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Pricing swing options in the electricity markets under regime-switching uncertainty. (English) Zbl 1210.91125
Summary: The spot price market for electricity is highly volatile. The time series of the daily average electricity price is characterised by seasonality, mean reversion, jumps, and regime-switching processes. In electricity markets, ’swing’ contracts, which can provide some protection against the day-to-day price fluctuations, are used to incorporate flexibility in acquiring given quantities of electricity. We develop a lattice approach for the valuation of swing options by modelling the daily average price of electricity by a regime-switching process that utilises three regimes, consisting of Brownian motions and a mean-reverting process. Various numerical examples are presented to illustrate the methodology.

MSC:
91G10 Portfolio theory
91G99 Actuarial science and mathematical finance
91G60 Numerical methods (including Monte Carlo methods)
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References:
[1] DOI: 10.3905/jod.1998.408011 · doi:10.3905/jod.1998.408011
[2] DOI: 10.1287/mnsc.45.5.670 · Zbl 1231.91288 · doi:10.1287/mnsc.45.5.670
[3] DOI: 10.1093/rfs/2.2.241 · doi:10.1093/rfs/2.2.241
[4] DOI: 10.1016/0304-405X(79)90015-1 · Zbl 1131.91333 · doi:10.1016/0304-405X(79)90015-1
[5] DOI: 10.1016/0377-2217(95)00279-0 · Zbl 0924.90014 · doi:10.1016/0377-2217(95)00279-0
[6] DOI: 10.1016/j.eneco.2008.04.006 · doi:10.1016/j.eneco.2008.04.006
[7] DOI: 10.1016/S0140-9883(03)00041-0 · doi:10.1016/S0140-9883(03)00041-0
[8] Hull J, Options, Futures, and Other Derivatives (2002)
[9] DOI: 10.1287/mnsc.1040.0240 · Zbl 1232.90340 · doi:10.1287/mnsc.1040.0240
[10] DOI: 10.1287/mnsc.37.12.1640 · Zbl 0825.90061 · doi:10.1287/mnsc.37.12.1640
[11] DOI: 10.1016/j.eneco.2006.05.012 · doi:10.1016/j.eneco.2006.05.012
[12] DOI: 10.1016/j.eneco.2007.07.011 · doi:10.1016/j.eneco.2007.07.011
[13] DOI: 10.1093/rfs/14.1.113 · Zbl 1386.91144 · doi:10.1093/rfs/14.1.113
[14] DOI: 10.1023/A:1013846631785 · Zbl 1064.91508 · doi:10.1023/A:1013846631785
[15] DOI: 10.1016/j.eneco.2005.09.008 · doi:10.1016/j.eneco.2005.09.008
[16] DOI: 10.1093/rfs/3.3.393 · doi:10.1093/rfs/3.3.393
[17] DOI: 10.1080/13504860210132879 · Zbl 1013.91049 · doi:10.1080/13504860210132879
[18] Weron R, Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach (2006) · doi:10.1002/9781118673362
[19] DOI: 10.1016/j.eneco.2007.05.004 · doi:10.1016/j.eneco.2007.05.004
[20] DOI: 10.1016/j.physa.2004.01.008 · doi:10.1016/j.physa.2004.01.008
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