This chapter briefly defines portfolio analysis and outlines portfolio construction, strategy and the concept of bundling projects. Models used in financial markets are then examined. Cash flows and cash flow principles are also outlined and an example of portfolio modelling and its benefits is discussed.

Ghasemzadeh and Archer (2000) define portfolio selection as the periodic activity involved in selecting a portfolio of projects which meets an organisation’s stated objectives without exceeding the available resources or violating other constraints. The present authors suggest that a corporate body can consider its SBU as part of a portfolio of businesses and similarly an SBU can consider its projects as a portfolio of investments.

Figure 6.1 Typical risk/return profile

An efficient portfolio is one that provides the greatest expected return for a given level of risk, or, equivalently, the lowest risk for a given expected return (Fabozzi and Markowitz 2002).

Figure 6.2 Risk adjusted return/risk profile (Pressinger 2005)

Projects in general and more specifically construction projects have a cash flow ranging over a period of time from 5 to 25 years. This is known as the life cycle.

The Boston matrix is a management tool developed to assist in portfolio planning. It has two controlling aspects, namely market share (meaning relative to the competition) and the rate of market growth. Each individual product or project in a portfolio is placed into the matrix to determine relative market share. This is simplistic in many ways and the matrix has some understandable problems, but the authors consider that the balanced mix described by Johnson and Scholes (1999) below can be assessed within a portfolio:

In many cases, only projects with robust revenue streams are likely to be financed through the private sector. However, investors with highearning /low-risk infrastructure stock may be willing to accept less attractive stock (piggybacking) which may offer rewards in the long term (Merna and Smith 1999).

Scenario analysis is a derivative of sensitivity analysis, which tests alternative scenarios as options. When undertaking a scenario analysis the key variables are identified together with their values (Flanagan and Norman 1993). The present authors suggest that a financial engineer may wish to assess a number of different financial instruments in a portfolio of projects. If the instrument of choice is debt then the scenarios will be based on the most likely, optimistic and pessimistic forecasts of three possible interest rates. The results will represent the range of possible outcomes. The effects of these changes in one project can then be assessed with changes in the portfolio of projects.

Pollio (1999) states that diversification is used to minimise the risk of the overall loan portfolio and thus stabilise interest income. Diversification is the key to the management of portfolio risk because it allows investors to lower portfolio risk significantly without adversely effecting return.

Figure 6.3 Positively correlated cash flows

Portfolio managers need to be concerned with the different stages in maturity of the portfolio, which varies according to the sizes of the projects, the geographical location of the projects, the different stages each project is at within the portfolio, the operational track record of each project, and the experience and creditworthiness of sponsors and counterparts (Silk et al. 2002).

Figure 6.4 Negatively correlated cash flows

Figure 6.5 Interdependencies of projects within a portfolio

There are two reasons for adopting portfolio risk management:

As far as the risk management associated with project portfolios is concerned, there may be several aspects in analysis and making strategic choices associated with the projects at the strategic business level. For example, for an organisation operating in international markets, country and area and specific local risk need to be taken into account. The country risks may not affect a project alone, but may affect the whole portfolio indirectly (Ariani 2001). Country risks are discussed in Chapter 4.

Portfolio risk management can have the following benefits:

The authors suggest that portfolio risk management should first consider the risks associated with the economic parameters of each project within the portfolio and project interdependencies before assessing the portfolio of projects as one entity.

Dybvig (1988) first used the term bundling to represent the particular consumption of a bundle of similar commodities, in this case electricity, purchased from different electricity generating organi-sations. The distribution price of the bundle is determined by setting a margin above the purchase price(s) and then developing an average sale price that the market will bear for sale to consumers. The word ‘bundling’ is used today throughout the business world and in particular in private finance initiative (PFI) projects.

Benefits of bundling to project management according to Frank and Merna (2003) and Lamb and Merna (2004a) are:

Bundling projects consolidates operational, financial and strategic activities into one package. This is an option governments are now considering in order to sanction smaller PFI projects. However, the task can be difficult. Public-private partnerships (PPPs) often involve the private sector partner providing a bundle of services such as the design, construction, operation and maintenance, and both soft and hard services. Bundling thus differs from traditional contracting out whereby separate contracts are let for each service. Bundling can provide VFM which cannot be obtained by contracting services separately. Integration of design, operation and maintenance over the life of an asset, within a single-project finance package, improves performance and reduces project life costs (McDowall 2001).

Bringing projects together for financing, however, must consider the following issues (Frank and Merna 2003):

Each of these complexities needs to be addressed in both the project and financial documentation.

Figure 6.6 illustrates how a project or bundle of projects transpires from an idea by the principle through to the financing of the venture.

Figure 6.6 The lending ladder

Most projects are traditionally procured on a standalone or stranded basis, their commercial success being dependent on the revenues generated by the project’s assets, although projects procured using corporate finance often receive financial assistance from the corporate body when they suffer short-term liquidity problems. In standalone projects it is prohibited to offset gains and losses from one project to another. When projects are bundled together in a portfolio, cross-collateralisation can take place by combining project cash flows over the length of the concession or by one project’s revenues cross-collateralising with another project’s over a specified duration before combining cumulative cash flow in a portfolio.

Cash flows are a measure of a project’s health. They are simply cash receipts minus cash payments, over a given period of time. It is the cycle of cash inflows and outflows that determines business solvency (Turner 1994).

Figure 6.7 Cumulative cash flow curves of a typical base case for discounted and non-discounted inflows and outflows of cash

The authors define a cash flow as an external flow of cash and/or securities (capital additions or withdrawals) that is client initiated. Transfers of assets between asset classes within a portfolio or manager-initiated flows must not be used to move portfolios out of composites on a temporary basis. The cash flow may be defined by the organisation as a single flow or an aggregate of a number of flows within a stated period of time. In cases of multiple cash flows over an extended period of time, organisations should refer to the discretion section of the guidance statement on the definition of composites and consider whether the portfolio should be classified as non-discretionary.

Figure 6.8 Cumulative combined base case cash flow for (a) Project 1, (b) Project 2 and (c) Projects 1 and 2

Figure 6.9 Comparison of the red line (lower curve) cumulative cash flow

A project or portfolio is a commercial venture. All the important parties associated with a project, such as the promoter, the contractor and the providers of capital, invest in the project with the aim of achieving some desired benefits or returns. Normally the most important financial objective is always profitability and liquidity. Smith (1975) suggests that profitability implies making an adequate return on the capital and assets employed in the enterprise, whereas liquidity implies an adequacy of cash flows to enable the unit to pay its way and ensure continuation of the operation. Financial management in a business hinges on the management of cash flows. Whether or not a business survives is a matter of suitable cash flows, rather than profitability, which is realised at a later stage in any project. Profitability is dependent on the cash flow. Good management of a project is, therefore, not only dependent on achieving the triple constraints of specification, budget and schedule but is also dependent on being able to manage the liquidity (cash flow) of a project. Cash flow curves are highly sensitive to changes in project conditions and therefore can act as an early warning system, in case of problems, to help initiate proper rectification measures, for example, a change in the design of the project which increases or decreases the project cost, delays leading to cost overruns, fluctuations in the interest rate affecting the cost of capital used and fluctuations in the input and output costs can be easily depicted on a cash flow curve.

Some project cash flows can generate NPV = 0 at two different discount rates (Brealey and Myers 2000). An investment project in which the summary cash flow numbers are characterised by alternating cash inflows and outflows can have more than one, or multiple, IRRs. Projects can be denoted by (− +, −) or (+, − +) where the signs correspond to the sequence of the cash flows. There can be as many IRRs as there are reversals in the direction of cash flow (Werner and Stoner 2002). In projects procured by project finance an existing revenue, followed by a cash outflow and a further revenue, may form part of a concession contract (Merna and Smith 1996). Figure 6.10 illustrates the cumulative cash flow of such a project.

Figure 6.10 Cumulative cash flow-generating multiple IRRs

The following five stages to build a model cash flow curve are recommended by the present authors:

The model cash flow curve depicts the forecasted pattern of money inflows and money outflows, in money terms or real terms, of the accounts of the project during its life. However, it is not realistic to expect a very high degree of accuracy in any financial prediction based on this cash flow because it uses certain assumptions and estimates. In order to overcome this problem, normally a range of possible changes in the cash flow, both beneficial as well as adverse, as a result of risks and uncertainty, are built into the model. This provides a band around the model cash flow.

Figure 6.11 Risk envelope for project or portfolio

The following example uses a risk management software package based on Monte Carlo simulation to generate worst and best case scenarios from risks identified by the techniques discussed in Chapter 4.

Figure 6.12 Trend chart of probabilities in terms of cumulative cash flow over time

As discussed in Chapter 5, individual projects are typically financed by a combination of financial instruments that often include debt, mezzanine finance (bonds) and equity. Merna and Khu (2003) state that the types of financial instruments available for project financings have always been of concern to investors and promoters. In many infrastructure projects the debt-equity ratio is seen to be a measure of the risk in a project, the greater the risk the greater the equity contribution. In effect equity, particularly ordinary equity, can be described as risk capital in project financings.

The mechanism depends on the identification of the following outputs:

Each project P₁ to P_n is assessed on the basis of an individual project. Typically these are based on a network of project activities which are time and cost related. The software is used to assess the economic parameters of the base case without risks being considered. Ranges representing risks are then attached to activities in the network to determine the sensitivity of each activity to risk and a probability distribution is computed. Each project is assessed in a similar way (Merna and Khu 2003).

With advances in technology and improvements in Excel itself, Excel has become the preferred tool for creating all but the largest and most computationally intensive financial models. The advantages of Excel for financial modelling are numerous and are discussed in Chapter 5. Excel’s application for business management and analytical requirements has several benefits which are useful within a business environment, these include:

Figure 6.13 Straight-line interpolation of base case cumulative cash flow

However, despite its power, Excel has many limitations, and there are many financial models – some even relatively simple ones – that either cannot be created in Excel or will be overly complex or cumbersome to create in Excel. What’s more, when you create a highly complex model in Excel, it can be difficult to understand, debug and maintain (Sengupta 2004).

Figure 6.14 Mechanism for portfolio assessment

The example used involves the construction of seven new projects and the refurbishment and operation of eight existing facilities. The projects are to be procured using project finance. The cost of constructing seven new projects is estimated at £956 484 900 and the cost of the refurbishment of the eight existing facilities is estimated at £290 000 000.

Table 6.1 Individual and total project costs and revenues

Table 6.2 Worst, base and best case economic parameters for a batch of seven new projects

Table 6.3 Worst, base and best case economic parameters for a batch of eight refurbished facilities

Figure 6.15 Cumulative cash flow for a portfolio of projects (worst, base, and best cases)

Figure 6.16 Sensitivity analyses for portfolio shown in Table 6.4 for economic parameters CLU, PB and NPV in relation to IRR

Figure 6.17 Probability analyses for portfolio shown in Table 6.4 for economic parameters for mean, best and worst cases in relation to IRR

Table 6.4 Worst, base and best case economic parameters for a portfolio of 15 projects

Within any portfolio the potential for uncertainty increases with the breadth of the portfolio and the range of the projects or investments. The level of interdependencies and interrelationships will also affect the potential for positive or negative risks.