Financial Analysis and the Modeling of Ship Investment

14 Financial Analysis and the Modeling of Ship Investment Lars Patterson 14.1 Introduction Financial modeling of ship investments can quantify downside risk and upside potential before a decision to invest is made, and also be used as a tool to monitor risks and performance during the investment period. A good financial model is also an excellent tool for communicating opportunities or potential problems to management, lenders and investors. This allows for opportunities or potential problems to be identified early and plans for alternative actions to be prepared in advance. Meaningful financial analysis and modelling of ship investments can, therefore, contribute to better management of risks and hence better risk-adjusted returns. Some of the questions we may want answers to are: 1. How much capital is needed for the project? 2. What is the debt capacity of the project? 3. What is the timing of the purchase and sale, the chartering policy and the financing structure that maximizes the net present value (NPV) of equity invested? 4. What is the forecast cash impact of financing alternatives, chartering policies and market developments? L. Patterson ( ) Vetlejord, Eksingedalsvegen 356, 5728 Eidslandet, Norway © The Author(s) 2016 M.G. Kavussanos, I.D. Visvikis (eds.), The International Handbook of Shipping Finance, DOI 10.1057/978-1-137-46546-7_14 315 316 L. Patterson 5. What is required to meet the target return on equity? 6. How long will current cash last under various scenarios? A good financial model has the following characteristics: 1. key input parameters are clearly identified; 2. the model uses formulas to adjust automatically for changes in input parameters; 3. it has a user-friendly, interactive interface and clearly separates input (assumptions) and output (calculated results); 4. the model is dynamic, robust, covers multi-periods and produces all the important financial output metrics including NPV and internal rate of return (IRR). 14.2 An Example of a Financial Model Table 14.1 shows an example of a very simple financial model for analyzing investment in a single ship. We estimate the cash flow and calculate the NPV and IRR based on certain assumptions (the Excel spreadsheet of Table 14.1 can be downloaded from the website: www.pacomarine.com). Table 14.1 Example of a financial model of ship investment for a five-year-old Panamax (USD millions) Ship investment cash-flow for 5 year old Panamax Year 0 Ship purchase price Charter income Operating expense Dry docking/special survey –$27.0 Ship operating cash flow 1 2 3 4 5 4.6 –2.4 0.0 4.4 –2.4 –0.3 4.6 –2.5 0.0 4.6 –2.6 0.0 4.6 –2.7 0.0 2.2 1.7 2.0 2.0 1.9 –0.6 –0.7 0.0 0.0 –0.6 –0.7 0.0 0.0 –0.5 –0.7 0.0 0.0 –0.5 –0.7 0.0 0.0 –0.5 –0.7 –10.1 37.0 Drawdown of debt Loan interest payments Loan repayments Repayment of debt on sale Residual value (ship sale) 13.5 Net cash-flow –13.5 0.9 0.4 0.8 0.8 27.7 Discount factor 1.00 1.20 1.44 1.73 2.07 2.49 PV of cash flows 20.0% –13.50 0.74 0.28 0.47 0.37 11.11 IRR NPV 19.0% –0.53 14 Financial Analysis and the Modeling of Ship Investment 317 Table 14.2 Assumptions for simple financial model Ship type Ship age at time of purchase Ship purchase price Timecharter rate Broker’s commission on charter Off hire days per year: Operating expense Annual increase in OPEX Dry-docking cost Days in dry dock (off hire) Ship residual value (sale price) Year of dry docking Year of ship sale Debt finance Loan profile Loan balloon Loan interest rate Dry Bulk Panamax 5 years USD27.0 million USD13,500 per day 5.00% of charter hire 10 days USD6,500 per day excluding DD/SS 3.0% per annum USD0.3 million 12 USD37.0 million, net of broker’s commission 2 according to dry-docking schedule 5 years from time of purchase 50.0%, as percentage of ship purchase price 8 years with semi-annual installments USD8.0 million 4.5% p.a. payable semi-annually Note: DD dry docking, SS special survey Key assumptions are ship purchase price, charter income and operating expenses (OPEX) during the investment period and the ship sale price (residual value) at the time of exit. Assumptions are also made on the percentage of debt financing, the cost of debt and the debt repayment profile. This can be regarded as a conventional approach used to identify the right ship(s) to buy and the best possible charter fixture to take (in terms of length of period), together with a financing structure optimizing the return on equity (ROE). The standard decision rule is that a project that has a negative NPV does not generate a sufficient return to meet the required return, so as to justify the investment. All the assumptions used to calculate the cash flows in Table 14.1 are listed in Table 14.2. Some of these assumptions are factual input at the time of making the investment decision. These include known market prices for ships, market rates for charters of different durations and available terms and conditions of debt financing. Other factors, like the future residual value, are not known, and to get a better understanding of the dynamics of future outcomes, sensitivity analysis is performed as summarized in Table 14.3. The table shows how the IRR for the equity invested varies in response to changes in the input assumption listed to the left of the IRR columns for each of the assumptions (OPEX per day, average time charter (TC) rate per day, ship residual value, ship purchase price and loan interest rate). This of course is in addition to detailed market analysis, which takes into account expected future demand and supply, as well as historical data. 318 L. Patterson Table 14.3 Sensitivity table I: sensitivity of equity IRR to changes in assumptions Ship OPEX (ex DD) IRR (USD) (%) 5,700 5,900 6,100 6,300 Base case: 20.8 20.3 19.9 19.4 Average TC rate per day IRR (USD) (%) Ship residual value IRR (USD) (%) Ship purchase price IRR (USD) (%) Loan interest rate IRR (USD) (%) 9,500 10,500 11,500 12,500 33.00 34.00 35.00 36.00 23.00 24.00 25.00 26.00 0.50 1.50 2.50 3.50 21.8 21.1 20.4 19.7 11.3 13.2 15.1 17.0 15.6 16.5 17.3 18.2 25.9 24.0 22.3 20.6 6,500 19.0 13,500 19.0 37.00 19.0 27.00 19.0 4.50 19.0 6,500 6,700 6,900 7,100 20.9 22.9 24.9 26.9 19.8 20.5 21.3 22.0 17.4 16.0 14.5 13.2 18.3 17.6 16.8 16.1 19.0 18.5 17.6 16.3 14,500 15,500 16,500 17,500 38.00 39.00 40.00 41.00 28.00 29.00 30.00 31.00 5.50 6.50 7.50 8.50 Table 14.4 Sensitivity table II: sensitivity of equity IRR to changes in ship residual value and average TC rate Average TC rate during project period Ship residual value => $34.0 $35.0 $36.0 $37.00 $11,500 12.4% 13.3% 14.2% 15.1% $12,500 14.4% 15.3% 16.2% 17.0% $13,500 16.5% 17.3% 18.2% 19.0% $14,500 18.5% 19.3% 20.1% 20.9% $15,500 20.6% 21.4% 22.1% 22.9% $16,500 22.6% 23.4% 24.2% 24.9% $38.0 $39.0 $40.0 $41.0 $42.0 15.9% 16.7% 17.5% 18.3% 19.1% 17.8% 18.6% 19.4% 20.2% 20.9% 19.8% 20.5% 21.3% 22.0% 22.7% 21.7% 22.4% 23.2% 23.9% 24.6% 23.7% 24.4% 25.1% 25.8% 26.5% 25.6% 26.3% 27.0% 27.7% 28.4% A two-way sensitivity analysis may also be performed to obtain an understanding of how the return (IRR) of the investment varies with the change of two variables, such as the ship sale price (residual value) and the average charter rate achieved during a given period, as shown in Table 14.4. The table shows how the IRR for equity invested varies in response to changes in the assumptions for the combination of average TC rate and ship residual value. Key ratios and indicators are also calculated, as shown in Table 14.5. A discussion of these key ratios and indicators follows below. Loan To Value (LTV) This is a ratio that shows the extent to which the balance of the outstanding loan is covered (secured) by the market value of 14 319 Financial Analysis and the Modeling of Ship Investment Table 14.5 Key ratios and indicators Year 0 LTV 120% Required minimum value (USD million) 16.2 Debt service ratio Interest cover ratio Debt service USD per day Debt service break even USD per day 1 2 3 4 5 120% 120% 120% 120% 120% 15.4 1.7 3.6 3,626 14.6 1.3 2.9 3,663 13.7 1.7 3.8 3,452 12.9 1.6 3.9 3,365 12.1 1.6 4.0 3,278 10,647 11,137 10,880 11,005 11,137 the ship. It is normally found as a covenant in term sheets and loan agreements. Traditionally, it used to be expressed as the ratio of the market value of the ship divided by the outstanding loan balance, in other words the “value to loan”. It has, however, become more common to show the maximum outstanding loan balance allowed under this covenant as a percentage of the market value of the ship. For example, a covenant of maximum loan, being 50% of the market value of the ship, means that if the market value of the ship is USD20 million, then the maximum loan allowed is USD10 million. The reason banks traditionally used to express LTV the other way around is probably that the ratio of ship value to outstanding loan easily illustrates how much the ship can fall in value before the loan is not covered. Required Minimum Value This figure shows the minimum market value the ship can have before a loan is in breach of its minimum value covenant. It is calculated by taking the outstanding loan balance and multiplying it by the LTV ratio. For example, if the loan balance is USD10 million and the LTV covenant is 130%, the required minimum value will be USD13 million. As the loan is amortized the required minimum value will be reduced, but the ship will also be older and subject to a fall in value, due to its having less remaining economic life. The repayment profile of most shipping loans is normally structured so that the loan balance is scheduled to reduce faster than the ship age, and an argument can be made that the LTV should be somewhat less onerous at the beginning of the loan. Debt Service Ratio This ratio is calculated by taking the total cash flow available to service debt during a specified period and dividing it by the total amount of debt repayment plus interest payment for the same period. The 320 L. Patterson period chosen is normally that from one debt repayment date to the next (typically, six months). Interest Cover Ratio This ratio is calculated by dividing the total cash flow available to service debt during a specific period and dividing it by the amount of interest payments for the same period. Where interest is not being paid, the lending bank will have to account for the loan as being non-performing and make necessary loss provisions in its accounts. The bank may however agree to delay repayment of the principal loan balance without necessarily having to account for the loan as being non-performing. If a loan is classified as non-performing the bank has to make provisions for the potential loss and also increase its risk weighting for that loan. This again affects the cost of funding for the bank. Debt Service Per Day This figure is calculated by taking the total debt service during a period and dividing it by the number of days in the period, but adjusted for off-hire. For example, if the debt service (scheduled loan repayments plus interest payments) for a period is USD1.2 million over 182 days and the expected off-hire in the same period is five days, then the debt service per day would be USD1.2 million divided by 177, which is USD6,780 per day. Debt Service Break Even This is calculated by taking the debt service per day and adding the OPEX per day, including provisions for periodical dry docking (DD)/special survey (SS). If the debt service per day is USD6,780, the OPEX (excluding dry docking) is USD5,800 per day, and the estimated cost of the next dry docking is USD250,000 with 887 earnings days (30 months adjusted for ten days off-hire per year) to the next dry docking, then the debt service break even is USD12,862 per day, which is the required time-charter equivalent (TCE) earnings per day, net of any commissions payable. 14.3 Theory Behind the Ship Investment Criteria and Value Drivers It is impossible to build or make meaningful use of a financial model without having an understanding of the financial theories upon which the model is based. In the following section some of the practical applications of financial theory, as they relate to ship investments, are discussed. 14 321 Financial Analysis and the Modeling of Ship Investment The total return from a ship investment has two components: the return generated from a change in asset value (ship price), and the return generated from the cash flow provided by earnings: Total Return = Asset Return + Earnings Return. Risk is commonly expressed by the standard deviation of these returns. Figure 14.1 illustrates the historical risk/return trade-off for some generic ship types, where there is a large number of similar ships that are traded in active markets for sale and purchase (S&P), as well as chartering. The annual returns are calculated by using the income from one-year TCs minus the estimated operating expense for the same period (including age depreciation) divided by the ship price at the beginning of the period as a measure of earnings return. The asset return is calculated as the ship price at the end of the investment period minus the ship price at the beginning of the investment period divided by the ship price at the beginning of the investment period. The investment period used here is 12 months. As the earnings return has been calculated using the one-year TC rate, the earnings for tankers do not reflect the peaks and high volatility of spot earnings in the tanker market. Note also that when using the one-year TCE as a measure of earnings for containerships, we are measuring the earnings of ships on TC and not those of the container liner companies. The graph therefore has many limitations, but it illustrates that the ships with the highest volatility 45% 40% 35% Annual Returns % Capesize Panamax Handymax 30% Handysize 25% 20% Suezmax 15% Container VLCC Aframax Product 10% 5% 0% 0% 10% 20% 30% 40% 50% 60% 70% Standard Deviaon of Returns % Fig. 14.1 Ship investment risk and returns (Source: Author’s calculations based on data from Clarksons SIN) 322 L. Patterson in earnings and ship prices in general are compensated for the higher risk by a higher return. The key value drivers of a ship investment are cash invested in purchasing the ship, cash generated during the time the ship is held as an investment, and the cash generated when the ship is sold. From a financial analysis point of view, the following investment criteria are used: • NPV—which is calculated by discounting the future cash flows, using a discount rate reflecting the required return. A more risky investment requires a higher return than a less risky investment. When determining the level of risk the volatility of ship prices and charter rates are taken into account, as well as the market liquidity for the type of ship the analysis is performed. • IRR—which is the discount rate that returns an NPV of zero. • We also take into account the value of flexibility (the value of optionality) embedded in the ship investment. Ships operate in a volatile trading environment. Freight rates, particularly in the spot market, can be extremely volatile, although term rates (that is, charters for fixed terms of months or years) may not reflect the degree of volatility seen in the spot market. The volatility of earnings is also reflected in ship prices. This volatility is, of course, a source of potential additional profit. 14.3.1 The Value of Flexibility (Optionality) The timing of purchase of a ship, its sale, the type of charter chosen and the amount of debt financing provide the shipowner with many options. In the terminology of real options analysis (ROA), which often uses the terms “option to contract”, “option to abandon”, “option to expand” and “option to defer”, some of the real options and how they apply to ship investments are: 1. Selling a ship is an example of an option to abandon. 2. Declaring an option on a newbuilding under a shipyard contract, or extending a charter, are examples of options to expand. Declaring a purchase option on a ship on charter with purchase options is also an option to expand. 3. Deciding to wait to buy a ship until market conditions are more favorable or financing is available on better terms are examples of options to defer. 14 Financial Analysis and the Modeling of Ship Investment 323 4. Slow steaming (speed reduction) or the lay-up of ships are examples of options to contract for an individual ship or ships, but with the objective from the shipowner’s perspective of improving market earnings by cutting supply (slow steaming reduces supply by voyages that take longer to perform, thereby more ships are needed to satisfy the same ton-mile demand). Without taking into account the value of optionality, it is clear that the standard NPV analysis understates the value of a ship investment. Investors who are not aware of the value of the optionality may reject ship investments in favor of more traditional investments that in reality produce a lower return with a higher risk. Real options capture the value of flexibility and provide trigger points that inform as to when to take a decision. The main factors determining the value of optionality, as the combined value of volatility and flexibility, are: 1. Investment cost The value of optionality depends on the cost of entry/cost of purchasing the ship. The lower the purchase cost, the higher the option value. 2. Time to expire A longer time to expiration increases the value of the option. For a ship investment, the time to expiry is the remaining economic life of a ship until scrapping. The decision on when to scrap a ship depends, amongst other things, on expected future charter rates and the (uncertain) costs of continued maintenance of an old ship. The remaining economic value (or “time to expiry”) can therefore vary, and so we are dealing with a complex option. 3. Uncertainty (volatility) With managerial flexibility an increase in uncertainty (volatility) will increase the value of optionality. Whilst it is useful to try to quantify the value of optionality using financial/ mathematical models, there is in practice no substitute for understanding market dynamics based on market presence and experience. More important than arriving at any particular number is the structured process, which takes into account as many relevant factors and possible outcomes as possible. Financial models of ship investment making use of Monte Carlo simulation, sensitivity analysis and scenario analysis furnish the decisionmaker with a range of possible outcomes and the probability with which they will occur.1 Most importantly it also shows the consequences of what happens when the extreme possibilities occur. 324 L. Patterson 14.4 A Few Comments on Ship Investment Practice The following provides some useful hints on how a practitioner may approach some of the key ship investment issues in practice. 14.4.1 Ship Purchase and Timing of Exit Figure 14.2 shows the historical monthly price of a five-year-old dry-bulk Panamax in the second-hand market for a ten-year period, from June 2005 to May 2015, together with the one-year TC rate (in USD per day) for the same period. The high correlation (0.98) between ship prices and one-year TC rates is noted. One explanation for this high correlation may be that there is no lead time to sell a second-hand ship in the market, as it can be sold more or less immediately, while it normally takes less than a year to build a new ship. Even with a backlog of orders for newbuildings, where the lead time from order to delivery is more than a year, shipowners are not willing to pay a lot for “hope value” or future expectations. 14.4.2 Newbuilding versus Second-hand Purchase The difference of the NPV of an investment in a newbuilding and the NPV of an investment in a second-hand ship will depend on several factors, including: $90,000 $80,000 $70,000 $60,000 $50,000 $40,000 $30,000 $20,000 $10,000 $0 Panamax 76K Bulkcarrier 5 Year Old 2015-Jan 2014-Aug 2013-Oct 2014-Mar 2013-May 2012-Jul 2012-Dec 2012-Feb 2011-Apr 2011-Sep 2010-Nov 2010-Jan 2010-Jun 2009-Aug 2008-Oct 2009-Mar 2008-May 2007-Jul 2007-Dec 2007-Feb 2006-Apr 2006-Sep 2005-Jun Correlaon coefficient = 0.98 Timecharter Rate per Day $100 $90 $80 $70 $60 $50 $40 $30 $20 $10 $0 2005-Nov Ship Price US$ Million • when delivery of the ship can be taken for use; 1 Year Timecharter Rate Fig. 14.2 Historical ship prices and one-year TC rates (Source: Author’s calculations based on data from Clarksons SIN) 14 325 Financial Analysis and the Modeling of Ship Investment • the value of the income the second-hand ship can earn during the period before delivery of the newbuilding; • the difference in numbers of years left before the secondhand ship will be scrapped compared to the number of years left before the newbuilt ship will be scrapped (difference in remaining economic life). $100 $80 $60 $40 $20 Panamax 76K Bulkcarrier 5 Year Old Panamax 75K Bulkcarrier 10 Year Old 10 Year Average of 5 Year Old Ship 10 Year Average of 10 Year Old Ship 2015-Jan 2014-Aug 2013-Oct 2014-Mar 2013-May 2012-Jul 2012-Dec 2012-Feb 2011-Apr 2011-Sep 2010-Nov 2010-Jan 2010-Jun 2009-Aug 2008-Oct 2009-Mar 2008-May 2007-Jul 2007-Dec 2007-Feb 2006-Apr 2006-Sep 2005-Jun $0 2005-Nov Ship Price US$ Million The status of the order book for shipyards may result in a growing lead time before work starts building a ship on order. The varying length of time from new order to delivery combined with the state of the freight market are the key factors in determining the spread between newbuilding prices and prices for ships in the second-hand market. Ships have a limited economic life (typically 25–30 years from new), depending on, amongst other things, ship type, wear and tear in the trades where the ship has been employed, as well as maintenance policy and quality of maintenance. A ship can be bought and sold several times in the secondhand market before it is finally sold for scrap. If the investment strategy is “asset play”, a ship is sold in the second-hand market when a considerable gain in the second-hand value over the original purchase price can be realized. For the purpose of quantifying potential upside when deciding to buy the ship, it is fairly normal practice to use the age-adjusted historical average secondhand price of the ship as a base case and then perform sensitivity analysis or scenario analysis using the historical maximum and minimum ship price to get a high and low case. Figure 14.3 shows the monthly historical ship price for a five-year-old and a ten-year-old dry-bulk Panamax ship over a period of 120 months, from June 2005 to May 2015. It is noted that the average ship Fig. 14.3 Historical ship prices for five-year-old and ten-year-old dry-bulk Panamax (Source: Author’s calculations based on data from Clarksons SIN Note: The averages refer to those calculated over the entire period of the dataset displayed on the graph) 326 L. Patterson price for a five-year-old Panamax here is USD37.3 million and for a ten-yearold is USD29.7 million. However, whilst historical ship prices can give a fairly good idea about the range of possible outcomes and their probability distribution, we do not know when the prices will occur. It may also be advisable to exclude the extremely high values during a super cycle, as the one observed in 2007–08, when calculating historical averages as benchmarks for upside potential. Note that both the probability distribution and the average may change over time. There is no basis for suggesting mean reversion of either ship prices or charter rates. It can, however, be argued that the return expressed as cash yield (a function of both ship price and charter rate) is mean reverting. 14.4.3 Sale for Scrap The financial evaluation of the decision to sell a ship for scrap can be made by comparing the present value of cash from scrapping the ship immediately, with the present value of the cash flow of future earnings from continuing to trade, followed by a delayed sale of the ship for scrap, minus the additional cost of docking the ship. Net receivable earnings from scrapping the ship is the net price paid for the scrap metal (steel, measured in scrap price per light weight ton or light displacement ton, minus the cost of sailing the ship to the scrapyard after delivery of its last cargo and the usual associated costs, such as repatriation of the crew and port and agency fees. The main inputs for comparing the cash flows from scrapping with continued trading are: 1. future income from continued trading (which is likely to be uncertain); 2. cost of docking for an old ship (which is uncertain, although the owner will have a guesstimate); 3. the future scrap price; 4. opportunity value of cash (this is a given, but different owners will have different views on if/when/how to reinvest). Amongst these, clearly the most important factors are the expectations (or hopes) for future earnings and the costs of maintaining the ship for the longer term, which include docking costs as well as anticipated daily running costs. Figure 14.4 shows the historical scrap value and second-hand price for a ship similar to the dry-bulk Panamax used in our example. Note that in a high market the scrap value of the ship is a lower percentage of the charter free value of the ship than in a low market. For an old ship in a low market, 327 Financial Analysis and the Modeling of Ship Investment Scrap Value 10 Year Old Secondhand Prices 2015-Jan 2014-Aug 2013-Oct 2014-Mar 2013-May 2012-Jul 2012-Dec 2012-Feb 2011-Apr 2011-Sep 2010-Nov 2010-Jan 2010-Jun 0% 2009-Aug 5% $0 2008-Oct 10% $10 2009-Mar 15% $20 2008-May 20% $30 2007-Jul 25% $40 2007-Dec 30% $50 2007-Feb 35% $60 2006-Apr 40% $70 2006-Sep 45% $80 2005-Jun $90 2005-Nov US$ Million 14 Scrap Value as % of Price Fig. 14.4 Dry-bulk Panamax scrap value and ship price (Source: Author’s calculations based on data from Clarksons SIN) the scrap value will be a high percentage of the market value of the ship since the market value is related to the present value of the expected cash flow over the remaining economic life of the ship. 14.4.4 OPEX The cost of operating a ship primarily consists of the following, where off-hire is not a cash expense, but a reduction in cash earnings: • • • • crew; spare parts; insurance; DD/SS, in accordance with DD/SS schedule. Shipowners normally calculate and budget OPEX on the basis of 365 operating days per year, whether the ship is on-hire or not. When the ship is off-hire, the charterer does not pay charter hire, and off-hire is, therefore, an income reduction. In the model example, we have assumed ten days ordinary off-hire per year and a further 12 days off-hire for the period when the ship is being dry docked. The regulatory regime requires a ship to pass through a “special” docking survey every five years and to undergo a cycle of regular maintenance in between, including, in most cases, an “intermediate” docking at 30-month intervals between the SSs. As the ship gets older, the wear and tear clearly shows, and the externally imposed upgrading/repair work becomes incrementally expensive. Whilst in many cases the shipowner may be able to anticipate 328 L. Patterson roughly what the costs for a future docking will be, the actual cost will only be ascertained once the independent assessment (by a representative of the vessel’s classification society) has been carried out with the ship already in dock to the SS requirements. Once the SS has been successfully undertaken, the ship is allowed to trade for another 30 months, before a further (the intermediate) docking is required. The decision to pay for the dry docking can be looked upon as buying an option with 30 months to expiry, with the pay-out on the option being dependent on the realized charter income and future scrap price. When shipowners or shipmanagers quote a figure for OPEX per day, it is important to check if that is a figure which includes a daily provision for the future cost of DD/SS or not. A provision is an accrued cost. For the purpose of calculating NPV and IRR the cash expense of DD/SS is timed when it takes place in accordance with DD schedule. It is, however, crucially important to make sure that sufficient cash is available to pay for DD either from accumulated cash flow or, if necessary, from extra cash injected by the owner. Financial modeling will show how much cash will be generated under various scenarios and under what circumstances it may be necessary for the owner to inject further cash. Great attention is paid to the OPEX number, sometimes at the expense of what really matters, which is to keep the ship operating to ensure its safe and uninterrupted performance as an earnings-generating asset and to preserve its quality in a cost efficient way, with a view to maximizing its value when sold. As can be seen from the sensitivity table in Table 14.3, OPEX is not the most critical number in terms of investment performance. The IRR of a ship investment is not highly sensitive to higher/lower OPEX within a small margin. The overall cash flow is what matters, and in this context it is important to keep OPEX under tight control without impairing the value of the ship. 14.4.5 Employment: “The Decision to Fix” The type of employment chosen for the ship affects the volatility of earnings, the percentage of debt that can be used (debt capacity) and the expected average earnings. Short-term charters generally have higher expected earnings but more volatility. Longer-term charters to good credits normally make it possible to use more debt. In practice, there is a trade-off between market risk and credit risk. Credit risk is in principle a function of to whom the ship is chartered and for how long. This is the ability of the charterer to perform his or her contractual obligations, which may vary depending on the tenor. The level of exposure at future dates can be calculated by taking the difference 14 329 Financial Analysis and the Modeling of Ship Investment 6 Month Timecharter Rate 1 Year Timecharter Rate 3 Year Timecharter Rate Average 6 Month Timecharter Rate Average 1 Year Timecharter Rate Average 3 Year Timecharter Rate 2014-Jul 2014-Dec 2014-Feb 2013-Apr 2013-Sep 2012-Nov 2012-Jan 2012-Jun 2011-Aug 2010-Oct 2011-Mar 2010-May 2009-Jul 2009-Dec 2009-Feb 2008-Apr 2008-Sep 2007-Nov 2007-Jan 2007-Jun 2006-Aug 2005-Oct 2006-Mar $1,00,000 $90,000 $80,000 $70,000 $60,000 $50,000 $40,000 $30,000 $20,000 $10,000 $0 2005-May Timecharter Rate US$ per Day between the agreed rate in the charter committed to perform and the current market rate for a charter of similar tenor to the balance still outstanding. This is “marking-to-market” the charter contract exposure. If, for example, we have committed to perform a two-year TC at a rate of USD25,000 per day and there is one year left of the charter, and the current market rate is USD12,000 per day, then our credit exposure on the remaining charter is USD25,000 minus USD12,000 multiplied by 365 days minus relevant off-hire days. With seven off-hire days, the exposure is USD4.7 million, which we then subject to a credit risk weighting based on the financial solidity and reputation of the charterer. If we do not fix the ship on a long-term charter, we are fully exposed to market risk (the short-term continuous fluctuations in charter rates and availability of cargoes) and can expect to be able to obtain less debt financing. As Fig. 14.5 illustrates, in this case the average TCE from long-term charters are significantly less than the average TCE for shorter charters or TCE from spot operations. We should, therefore, take into account in the financial analysis of the ship investment that less debt on the project (whilst requiring a larger equity investment) may well produce a higher return due to higher average earnings in the spot market. It should also be noted that it does not make sense to lock into a long-term charter in a low market, where the result may be that we do not benefit from an upturn in charter rates when the market improves. Fig. 14.5 Comparison of six-month, one-year and three-year TC rates (Source: Author’s calculations based on data from Clarksons SIN Note: The averages refer to those calculated over the entire period of the dataset displayed on the graph) 330 L. Patterson It should be noted that in a low market environment older ships will have more days when they are not earning money (off-hire) due to an inability to find immediate employment. Charterers, particularly in softer market environments, can afford to pick and choose between ships, and will tend to ignore older ones if younger ones are available. As the ship gets older, and uncertainty related to possible technical breakdown and off-hire increases, term charter may not be an option for the owner—i.e. he cannot find a charterer willing to take his ship on a term charter even if that is his preference. He will, therefore, have to make assumptions about possible spot earnings. 14.4.6 Financing One of the benefits of a good financial model for analysis of a ship investment is the ability to identify what financing arrangement adds most value to the deal. Once the deal cash flow (and its uncertainties) is established, financing is structured to match it. The following should be noted: 1. there is normally a trade-off between the benefit of a higher percentage of debt and the lenders’ requirement for long-term charter employment to support higher debt; 2. a higher percentage of equity provides flexibility in terms of employment and possible dividend payments; 3. banks typically have restrictions on age, in terms of not lending on ships older than 12–15 years and those free of any debt by a certain age (e.g. 20 years). The example in Table 14.6 shows how the maximum debt capacity is calculated for a ship investment based on the cash flow estimated in the earlier example; when applying it to the loan criteria used by the bank we are asking to provide debt financing (normally a first priority ship mortgage loan). When evaluating a debt financing of a ship, it is also useful to calculate what we may call the “trade out rate” of a loan. This is helpful to both the lender and the borrower as it gives an indication of the ability of a ship to generate enough cash to make interest payments and pay off the loan in full over the remaining economic life of the ship to scrap. Calculation of the trade out rate is shown in Table 14.7. The calculation of the bareboat rate per day required to pay off the outstanding loan balance over the number of years when the ship still is young 14 Financial Analysis and the Modeling of Ship Investment 331 Table 14.6 Individual bank lending criteria (illustrative assumptions) Maximum age at final repayment Loan profile Bank loan tenure Loan residual value (as% of historical average ship price) 20 years 15 years 8 years 20% Calculation of debt capacity Ship operating cash flow per year Required debt service ratio Debt service capacity Tenure of loan Debt service during loan term Minus sum interest payments Equals sum total instalments Plus maximum balloon USD4.0 million 1.4 USD2.9 million 8 years USD22.9 million USD5.3 million USD17.6 million USD6.0 million = Maximum loan USD23.6 million Table 14.7 Calculation of loan trade out rate Ship age at end of current employment (TC) Remaining economic life of ship Loan required to be repaid by ship age Remaining time for loan to be repaid Loan balance when coming off TC Cost of future debt Required loan trade out rate to zero Estimated scrap value Required loan trade out rate to scrap 10 years 15 years 20 years 10 years USD13.6 million 4.5% p.a. USD1,894 per day bareboat USD1.2 million USD1,792 per day bareboat enough to meet the banks loan criteria is simply the annuity (PMT function in Excel) of the specified number of years, using the cost of debt and dividing by 365 days. To make this into a TC or TCE rate, we simply add the estimate for OPEX per day going forward and adjust for estimated off-hire days. When comparing the calculated rate (expressed as either bareboat or TCE, in USD per day) with not only the historical average but also with the historical minimum rate, we see that even if the market continues to be weak, the ship providing security for the loan will be able to pay all interest and the principal. If the bank agrees to restructure the loan to allow repayment over the remaining economic life of the ship, the loan will be repaid in full even if we do not take into account any residual value. If we allow for some contribution from the scrap value of the ship, the rate required to pay off all the debt is even lower. It must of course be added that as soon as the market picks up again, the original debt repayment schedule can be resumed, possibly with an acceleration of repayment to get back on track. 332 L. Patterson 14.5 Ships as an Investment Ships as investments have many features similar to marketable financial instruments like shares, bonds or traded options: 1. The market price of a ship can be interpreted as the present value of the expected cash flow from the ship during its remaining economic life, discounted at a rate of return that reflects the market’s perception (pricing) of downside risks and upside potential. 2. The cash flow generated by operation of the ship over a period of time can be expressed as a percentage of the ship price. This is similar to the yield from the dividends on a listed share or the yield from the coupon on a bond. 3. Charters have different durations and rates may vary with the tenor (period) of the charter. 4. There are yield curves for charters, which reflect forward expectations (a rising market or a falling market). Clarkson’s SIN database normally reports six-month, one-year, three-year and five-year charter periods. The forward curve can also be read out of the various market reports for forward freight agreements (FFA). 5. Ships are traded in liquid, transparent and well-reported global markets continuously throughout the day. 6. The cash flow is subject to credit risk (counterparty risk on charters). 7. The cash flow is subject to market risk (changes in ship prices and charter rates). 8. The age of the ship determines the remaining economic life to demolition, which can be seen as similar to the remaining life to maturity for bonds and options. Since ship prices and income are determined in active liquid markets subject to volatility (risk), it is also relevant to consider the following issues when analyzing a ship investment. 14.5.1 Are Ships Priced in Efficient Markets? Without making any bold statements about market efficiency, it is taken for granted that an investment in a ship with a higher level of risk requires a higher level of (expected) return than a less risky investment. For the purpose of the analysis, it is assumed that ship prices and charter rates reflect all 14 Financial Analysis and the Modeling of Ship Investment 333 relevant information at any time, and that new information will be reflected quickly in changing ship prices and charter rates. An efficient market prices risk so that a more risky investment will require a higher expected return than a less risky investment. In real life, markets may not always be 100% efficient and assets may be overpriced or underpriced. When evaluating a ship investment, the fundamental questions are: • When will ship prices and charter rates increase or fall? • How long will ship prices and charter rates remain at various levels? Much effort is put into forecasting supply and demand in shipping markets. What is often overlooked is the dynamics of how supply adjusts in response to ever changing demand. For the purpose of investment analysis it is therefore helpful to look at the formation of ship prices as a stochastic process. This means that ship prices are a random variable, but each of the possible values of the variable ship price does not have equal probability. The rate of change of the ship price (“speed of change”) and the amount of change in ship price (“step change”) are also subject to change and vary over time. Add to that the relationship between ship prices and charter rates, and the picture becomes quite complex. The rate at which the change takes place (“acceleration”) is also relevant. The ship price or charter rate today does not predict the ship price or charter rate tomorrow. In that sense, it is stochastic. A stochastic variable has a probability distribution where some outcomes may be more likely than others. 14.5.2 Are Ship Prices, Charter Rates and Investment Returns Mean Reverting? There are different opinions on this. In practice, it is useful to use historical averages of ship prices and charter rates as a benchmark for the long-term equilibrium of ship prices and charter rates, but this should be done with caution. As mentioned earlier, it may be advisable to exclude extreme values we may observe during a “super-cycle”. However, extremely high values are indeed possible. Also bear in mind that the averages will change over time due to factors such as cost increases of the necessary input factors when building a new ship (steel, labor, machinery and equipment), as well as the costs of operating it (crew, supplies, insurance). It is also useful to look at the historical maximum and minimum values of ship prices and charter rates to form a view of potential upsides and downsides. Extremely high and extremely low prices do not last for very long; that is, the market is “self-correcting”. 334 L. Patterson 14.6 Conclusion Financial modeling of ship investments helps the analyst to get a better understanding of the deal. It makes him or her mindful of the deal and helps to identify what makes it work. Some seasoned shipowners can do this perhaps intuitively on the back of an envelope. For the rest of us, financial modeling is a necessary tool, not least so as to be able to document the thought process to third-party investors. Note 1. Monte Carlo simulation is a computerized mathematical technique used to analyze risk. Monte Carlo simulation performs risk analysis by building computer models of possible results by substituting a range of values—a probability distribution—for any factor that has uncertainty. It then calculates results over and over, each time using a different set of random values from the specified probability function for each factor. It furnishes the decision-maker with a range of possible outcomes and the probability they will occur for any action—it shows how variations in important factors interact. It also shows the extreme possibilities. Results show not only what could happen, but how likely each outcome is. Probability distributions are a much more realistic way of describing uncertainty in variables than deterministic or “single-point estimate” analysis. References and Links Market Data Clarksons Shipping Intelligence Network contains the full range of information collected by Clarkson Research including its periodicals, extensive lists and analysis of the fleet, order book and time-series of key commercial shipping data: https://sin.clarksons.net. OPEX Data Moore Stephens provide online data as a benchmarking tool for all major vessels’ operating costs, currently covering 24 vessel types: www.moorestephens. co.uk/Shippingopcost.aspx. 14 Financial Analysis and the Modeling of Ship Investment 335 Software for Financial Modeling of Ship Investments Microsoft Excel® is most widely used for financial modeling and users can either employ Excel to build their own models from scratch, or make use of some of the Excel based ship investment applications like ShipInvest (www. scscom.demon.co.uk), Invest in Ships (www.seaxl.com) or Pacoship (www. pacomarine.com). Bibliography Benninga, S. (2014), Financial Modeling, John Wiley & Sons, Inc., Hoboken, New Jersey. Benninga, S. (2010), Principles of Finance with Excel, John Wiley & Sons, Inc., Hoboken, New Jersey. Copeland, T. and Antikarov, V. (2003) Real Options: A Practitioners Guide, Thomson-Texere, New York. Fabozzi, F.J., Focardi, S.M., and Kolm, P.N. (2006), Financial Modeling of the Equity Market. From CAPM to Cointegration, John Wiley & Sons, Inc., Hoboken, New Jersey. Merton H.M. and Modigliani, F. (1958), The Cost of Capital, Corporation Finance and the Theory of Investment, The American Economic Review. Pires, F.C.M., Assis, L.F. and Fiho, M.R. (2012), A Real Options Approach to Ship Investment Appraisal, African Journal of Business Management, vol. 6(25), 7397–7402. Razgaitis, R. (2003), Dealmaking Using Real Options and Monte Carlo Analysis, John Wiley & Sons, Inc., Hoboken, New Jersey. Rees, M. (2008), Financial Modelling in Practice: A Concise Guide for Intermediate and Advanced Level, The Wiley Finance Series.