Green bonds have gained a significant share in the bond market. However, dynamic risk and its spillover to other conventional bond investments plays an important role in its understanding. In this paper, we analyze the volatility and correlation dynamics between conventional bond and green bond assets under both loose and stringent eligibility green-labeled criteria. We build dynamic conditional correlation (DCC) model specifications using alternative distributional assumptions. We also assess risk dynamics expressed by Value-at-Risk (VaR) and its corresponding loss function. We illustrate risk assessment in within and out-of-sample periods using conventional and green bond returns. The results show that there is significant spillover between conventional and green bond assets, triggering significant hedging strategies. However, these spillover effects are subjected to the type of green-labeled criteria. Finally, a risk assessment using VaR forecasting and its corresponding loss function estimation also demonstrates significant differentiation between green and conventional bonds.
Citation: Aikaterini (Katerina) Tsoukala, Georgios Tsiotas. Assessing green bond risk: an empirical investigation[J]. Green Finance, 2021, 3(2): 222-252. doi: 10.3934/GF.2021012
Green bonds have gained a significant share in the bond market. However, dynamic risk and its spillover to other conventional bond investments plays an important role in its understanding. In this paper, we analyze the volatility and correlation dynamics between conventional bond and green bond assets under both loose and stringent eligibility green-labeled criteria. We build dynamic conditional correlation (DCC) model specifications using alternative distributional assumptions. We also assess risk dynamics expressed by Value-at-Risk (VaR) and its corresponding loss function. We illustrate risk assessment in within and out-of-sample periods using conventional and green bond returns. The results show that there is significant spillover between conventional and green bond assets, triggering significant hedging strategies. However, these spillover effects are subjected to the type of green-labeled criteria. Finally, a risk assessment using VaR forecasting and its corresponding loss function estimation also demonstrates significant differentiation between green and conventional bonds.
[1] | Agliardi E, Agliardi R (2021) Pricing Climate-related Risks in the Bond Market. Jour of Fin Stab 54: 100868. doi: 10.1016/j.jfs.2021.100868 |
[2] | Bollerslev T (1986) Generalized autoregressive conditional heteroscedasticity. J Economet 31: 307-327. doi: 10.1016/0304-4076(86)90063-1 |
[3] | Broadstock DC, Cheng LTW (2019) Time-varying relation between black and green bond price benchmarks: macroeconomic determinants for the first decade. Financ Res Let 29: 17-22. doi: 10.1016/j.frl.2019.02.006 |
[4] | Chen F, Sutcliffe C (2012) Better cross hedges with composite hedging? Hedging equity portfolios using financial and commodity futures. Eur J Financ 18: 575-595. doi: 10.1080/1351847X.2011.620253 |
[5] | Christoffersen P (1998) Evaluating interval forecasts. Int Econ Rev 39: 841-862. doi: 10.2307/2527341 |
[6] | Engle RF (2002) Dynamic conditional correlation: a simple class of multivariate GARCH models. J Bus Econ Stat 20: 339-350. doi: 10.1198/073500102288618487 |
[7] | Flammer C (2018) Corporate Green Bonds. Working Paper. SSRN. |
[8] | Huynh TLD, Hillec E, Nasir MA (2020) Diversification in the age of the 4th industrial revolution: The role of artificial intelligence, green bonds and cryptocurrencies. Technol Forecast Soc Change 159: 120188. doi: 10.1016/j.techfore.2020.120188 |
[9] | Huynh TLD (2020) When 'green' challenges 'prime': empirical evidence from government bond markets. J Sust Financ Investments, 1-14. |
[10] | Huynh TLD, Foglia M, Nasir MA, et al. (2021) Feverish sentiment and global equity market during COVID-19 Pandemic. J Econ Behav Organ [In Press]. |
[11] | Gianfrate G, Peri M (2019) The green advantage: exploring the convenience of issuing green bonds. J Clean Prod 219: 127-135. doi: 10.1016/j.jclepro.2019.02.022 |
[12] | ICMA (2017) The Green Bond Principles 2017: Voluntary Process Guidelines for Issuing Green Bonds. Annual Report. Switzerland. Available from: https://www.icmagroup.org/assets/documents/Regulatory/\Green-Bonds/GreenBondsBrochure-JUNE2017.jpg. |
[13] | Jin J, Hanb L, Wu L (2020) The hedging effect of green bonds on carbon market risk. Int Rev Financ Anal 71: 1057-1072. |
[14] | Kanamura T (2020) Are green bonds environmentally friendly and good performing assets? Energy Econ 88: 47-67. |
[15] | Karpf A, Mandel A (2018) The changing value of the 'green' label on the US municipal bond market. Nat Climate Change 8: 61-165. doi: 10.1038/s41558-017-0062-0 |
[16] | Kroner KF, Sultan J (1993) Time-Varying Distributions and Dynamic Hedging with Foreign Currency Futures. J Financ Quant Anal 28: 535-551. doi: 10.2307/2331164 |
[17] | Kupiec PH (1995) Techniques for verifying the accuracy of risk management model. J Deriv 3: 73-84. doi: 10.3905/jod.1995.407942 |
[18] | Lee HT (2010) Regime switching correlation hedging. J Bank Financ 34: 2728-2741. doi: 10.1016/j.jbankfin.2010.05.009 |
[19] | Lee HT, Yorder JK (2007) A bivariate markov regime switching GARCH approach to estimate time varying minimum variance hedge ratios. Appl Econ 39: 1253-1265. doi: 10.1080/00036840500438970 |
[20] | Nanayakkara M, Colombage S (2019) Do investors in Green Bond market pay a premium? Appl Econ 40: 4425-4437. doi: 10.1080/00036846.2019.1591611 |
[21] | Nguyen SP, Huynh TLD (2019) Portfolio optimization from a Copulas-GJR-GARCH-EVT-CVAR model: Empirical evidence from ASEAN stock indexes. Quant Financ Econ 3: 562-585. doi: 10.3934/QFE.2019.3.562 |
[22] | OECD (2017) Mobilising Bond Markets for a Low-Carbon Transition, Green Finance and Investment. Paris: EOCD Publishing. Available from: http://doi.org/10.1787/9789264272323-en. |
[23] | Partridge C, Medda FR (2020) The evolution of pricing performance of green municipal bonds. J Sust Financ Investment 10: 44-64. doi: 10.1080/20430795.2019.1661187 |
[24] | Pham L (2016) Is it risky to go green? A volatility analysis of the green bond market. J Sust Financ Investment 6: 263-291. doi: 10.1080/20430795.2016.1237244 |
[25] | Pham L, Huynh TLD (2020) How does investor attention influence the green bond market? Financ Res Lett 35: 101533J. doi: 10.1016/j.frl.2020.101533 |
[26] | Reboredo JC (2018) Green bond and financial markets: Co-movement, diversification and price spillover effects. Energy Econ 74: 38-50. doi: 10.1016/j.eneco.2018.05.030 |
[27] | S&P Green Bond Indices Methodology. S&P Dow Jones Indices: Indices Methodology, February 2021. |
[28] | Tsay RS (2005) Analysis of financial time series, NJ: Wiley 2nd edition. |
[29] | Tse YK, Tsui AKC (2002) A multivariate GARCH model with time-varying correlations. J Bus Econ Stat 20: 351-362. doi: 10.1198/073500102288618496 |
[30] | Tsiotas G (2018) A Bayesian encompassing test using combined Value-at-Risk estimates. Quant Financ 18: 395-417. doi: 10.1080/14697688.2017.1330551 |
[31] | Tsiotas G (2020) An ABC approach for CAViaR models with an asymmetric decision rule. J Stat Comput Simul 90: 1373-1398. doi: 10.1080/00949655.2020.1727477 |
[32] | Zerbib OD (2017) The Green Bond Premium, University of Chicago Press. |
[33] | Zerbib OD (2019) The Effect of Pro-Environmental Preferences on Bond Prices: Evidence from Green Bonds. J Bank Financ 98: 39-60. doi: 10.1016/j.jbankfin.2018.10.012 |