# Maritime Compass Llc

Table of Content

How much is the Bet Performer worth based on comparable transactions? What ship is the best reference transaction? (the closest comparable)? Comparable transaction is a conventional method of evaluating the value of something that is ready for sale. To value a ship, one had to identify a set of “comparable” ships where comparability was based on four main factors: ship type, size (DWT), age, and condition. The Bet Performer was a 11 year old ship, built in 1997, 172,000 DWT capsize bulk carrier.

From the Exhibit 4, there are five ships which are the most comparable to Bet Performer. They are Martha Verity, Ingenious, Sumihou, Cape Sun, and Coppersmith. These ships all have the most similar characteristics, in terms of ship type, DWT, ship age and gears. We have to have atleast 5 benchmark transactions to identify the purchase price. Sale Date Ship Name Ship Type DWT Year Built Age at Sale Gear Purchase Price Mar-07 Martha Verity Capesize ? 158. 0 1995 12 gearless ? \$63. May-07 Ingenious Capesize 170. 0 1996 11 gearless \$64. 2 Nov-07 Sumihou Capesize 171. 1 1996 11 gearless \$106. 0 Mar-08 Cape Sun Capesize 171. 7 1999 9 gearless \$135. 0 May-08 Bet Performer Capesize 172. 1 1997 11 gearless \$133. 0 Jul-08 Coppersmith Capesize 149. 7 1995 13 gearless \$101. The closet comparable transaction was that of Sumihou Capesize, and so Bet performer’s best reference/comparable transaction might be \$ 106 mln. 2. Regression Analysis a. What is the expected relationship between ship price and each factor listed in Exhibit 4 (size, age and charter rates)? What is the economic logic for why each factor might affect ship value? Relationship between Size and Ship Price: On running a regression analysis, we find that one ton change (increase) in the dead weight ton, results in an increase of \$ 0. 24 mln in the ship price. This is logical because, larger the ships, more load ould they carry, and thus make higher profits, so are priced higher. Relationship between Age and Ship Price: From the regression, we find that as the ship ages by one year, the price of the ship drops by \$ 4. 54 mln. This makes sense because as with any other vehicle or asset, the efficiency of the ship drops with age. As it gets older, the carrying value of the ship lowers due to depreciation. Relationship between Charter rates and Ship Price: With one point increase in the Capesize ship index, there is a slight increase in the price of the ship by \$0. 007 mln.

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The Capesize ships took like a year to build, and are good for 25 years, after which they are demolished and sold for scrap. The economics of this “ship breaking” differed by ship size and type category. So higher this index, higher is the price of the ship. b. Can you think of other factors that might predict ship prices? Apart from the 4 factors ship type, DWT, ship age and gears, there are a couple of other factors which affect the ship price. They are •Type of main engine, •Confirmed time charter contracts with creditworthy counter parties •Loading equipment (cranes and derricks) Shipyard (original builder) •Location (where the ship was at the time of sale) All these affected the price of the ship, and hence can be used to predict price. c. How well do all three factors explain ship prices? R2 is the percent of the total variation that can be explained by the regression equation, in this case the three factors that explain the ship prices. R2 here is 0. 92, which is very high, and means that these three factors can explain 92% of the total variation of the regression equation.

The largest value of R2 will always occur when all of the predictor variables are included, even if those predictor variables don’t significantly contribute to the model. R2 will only go down (or stay the same) as variables are removed, but never increase. The Adjusted-R2 uses the variances instead of the variations. That means that it takes into consideration the sample size and the number of predictor variables. The value of the adjusted-R2 can actually increase with fewer variables or smaller sample sizes. The Adjusted-R2 in this case is 0. 915.

The 3 factors very well explain the ship prices. d. Using all three factors, what is the predicted price for the Bet Performer? We use the Least Square method to predict the ship price. The model would be, Price= ? 0 + ? 1X1+ ? 2X2+ ? 3X3+€, where b0 = ^? 0= 44. 23, b1 = ^? 1= -4. 5, b2 = ^? 2= 0. 24, b3 = ^? 3= 0. 007. S= 9. 88. The equation is, price= 44. 23+ age*-4. 5 + DWT*0. 24 + charter rates*0. 007. We first calculate ^y, and calculate the residual from this, which is (y-^y). The Least Squares estimates are the values that minimize the quantity, .

The observed variability of the responses about this fitted model is measured by the variance, and the regression standard error, . The sum of squares decomposition and the associated degrees of freedom are In this case, the predicted price for the Bet performer was found to be \$89. 5 mln. e. What would the price be if the Bet Performer were five years younger (6 years old rather than 11 years old), if the ship were 20K DWT smaller (150K DWT rather than 170K DWT) or if charter rates in May 2008 were 30% lower (the trailing Capesize Index were 8735 instead of 12,479)?

In each case, assume all other factors remain the same. 3. If you were Basil Karatzas, what would you recommend to your client regarding an offer price for the Bet Performer? Briefly explain your rationale. 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. 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. 2 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.