me during the writing of my final work at the Delft University of Technology. Delft, 14 January 2019 ix x ABSTRACT Liberalisation of the rail market in Europe has made the rail vehicle market more dynamic. Since the nineteen-nineties, the European Economic Community (now the European Commission) has aimed at increasing the competitiveness of rail transport. By reducing entrance barriers and increasing interoperability of the rail system, the number of active operators received a boost. The development of standardized vehicle platforms for Europe-wide operations and the creation of rail vehicle leasing companies has further facilitated the entry of new rail operators to the market. DVB Bank (Metz & Radstake, 2013) estimates that the total investment in new rail vehicles in Europe amounted circa eight billion euros in 2013. More parties active on the demand side of the rolling stock market has resulted in more second-hand transactions. To quickly increase transport capacity in times of increasing demand – supported by the time-consuming and costly certification process for new vehicles in other countries – rail operators increasingly eye second-hand vehicles. The respective sizes of the markets for new and used vehicles in 2013 are presented in Table 1. TABLE 1: MARKET SIZE NEW AND USED RAIL VEHICLES VEHICLE TYPE NEW SECOND-HAND Multiple units and rail cars 900 80 High speed trains 50 - (unknown) Passenger coaches 400 80 Locomotives 800 300 Freight wagons 10,000 - (unknown) Source: Metz & Radstake (2013) Determined by means of straight-line depreciation, rail vehicle selling prices depend mainly on the book value and thus age. Mostly determined by an appraiser, a deviation factor is added to include technical characteristics and condition of the vehicle, under certain market conditions. Finally, the interaction between supply and demand determines the fair market value. This process may be costly and time-consuming for large and/or spread-out fleets, especially as railways are very capital intensive. Better estimation of vehicle values can reduce financial risks when making investment choices by reducing over- and under-pricing. Faster and more accurate valuation is also of interest for other involved parties, such as insurance companies and finance companies. RESEARCH AIMS AND APPROACH Within the rail industry, there is growing interest in more accurate, efficient and automated valuation approaches, based on market and rolling stock specific factors. Such approaches readily exist in ship and aircraft valuation, offering financial and efficiency benefits to vehicle owners, lessors, banks, investment funds, producers and insurance companies, and facilitating a dynamic and competitive vehicle market. Scientific theory identifies five broad explanatory factors influencing mobile asset value: Sectors (groups of vehicles with sufficiently similar economics to be modelled together) Age Size Earnings (or a different market related factor) Technical features. This thesis aims to support this improvement in rail vehicle valuation by filling a scientific gap, as up until now scientific focus has been mainly on ships and aircraft, whilst this field of research has remained largely uncharted for rail vehicles. Therefore, the following main research question has been formulated: xi 1. What are the main determinants of locomotive and freight wagon value; and 2. how does locomotive and freight wagon value depend on these factors economically and statistically? This twofold question comprises a qualitative and a quantitative part. In the former, academic and professional literature are reviewed to find suitable notions for the five broad explanatory factors for use in rail vehicle valuation, considering possible analogies with aircraft and ship valuation. Additionally, a number of explanatory factors specific to rail are identified and existing economic principles are established. Combined, it provides a framework for the use of statistical data analysis to support theoretical findings and to identify the dependence of rail vehicle value on the identified explanatory factors according to the framework model as visualized in Figure 1. FIGURE 1: RESEARCH FRAMEWORK In a first step of the quantitative part of this thesis, the aspects of data availability and quality are addressed. The viability of quantitative research builds on the availability of sufficient data to determine the relevance of possible determinants of rolling stock value validly. Data availability highly influences the scope of the research and the analysis possibilities. As such, this step functions as an input filter for the actual statistical data analysis. Using multiple regression, the statistical data analysis employs a combination of the first statistical findings and theoretical knowledge. The advantage of this technique is the possibility to combine both quantitative and qualitative variables. By means of a theory-driven trial and error approach, a basic valuation model is extended systematically into more elaborate models. Here, the goal is to achieve parsimonious models to warrant high validity of the results. Subsequent verification, (visual) evaluation and validation ensures that the outcomes are valid and generalizable. This diagnosis of the results aids in identifying if the assumption of linearity is indeed in place for the individual relations and the value function as a whole. Furthermore, it allows to draw conclusions about the dependence of locomotive and freight wagon value on these factors. DETERMINANTS OF RAIL VEHICLE VALUE, THE RESULTS Collected from a variety of sources, ranging from professional railway media, investment funds and online market places, 128 locomotive and 98 freight wagon transactions, closed between 2004 and 2016, were used for analysis.