تصمیم سرمایه گذاری در کارخانجات مجتمع فولادسازی در شرایط عدم اطمینان

Steel is an alloy composed of iron and carbon for which there are two main large-scale production processes: using iron ore and coal as raw materials through a method known as integrated plants with blast furnaces and using iron scrap melted in electrical furnaces, also known as mini-mills or semi-integrated plants. The production in integrated plants typically implies greater investment, but is more cost-competitive as it provides greater economies of scale. The disadvantage of this method is that the furnaces basically need to work almost continuously through their life span, thus reducing the flexibility of production adjustment to market demands. To attenuate this problem, huge investments in lamination assets are commonly made, generating the possibility of production diversification and valuable switch options. This work values an output switch option in a hypothetical integrated steel plant composed of a blast furnace and a hot laminator. Results show that this option can generate a significant increase in the NPV of blast furnace plants. Results also emphasize the importance of correctly choosing the stochastic process for the underlying uncertainty and the effect it may have on the switch option value.

Steel is an alloy composed of iron and carbon. There are two main large-scale production methods. The first involves using iron ore and coal as raw materials in a process known as production in blast furnaces or integrated plants. The second method uses iron scrap (or solid pig iron) melted down in electrical furnaces known as mini-mills or semi-integrated plants. In the integrated plant process, coal has two functions: as a fuel and as a reducer. As a fuel, coal provides the high temperatures – approximately 1500 °C – that are fundamental for iron ore fusion. Acting as a reducer, coal helps to remove the oxygen from iron, allowing the iron to combine with the carbon. Several steps are necessary before it becomes crude steel in the form of slabs or billets. Generally, the production of steel in blast furnaces implies a greater initial investment, but the process proves to be more cost competitive. The main disadvantage is the almost continuous operation of the blast furnaces, which decreases the possibility of reducing production scale when the demand decreases. Steel is a commodity with significant price volatility. As an example of this variation, the price of a ton of hot rolled steel in the U.S. market fluctuated from approximately US$250.00 to US$1200.00 between January 2000 and September 2009. Moreover, steel demand is very unstable with great variations during economic booms and recessions. These variabilities, both in prices and quantities, can significantly affect steel companies' turnover and, consequently, their profitability. As a way of attenuating the effect of these price and demand variations on the plants' profits, it is common for steel companies to adopt an output product switch strategy. Different steel products are demanded by distinct sectors of the economy, and the variations in their prices, even though correlated, are not identical over time. Aiming at taking advantage of this flexibility of product/market demand, steel companies invest in lamination assets – the step of production in which the steel shape is defined – generating valuable product switch options. Although it is intuitive that these options appear to have a significant value, it is important to know how to value them to correctly appraise the necessary investments in lamination assets required to create them. This article values the incremental benefit of product switch options in integrated steel plant projects. To achieve this, a hypothetical integrated plant composed of a blast furnace and a hot laminator is considered. Using a Monte Carlo simulation, the switch option value is estimated, considering two different stochastic processes – Mean Reversion Model (MRM) and Geometric Brownian Motion (GBM) – as price behavior models. This paper is structured as follows: in the second section, a bibliographic revision on real-option valuation of projects is made; in the third section, we present a steel sector overview; in the fourth section, the case study is presented with the model and results; and in the fifth section, we conclude.

The investment decisions in steel plants are taken in an uncertain environment where the price volatility of steel and the variability of quantities demanded have the capacity to significantly change the economic performance of projects in this sector. In the semi-integrated steel plants this problem can be attenuated by reducing production or even stopping production for a required amount of time. This strategy, nevertheless, is not available to integrated plants because the blast furnaces have the disadvantage of having to work in a continuous manner with little flexibility in the scale adjustment. On the other hand, integrated steel companies typically invest in lamination assets which enable them to produce different kinds of steel products. Taking into consideration that these steel products are consumed by different industries and their price variations are correlated but not identical over time, these investments can generate valuable product switch options. In this paper, using a Monte Carlo simulation, we analyze the value of a product switch option in a hypothetical integrated steel plant consisting of a blast furnace and a hot laminator, both with a maximum yearly capacity of 2.8 million ton/year. As price behavior models, two different kinds of stochastic processes are considered, the Mean Reversion Model (MRM) and the Geometric Brownian Motion (GBM). We find that, independent of the chosen process, this option has significant value and enhances considerably the value created for shareholders of integrated steel projects. In some cases, this important real option can even make the difference with respect to the viability of the project itself. As further research in this sector, other options could be investigated, such as capacity expansion.