An official website of the United States government
Abstract Hydrologic variability poses an important source of financial risk for hydropower‐reliant electric utilities, particularly in snow‐dominated regions. Drought‐related reductions in hydropower production can lead to decreased electricity sales or increased procurement costs to meet firm contractual obligations. This research contributes a methodology for characterizing the trade‐offs between cash flows and debt burden for alternative financial risk management portfolios, and applies it to a hydropower producer in the Sierra Nevada mountains (San Francisco Public Utilities Commission). A newly designed financial contract, based on a snow water equivalent depth (SWE) index, provides payouts to hydropower producers in dry years in return for the producers making payments in wet years. This contract, called a capped contract for differences (CFD), is found to significantly reduce cash flow volatility and is considered within a broader risk management portfolio that also includes reserve funds and debt issuance. Our results show that solutions relying primarily on a reserve fund can manage risk at low cost but may require a utility to take on significant debt during severe droughts. More risk‐averse utilities with less access to debt should combine a reserve fund with the proposed CFD instrument in order to better manage the financial losses associated with extreme droughts. Our results show that the optimal risk management strategies and resulting outcomes are strongly influenced by the utility's fixed cost burden and by CFD pricing, while interest rates are found to be less important. These results are broadly transferable to hydropower systems in snow‐dominated regions facing significant revenue volatility.
more »
« less
Hedging and Evaluating Tail Risks via Two Novel Options Based on Type II Extreme Value Distribution
Tail risk is an important financial issue today, but directly hedging tail risks with an ad hoc option is still an unresolved problem since it is not easy to specify a suitable and asymmetric pricing kernel. By defining two ad hoc underlying “assets”, this paper designs two novel tail risk options (TROs) for hedging and evaluating short-term tail risks. Under the Fréchet distribution assumption for maximum losses, the closed-form TRO pricing formulas are obtained. Simulation examples demonstrate the accuracy of the pricing formulas. Furthermore, they show that, no matter whether at scale level (symmetric “normal” risk, with greater volatility) or shape level (asymmetric tail risk, with a smaller value in tail index), the greater the risk, the more expensive the TRO calls, and the cheaper the TRO puts. Using calibration, one can obtain the TRO-implied volatility and the TRO-implied tail index. The former is analogous to the Black-Scholes implied volatility, which can measure the overall symmetric market volatility. The latter measures the asymmetry in underlying losses, mirrors market sentiment, and provides financial crisis warnings. Regarding the newly proposed TRO and its implied tail index, economic implications can be offered to investors, portfolio managers, and policy-makers.
more »
« less
- Award ID(s):
- 2012298
- PAR ID:
- 10340963
- Date Published:
- Journal Name:
- Symmetry
- Volume:
- 13
- Issue:
- 9
- ISSN:
- 2073-8994
- Page Range / eLocation ID:
- 1630
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract Climate change is intensifying the frequency and severity of extreme events, posing challenges to food security. Corn, a staple crop for billions, is particularly vulnerable to heat stress, a primary driver of yield variability. While many studies have examined the climate impact on average corn yields, little attention has been given to the climate impact on production volatility. This study investigates the future volatility and risks associated with global corn supply under climate change, evaluating the potential benefits of two key adaptation strategies: irrigation and market integration. A statistical model is employed to estimate corn yield response to heat stress and utilize NEX-GDDP-CMIP6 climate data to project future production volatility and risks of substantial yield losses. Three metrics are introduced to quantify these risks: Sigma (σ), the standard deviation of year-on-year yield change, which reflects overall yield volatility; Rho (ρ), the risk of substantial loss, defined as the probability of yield falling below a critical threshold; and beta (β), a relative risk coefficient that captures the volatility of a region’s corn production compared to the globally integrated market. The analysis reveals a concerning trend of increasing year-on-year yield volatility (σ) across most regions and climate models. This volatility increase is significant for key corn-producing regions like Brazil and the United States. While irrigated corn production exhibits a smaller rise in volatility, suggesting irrigation as a potential buffer against climate change impacts, it is not a sustainable option as it can cause groundwater depletion. On the other hand, global market integration reduces overall volatility and market risks significantly with less sustainability concerns. These findings highlight the importance of a multidimensional approach to adaptation in the food sector. While irrigation can benefit individual farmers, promoting global market integration offers a broader solution for fostering resilience and sustainability across the entire food system.more » « less
-
An index-based exchange traded fund (ETF) with underlying se- curities that trade on the same market creates potential opportu- nities for arbitrage between price deviations in the ETF and the corresponding index. We examine whether ETF arbitrage trans- mits small volatility events, termed mini flash crashes, from one of its underlying symbols to another. We address this question in an agent-based, simulated market where agents can trade an ETF and its two underlying symbols. We explore multiple market configurations with active and inactive ETF arbitrageurs. Through empirical game-theoretic analysis, we find that when arbitrageurs actively trade, background traders’ surplus increases because of the increased liquidity. Arbitrage helps the ETF more accurately track the index. We also observe that when one symbol experiences a mini flash crash, arbitrage transmits a price change in the opposite direction to the other symbol. The size of the mini flash crash de- pends more on the market configuration than the arbitrageurs, but the recovery of the mini flash crash is faster when arbitrageurs are present.more » « less
-
An index-based exchange traded fund (ETF) with underlying securities that trade on the same market creates potential opportunities for arbitrage between price deviations in the ETF and the corresponding index. We examine whether ETF arbitrage transmits small volatility events, termed mini flash crashes, from one of its underlying symbols to another. We address this question in an agent-based, simulated market where agents can trade an ETF and its two underlying symbols. We explore multiple market configurations with active and inactive ETF arbitrageurs. Through empirical game-theoretic analysis, we find that when arbitrageurs actively trade, background traders’ surplus increases because of the increased liquidity. Arbitrage helps the ETF more accurately track the index. We also observe that when one symbol experiences a mini flash crash, arbitrage transmits a price change in the opposite direction to the other symbol. The size of the mini flash crash depends more on the market configuration than the arbitrageurs, but the recovery of the mini flash crash is faster when arbitrageurs are present.more » « less
-
null (Ed.)Pricing multi-interval economic dispatch of electric power under operational uncertainty is considered in this two-part paper. Part I investigates dispatch-following incentives for generators under the locational marginal pricing (LMP) and temporal locational marginal pricing (TLMP) policies. Extending the theoretical results developed in Part I, Part II evaluates a broader set of performance measures under a general network model. For networks with power flow constraints, TLMP is shown to have an energy-congestion-ramping price decomposition. Under the one-shot dispatch and pricing model, this decomposition leads to a nonnegative merchandising surplus equal to the sum of congestion and ramping surpluses. It is also shown that, comparing with LMP, TLMP imposes a penalty on generators with limited ramping capabilities, thus giving incentives for generators to reveal their ramping limits truthfully and improve their ramping capacities. Several benchmark pricing mechanisms are evaluated under the rolling-window dispatch and pricing models. The performance measures considered are the level of out-of-the-market uplifts, the revenue adequacy of the system operator, consumer payment, generator profit, level of discriminative payment, and price volatility.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/sym13091630
