@MASTERSTHESIS\{IMM2013-06541,
    author       = "J. R. Thorsgaard Steen",
    title        = "Optimal freight rate management for {VLCC}",
    year         = "2013",
    school       = "Technical University of Denmark, {DTU} Compute, {E-}mail: compute@compute.dtu.dk",
    address      = "Matematiktorvet, Building 303{-B,} {DK-}2800 Kgs. Lyngby, Denmark",
    type         = "",
    note         = "{DTU} supervisors: Kourosh Marjani Rasmussen and Lasse Engbo Christiansen, laec@dtu.dk, {DTU} Compute",
    url          = "http://www.compute.dtu.dk/English.aspx",
    abstract     = "The objective of the thesis is to develop a stochastic framework as a practical decision support tool for managing {VLCC} chartering, and to analyse the efficiency of such a framework. The efficient managing process, determined by the modelling framework, is within the usage of {FFA} contracts in fixing future prices on voyage contracts. Prices on voyage contracts are determined by a volatile spot market, which can be hedged using {FFA}’s. The work is divided into three different parts with the main purpose of developing a stochastic programming model. The three parts are divided into a presentation of the freight rate market and financial derivatives, the development of a statistical framework making predictions in spot rates and the development of a stochastic programming model making allocation decisions. The scope of the thesis is limited by the lack of previous prepared studies in the dirty tanker freight rate market.
When it comes to the usage of financial derivatives in the tanker market, studies are almost none existent. Only very few studies has been made to introduce the derivative market. The thesis therefore introduces the derivative market in the form of introducing Forward Freight Agreements and {FFA} Options. It is examined how the financial derivatives are structured, with the purpose of disseminating knowledge of financial derivatives in the market, and to examine the efficiency and limitations in using derivatives, such as lack of liquidity. Furthermore, the entire set-up of doing {VLCC} chartering is examined to give the reader the understanding of the chartering process. The work is based on the Dirty Tanker 3 (TD3) index published on the Baltic Exchange, in the form of Worldscale points.
A minor statistical analysis is made on the dirty tanker index with the purpose of developing a statistical framework in which to make reasonable predictions on the future level of freight rates. There has not yet been made any studies that determines a precise way to make predictions on tanker freight rates. It has therefore been chosen to make a well known time series analysis on the TD3 index. It has been examined how autoregressive processes and {ARMA-GARCH} processes performs in the freight rate market. It seems that none of these processes perform significantly better than a simple bootstrap method. The bootstrap method has therefore been chosen in the thesis as the most adequate choice of making predictions on the TD3 index, even though it is a very naive way of doing predictions.
The final work of the thesis is to develop a stochastic programming framework, in which to make optimal decisions on how to manage {VLCC} chartering. The framework adopted in the thesis is a well known decision model in financial engineering, proposed by Stavros as a CVaR programming model. The model optimizes the expected income of the chosen strategy, and minimizes the down side risk exposure in terms of Conditional Value at Risk. The results from implementing and analysing the framework on prior historical records seem reasonable. It is very clear that introducing {FFA} in the managing process is indeed controlling risk exposures in a positive way. All strategies including {FFA}’s seem to outperform strategies without using {FFA}’s, both in risk exposure and in expected income."
}