Forward Price Curve Research Articles

The Levelised Cost of Frequency Control Ancillary Services in Australia’s National Electricity Market

Over the period 2016–2021 Australia’s National Electricity Market (NEM) experienced an investment supercycle with 16,000MW of new utility-scale renewable plant commitments in a power system with a peak demand of 35,000MW, and the disorderly loss of 5,000MW of synchronous coal-fired plant. This placed strains on system security, most visibly in the distribution of the power systems’ frequency, requiring material changes to the NEM’s suite of Frequency Control Ancillary Service (FCAS) markets. Utility-scale batteries are ideally suited for FCAS duties, but there is no forward price curve for FCAS markets, nor is there any systematic framework for determining equilibrium prices that might otherwise be used for investment decision-making. In this article, we develop an approach for quantifying long run equilibrium costs and stochastic spot prices in the markets for Frequency Control Ancillary Services, with the intended application being to guide the suitability of utility-scale battery investments under conditions of uncertainty and missing forward FCAS markets.

Etrm: Energy Trading and Risk Management in R

This paper introduces [etrm](https://CRAN.R-project.org/package=etrm), an R package with tools for trading and financial risk management in energy markets. Contracts for electric power and natural gas differ from most other commodities due to the fact that physical delivery takes place over a time interval, and not at a specific point in time. There is typically strong seasonality, limited storage and transmission capacity and strong correlation between price and required volume. Such characteristics need to be taken into account when pricing contracts and managing financial risk related to energy procurement. Tools for these task are usually bundled into proprietary Energy Trading Risk Management (ETRM) systems delivered by specialized IT vendors. The [etrm](https://CRAN.R-project.org/package=etrm) package offers a transparent solution for building a forward price curve for energy commodities which is consistent with methods widely used in the industry. The user's fundamental market view may be combined with contract price quotes to form a forward curve that replicate current market prices, as described in @ollmar2003analysis and @benth2007extracting. [etrm](https://CRAN.R-project.org/package=etrm) also provides implementations of five portfolio insurance trading strategies for energy price risk management. The forward market curve and the energy price hedging strategies are core elements in an ETRM system, which to the best of the author's knowledge has not been previously available in the R ecosystem.

Stochastic simulation of Brazilian forward energy prices

Energy trading offers great gain opportunities but also exposure to risk due to price volatility. A proper price model is a key element of risk analysis by electricity market traders and represents a strong tool for providing a better understanding of market dynamics. Despite the existing methodologies, the agenda for new research development is still open, mainly considering specific regulatory conditions and the dynamics of energy markets under development. This work provides a technique to simulate stochastic forward price curves for the Brazilian energy market by using stochastic procedures widely used in the financial and stock markets. The results of this work conveniently represent the uncertainty in Brazilian energy market prices and can be applied in risk management and decision making.

A structural Heath–Jarrow–Morton framework for consistent intraday spot and futures electricity prices

The framework is based on stochastic processes with economic interpretations and is consistent with the initial forward price curve

Energy Factors, Leasing Structure and the Market Price of Office Buildings in the U.S.

This paper presents an empirical analysis of the relation between energy factor markets, leasing structures, and the transaction prices of office buildings in the U.S. We employ a large sample of 15,133 office building transactions between 2001 and 2010. In addition to building characteristics, we also include information on the operating expenses, net operating income, and market capitalization rates at sale to estimate an asset-pricing model for commercial office real estate assets. A further set of important controls in our analysis is the forward/futures contract prices for electricity and natural gas. We also include weather metrics for each building’s location and sale date. Our final set of controls includes information on the dominant contractual leasing structure of the buildings. Our empirical results suggest that Energy Star labels do not explain additional variance in property prices once the key asset-pricing factors of expenses, income and market capitalization rates are included. By contrast, energy-factor market prices, the shape of the energy forward price curves, and weather metrics are consistently significant determinants of office building transaction prices, suggesting that commercial office building prices are exposed to shocks in these markets.

Equilibrium Price Dynamics of Emission Permits

This article presents a stochastic equilibrium model for environmental markets that allows us to study the characteristic properties of emission permit prices induced by the design of today’s cap-and-trade systems. We characterize emission permits as highly nonlinear contingent claims on economy-wide emissions and reveal their hybrid nature between investment and consumption assets. Our model makes predictions about the dynamics and volatility structure of emission permit prices, the forward price curve, and the implications for option pricing in this market. Empirical evidence from existing emissions markets shows that the model explains the stylized facts of emission permit prices and related derivatives.

Electricity forward curves with thin granularity: Theory and empirical evidence in the hourly EPEXspot market

We propose a constructive definition of electricity forward price curve with cross-sectional timescales featuring hourly frequency on. The curve is jointly consistent with both risk-neutral market information represented by baseload and peakload futures quotes, and historical market information, as mirrored by periodical patterns exhibited by the time series of day-ahead prices. From a methodological standpoint, we combine nonparametric filtering with monotone convex interpolation such that the resulting forward curve is pathwise smooth and monotonic, cross-sectionally stable, and time local. From an empirical standpoint, we exhibit these features in the context of EPEX Spot and EEX Derivative markets. We perform a backtesting analysis to assess the relative quality of our forward curve estimate compared to the benchmark market model of Benth, Koekebakker, and Ollmar (2007).

Electricity Forward Curves with Thin Granularity

We put forward a constructive definition of electricity forward price curve with cross-sectional timescale encompassing hourly frequency upward. The curve is jointly consistent to both risk-neutral market information, as represented by base load and peak load futures quotes, and historical market information, as mirrored by periodical patterns exhibited by time series of day-ahead prices. On a methodological ground, we combine non-parametric filtering with monotone convex interpolation in a way that the resulting forward curve is path wise smooth and monotonic, cross-sectionally stable, and time local. On an empirical ground, we exhibit these features in the joint context of EPEX Spot and EEX Derivative markets. A back testing analysis assesses the relative quality of our forward curve estimate compared to the benchmark market model of Benth et al. (2007).

THE EVALUATION OF MULTIPLE YEAR GAS SALES AGREEMENT WITH REGIME SWITCHING

A typical gas sales agreement (GSA), also called a gas swing contract, is an agreement between a supplier and a purchaser for the delivery of variable daily quantities of gas, between specified minimum and maximum daily limits, over a certain number of years at a specified set of contract prices. The main constraint of such an agreement that makes them difficult to value is that in each gas year there is a minimum volume of gas (termed take-or-pay or minimum bill) for which the buyer will be charged at the end of the year (or penalty date), regardless of the actual quantity of gas taken. We propose a framework for pricing such swing contracts for an underlying gas forward price curve that follows a regime switching process in order to better capture the volatility behavior in such markets. With the help of a recombining pentanomial tree, we are able to efficiently evaluate the prices of the swing contracts, find optimal daily decisions and optimal yearly use of both the make-up bank and the carry forward bank at different regimes. We also show how the change of regime will affect the decisions.

An Online Appendix to: 'Violations of Uncovered Interest Rate Parity and International Exchange Rate Dependences'

This online appendix to "Violations of Uncovered Interest Rate Parity and International Exchange Rate Dependences" includes the copula density function for the Clayton-Frank-Gumbel mixture copula and the details for the likelihood based estimation of the multivariate currency basket log returns. Currency carry trade high and low interest rate baskets over time are shown. Further results for the copula parameter fits and associated dependence measures are then analysed. A description of the method used to calculate the confidence intervals for the covariance regression is given. Finally, the method used to interpolate the one month forward price curve is explained.The paper "Violations of Uncovered Interest Rate Parity and International Exchange Rate Dependences" to which these Appendices apply is available at the following URL: http://ssrn.com/abstract=2638163

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.

The forward dynamics in energy markets – infinite-dimensional modelling and simulation

In this paper an infinite-dimensional approach to model energy forward markets is introduced. Similar to the Heath–Jarrow–Morton framework in interest-rate modelling, a first-order hyperbolic stochastic partial differential equation models the dynamics of the forward price curves. These equations are analysed, and in particular regularity and no-arbitrage conditions in the general situation of stochastic partial differential equations driven by an infinite-dimensional martingale process are studied. Both arithmetic and geometric forward price dynamics are studied, as well as accounting for the delivery period of electricity forward contracts. A stable and convergent numerical approximation in the form of a finite element method for hyperbolic stochastic partial differential equations is introduced and applied to some examples with relevance to energy markets.

Policy Uncertainty about Australia's Carbon Price: Expert Survey Results and Implications for Investment

AbstractAustralia's carbon‐pricing policy remains in doubt due to a lack of bipartisan political support. A survey of Australian‐based carbon‐pricing experts demonstrates profound policy uncertainty: 40 per cent of respondents expect the current carbon‐pricing mechanism to be repealed, but 80 per cent expect that there will be a carbon price in 2020. The forward price curve is U‐shaped and has great variance, with the 60 per cent confidence interval spanning from zero to A$25/t in 2020. Carbon policy uncertainty causes large excess costs in Australia's energy sector and may result in delay and diversion of investment.

Table of Contents

Abstract Features Force Majeure to Apply Small Comfort to Some Crisis‐Affected Contracts A. Michael Sabino Anticipated Recession Effects—Natural Gas Recession Aside, Depending on NYMEX Forward Price Curve Is Mistake Dale M. Nesbitt and Thomas Y. Choi Anticipated Recession Effects—Gas Prices Natural Gas Prices in a Recession Christopher Gulick Anticipated Recession Effects—Storage Can Gas Storage Development Survive the Recent Financial Market Collapse? Kenneth L. Beckman Anticipated Recession Effects FERC Winter Outlook Shows Changing Economic Conditions, Falling Prices FERC Staff Columns Federal Regulation and Energy Issues Is the Era of Big Government Back? James J. Hoecker Energy and the Environment Measuring the Costs and the Benefits of Energy Development Jonathan A. Lesser

04/01339 Constructing forward price curves in electricity markets: Fleten, S.-E. and Lemming, J. Energy Economics, 2003, 25, (5), 409–424

04/01339 Constructing forward price curves in electricity markets: Fleten, S.-E. and Lemming, J. Energy Economics, 2003, 25, (5), 409–424

Constructing forward price curves in electricity markets

We present and analyze a method for constructing approximated high-resolution forward price curves in electricity markets. Because a limited number of forward or futures contracts are traded in the market, only a limited picture of the theoretical continuous forward price curve is available to the analyst. Our method combines the information contained in observed bid and ask prices with information from the forecasts generated by bottom-up models. As an example, we use information concerning the shape of the seasonal variation from a bottom-up model to improve the forward price curve quoted on the Nordic power exchange.

BUYING TIME: The New Merchant Power Dialectic

Power business strategists have all long since come to the conclu-sion that the unique monopoly service of generation provision hasbecome a commodit y business, in which skill at cost control, operatingefficiency and price speculation through trading are the drivers of suc-cess. On a parallel track, regulators increasingly derive self satisfactionfrom the increasing conformity of their domains to true marginal costcomp etition. For all these pla yers, the power business finally seems to befitting int o that Econom ics /Finance 101 box we know so well: valuationof alternative strategies discounted cash flow streams.Thi s almost Newtonian certainty of how the world work s also is tobe found in analysis of the current acquisition boom triggered by de-regulati on, i.e. it is all interpreted as bidder match-ups of present valuecash stream analysis to corporate strategy. Sales of assets are dri ven byre gulator y compliance or core business focus . Purchasers are drawn ofasset s by one of three basic approaches: economics of scale, initiallythrou gh the fuel suppl y chain; asset backed trading of retail and whole-sale en erg y services; and operational efficiencies based on improvedmana gem ent of specific sites. Power strategies are thus characterized asall ab out alternative appraisals of cash flow potential; different cost ofcapital hurdle rates and different forward price curve s for the regionalmark et s int o which the particular auction is being carved.