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Structured climate financing: valuation of CDO on inhomogeneous asset pools

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  • N. Packham

    (Berlin School of Economics and Law)

Abstract

Recently, a number of structured funds have emerged as public-private partnerships with the intent of promoting investment in renewable energy in emerging markets. These funds seek to attract institutional investors by tranching the asset pool and issuing senior notes with a high credit quality. Financing of renewable energy (RE) projects is achieved via two channels: small RE projects are financed indirectly through local banks that draw loans from the fund’s assets, whereas large RE projects are directly financed from the fund. In a bottom-up Gaussian copula framework, we examine the diversification properties and RE exposure of the senior tranche. To this end, we introduce the LH++ model, which combines a homogeneous infinitely granular loan portfolio with a finite number of large loans. Using expected tranche percentage notional (which takes a similar role as the default probability of a loan), tranche prices and tranche sensitivities in RE loans, we analyse the risk profile of the senior tranche. We show how the mix of indirect and direct RE investments in the asset pool affects the sensitivity of the senior tranche to RE investments and how to balance a desired sensitivity with a target credit quality and target tranche size.

Suggested Citation

  • N. Packham, 2021. "Structured climate financing: valuation of CDO on inhomogeneous asset pools," SN Business & Economics, Springer, vol. 1(4), pages 1-23, April.
  • Handle: RePEc:spr:snbeco:v:1:y:2021:i:4:d:10.1007_s43546-021-00057-6
    DOI: 10.1007/s43546-021-00057-6
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    1. Nicolas Krauss & Ingo Walter, 2009. "Can Microfinance Reduce Portfolio Volatility?," Economic Development and Cultural Change, University of Chicago Press, vol. 58(1), pages 85-110, October.
    2. Gordy, Michael B., 2003. "A risk-factor model foundation for ratings-based bank capital rules," Journal of Financial Intermediation, Elsevier, vol. 12(3), pages 199-232, July.
    3. Merton, Robert C, 1974. "On the Pricing of Corporate Debt: The Risk Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 29(2), pages 449-470, May.
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    More about this item

    Keywords

    Renewable energy finance; Structured finance; CDO pricing; LH++ model;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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