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Forecasting Corporate Green Investment Bonds – An Out of Sample Approach

Collins Ngwakwe ()
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Collins Ngwakwe: University of Limpopo

The Journal of Accounting and Management, 2021, issue 1(11), 163-172

Abstract: Growing corporate awareness and advocacy for ethical finance and production and services has led to growth in green finance and green bonds, but research dealing on forecasting green bonds is scarce. The objective of this paper is to present a global analysis of in-sample and out of sample forecast of global corporate green investment bonds. The Prior work foundation of this paper is inclined on the fusion of modern portfolio theory with sustainable investment. Similarly, global climate vision 2050 highlights the necessity of forecasting global green investment bond availability. Green investment bond data were collected from the S&P Green Bonds Index and the Gretl econometrics and statistics software were used to conduct insample and out-of-sample forecast of green bonds. The results show that the in-sample forecast of green bonds provided a good approximation of actual green bonds at a low error rate of 1.3%. in the same vein, the out-of-sample forecast had a very low standard error of less than 1.5% and the forecast trend line lye within the 95% confidence error bars. It provides future information for investors’ green bond hedging; provides insight for climate policy advocates on the future of green finance to help plan climate adaptation and mitigation and useful for European countries who carry the burden of climate mitigation fund to developing countries. Future research should apply this method in other sustainable finance research. This paper provides the first analysis of green bonds’ in-sample and out of sample forecast using the S&P green bonds index; it thus provides information that bridges research gap and that bridges future green bond uncertainty.

Keywords: Capital market; forecasting; green bonds; green stock; environmental investment (search for similar items in EconPapers)
Date: 2021
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Handle: RePEc:dug:jaccma:y:2021:i:1:p:163-172