La división político-administrativa a. Cora y distrito

5.

Analysis of the parameters

As described in 2.1.2, principally, the evaluation of ships takes place without factoring in a charter income. However, the mathematical approach of the LTAV includes the calculation of the charter revenue in order to assess ship values. This is a renunciation of the traditional ship evaluation to a ship appraisal on the net present value.

Yet, indeed the evaluation of a vessel by the earning rate is typically undertaken in-house prior to purchasing. The calculation on how much revenue an investment will generate is the fundamental economic question of a willing buyer before investing in a ship. Further, usually a risk-return analysis is undertaken, which reflects the risk structure of the investment. A higher systematic risk and a greater specific risk of the investment, implies that an investor would require a higher expected return to hold it, and vice versa.

Therefore, the approach by the earning rate principally reflects the value of a ship, since it represents the amount, which an investment into a ship will gain in return under the premises of stipulated market risks.

5.1 Charter income

Nonetheless, the assumptions on future return contain jeopardises of incorrect predictions. However, as mentioned in 4.3.1, the LTAV makes a distinction between the calculation of charter income of charter-free (a) vessels and of vessels, which are in an existing charter contract (b). Further, the net charter income is calculated by considering the rate of occupancy (c), and deducting the management fee and brokerage (d). If a fusion rate (e) is applicable, this has to be taken into account as well.

a) Charter-free vessels are calculated by using an index charter rate at time of

evaluation. This charter rate reflects the market sentiment and is assumed to prevail for the proximate three years. Then the proceeding years, until the end of the life of the ship, are simulated by the use of a 10-year average charter rate.

Initially, this is a sufficient approach, since the market sentiment of the charter market has significant influence on the value of a ship. Furthermore, the evaluation on the basis of the discounted cash flow is commonly used for the appraisal of real estate, and as such is in line with IDW S1. However, the prospected earnings of the assessed vessel are subject to

5. Analysis of the parameters

change, and thus have to be regarded with a certain degree of wariness. These earnings are only assumptions and require accurate predictions of the trend on the charter market. Even though these predictions gain a higher dependability, due to the introduction of a detailed planning phase of three years, multi-layered factors have to be regarded in order to predict the trend.

The function of the future earning rate, for instance, includes the supply and demand ratio of tonnage. While demand is driven by the global economy, seaborne commodity trades, the average haul, random shocks and transport costs, the supply function is impelled by the size of the world fleet, the fleet productivity, shipbuilding production, scrapping and the fright revenue.74 Hence, a wide variety of factors have to be predicted in order to estimate a sound base for the future rate of return of a ship. The simplified shipping market model illustrated below demonstrates how demand and supply affect the freight rate.

Figure 6: Simplified shipping market model

Source: Referring to Tasto, M., 2009, Institute of Shipping Economics and Logistics (ISL), Bremen, Based on: Stopford, M., 2009. Maritime Economics 3rd _{ed., Routledge, p. 137 ff..}

However, whereas the supply side is assessable by looking at figures concerning the existing fleet, the orderbook and the prospected scrapping rate, demand is much more difficult to predict, as the development of the world economy and seaborne commodity trades is dependable on the sentiment and conditions on the market, and requires a deep knowledge on international economics. Changes in interest rate and economic growths play a role as well as commodity prices and the accommodation of loans or letter of credits by banks. Hence, the function for demand depends on various factors, which make an explicit prognosis very difficult, and thus complicates the accurate prediction of charter income. Although supply may adjust to the level in demand, it is to some extent

74 _{Cf. Stopford, M., 2009. Maritime Economics 3}rd

ed., Routledge, p. 137 ff.

5. Analysis of the parameters

constricted as shipbuilding requires certain time. Yet, adjustments of supply may also include slow-steaming or lay up and are therefore comparatively fast.

Mr. Plankar uses the illustration below in order to explain the freight rate mechanism. The charter rate results from the utilisation capacity of the fleet and thus from supply and demand.75

Demand for Transportation: Economic growth

- Importregions

o Iron ore/ coking coal/ steal cons. o consumption of energy

ƒ Crude oil, oil prodcts ƒ Coal ƒ Liquefied gas - Minor Bulks - Consumer products Export/Routing Degree of utilization of the fleet Charter Rate

Supply for Transportation: Existing fleet

Orders

- Capacity of the yards - Prognosis on newbuildings Fleet productivity

- Speed

- Laytime and idle time Scrapping

- Age structure

- Statutory requirements

Figure 7: Formation of charter rate resulting from supply and demand

Source: Referring to Plankar, M., Branchenrisikomanagement am Beispiel der Schifffahrtsbranche, in: Bankrisikomanagement: Mindestanforderungen, Instrumente und Strategien für Banken , 2008, pp. 325-362.

This scheme appoints various factors for demand and supply of transportation, which affect the degree of utilization and consequently have effect on the charter income. As a result, conclusions on the future charter rate can be drawn by examining the individual supply and demand drivers. Plankar confirms that the demand is affected by the world economy, through business cycles and regional growths trends. Therefore, especially commodity trades may modify the growth trends. Here in particular the development in the steel industry or the consumption of energy is mentioned, since that may influence the iron ore and crude oil trade.

Therefore, the predictions of the charter revenue have to be undertaken by reference to the individual trade. While, some segments are more likely to be influenced by certain factors (e.g. steel productions – iron ore), others may need different demand drivers.

75 _{Cf. Everling, O., [et al.], 2008, Bankrisikomanagement : Mindestanforderungen, Instrumente und Strategien}

für Banken, Gabler.

5. Analysis of the parameters

However, in addition the relevant fixtures of freight future agreements (FFAs) can reflect the future market trends. Consequently, these fixtures may be useful for the prediction of the future level in charter rates, since, due to their nature, they are traded well in advanced. Yet, on the other hand the application of a 10-year average rate after termination of the initial charter contract is coined by uncertainty. Even though shipping cycles have always existed and thus are reoccurring “events”, the amplitudes always changed and especially the latest decline on the shipping markets showed how unpredictable and volatile the shipping economy has become. Therefore, a 10-year average of the charter rates does not necessarily reflect the future income.

b) However, the calculation of the charter income for vessels, which are in a valid

charter agreement, seems to be more accurate, since these revenues are more probable.

The charter income can accurately be presumed for the period of the charter agreement, which enables a precise estimation on the earning potential of the ship. Thus, inaccuracies resulting from assumptions on the prospected supply and demand ratio occur to a lesser extent. Yet, as mentioned in 4.3.1, the charterer must have a reliable credit rating in order to accept the charter contract as a valid piece of evidence.

Further, the application of the 10-year average, after completion of the opening charter, is containing the same weaknesses in the calculation of the charter income as mentioned in (a). The question of whether or not historical charter levels enable a conclusion on future earning potentials of ships remains in force. This may be especially challenged if one took a look at the charter level of the past 5 years in contrast to the last 50 years. Especially the container segment and to some extent the bulker segment have seen an unprecedented boom throughout the past years, which could pervert the 10-year average rate. However, if one alleges that the current crisis is nothing but a dent, and charter revenues will eventually prosper as they did before the economic crisis, the 10-year average of the charter rates appears suitable to display future earning potentials.

c) The LTAV divides the rate of occupancy into two parts. On the one hand, allowing

a 1 % rate of unemployment resulting from technical issues, 358 days per year are taken as a basis for the calculation of the charter revenue. This deduction by 1 % properly reflects the frequency of loss of hire resulting from technical insufficiencies. Yet, on the other

5. Analysis of the parameters

hand the years of class inspection acknowledge a rate of occupancy of only 343 days per annum. This subdivision also seems to be suitable, as the years of class inspections notably permit less employment of the vessel.

d) The management fee and brokerage are reflected adequately by the formula of the

LTAV. This thesis orientates towards the data of the Leitfaden zum SFI TKL.Ship Fund

Index by TKL Fonds Gesellschaft für Fondsconception und –Analyse MBH in cooperation

with Prof. Dr. Wolfgang Drobetz76, and therefore considers the range of 3 % to 5 % for management fee and 1.25 % to 5 % for brokerage as marketable.

e) Furthermore, for vessels with a period under consideration of 25 years, the mentioned fusion rate has to be applied. This fusion rate accommodates the circumstance that vessels, after having exceeded the economic life of 20 years, obtain significantly lower charter rates. That is because of the fact that these ships are more likely to have technical insufficiencies, usually have higher operating costs, and are often below the technical standard, which causes negative effects on the charter rate. Consequently, the average charter rate is reduced by 30 % for bulk-carriers, as well as by 15 % for containerships and tankers for the purpose of the calculation of the charter income in the years of age 21 – 25. 3 > t t C 77

In fact, the size of the vessel is not as relevant and consequently is not as important for the fusion rate. Moreover, the fusion rate is determined by the experiences of the members of the VHSS. Upon maturity, Bulk carriers are often in a worse condition than container ships or tankers at the same age, as they carry a choice of cargo, which has a higher potential to inflict damage to the ship (e.g. scrap). Hence, their average charter income has to be reduced to a higher degree, since their condition may limit their ability to operate on the market.

5.2 Operation costs

The calculation of the operation costs is a determining factor for the calculation of the LTAV of a ship. Principally, the expenses originate in costs for personnel, consumable

76 _{CF. TKL Fonds Gesellschaft für Fondsconception und –Analyse MBH, Drobetz, W., Leitfaden zum SFI}

TKL.Ship Fund Index, [Online] Available at: http://www.hamburg-

maritime.de/Leitfaden_SFI.pdf?PHPSESSID=gdhvmqxe , [Accessed on 16.02.2010].

77 _{Vereinigung Hamburger Schiffsmakler und Schiffsagenten e.V., [Online] Available at: www.vhss.de ,}

[Accessed on 19.02.2010].

5. Analysis of the parameters

goods (e.g. oil, bunker, gas, etc.), spare parts, insurance, maintenance, repair, routine docking and class renewal. The variety of cost positions lead to very individual operation expenses for every ship. This is the reason why the operation costs are assessed by experience of the ship owner, and cannot be assessed by average.

However, by factoring in the operation costs, the LTAV reflects the expenses, which are deducted from the charter income in order to calculate the net charter. Consequently, the LTAV reflects the idea mentioned in 2.1.3. The effect of high operation expenses is more relevant in a low charter market, whereas the OPEX are of minor relevance when high charter revenues are achievable. Thus, the evaluation as to the LTAV correctly displays the idea of Stopford that, in a weak charter market, vessels with higher operating costs will simply get pushed out of the market earlier, while vessels with low operation expenses are able to operate longer, since they are able to realise a positive net charter income due to less operation expenses.78 _{Subsequently, the LTAV comprises the importance of the}

OPEX in the calculation of the charter revenue and consequently for the achievable internal rate of return of the investment. Hence, the ship-specific risk of high operation costs is reflected in the ship value. A ship, which is only able to operate on high expenses, does not achieve as much return as a ship with lower OPEX. Consequently, the ship value of a ship with higher OPEX has to be less than the value of the same ship with less OPEX.

5.3 Discount rate

The evaluation of the discounted cash flow (WACC approach) is a common attempt for the appraisal of assets (e.g. property/real estate). Therefore, ship appraisal by the Hamburg

Ship Evaluation Standard concurs to the standard of the Institut der deutschen Wirtschaftsprüfer für Unternehmensbewertung (IDW S1).79 Further, the application of a

discount rate enables an accurate consideration of the ship values to the date of reference. As referred to in 4.3.3, the LTAV is based on the WACC approach and relies on the costs of equity capital, the costs of debt capital, and the dept-equity ratio.

The LTAV utilises the Capital Asset Pricing Model for the calculation of the cost of equity capital. The CAPM is an established and the predominant model for the capital market-oriented derivation of costs of equity capital, and suitably reflects the value of the

78 _{Cf. Stopford, M., 2009. Maritime Economics 3}rd

ed., Routledge, p. 160 ff..

79 _{German Institute of Auditors Standard for Corporate Evaluation.}

5. Analysis of the parameters

cost of equity on the target date. Specifically, the utilisation of current yield curves for the calculation of the risk free basic rate of interest ensures an appraisal to a reference date, because the yield curves80 reflect the current basic market risk.

However, apart from the (virtually) risk free basic rate of interest, the costs of equity capital are also depending on risk premiums. While the unsystematic risks are not remunerated for by the interest rate, as they can be eliminated by diversification, the systematic risk is reflected by the market risk premium. Hence, the discount rate considers the amount of interest which reflects the risk of the investment.

The CAPM determines the market risk premium by ascertaining the market value for the acceptance of a risk (MRP) based on data of the capital markets. Hence, the MRP is the expected return subtracted by the (virtually) risk free rate of interest. In other words, the

MRP expresses the expected “excess return” of investments in risky instead of risk less stocks. Reason for the dependence on data of the US monetary markets, mentioned in

4.3.3 a), is the equivalence to the discounted cash flows, which in shipping are usually generated in USD.81

Additionally, the MRP is multiplied by the specific risk (β -coefficient). The thereof resulting risk add-on is customised for the individual project, and considers the project- specific risk structures. Still, as mentioned in 4.3.3, the individual beta coefficient for the assessment of ship values by the LTAV are determined by peer groups listed on the stock markets, and accordingly relate to indebted companies.

Apart from the operational risk, they depict also the risk of the capital structure of the respective shipping companies in the peer group. Therefore, the beta coefficients have to be unlevered in order to illustrate the beta of the shipping company without any debt (so called raw beta).

Unlevered β =β_Levered / ⎭ ⎬ ⎫ ⎩ ⎨ ⎧ + E D 1

By unlevering the beta any beneficial effects gained by adding debt to the firm's capital structure are removed. A comparison of the companies’ unlevered betas therefore gives an overview on the risks of the individual company irrespective to the liabilities.

80 _{There are three main economic theories attempting to explain how yield curves develop over time. However,}

explaining these theories would exceed the scope of this thesis. Yet, they have to be mentioned for the sake of completeness. There is the market expectations (pure expectations) hypothesis, the liquidity preference theory, and the market segmentation theory.

81 _{i.e. charter rate and operation costs are manly calculated in USD}

5. Analysis of the parameters

In conclusion, the unindebted median of the peer group’s beta coefficients is ascertained, and again has to be adjusted to the alleged capital structure of the appraised ship. Usually, the above mentioned formula is inverted in order to enable an utilisation for the conversion. Consequently, β_Levered of a ship appraised by the LTAV is calculated as follows: Levered β =βUnlevered * ⎭ ⎬ ⎫ ⎩ ⎨ ⎧ + E D 1

However, as mentioned the beta coefficient quantifies the MRP, whereby the beta coefficient of the investment is measured by the covariance between specific and systematic risk of shipping.

Consequently, variances in the project specific risk structures can lead to a change in the coefficient. As a result, a change may cause either lower (β<1), equal (β=1), or higher (β>1) cost of equity capital. Therefore, a variation of the beta coefficient results in a change of the interest of principal for the equity. While higher risks lead to a higher discount rate, a low risk of the investment is reflected by a lower discount rate. Accordingly, on the fundamental of an equal net income, the LTAV can result in different ship values. If the LTAV of a vessel was calculated on basis of an increased systematic risk, the LTAV would lead to a lower ship value. Yet, on the contrary low systematic risks result in a higher ship value, as the lower costs of equity capital would allow a smaller discount rate and therefore lead to a higher net present value.

However, an alteration of the beta coefficient can be induced by a variance in the specific risk of the shipping company. Since the beta coefficient depicts the covariance between the ship-specific risk and the systematic or market risk of shipping in general, a variety of economy-wide risk factors can lead to a change in the beta coefficient.

Yet, in spite of the economic importance of the shipping sector, related analyses were hardly undertaken until Grammenos and Markoulis (1996). By using stock market beta and firm-specific factors they explained the cross section of shipping returns and in conclusion reported a market beta below one for the sample of 11 shipping companies in the timeframe of 1989 to 1993. Analogously, Kavussanos and Markoulis (1997/1) investigated the market risk on firm level and tried to detect a coherence between the average beta in shipping and the overall US-stock market (S&P 500) during 1985-1995. In conclusion they were not able to establish a significant difference. In an additional study,

5. Analysis of the parameters

Kavussanos and Markoulis (1997/2) compared the return structure of water transportation and other transport industries. They recorded a market beta lower than unity in the water transportation sector.

However, Grammenos and Arkoulis (2002), for the first time,82 _{demonstrated a}

relationship between international shipping stock returns and macroeconomic variables, while Kavussanos et al. (2002) investigated sources of risk factors in different international industries. Both articles argue that global risk factors are crucial for an investment decision. Additionally, they proved that, due to the international nature of