247 resultados para Discounted Cash Flow


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Open pit mine operations are complex businesses that demand a constant assessment of risk. This is because the value of a mine project is typically influenced by many underlying economic and physical uncertainties, such as metal prices, metal grades, costs, schedules, quantities, and environmental issues, among others, which are not known with much certainty at the beginning of the project. Hence, mining projects present a considerable challenge to those involved in associated investment decisions, such as the owners of the mine and other stakeholders. In general terms, when an option exists to acquire a new or operating mining project, , the owners and stock holders of the mine project need to know the value of the mining project, which is the fundamental criterion for making final decisions about going ahead with the venture capital. However, obtaining the mine project’s value is not an easy task. The reason for this is that sophisticated valuation and mine optimisation techniques, which combine advanced theories in geostatistics, statistics, engineering, economics and finance, among others, need to be used by the mine analyst or mine planner in order to assess and quantify the existing uncertainty and, consequently, the risk involved in the project investment. Furthermore, current valuation and mine optimisation techniques do not complement each other. That is valuation techniques based on real options (RO) analysis assume an expected (constant) metal grade and ore tonnage during a specified period, while mine optimisation (MO) techniques assume expected (constant) metal prices and mining costs. These assumptions are not totally correct since both sources of uncertainty—that of the orebody (metal grade and reserves of mineral), and that about the future behaviour of metal prices and mining costs—are the ones that have great impact on the value of any mining project. Consequently, the key objective of this thesis is twofold. The first objective consists of analysing and understanding the main sources of uncertainty in an open pit mining project, such as the orebody (in situ metal grade), mining costs and metal price uncertainties, and their effect on the final project value. The second objective consists of breaking down the wall of isolation between economic valuation and mine optimisation techniques in order to generate a novel open pit mine evaluation framework called the ―Integrated Valuation / Optimisation Framework (IVOF)‖. One important characteristic of this new framework is that it incorporates the RO and MO valuation techniques into a single integrated process that quantifies and describes uncertainty and risk in a mine project evaluation process, giving a more realistic estimate of the project’s value. To achieve this, novel and advanced engineering and econometric methods are used to integrate financial and geological uncertainty into dynamic risk forecasting measures. The proposed mine valuation/optimisation technique is then applied to a real gold disseminated open pit mine deposit to estimate its value in the face of orebody, mining costs and metal price uncertainties.

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In this study, we provide an insight into how private equity players choose their targets and the bid arrangements they prefer. We test our expectations of the unique features of private equity targets using a sample of 23 listed private equity target firms during 2001–2007. We find, relative to a benchmark sample of 81 corporate targets matched by year and industry, the private equity target firms to be larger, more profitable, use their assets more efficiently, more highly levered and have greater cash flow. Multivariate testing indicates that private equity targets have relatively greater financial slack, greater financial stability, greater free cash flow and lower measurable growth prospects. All conclusions are found to be robust to a control sample of 502 takeover bids during 2001–2007.

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This paper examines the case of a procurement auction for a single project, in which the breakdown of the winning bid into its component items determines the value of payments subsequently made to bidder as the work progresses. Unbalanced bidding, or bid skewing, involves the uneven distribution of mark-up among the component items in such a way as to attempt to derive increased benefit to the unbalancer but without involving any change in the total bid. One form of unbalanced bidding for example, termed Front Loading (FL), is thought to be widespread in practice. This involves overpricing the work items that occur early in the project and underpricing the work items that occur later in the project in order to enhance the bidder's cash flow. Naturally, auctioners attempt to protect themselves from the effects of unbalancing—typically reserving the right to reject a bid that has been detected as unbalanced. As a result, models have been developed to both unbalance bids and detect unbalanced bids but virtually nothing is known of their use, success or otherwise. This is of particular concern for the detection methods as, without testing, there is no way of knowing the extent to which unbalanced bids are remaining undetected or balanced bids are being falsely detected as unbalanced. This paper reports on a simulation study aimed at demonstrating the likely effects of unbalanced bid detection models in a deterministic environment involving FL unbalancing in a Texas DOT detection setting, in which bids are deemed to be unbalanced if an item exceeds a maximum (or fails to reach a minimum) ‘cut-off’ value determined by the Texas method. A proportion of bids are automatically and maximally unbalanced over a long series of simulated contract projects and the profits and detection rates of both the balancers and unbalancers are compared. The results show that, as expected, the balanced bids are often incorrectly detected as unbalanced, with the rate of (mis)detection increasing with the proportion of FL bidders in the auction. It is also shown that, while the profit for balanced bidders remains the same irrespective of the number of FL bidders involved, the FL bidder's profit increases with the greater proportion of FL bidders present in the auction. Sensitivity tests show the results to be generally robust, with (mis)detection rates increasing further when there are fewer bidders in the auction and when more data are averaged to determine the baseline value, but being smaller or larger with increased cut-off values and increased cost and estimate variability depending on the number of FL bidders involved. The FL bidder's expected benefit from unbalancing, on the other hand, increases, when there are fewer bidders in the auction. It also increases when the cut-off rate and discount rate is increased, when there is less variability in the costs and their estimates, and when less data are used in setting the baseline values.

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This study explores the accuracy and valuation implications of the application of a comprehensive list of equity multiples in the takeover context. Motivating the study is the prevalent use of equity multiples in practice, the observed long-run underperformance of acquirers following takeovers, and the scarcity of multiplesbased research in the merger and acquisition setting. In exploring the application of equity multiples in this context three research questions are addressed: (1) how accurate are equity multiples (RQ1); which equity multiples are more accurate in valuing the firm (RQ2); and which equity multiples are associated with greater misvaluation of the firm (RQ3). Following a comprehensive review of the extant multiples-based literature it is hypothesised that the accuracy of multiples in estimating stock market prices in the takeover context will rank as follows (from best to worst): (1) forecasted earnings multiples, (2) multiples closer to bottom line earnings, (3) multiples based on Net Cash Flow from Operations (NCFO) and trading revenue. The relative inaccuracies in multiples are expected to flow through to equity misvaluation (as measured by the ratio of estimated market capitalisation to residual income value, or P/V). Accordingly, it is hypothesised that greater overvaluation will be exhibited for multiples based on Trading Revenue, NCFO, Book Value (BV) and earnings before interest, tax, depreciation and amortisation (EBITDA) versus multiples based on bottom line earnings; and that multiples based on Intrinsic Value will display the least overvaluation. The hypotheses are tested using a sample of 147 acquirers and 129 targets involved in Australian takeover transactions announced between 1990 and 2005. The results show that first, the majority of computed multiples examined exhibit valuation errors within 30 percent of stock market values. Second, and consistent with expectations, the results provide support for the superiority of multiples based on forecasted earnings in valuing targets and acquirers engaged in takeover transactions. Although a gradual improvement in estimating stock market values is not entirely evident when moving down the Income Statement, historical earnings multiples perform better than multiples based on Trading Revenue or NCFO. Third, while multiples based on forecasted earnings have the highest valuation accuracy they, along with Trading Revenue multiples for targets, produce the most overvalued valuations for acquirers and targets. Consistent with predictions, greater overvaluation is exhibited for multiples based on Trading Revenue for targets, and NCFO and EBITDA for both acquirers and targets. Finally, as expected, multiples based Intrinsic Value (along with BV) are associated with the least overvaluation. Given the widespread usage of valuation multiples in takeover contexts these findings offer a unique insight into their relative effectiveness. Importantly, the findings add to the growing body of valuation accuracy literature, especially within Australia, and should assist market participants to better understand the relative accuracy and misvaluation consequences of various equity multiples used in takeover documentation and assist them in subsequent investment decision making.

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Two dimensional flow of a micropolar fluid in a porous channel is investigated. The flow is driven by suction or injection at the channel walls, and the micropolar model due to Eringen is used to describe the working fluid. An extension of Berman's similarity transform is used to reduce the governing equations to a set of non-linear coupled ordinary differential equations. The latter are solved for large mass transfer via a perturbation analysis where the inverse of the cross-flow Reynolds number is used as the perturbing parameter. Complementary numerical solutions for strong injection are also obtained using a quasilinearisation scheme, and good agreement is observed between the solutions obtained from the perturbation analysis and the computations.