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Multi-Period VaR-Constrained Portfolio Optimization with Applications to the Electric Power Sector

This paper considers the optimization of portfolios of real and contractual assets, including derivative instruments, subject to a Value-at-Risk (VaR) constraint, with special emphasis on applications in electric power. The focus is on translating VaR definitions for a longer period of time, say a year, to decisions on shorter periods of time, say a week or a month. Thus, if a VaR constraint is imposed on annual cash flows from a portfolio, translating this annual VaR constraint into appropriate risk management/VaR constraints for daily, weekly or monthly trades within the year must be accomplished. The paper first characterizes the multi-period VaR-constrained portfolio problem in the form Max {E � kV} subject to a set of separable constraints over the decision variables (the level of assets of different instruments contained in the portfolio), where E and V are, respectively, the expected value and variance of multi-period cashflows from operations covered by the portfolio. Then, assuming the distribution of multi-period cashflows satisfies a certain regularity condition (which is a generalization of the standard Gaussian assumption underlying VaR), we derive computationally efficient methods for solving this problem that take the form of the standard quadratic programming formulations well-known in financial portfolio analysis.

Purchase ( $25 )

Energy Specializations: Energy Investment and Finance – Public and Private Risks, Risk Management; Energy Modeling – Energy Data, Modeling, and Policy Analysis; Electricity – Markets and Prices ; Electricity – Policy and Regulation

JEL Codes: G11: Portfolio Choice; Investment Decisions, Q41: Energy: Demand and Supply; Prices, Q40: Energy: General, G32: Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill, G13: Contingent Pricing; Futures Pricing; option pricing

Keywords: Electricity, Value-at-Risk (VAR), Portfolio analysis, electric power trading

DOI: 10.5547/ISSN0195-6574-EJ-Vol26-No1-1

Published in Volume 26, Number 1 of the bi-monthly journal of the IAEE's Energy Economics Education Foundation.