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(An example Julia model using the LSM approach for option valuation is here. While Analytica is my favorite modeling environment, a plan for the summer is to redo many of my posts in Julia, which is a great open source alternative to Matlab. However unlike the Matlab example, the model here allows the user to enter the order of the approximating power series, which can only be of order three in the Matlab model. The price process is the same in the Analytica model and in the Matlab example. I might add these features in a separate post, so stay tuned.

Real options valuation monte carlo how to#

Additionally the Matlab example demonstrates how to bound the value of the option between upper and lower bounds using European and American option values.

Real options valuation monte carlo series#

The Matlab model is a little more extensive than my example, as it also demonstrates using a smoothing spline regression as an alternative to approximating the continuation value with a power series regression.

Real options valuation monte carlo download#

You can download the swing options example here:Ī comparable model in Matlab, on which my example is based, is demonstrated at the MathWorks website here.

Real options valuation monte carlo free#

You will need the free version to open and change the model. The model here was created in Analytica, which remains my favorite modeling language. Lastly Glasserman (2004) chapter 8 has an in depth discussion of how to solve options with early exercise features using the LSM approach along with several other Monte Carlo techniques and how they all fit together. Additionally see this nice answer on the StackExchange Quant Finance discussion describing the LSM algorithm in plain English. For further discussion and examples on LSM see my earlier posts where the LSM method is used to value a mine and also value a pharmaceutical patent. LSM is a powerful technique that combines Monte Carlo simulation with regression analysis and dynamic programming. The valuation method used in this post is LSM. See Jaillet et al (2004) for a discussion of the relationship between the three option types.) (European and American options could be used but they would be excessively expensive due to their exercise features. A swing option in this situation would give the power company the ability to hedge their fuel needs on these hot days without having to pay the high daily spot price. A heat wave will cause a spike in electricity usage and energy prices as people crank up their air conditioners to stay cool. During the summer there is the risk of a heat wave hitting the city on any given day. be “swung”, between a high and a low volume level.Īs an example of why swing options are useful consider a power utility in Los Angeles that must prepare for the summer months. The options are called “swing” options because when the option is exercised the quantity can vary, i.e. These option contracts are important because of the high level of uncertainty in the volume needed to meet supply and demand as these conditions change rapidly over time. They allow managers flexibility in determining both the timing and quantity of delivery for energy and related commodities. Swing options are common option contracts in the energy industry. The article shows that a proper combination of lines and FACTS leads to efficient investments by allowing a progressive adaptation of the transmission grid to the changing scenarios.This post provides an example of how to value a natural gas swing option using the Least Squares Monte Carlo method (LSM). In order to illustrate the practicability of the proposed valuation approach, a traditional expansion strategy (lines) and a flexible investment strategy (lines and FACTS) are compared in a real study case. The flexibility provided by FACTS investments-option to abandon and to relocate-is assessed through a real option valuation approach based on the novel least square Monte Carlo method. This article proposes an investment valuation approach which properly assesses the option value of deferring transmission lines investments whereas gaining flexibility by investing in FACTS devices. In this sense, flexible AC transmission systems (FACTS) devices appear as an effective manner of adding flexibility to the transmission 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. Efficient and well-timed investments in electric transmission networks that cope with the large ongoing power market uncertainties are currently an open issue of significant research interest.