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Efficiency impact of convergence bidding in the california electricity market

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  • Ruoyang Li
  • Alva Svoboda
  • Shmuel Oren

Abstract

The California Independent System Operator (CAISO) has implemented Convergence Bidding (CB) on February 1, 2011 under Federal Energy Regulatory Commission’s September 21, 2006 Market Redesign and Technology Upgrade Order. CB is a financial mechanism that allows market participants, including electricity suppliers, consumers and virtual traders, to arbitrage price differences between the day-ahead (DA) market and the real-time (RT) market without physically consuming or producing energy. In this paper, market efficiency is defined in terms of trading profitability, where a zero-profit competitive equilibrium implies market efficiency (Jensen in, J Financial Econ 6(2):95–101, 1978 ). We analyze market data in the CAISO electric power markets, and empirically test for market efficiency by assessing the performance of trading strategies from the perspective of virtual traders. By viewing DA–RT spreads as payoffs from a basket of correlated assets, we can formulate a chance constrained portfolio selection problem, where the chance constraint takes two different forms as a value-at-risk constraint and a conditional value-at-risk constraint, to find the optimal trading strategy. A hidden Markov model (HMM) is further proposed to capture the presence of the time-varying forward premium. This is meant to be a contribution to the modeling of regime shifts in the electricity forward premium with unobservable states. Our backtesting results cast doubt on the efficiency of the CAISO electric power markets, as the trading strategy generates consistent profits after the introduction of CB, even in the presence of transaction costs. Nevertheless, by comparing with the performance before the introduction of CB, we find that the profitability decreases significantly, which enables us to identify the efficiency gain brought about by CB. Convincing evidence for the improvement of market efficiency in the presence of CB is further provided by the test for the Bessembinder and Lemmon (J Finance 57(3):1347–1382, 2002 ) model. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Ruoyang Li & Alva Svoboda & Shmuel Oren, 2015. "Efficiency impact of convergence bidding in the california electricity market," Journal of Regulatory Economics, Springer, vol. 48(3), pages 245-284, December.
  • Handle: RePEc:kap:regeco:v:48:y:2015:i:3:p:245-284
    DOI: 10.1007/s11149-015-9281-3
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    3. Ehsan Samani & Mahdi Kohansal & Hamed Mohsenian-Rad, 2021. "A Data-Driven Convergence Bidding Strategy Based on Reverse Engineering of Market Participants' Performance: A Case of California ISO," Papers 2109.09238, arXiv.org.
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    8. Francisco D. Munoz & Sonja Wogrin & Shmuel S. Oren & Benjamin F. Hobbs, 2018. "Economic Inefficiencies of Cost-based Electricity Market Designs," The Energy Journal, , vol. 39(3), pages 51-68, May.
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    More about this item

    Keywords

    Convergence bidding; Market efficiency; Trading strategy; Value-at-risk; Conditional value-at-risk; Hidden Markov model; C44; C58; C61; D44; D47; L94; Q41; Q49;
    All these keywords.

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • D47 - Microeconomics - - Market Structure, Pricing, and Design - - - Market Design
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q49 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Other

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