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- Stochastic Models of Energy Commodity Prices and Their Applications: Mean-reversion with Jumps and Spikes
Stochastic Models of Energy Commodity Prices and Their Applications: Mean-reversion with Jumps and Spikes
- By Shijie Deng
- Published 10/1/2007
- Valuation , Price modeling
- Unrated
Shijie Deng
Shijie Deng is an associate professor in ISyE. He received a B.S. in applied mathematics from Peking University in P.R. China, an M.S. in mathematics from the University of Minnesota, and a Ph.D. in industrial engineering and operations research from the University of California.
Dr. Deng's research interests include financial asset pricing and real options valuation, financial engineering applications in energy markets, electricity transmission pricing and auction design, risk management and contract theory in supply chains, stochastic modeling and simulation. He has consulted with several private and public companies on issues of pricing, risk management, and asset valuation in the deregulated electricity industry.
View all articles by Shijie DengI propose several mean-reversion jump-diffusion models to describe spot prices of energy commodities that may be very costly to store. I incorporate multiple jumps, regime-switching and stochastic volatility into these models in order to capture the salient features of energy commodity prices due to physical characteristics of energy commodities. Prices of various energy commodity derivatives are derived under each model using the Fourier transform methods. In the context of deregulated electric power industry, I construct a real options approach to value physical assets such as generation and transmission facilities. The implications of modeling assumptions to the valuation of real assets are also examined.