scholarly journals Commodity Transaction Tax (CTT)

Author(s):  
Swamy Perumandla ◽  
Padma Kurisetti

This study aims to examine the time-varying correlations and volatility linkages between commodity and equity markets before and after the implementation of the commodity transaction tax (CTT) in India in 2013. The study utilizes symmetric and asymmetric DCC-EGARCH model to estimate correlation dynamics. Evidence suggests that the volatility and dynamic correlation linkages between commodities and equity markets are significantly affected by the triggering events. The time-varying correlations of Comdex-Nifty 50 show an unintended steep decline in the post-CTT period. It is an indication of a “flight to quality” phenomenon, where investors move capital from non-agricultural commodity futures to other cross markets and international markets. However, DCC of Comdex-Dhaanya pair is highly volatile in the post-CTT period and also noticed an increased correlation and volatility between the Dhaanya-Nifty 50 pair. Moreover, the correlation dynamics reveal a certain degree of interdependence between the cross markets, which are lower especially during the triggering episodes.

2021 ◽  
Vol 18 ◽  
pp. 1380-1388
Author(s):  
Tirngo Dinku ◽  
Worku Gardachw ◽  
Ngozi Adeleye

This study models the volatility of returns for selected agricultural commodity prices in Ethiopia using the generalized autoregressive conditional heteroskedasticity (GARCH) approach. GARCH family models, specifically threshold GARCH and exponential GARCH were employed to analyze the time varying volatility of selected agricultural commodities prices from 2010 to 2021. The data analysis results revealed that, out of the GARCH specifications, the EGARCH model with the normal distributional assumption of residuals was a better fit model for the price volatility of “teff” and “red pepper” in which their return series reacted differently to the “good” and “bad” news. The study indicated the existence of a leverage effect, which implied that the “bad” news could have a larger effect on volatility than the “good” news of the same magnitude, and the asymmetric term was statistically significant.


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