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Compass maritime case study essay

Executive Summary This report will show the methodology, analysis, concerns and final solution to the proposed problem of pricing the Bet Performer, a capesize bulk carrier. The Bet Performer is an 11 year old vessel, featuring 172, 000 deadweight ton capacity, originally built by Nihon Kokan Kabushiki-Kaisha of Japan. The most recent sale of this ship occurred in 2006 for $70 million. After a series of regression analyses including a multiple regression analysis accounting for the recent rise in the Baltic Dry Index, I have arrived at a recommended price of $109. million. This value accounts for all of the variables provided and gives our client the best chance at securing the Bet Performer for its current market value. Problems Faced Compass Maritime is facing a difficult decision regarding how to price the Bet Performer. There are many factors that must be included in the final decision, including the age of the ship, its deadweight ton capacity, the original shipbuilder, as well as the mechanicals underpinning this particular ship. The type and build of the ship is only one issue facing Compass Marine.

Another issue faced is determining what qualifies as a comparable ship, and what qualifies as a ‘ recent’ transaction. According to the data presented, there have been forty-eight ships sold in the previous seventeen months. Although this appears to be a substantial amount of transactions from which to procure data, the recent surge in the Baltic Dry Index for Bulk Carriers and the associated surge for capesize ships demands attention and should be factored into the analysis as well. Also the data provides only a small portion of specifics relating to the comparable ships.

Factors such as confirmed time charter contracts, location of the ship, loading equipment, and other specifics which could affect the prices of these ships has been left out. Methodology When determining a price for a ship such as the Bet Performer, it is important to utilize various types of analysis, including comparative analysis and regression analysis. While comparative analysis would usually be useful, because of the recent surge in the Baltic Dry Index, and the multitude of variables available for analysis, it was deemed inappropriate for this situation.

Therefore a series of regression analyses were used, ending in a multiple regression accounting for all variables provided for by the data given. The Analysis portion will go into further detail. Data Requirement In order to determine an optimum price and negotiation strategy for the purchase of the Bet Performer, historical data regarding recent sales transactions of comparable ships was necessary. The most pertinent data that was collected from the recent sales transactions include the age of the ship sold, its sales price, and its deadweight ton capacity. This information is contained in Appendix A.

The other required data was the information about our target ship, the Bet Performer. Its information is detailed in Appendix B. Key Assumptions In order to determine the fair market value of the Bet Performer, and more importantly a value that would yield a price acceptable to the sellers, a few key assumptions were made. First, it is assumed that the market for charter rates for 170K DWT capesize ships will remain steady at almost $250, 000 per day. That is important because the investor will need to perform its own financial analysis to determine whether or not to go ahead with the purchase at the recommended price.

Second, it is assumed that the global economy will remain growing at a steady pace, pushing the demand for shipping vessels higher. This is important because if there were to be a sudden slowdown in the global economy, shipping rates could possibly decline, leaving the buyer with a vessel worth less than the purchase price. A third assumption is that the client will be able to obtain financing for the vessel. Although credit markets have been relatively open recently, it is still something to consider.

A fourth assumption is that the Bet Performer will be useable for a ‘ typical’ lifespan of 25 years. This promises our buyer at least 14 years of useful life left. Analysis Initial analysis focused on single-regression analysis, utilizing only one variable at a time. The first analysis involved the price of the ship sold as a function of its age at the time of sale. This analysis returned an Adjusted R-squared score of 0. 61184. Although this is a relatively strong score, it was determined to not be strong enough, and it also leaves out an important variable, the size of the ship.

The next round of analysis tried to determine an optimum price by finding the price as a function of the vessels size (DWT. ) This analysis returned an Adjusted R-squared score of 0. 249047. Again, while this is a low R-squared score, it was noted that it left out other important variables, such as the age of the ships and how recent the transaction was. Next, a multiple regression analysis was performed, using the ships age at time of sale and DWT capacity to determine a price. This multiple regression returned a stronger Adjusted R-squared correlation of 0. 42638. Although this method did incorporate two of the most important factors in the pricing of capesize ships, it leaves out how the increase in the Baltic Dry Index has impacted the price of the ships. The next round of analysis attempted to include all of the variables associated with the purchase of the Bet Performer, including the age (11 years old,) its Dead-Weight Tons capacity (172, 000,) as well as factoring in the recent surge in Baltic Dry Index for Bulk Carriers. This was done utilizing a dummy variable.

The surge in the index occurred after June, 2007, so for all sales starting in July 2007 a dummy variable of 1 was introduced, and all sales prior to that received a dummy variable of 0. After running the regression analysis with this new variable introduced to account for the change in the market landscape, an Adjusted R-squared coefficient of 0. 901814 was returned. This demonstrates that utilizing the dummy variable has returned a much stronger correlation. It was this analysis that delivered our equation of Price=(-4. 62538*age)+(. 271862*DWT)+(35. 08358*DV)+78. 1402, where DV is the Dummy Variable, either a 0 or 1. Since the purchase of the Bet Performer would occur after June 2007, we use a 1 in the equation to account for the rise in recent sales prices. Appendix C, Exhibits 1-4 outline each regression analysis, and Exhibit 5 is a breakdown of each suggested price derived from the analyses. Conclusion and Concerns Some concerns that will surface during this negotiation and pricing include the condition of the Bet Performer, any pre-purchase inspections that need to be completed, and how many other potential buyers there are.

Although it will be impossible to know how many other buyers are out there, if we bid too low, there is a chance we may not receive a counteroffer, and therefore lose the opportunity altogether. It is thought that through this analysis we will provide our buyer the best chance to purchase the Bet Performer, balancing the current market conditions with the specifics of the vessel. It is my conclusion that a suggested bid price of $109. 2 million will give our client its best opportunity to purchase the Bet Performer. Compass Maritime Case Study MBA 603 2/21/2012 Andrew Schneider

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