QUANTIFYING MARKET POWER IN THE GERMAN WHOLESALE ELECTRICITY MARKET USING A DYNAMIC MULTI‐REGIONAL DISPATCH MODEL*

This paper quantifies the degree of market power in the German wholesale electricity market. A dispatch model simulates competitive marginal costs. In addition to common input factors like plant capacities, fuel prices and load structures, the model also incorporates international power exchange and dynamic effects like start‐up costs and hydro storage plant dispatch. The simulated prices are subsequently used as a benchmark for observed electricity prices. The analysis reveals significant market power in the German electricity market, mainly exhibited during peak periods. Producer surplus is also increased significantly due to strategic behavior.     

Estimating Facility Size for Variable or Uncertain Activity Levels

In this article, we propose a model and methodology for valuing the option to delay network investment decisions and calculating cost-based access prices. We model the value of the option to invest in each network element as a function of two stochastic variables: the flow of total variable profit from the service provided by the network element and the cost of new investment in that network element. We calculate the option value multiple to be applied to the investment cost component of three main network elements, conduct sensitivity analyses, and highlight key findings.     

Potential für Kraftwerke mit Kohlendioxidrückhaltung aus Systemperspektive

System considerations support a discussion of selected factors influencing the economic viability of power plants with CO₂ sequestration technology (CCS, for carbon dioxide capture and storage), leading to conclusions when and how much of their potential may conceivably be realised. The CCS realisation is interconnected to investments into other technologies, to technological advances, to the price of CO₂ emission certificates, to plant dispatch, and to the prices of power. In a system of CCS potential realisation by individual actors, these variables are endogenous. This article is mainly about them. CCS is more of a long term option than a bridge technology. In contrast to other CO₂ reduction technologies, both economic operation and economic investment necessarily require high CO₂ certificate prices. An increase in power plant efficiency without CCS, switching to natural gas and power generation from renewable sources involve more mature technologies that may benefit from further application within the coming decades. Even far beyond 2020 this effect may delay and dampen the potential of CCS technology. An economic or market potential is dependent to a lesser extent on assumptions about future barriers but rather on their dynamic interactions.     

Oil and Gas Exploration Valuation and the Value of Waiting

The timing flexibility of investments in oil and gas assets can potentially add value. In this article, we examine the value of waiting in exploration projects and propose a real option–based valuation method using least-squares Monte Carlo simulation. We show that the dynamics of the oil and gas prices have a large impact on the value of the option to wait, especially for projects with long lead times and durations. The uncertainty in the forward price curve is modeled using a two-factor stochastic price process. The article also presents the valuation method in the form of MATLAB functions and routines that can be used as an efficient test and analysis platform using the industry-standard input formats.     

Switch,Switch, Switch! A Regime-Switching Option-Based Model for Valuing a Tolling Agreement

This article proposes a real options valuation of a tolling contract using a combined switching option and volatility regime switching model. In a tolling-based transaction, the toller becomes the energy manager (but not the owner) of the power plant, having the option to switch it on or off to benefit from (mitigate) the upside (downside) potential related to frequent, jumpy fluctuations of power (and gas) prices. Value creation from such flexibility in managing the spark spread risk may be better captured by expanding the static NPV of the plant via exercise of a switching (compound) option having the plant itself as an underlying two-market-based asset portfolio (electricity and gas). Results from adoption of a pentanomial lattice pricing approach show that the set of tolling fees the toller would prefer to pay to the tollee “in equilibrium” is a decreasing function in the portfolio volatility because of the higher risk being borne by the former. Though the toller is willing to fairly pay equal or less than the value created from active management of the power plant, obtaining a positive net profit, the tollee may rely on a constant flow of bullet bond-like installments, securing remuneration of equity capital invested and arrangement of a project financing for plant construction.     

Preisdeterminanten des Stromgroßhandels in Frankreich

This article provides a model-based analysis of the French spot market for electricity. Therefore a cost optimizing dispatch model is applied in order to derive a broader understanding of the liberalized electricity market in France considering empirical spot market prices in 2009. At first analysis of market structure and power plant mix is done in accordance with the european framework. The state of supply side competition is suggested as well. Due to the high portion of nuclear energy in the French energy mix the technical availability forecast of the plants plays a crucial role during the price formation on the wholesale market. As a result prices determined by the model are highly correlated with the French spot market. The results suggest a functioning pricing mechanism although deviations occur by ex-ante uncertain demand or unscheduled non-usability of generating units.     

Immigration,Capital Flows and Housing Prices

Research on immigration and real estate has found that immigrants lower house prices in immigrant destination neighborhoods. In this article, we find that this latter result is not globally true. Rather, we show that immigrants can raise neighborhood house prices, at least in the case of the wealthy immigrants that we study. We exploit a surprise suspension and subsequent closure of a popular investor immigration program in Canada to use a difference‐in‐differences methodology comparing wealthy immigrant destination census tracts to nondestination tracts. We find that the unexpected suspension of the program had a negative impact on house prices of 1.7–2.6% in the neighborhoods and market segments most favored by the investor immigrants. This leads to an approximate lower bound on the effect of capital inflows of 5%.     

Repeat‐Sales Indexes: Estimation without Assuming that Errors in Asset Returns Are Independently Distributed

This article proposes an alternative specification for the second stage of the Case‐Shiller repeat‐sales method. This specification is based on serial correlation in the deviations from the mean one‐period returns on the underlying individual assets, whereas the original Case‐Shiller method assumes that the deviations from mean returns by the underlying individual assets are i.i.d. The methodology proposed in this article is easy to implement and provides more accurate estimates of the standard errors of returns under serial correlation. The repeat‐sales methodology is generally used to construct an index of prices or returns for unique, infrequently traded assets such as houses, art and musical instruments, which are likely to be prone to exhibit serial correlation in returns. We demonstrate our methodology on a data set of art prices and on a data set of real estate prices from the city of Amsterdam.     

MAKING USE OF REAL OPTIONS SIMPLE: AN OVERVIEW AND APPLICATIONS IN FLEXIBLE/MODULAR DECISION MAKING

This article focuses on how the use of real options can be made simple, providing an overview of the power of flexible and modular decision making and its use in various applications across industries. After common real options are discussed through a comprehensive example, the article reviews the key lessons and implications of real options thinking for flexible decision making. It then proceeds to propose a modular problem structuring approach that allows simplifying of complex real option problems by decomposing them into a few basic building-block option types (reviewed) connected by some basic decision operators. The resulting problem-structuring option map is depicted in a range of illustrative applications in various industries. Past areas of application of real options as well as research challenges ahead are also discussed.     

The derivation of R&D return indicators within a real options framework

The purpose of this paper is to rework the building blocks of real option applications and to introduce a basket option framework. We find that the characteristic parameters of the risk neutral density function implied in observed share prices within the real option framework represent a novel category of R&D return indicators. Empirical evidence for a set of 13 US bio-pharmaceutical companies is provided. The novel R&D return indicator can be used to analyse investor's expectations on R&D success of a particular firm. The implications of this indicator on decision making are mainly based on its information content on technological and market risk of the products under development in a particular firm. A proposal for a potential application of the stability index in innovation research is discussed as well. The study thus is at the interface between innovation research and (empirical) finance.     

Expansion planning for transmission network under demand uncertainty: A real options framework

In recent years, there has been much expectation that transmission expansion planning should address ever increasing demands for transmission services under significant and complex economic and regulatory uncertainties. In this article, toward meeting the aforementioned expectation, we develop and analyze a real options framework that provides the valuation of a transmission owner's option to expand in his or her network. What distinguishes our framework from the extant literature is that the evolution of the demand follows a geometric Brownian motion process, it explicitly accounts for the physical flow of the electric power economically manifested as the locational marginal prices, and it shows how the values of the expansion options can be determined in the transmission network. Furthermore, our framework shows how to value an option to expedite or delay can be determined given that a specific expansion is planned. An extensive numerical example is presented to illustrate the key features of our framework.     

Dark Fiber Valuation

Valuation of dark fiber has recently generated controversy, sparked particularly by the large sums booked for swaps of dark fiber between companies. One of the issues raised is valuation: i.e., what is the value of an asset that generates no revenue now and may do so at some unknown point in the future but only after investment, in an uncertain business climate, and where prices are dropping? The picture is further complicated because the result of investing to bring the asset to market (i.e. lighting the fiber) changes the supply and demand conditions of the market itself and hence invalidates price predictions. A realistic and consistent valuation methodology is necessary for increasingly cautious companies, auditors, and investors. In this paper we describe such a valuation methodology for dark fibre based on real options. Publicly available bandwidth price services start to make this practical by providing market price information. For dark fibre valuation the real option to be valued are the lighting decisions. We specifically include the effect on the market of adding new capacity by using the price-elasticity of demand within the stochastic price process itself, conditional on lighting decisions. Prices are generally volatile and decreasing with time. The evolution of lighting costs and maintenance are included in the valuation. The real options technique used here is novel in that it combines economic and market factors explicitly with mathematical finance to arrive at a valuation and optimal decisions. We found that the optimal lighting riming and capacity decisions to depend on many of the factors included in the analysis with no simple triggers: the details really matter.     

Real Option Pricing and Bounds in Incomplete Markets

This article prices a real option and constructs narrow bounds around the value of real options embedded in capital budgeting decisions by applying the minimax deviations approach to real options in incomplete markets. While it is straightforward to obtain the unique value of a real option with hyperbolic absolute risk aversion (HARA) utility functions, the parameters of risk aversion are often subject to misspecification and raise concerns for practical uses. Recognizing that investors allow deviation from parameter values related to a benchmark pricing kernel, we derive narrow bounds on a real option price. Comparison with the approaches in the literature clarifies advantages of the minimax bounds: simple, consistent, and efficient.     

Equilibrium Real Options Exercise Strategies with Multiple Players: The Case of Real Estate Markets

This article derives a closed-form solution for an equilibrium real options exercise model with stochastic revenues and costs for monopoly, duopoly, oligopoly and competitive markets. Our model also allows one option holder to have a greater production capacity than others. Under a monopolistic environment we find that the optimal option exercise strategy in real estate markets is dramatically opposite to that in a financial (warrant) market, indicating the importance of paying attention to the institutional details of the underlying market when analyzing option exercise strategies. Our model can be generalized to the pricing of convertible securities and capital investment decisions involving both stochastic revenues and costs under different types of market structures.     

Analyzing operational real options in metal mining investments with a system dynamic model

This article presents a detailed system dynamic (SD) model of a metal mining investment that is usable in ex-ante profitability and operations management analysis. We show how the SD model can be used to analyze the profitability effect of three operational real options: the option to temporarily close production, the option to abandon production, and the option to increase production through cutoff grade change. The SD model allows for intuitive modeling of the multiple interactive real options and arriving at results that are difficult, or impossible, to reach with commonly used spreadsheet software. We also analyze the effect of mining project debt ratio to the project value and show that correctly choosing the debt ratio affects project profitability. The effect on the project value of using three different future metal price scenarios with two different stochastic processes is illustrated to highlight the importance of correct process selection in modeling future metal price paths. A realistic case of a high-cost nickel (Ni) metal mine is used as a basis for the presented numerical illustration of the model.     

Appraisal-Based Real Estate Returns under Alternative Market Regimes

In this article we use Monte Carlo simulation to study the statistical properties of real estate returns. We set up a model where transactions prices are noisy signals of true prices. We then consider a number of appraisal rules, derived from Bayesian and non-Bayesian theory, to estimate the current true price and rate of return. The class of exponential smoothing and Kalman filter rules perform well at both the disaggregate (returns on an individual property) and aggregate (returns on a real property portfolio) levels. A special case of exponential smoothing (α= 1.0) places all weight on current market data. Since this case eliminates smoothing, our results suggest that appraisers should place all weight on current data (no weight on past data) provided that they want to estimate returns rather than values. However, these results should be used with caution if sales prices are very noisy.     

基于节能减排的厂内发电权交易机制研究

结合我国发电企业节能减排过程中各参与方的行为特点,以保证电厂投资人最低利润及发电量平衡为约束,以全厂煤耗量最小为目标,从合理分配投资人利润的角度,设计了适合于厂内节能减排的发电权交易机制,给出了相应的模型。并进一步引入补贴分享系数,在利润、煤耗率和发电权交易报价之间建立联系,指出了厂内发电权交易报价的合理范围,最后设计了模型的求解算法并给出了算例。     

Hedonic Models with Redevelopment Options under Uncertainty

In the hedonic model, implicit market prices can be interpreted as the present values of rents per unit of each hedonic characteristic. But when rents rise, there may be substantial value associated with the option to redevelop to higher intensity per unit land value. In the presence of option value, we first demonstrate that hedonic linear regressions should include an additive nonnegative term for the value of the option. This term increases in the variance of the underlying stochastic process. If this term is omitted, then estimates of implicit market prices for desirable (undesirable) characteristics will be biased downward (upward). This prediction is supported by recent empirical studies. We further suggest that future empirical work can employ the nonlinear functional form derived from our theory.     

An option pricing approach to the valuation of rubber and palm oil producers

Advances in the option pricing literature have important implications for more basic valuation problems. An option pricing approach to the valuation of risky firms can accommodate uncertainty about product market conditions and managerial decisions more readily than a discounted cash flow approach. This paper adapts the stock option pricing approach of Black and Scholes (1973) to the valuation of shares of rubber and palm oil producers. A case study assesses the power of an option-based model to predict market share prices of a rubber and palm oil producer listed on the Stock Exchange of Singapore.