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Monetary Policies on Green Financial Markets: Evidence from a Multi-Moment Connectedness Network (2405.02575v2)

Published 4 May 2024 in econ.GN and q-fin.EC

Abstract: This paper introduces a novel multi-moment connectedness network approach for analyzing the interconnectedness of green financial market. Focusing on the impact of monetary policy shocks, our study reveals that connectedness within the green bond and equity markets varies with different moments (returns, volatility, skewness, and kurtosis) and changes significantly around Federal Open Market Committee (FOMC) events. Static analysis shows a decrease in connectedness with higher moments, while dynamic analysis highlights increased sensitivity to event-driven shocks. We find that both tight and loose monetary policy shocks initially elevate connectedness within the first six months. However, the effects of tight shocks gradually fade, whereas loose shocks may reduce connectedness after one year. These results offer insight to policymakers in regulating sustainable economies and investment managers in strategizing asset allocation and risk management, especially in environmentally focused markets. Our study contributes to understanding the complex dynamics of the green financial market in response to monetary policies, helping in decision-making for sustainable economic development and financial stability.

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References (49)
  1. Connectedness of energy markets around the world during the covid-19 pandemic. Energy economics, 109:105900.
  2. Quantile connectedness: modeling tail behavior in the topology of financial networks. Management Science, 68(4):2401–2431.
  3. A network analysis of the volatility of high dimensional financial series. Journal of the Royal Statistical Society Series C: Applied Statistics, 66(3):581–605.
  4. Asymmetric network connectedness of fears. The Review of Economics and Statistics, pages 1–41.
  5. Switching generalized autoregressive score copula models with application to systemic risk. Journal of Applied Econometrics, 34(1):43–65.
  6. Connectedness in implied higher-order moments of precious metals and energy markets. Energy, 263:125588.
  7. Interconnectedness in the interbank market. Journal of Financial Economics, 133(2):520–538.
  8. Catania, L. (2021). Dynamic adaptive mixture models with an application to volatility and risk. Journal of Financial Econometrics, 19(4):531–564.
  9. Optimal monetary policy responses to carbon and green bubbles: A two-sector dsge analysis. Energy Economics, page 107281.
  10. Determinants of connectedness in financial institutions: Evidence from taiwan. Emerging Markets Review, 55:100951.
  11. Climate change, financial stability and monetary policy. Ecological Economics, 152:219–234.
  12. Multiscale interplay of higher-order moments between the carbon and energy markets during phase iii of the eu ets. Energy Policy, 156:112428.
  13. The effect of monetary policy and private investment on green finance: evidence from hungary. Journal of Risk and Financial Management, 15(3):117.
  14. On the network topology of variance decompositions: Measuring the connectedness of financial firms. Journal of Econometrics, 182(1):119–134.
  15. Trans-atlantic equity volatility connectedness: Us and european financial institutions, 2004–2014. Journal of Financial Econometrics, 14(1):81–127.
  16. Investigating the spillovers and connectedness between green finance and renewable energy sources. Renewable Energy, 197:709–722.
  17. Credit spreads and business cycle fluctuations. American economic review, 102(4):1692–1720.
  18. Monitoring banking system connectedness with big data. Journal of Econometrics, 212(1):203–220.
  19. Dynamic connectedness in the higher moments between clean energy and oil prices. Available at SSRN 4565305.
  20. Deconstructing monetary policy surprises—the role of information shocks. American Economic Journal: Macroeconomics, 12(2):1–43.
  21. Jordà, Ò. (2005). Estimation and inference of impulse responses by local projections. American economic review, 95(1):161–182.
  22. Large time-varying parameter vars. Journal of Econometrics, 177(2):185–198.
  23. Impulse response analysis in nonlinear multivariate models. Journal of econometrics, 74(1):119–147.
  24. Tracking carbon intensity changes between china and japan: Based on the decomposition technique. Journal of Cleaner Production, 349:131090.
  25. Emerging industry development and information transmission in financial markets: Evidence from china’s renewable energy. Energy Economics, 128:107192.
  26. Uncertainties and green bond markets: Evidence from tail dependence. International Journal of Finance & Economics, 28(4):4458–4475.
  27. How to effectively stabilize china’s commodity price fluctuations? Energy Economics, 84:104544.
  28. Tracking policy uncertainty under climate change. Resources Policy, 83:103699.
  29. Connectedness network and dependence structure mechanism in green investments. Energy Economics, 72:145–153.
  30. The directional volatility connectedness between crude oil and equity markets: New evidence from implied volatility indexes. Energy Economics, 57:78–93.
  31. Spillovers and connectedness between green bond and stock markets in bearish and bullish market scenarios. Finance Research Letters, 49:103120.
  32. Pham, L. (2021). Frequency connectedness and cross-quantile dependence between green bond and green equity markets. Energy Economics, 98:105257.
  33. Connectedness between monetary policy uncertainty and sectoral stock market returns: Evidence from asymmetric tvp-var approach. International Review of Financial Analysis, 90:102946.
  34. Price connectedness between green bond and financial markets. Economic Modelling, 88:25–38.
  35. Network connectedness of green bonds and asset classes. Energy Economics, 86:104629.
  36. The liquidity impact of chinese green bonds spreads. International Review of Economics & Finance, 82:318–334.
  37. Green bonds and conventional financial markets in china: A tale of three transmission modes. Energy Economics, 113:106200.
  38. How do fossil energy prices affect the stock prices of new energy companies? evidence from divisia energy price index in china’s market. Energy, 169:637–645.
  39. An analysis of the impact of fiscal and monetary policy fluctuations on the disaggregated level renewable energy generation in the g7 countries. Renewable Energy, 189:1154–1165.
  40. Bridging: locating critical connectors in a network. Social networks, 32(3):212–220.
  41. Energy market reforms in china and the time-varying connectedness of domestic and international markets. Energy Economics, 117:106495.
  42. Complex risk contagions among large international energy firms: A multi-layer network analysis. Energy Economics, 114:106271.
  43. Measuring climate transition risk spillovers. Review of Finance, page Forthcoming.
  44. Quantitative easing and volatility spillovers across countries and asset classes. Management Science, 63(2):333–354.
  45. The impact of the covid-19 pandemic and russia-ukraine war on multiscale spillovers in green finance markets: Evidence from lower and higher order moments. International Review of Financial Analysis, 89:102735.
  46. Global energy market connectedness and inflation at risk. Energy Economics, 126:106975.
  47. Cholesky gas models for large time-varying covariance matrices. Journal of Management Science and Engineering, 9(1):115–142.
  48. Fast estimation of a large tvp-var model with score-driven volatilities. Journal of Economic Dynamics and Control, 157:104762.
  49. Does us monetary policy affect the connectedness of global financial markets? Available at SSRN 4085953.

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