QBM-Ship Valuation Case

European University Quantitative Business Methods Case Study: Ship Valuation Professor Dawid Brychcy

Prepared By: Arif Ibrahimov Rola Ramadan Omar El Messaoudi Nosakare Ogbeifun

CASE SUMMARY Compass Maritime Services is a New Jersey based merchant having some expertise in the deal and buy of sea intersection vessels that convey mass merchandise. As of May 6, 2008, the Company got a call from a potential customer hoping to buy a particular vessel known as a capesize mass transporter. The business discovered that this specific capesize mass transporter, known as the Bet Performer, met the potential customer's details in that it was a 11-year old boat with 172,000 deadweight ton limit, had a Burmeister and Wain 6S70MC motor, had 9 holds and incubates and was implicit 1997 by a Japanese organisation. The Bet Performer was circumstantially sold 2 years before for $70 million and the present proprietors are hoping to offer it. The underneath contextual analysis includes seven inquiries around the correct valuation technique for the Bet Performer. 1. What are the key factors in ship valuation?

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Market approach -

This is based on clear market analysis and market price matching, takes into account the price of the most recent sale of a comparable vessel. Factors compared include: the type of vessel, age, size, and the condition which take into account the locations from which it docks to account for any wear and tear. Secondary considerations would be engine size, engine type, time charter contracts, loading equipment, shipyard, and location. In reference to Bet Performer, we can take into consideration the specifics of capsize bulk carriers in general. The typical carrier carries 170,000 DWT (up to 200,000 DWT), is 900 feet long, and has an average useful life of 25 years (must keep in mind the cost to retrofit the ship to bring it to 25 years).

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Income Approach- this method looks at the Net Present Value of future cash flows of the ship taking into account the daily charter rates in two ways: short-term or “rentals” and long-term or time-charters.

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Cost approach- takes a gander at the general expense to buy the vessel representing upgrades and alterations to meet current measures/regulations. Extra expenses will be incorporated for extraordinary or modified components. Ship Name

Price (in millions)

Age

Size (DWT)

Index

Zorbas II

$86.0

11

174.5

6,201

Fertilia

$50.0

10

172.6

6,201

Ingenious

$64.2

11

170.0

6,201

Sumihou

$106.0

11

171.1

9,663

Mean Price

$76.55

1. 2. How much is the Bet Performer worth based on comparable transactions? Which factors are crucial for comparing ships? Which ship is the best reference transaction (the closest comparable). From all of the comparable transactions done in the past 18 months, the above four were found to be the more comparable to each other. We chose these four ships based on the below: o Comparable dates: A range of one year above or below our ship, the Bet Performer’s 1997. o Comparable weight: A range for weight is 2,500 Tons above or below the Bed Performer’s 172,000 Tons.  Utilizing the four similar vessels, we calculated the normal mean of the cost in millions and found the Bet Performer's to be worth $76.55 million.  We also want to note, the Bet Performer sold for $70 million two years prior and as a general rule, that price can be used as the benchmark when comparing the Bet Performer’s resale value. REGRESSION ANALYSIS 3. What is the expected relationship between ship price and each factor – size, age and charter rate? What is the economic logic for each factor might affect ship value? Compare with the scatter plot of factor vs. prices. Below is the Regression data output for the formula Y = b0 + b1(x1) + b2(x2) + b3(x3) + E. We will examine the specific impact of each respective variable (age, weight and charter rate) below:

Age An important way of valuating a capsize vessel bulk carrier is to assess the age of the vessel. As seen in the Age chart below, the younger the age of the vessel, the higher its price is. There is an inverse relationship between age and price; every year that the vessel ages, the purchase price decreases by a multiple of -4.5438. Therefore the value of the ship will decrease by a multiple of 4.5438 times for every year that passes, holding the impact of the other two dependent variables constant. 200

160

Sale P ric e ($ U S millions )

P redic ted Sale P ric e ($ U S millions )

120

Sale Price ($US millions)

80

40 P ric e ($ U S millions )) Linear (P redic ted Sale

0 0

8

15

23

30

Age at sale (Years)

Weight (measured in Tons) Another major component of valuating a capsize vessel bulk carrier is how much weight it can carry. As seen below, every one thousand ton increase in weight bearing load will result in the purchase price increasing by a factor of 0.24215. In economic terms, per say every 1,000 dead weight tons, the ship’s value increases by $242.15, holding the impact of the other two dependent variables constant.

200

160

120 Sale Price ($US millions) Sale Price ($US millions)

80

Predicted Sale Price ($US millions)

Linear (Predicted Sale Price ($US millions))

40

0 55

110

165

220

Dead-Weight Tons (000)

Charter Rate Finally, the last component of valuating a capsize vessel bulk carrier is measuring the Charter Rate (the vessel’s rental rate). The current index for Baltic Dry Capsize is 12,479 as of May 2008. From the regression analysis information in the chart above, the multiple is .00721. In economic terms, for say every $1,000 in rental income, the ship’s value increases by $7.21, holding the impact of the other two dependent variables constant. 200

160

Sale P ric e ($ U S millions )

120

P redic ted Sale P ric e ($ U S millions )

Sale Price ($US millions) 80

Linear (P redic ted Sale P ric e ($ U40 S millions ))

0 3250

6500

9750

13000

Trailing 1-year Average Monthly Baltic Dry Capesize Index

4. Which single factor is the best predictor of ship prices (for each factor analyze the single regression with given factor as the explanatory variable)? To determine the most significant factor that contributes to the overall ship price, we have to examine the R Square percentage result from the Regression table. As seen in the summary table below, the Age factor carries a weight of 62% which affects significantly the overall impact of the ship’s valuation. Weight is at 26.5% and the index follows at 12.4%. (%)

R Square Output

Factor

62.0%

0.620141688

Age

26.5%

0.265024544

Weight

12.4%

0.124148804

Index

5. How well do all the three factors jointly explain ship prices? To decide the general impact of the three fundamental variables in boat evaluating, we can take a look at the general R Square yield data (R2). Here, the Regression Analysis shows that there is a 92% certainty rating, which implies that the cost is 92% exact. Obviously, if there were more variables added to the Regression Analysis, we would hope to see this rate gradually move towards 100%, however as there will always be elements that effect the valuing of the boat, 100% is hard to reach. At 92% certainty, we are almost guaranteed that our ship's valuation is precise. (%)

R Square Output

Factor(s)

92.0%

0.920435259

Age, Weight, Index

6. Using all three factors, which is the predicted price for the Bet Performer? In order to determine the final price that Bet Performer should be sold for, we can look at the following formula: Y = b0 + b1(x1) + b2(x2) + b3(x3) + E. Applying our Regression Analysis results into the formula, we have the equation below: Y = 44.2255 – 4.5438(11 years) + 0.242415(172.000) + .00720(12,479) Y = $125.8 million. Based on our Regression Analysis, the statistical output leads us

to believe that the true market price for Bet Performer, given the independent variables, is $125.8mm. 7. What would the price be if the Bet Performer were 5 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 Baltic Capesize Index were 70% instead of 12,479). In each case assume all other factors remain the same.

Given the above changes, we simply adjust our data input to reflect the desired information. Similarly, applying our Regression formula, we have the following equation: Y = 44.2255 – 4.5438(6 years) + 0.242415(150.000) + .00720(8,735.3) Y = $116.2 million. CONCLUSION When comparing the price valuation of Bet Performer we have gotten a price of $76.55 million using the market approach in which we compared similar transactions of 4 different ships, and another method of using regression analysis resulted in the price of $125.8 million. We thus found a price difference of $49.25 million. For the seller then it will be more beneficial to use the regression analysis, as there is a higher value. However for the buyer, the market approach would produce a better bargain at a lower value.