Risk Transfer in an Electricity Market

Energy is traded using different products; long-term contracts or electricity forward contracts can assure the future transaction price. However, due to the difficulties in storing electrical energy for long periods and in large amounts, risks must be incorporated when defining contract prices through a Forward Risk Premia (FRP). This study analyzes the transfer of uncertainty from electricity market variables to the FRP in long-term contracts. We evaluate a type of econometric risk with the construction of Autoregressive Distributed Lag contagion models for the FRP using electricity demand, spot price, power generation via different technologies, and the Oceanic Niño Index. As a case study, we consider the Colombian electricity market. Our results show empirical models where the FRP has a short-term response with the following variables: hydropower generation, coal power generation, electricity demand, and Oceanic Niño Index, even though its transaction is reflected one or two years after the occurrence of the event.

Stochastic approach to model spot price and value forward contracts on energy markets under uncertainty

The paper deals with a model of electricity spot prices. The proposed dynamics of electricity spot prices is driven by a mean reverting diffusion with jumps having hyperexponential distribution. The analytical formula for the forward contract’s price is derived in a crisp case. Inasmuch as the model parameters are considered to be evaluated imprecisely, their fuzzy counterparts are introduced. With usage of the fuzzy arithmetic, the analytical expression for the forward contract’s price is derived. Several numerical examples highlighting attributes of the fuzzy forward electricity prices are brought out.

Sensitivity analysis in the infinite dimensional Heston model

We consider the infinite dimensional Heston stochastic volatility model proposed in Ref. 7. The price of a forward contract on a non-storable commodity is modeled by a generalized Ornstein–Uhlenbeck process in the Filipović space with this volatility. We prove a representation formula for the forward price. Then we consider prices of options written on these forward contracts and we study sensitivity analysis with computation of the Greeks with respect to different parameters in the model. Since these parameters are infinite dimensional, we need to reinterpret the meaning of the Greeks. For this we use infinite dimensional Malliavin calculus and a randomization technique.

Modeling Electricity Price and Quantity Uncertainty: An Application for Hedging with Forward Contracts

Energy transactions in liberalized markets are subject to price and quantity uncertainty. This paper considers the spot price and energy generation to follow a bivariate semi-nonparametric distribution defined in terms of the Gram–Charlier expansion. This distribution allows us to jointly model not only mean, variance, and correlation but also skewness, kurtosis, and higher-order moments. Based on this model, we propose a static hedging strategy for electricity generators that participate in a competitive market where hedging is carried out through forward contracts that include a risk premium in their valuation. For this purpose, we use Monte Carlo simulation and consider information from the Colombian electricity market as the case study. The results show that the volume of energy to be sold under long-term contracts depends on each electricity generator and the risk assessment made by the market in the forward risk premium. The conditions of skewness, kurtosis, and correlation, as well as the type of the employed risk indicator, affect the hedging strategy that each electricity generator should implement. A positive correlation between the spot price and energy production tends to increase the hedge ratio; meanwhile, negative correlation tends to reduce it. The increase of forward risk premium, on the other hand, reduces the hedge ratio.

BUSINESS ANALYTICS IN FINANCIAL RISK MANAGEMENT

The article examines the definition of the category "risk" in the works by domestic scientists. Financial risk management in the company management system is considered. Its basic principles and postulates are established. Risk management is defined as the process of identifying, analysing, and making or reducing uncertainty in making investment decisions. Approaches to the formation of modern strategies and tactics of risk management are generalized. The sequence of stages, which most fully reflects the essence of the risk management process, is presented. The main stages of financial risk management are characterized and their functional significance is determined. It is established that the main direction for improving the management system is the deve-lopment and implementation of active management based on systemic and situational approaches. To choose the optimal tactics for managing financial risks, it is advisable to classify them into industry and quality. The strategies for financial risk management of modern business are generalized in two categories: passive and active response. The use of integrated approaches and new business concepts for efficient financial risk management is substantiated. The main means of reducing financial risk are identified, namely insurance and sale of financial instruments (forward contracts, futures contracts, swaps and options). The main elements of using business analytics tools are considered and analysed. It is noted that most business analytics tools are used to improve risk management; therefore, risk management tools benefit from business analytics approaches. The use of artificial intelligence models, such as neural networks and the method of reference vectors, agent-oriented theory, cognitive computation, is characterized. The proposed approach is aimed at combining several expert solutions, achieving the highest return on investment and reducing losses by working with difficult situations in a dynamic market environment. It is proved that researching business analytics tools in the field of risk management is useful for both practitioners and academic researchers.

Option Pricing Incorporating Factor Dynamics in Complete Markets

Using the Donsker–Prokhorov invariance principle, we extend the Kim–Stoyanov–Rachev–Fabozzi option pricing model to allow for variably-spaced trading instances, an important consideration for short-sellers of options. Applying the Cherny–Shiryaev–Yor invariance principles, we formulate a new binomial path-dependent pricing model for discrete- and continuous-time complete markets where the stock price dynamics depends on the log-return dynamics of a market influencing factor. In the discrete case, we extend the results of this new approach to a financial market with informed traders employing a statistical arbitrage strategy involving trading of forward contracts. Our findings are illustrated with numerical examples employing US financial market data. Our work provides further support for the conclusion that any option pricing model must preserve valuable information on the instantaneous mean log-return, the probability of the stock’s upturn movement (per trading interval), and other market microstructure features.

COUNTERVAILING RISK MANAGEMENT IN THE FOREST SECTOR THROUGH EXCHANGE-TRADED INSTRUMENTS: CONDINIONS AND DEVELOPMENT PROSPECTS

For the world community, 2020 marked the beginning of change on a global scale. Pulmonary disease epidemic, which spread at a lightning speed throughout the globe, not only exposed the negative aspects of globalization, multicultural society and single economic plateaus, but also provided opportunities for the formation of new trends in economic management. In isolation, positive dynamics were observed in areas with on-line trade opportunities, and negative in traditional energy markets. In this regard, the author carried out a comprehensive analysis of the financial instruments used on the exchange, which made it possible to form a comparative characteristic of hedging, option, futures, derivative and forward. The relationship between the values of wood and the forest area on which it grows has been established and presented by the inequality system. Methods of compounding and discounting are considered in detail, on the basis of which a mechanism for determining the net present value of the cost of growing forest plantations as a capital benefit is proposed. The author gives a calculation of the costs of growing ordinary pine seedlings, and a comparison of the weighted average interest rate on deposits (in rubles) and average inflation, made it possible to prove the investment attractiveness of forestry not only for private business, but also for the state. The study provides an overview of the practices of leading «forest» States on interest rates applied to forest investment. In the conclusion of the article, the author concludes that compensatory risk management in the forest industry is possible using the hedging mechanism of measures by concluding forward contracts for the cultivation of seedlings of a certain tree species.

Application of Option Pricing Framework for Analyzing and Predicting Stock Prices in Energy Markets

In this study, the evaluation of the pricing framework for predicting West Texas Intermediate crude oil stock was implemented where detailed analysis with varying changepoint shows that an arbitrage-free forward price can be derived from the buy-and hold strategy in the energy market thereby enabling investors in the market willing to be salvage from the market uncertainties as well as Arrow-Debreu situations to execute a spot or forward contracts depending on the time and place the market becomes favorable.