![]() ![]() (Eur Financ Manag 18(4):543–575, 2012) using the least-squares Monte Carlo method. The one-factor setting was originally proposed by Brennan and Schwartz (J Bus 58(2):135–157, 1985), who used partial differential equations (PDEs) and finite differences to approximately solve the valuation problem extensions to two and three factors were later analysed by Tsekrekos et al. ![]() We re-visit the well-known example of a copper mine project under a one-factor and two multi-factor models using the influence diagram simulation-and-regression (IDSR) approach. The need to evaluate natural resource investments under uncertainty has given rise to the development of real options valuation however, the analysis of such investments has been restricted by the capabilities of existing valuation approaches. (2012) considered both the two-factor model of Gibson and Schwartz (1990) and the three-factor models of Schwartz (1997) Casassus and Collin-Dufresne (2005). (2008), who applied the three-factor model of Cortazar and Schwartz (2003), and Tsekrekos et al. Multi-factor model extensions of the mine example were studied by Cortazar et al. (2008) indicates that it is optimal to open the mine at US$ 0.70/lbs. (2008) are not in line with Brennan and Schwartz (1985) and are also inconsistent because the switching policy of Gamba (2003) is cyclic in the copper price rather than being linear, and the policy implied by Cortazar et al. However, as noted by Abdel Sabour and Poulin (2006), the switching decisions obtained by Gamba (2003), Cortazar et al. (2008) re-assessed the copper mine example of Brennan and Schwartz (1985). Extending the least-squares Monte Carlo (LSM) method of Longstaff and Schwartz (2001) to optimal switching problems, Gamba (2003), Abdel Sabour and Poulin (2006), Cortazar et al. Endowed Chair for Corporate Finance and Capital Markets, European Business School, 65375 Oestrich-Winkel, Germany. We are also grateful to Hassan Sohbi from Taylor Wessing LLP for his interview on VC contracting practices in Europe. EFM classification: 810, 430, 310 * We thank the law firm Fenwick & West LLP for access to the dataset underlying its quarterly report on "Trends in Terms of Venture Financings in Silicon Valley" we are especially indebted to the authors of this report, Barry Kramer and Michael Patrick, for the detailed explanations that facilitated the data evaluation and the interpretation of results. We obtain estimates of the value of individual terms and the total value of contracts in realistic scenarios, with multiple financing rounds and multiple investors. The pricing model is cali-brated using a dataset of deal terms in Silicon Valley collected by the law firm Fenwick & West LLP, as well as industry statistics from the NVCA. We identify the options embedded in model contracts as published by the National Venture Capital Association (NVCA) and show how they can be priced in interaction using Least Squares Monte Carlo simulation. ![]() This article derives the economic value of venture capital contracts using option pricing techniques. The article shows that a proper arrangement of feeders and DG may lead to efficient investments by allowing a progressive adaptation of the distribution grid to the changing scenarios. The flexibility provided by DG investments -option to abandon and to relocate-is assessed through a Real Option Valuation approach based on the novel Least Square Monte Carlo method (LSM).In order to illustrate the feasibility of the proposed valuation approach, a traditional expansion strategy (distribution feeders) and a flexible investment strategy (distribution feeders and DG) are compared in a study case. This article proposes an investment valuation approach which properly assesses the option value of deferring investments in distribution feeders whereas gaining flexibility by investing in DG units. In this sense, DG units appear as an effective manner of adding flexibility to the distribution expansion planning. Strategic flexibility for seizing opportunities and cutting losses contingent upon an unfavorable unfolding of the long-term uncertainties is an attribute of enormous value when assessing irreversible investments in Distribution Systems. The identification of efficient and well-timed investments in electric distribution networks that cope with large power market uncertainties is currently an open issue of significant research interest. After deregulation of the electricity sector, Distributed Generation (DG)has received increasing interest in the power systems development. ![]()
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