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1. Managing Financial Risk Trade‐Offs for Hydropower Generation Using Snowpack‐Based Index Contracts

   https://doi.org/10.1029/2020WR027212  

   Hamilton, Andrew L. ; Characklis, Gregory W. ; Reed, Patrick M. ( October 2020 , Water Resources Research)

   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.

    

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2. Resource Scarcity and Sustainability—The Shapes Have Shifted but the Stakes Keep Rising

   https://doi.org/10.3390/su13105751  

   Randall, Alan ( May 2021 , Sustainability)

   null (Ed.)

   The objective is to provide an interpretive reading of the literature in resource scarcity and sustainability theory from the nineteenth century to the present time, focusing on shifts that have occurred in problem definition, conceptual framing, research tools applied, findings, and their implications. My reading shows, as one would expect, that the discourse has become more technical and the analysis more sophisticated; special cases have been incorporated into the mainstream of theory; and, where relevant, dynamic formulations have largely supplanted static analysis. However, that is barely scratching the surface. Here, I focus on more fundamental shifts. Exhaustible and renewable resource analyses were incorporated into the mainstream theory of financial and capital markets. Parallels between the resources and environmental spheres were discovered: market failure concepts, fundamental to environmental policy, found applications in the resources sector (e.g., fisheries), and renewable resource management concepts and approaches (e.g., waste assimilation capacity) were adopted in environmental policy. To motivate sustainability theory and assessment, there has been a foundational problem shift from restraining human greed to dealing with risk viewed as chance of harm, and a newfound willingness to look beyond stochastic risk to uncertainty, ambiguity, and gross ignorance. Newtonian dynamics, which seeks a stable equilibrium following a shock, gave way to a new dynamics of complexity that valued resilience in the face of shocks, warned of potential for regime shifts, and focused on the possibility of systemic collapse and recovery, perhaps incomplete. New concepts of sustainability (a safe minimum standard of conservation, the precautionary principle, and planetary boundaries) emerged, along with hybrid approaches such as WS-plus which treats weak sustainability (WS) as the default but may impose strong sustainability restrictions on a few essential but threatened resources. The strong sustainability objective has evolved from maintaining baseline flows of resource services to safety defined as minimizing the chance of irreversible collapse. New tools for management and policy (sustainability indicators and downscaled planetary boundaries) have proliferated, and still struggle to keep up with the emerging understanding of complex systems. 

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3. Trading networks and Hodge theory ∗

   https://doi.org/10.1088/2399-6528/abd1c2  

   Schenck, Henry ; Sowers, Richard ; Song, Rui ( January 2021 , Journal of Physics Communications)

   The problem of analyzing interconnectedness is one of today’s premier challenges in understanding systemic risk. Connections can both stabilize networks and provide pathways for contagion. The central problem in such networks is establishing global behavior from local interactions. Jiang-Lim-Yao-Ye (Jianget al2011Mathematical Programming 1271203–244) recently introduced the use of theHodge decomposition(see Lim 2020SIAM Review62685–715 for a review), a fundamental tool from algebraic geometry, to construct global rankings from local interactions (see Barbarossaet al2018(2018 IEEE Data Science Workshop (DSW), IEEE)pp 51–5; Haruna and Fujiki 2016Frontiers in Neural Circuits1077; Jiaet al2019(Proc. of the XXV ACM SIGKDD International Conf. on Knowledge Discovery & Data Mining, pp 761–71 for other applications). We apply this to a study of financial networks, starting from the Eisenberg-Noe (Eisenberg and Noe 2001Management Science47236–249) setup of liabilities and endowments, and construct a network of defaults. We then use Jiang-Lim-Yao-Ye to construct a global ranking from the defaults, which yields one way of quantifying ‘systemic importance’.

    

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4. On some extended mixed integer optimization models of the Eisenberg–Noe model in systemic risk management

   https://doi.org/10.1111/itor.12939  

   Dong, Zhi‐Long ; Peng, Jiming ; Xu, Fengmin ; Dai, Yu‐Hong ( February 2021 , International Transactions in Operational Research)

   The Eisenberg and Noe (EN) model has been widely adopted in the systemic risk management for financial networks. In this paper, we propose a unified EN (U‐EN) model, which incorporates both liquidation and bankruptcy costs. We show that the U‐EN model is polynomial‐time solvable and develop an efficient greedy algorithm to solve it. Then we consider identifying the optimal bailout strategy based on stress testing background and propose a binary EN model with bailout budget constraint (B‐EN‐B). The B‐EN‐B model is shown to be NP‐hard. We present analysis on the parameter selection and design some preprocessing procedures correspondingly. A sequential coefficient strengthening algorithm is designed to solve the B‐EN‐B model. Global convergence of the algorithm is established. Moreover, we show that the systemic risk level obtained from the B‐EN‐B model can be used as a precaution for the social planner. Experiments based on both simulated data and data from the Chinese listed banks' network are reported to demonstrate the efficiency of the proposed algorithms.

    

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5. Integrating Operational and Organizational Aspects in Interdependent Infrastructure Network Recovery

   https://doi.org/10.1111/risa.13340  

   Gomez, Camilo ; González, Andrés D. ; Baroud, Hiba ; Bedoya‐Motta, Claudia D. ( June 2019 , Risk Analysis)

   Managing risk in infrastructure systems implies dealing with interdependent physical networks and their relationships with the natural and societal contexts. Computational tools are often used to support operational decisions aimed at improving resilience, whereas economics‐related tools tend to be used to address broader societal and policy issues in infrastructure management. We propose an optimization‐based framework for infrastructure resilience analysis that incorporates organizational and socioeconomic aspects into operational problems, allowing to understand relationships between decisions at the policy level (e.g., regulation) and the technical level (e.g., optimal infrastructure restoration). We focus on three issues that arise when integrating such levels. First, optimal restoration strategies driven by financial and operational factors evolve differently compared to those driven by socioeconomic and humanitarian factors. Second, regulatory aspects have a significant impact on recovery dynamics (e.g., effective recovery is most challenging in societies with weak institutions and regulation, where individual interests may compromise societal well‐being). And third, the decision space (i.e., available actions) in postdisaster phases is strongly determined by predisaster decisions (e.g., resource allocation). The proposed optimization framework addresses these issues by using: (1) parametric analyses to test the influence of operational and socioeconomic factors on optimization outcomes, (2) regulatory constraints to model and assess the cost and benefit (for a variety of actors) of enforcing specific policy‐related conditions for the recovery process, and (3) sensitivity analyses to capture the effect of predisaster decisions on recovery. We illustrate our methodology with an example regarding the recovery of interdependent water, power, and gas networks in Shelby County, TN (USA), with exposure to natural hazards.

    

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