In portfolio theory, the most commonly used model for estimating the val= ue of an option is the Black and Scholes model [1]. This model is base= d upon the assumptions of modern portfolio theory, where prices reflect all= the available information. The Black and Scholes model gives the value of = an option as a function of the spot price and the volatility of the underly= ing asset, the strike price, the time and the risk free rate. It is suitabl= e for European options, while the estimation of an American option will req= uire in addition to estimate the likelihood of early exercise (generally re= sulting from discontinuity events such as dividend distribution or bankrupt= cy).

Option pricing in energy markets raises specific issues, due to difficul= t storage and the existence of spot price models [2,3]. For this = reason, the time of exercise is a much more crucial parameter than in finan= cial markets, and can be negotiated between the parties. Therefore, Europea= n and American options shall be treated separately. European options can be= priced by predicting a spot price and using an approach similar to the Bla= ck and Scholes model. For American options, the Black and Scholes equation = becomes an inequality which solution can be approximated by robust optimiza= tion models [4,5].

The ongoing transition from centralized architecture to interoperable gr= ids managed by competing operators is expected to boost inter-grid transact= ions. The expected cost reduction in storage solution will offer to operato= rs a more and more viable alternative to the sale of production surplus. Th= ese parameters must be taken into account in a model for derivative pricing= .

[1] The Pricing of Options and Corporate Liabilities, Fischer Black and = Myron Scholes, Journal of Political Economy, Vol. 81, No. 3 (May - Jun., 19= 73), pp. 637-654.

[2] ELECTRICITY MARKET DESIGN: Energy Trading Practice and Market Manipu= lation Theory, William W. Hogan, 7th Annual Nodal Trader Conference, New Yo= rk, NY, October 9, 2014.

[3] Modeling and evaluating electricity options markets with intelligent= agents, Lane, D.W.; Richter, C.W., Jr.; Sheble, G.B., International Confer= ence on Electric Utility Deregulation and Restructuring and Power Technolog= ies, 2000.

[4] Electricity derivatives and risk management, S.J. Deng, S.S. Oren, E= nergy, Volume 31, Issues 6=E2=80=937, May=E2=80=93June 2006, Pages 940=E2= =80=93953.

[5] Energy and Power Risk Management, New developments in Modeling, Pric= ing, and Hedging, Alexander Eydeland and Krzysztof Wolniec, Wiley, 2003.

**Contributor**

Dr Philippe Ezran, Large Networks and Systems Group (LANEAS)

Dr. Yoram Haddad, Jerusalem College of Technology