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.
Published in: Proceedings of the 32nd Hawaii International Conference on System Sciences Volume 3
Publication year: 1999
Co-author 1: Aram Sogomonian
Co-author 2: Blake Johnson
This paper presents and applies a methodology for valuing electricity derivatives by constructing replicating portfolios from electricity futures and the risk free asset. Futures based replication is argued to be made necessary by the non-storable nature of electricity, which rules out the traditional spot market, storage-based method of valuing commodity derivatives. Using the futures based approach, valuation formulae are derived for spark spread options for both geometric Brownian motion and mean reverting price processes. The valuation result is in turn used to construct real options based valuation formula for generation assets. Finally, the valuation formula derived for generation assets is used to value a sample of assets that have been recently sold, and the theoretical values calculated are compared to the observed sales prices of the assets.
This paper presents and applies a methodology for valuing electricity derivatives by constructing replicating portfolios from electricity futures and the risk free asset. Futures based replication is argued to be made necessary by the non-storable nature of electricity, which rules out the traditional spot market, storage-based method of valuing commodity derivatives. Using the futures based approach, valuation formulae are derived for spark spread options for both geometric Brownian motion and mean reverting price processes. The valuation result is in turn used to construct real options based valuation formula for generation assets. Finally, the valuation formula derived for generation assets is used to value a sample of assets that have been recently sold, and the theoretical values calculated are compared to the observed sales prices of the assets.