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Analysis of lead-lag relationship and volatility spillover: evidence from Indian agriculture commodity markets

Muneer Shaik et al.

International Journal of Bonds and Derivatives2021https://doi.org/10.1504/ijbd.2021.116972article
ABDC C
Weight
0.39

What the paper says

This study examines the lead-lag relationship and volatility spillover in the Indian commodity derivatives market. The study has been conducted with ten commodities based on the availability of data and liquidity for the period of 2010 to 2020. Augmented dickey-fuller (ADF) test is used to check the stationarity of the price series. The study uses Johansen's cointegration test to check for the long-run relationship between the spot and the futures market. VECM and EGARCH(1,1) analysis is performed to examine the market efficiency, price discovery relationships, short-run relationships, and volatility spillover in Indian commodity markets. The study found efficiency in both the future and the spot market. Futures market leads spot markets for some commodities and absorbs the information shock faster and hence are more efficient and the same is verified by Granger causality. There is also evidence of bidirectional causality. The study found leverage effect, persistence effect, and volatility spillover effect for spot and futures markets.

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https://doi.org/https://doi.org/10.1504/ijbd.2021.116972

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@article{muneer2021,
  title        = {{Analysis of lead-lag relationship and volatility spillover: evidence from Indian agriculture commodity markets}},
  author       = {Muneer Shaik et al.},
  journal      = {International Journal of Bonds and Derivatives},
  year         = {2021},
  doi          = {https://doi.org/https://doi.org/10.1504/ijbd.2021.116972},
}

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Analysis of lead-lag relationship and volatility spillover: evidence from Indian agriculture commodity markets

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Evidence weight

0.39

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.11 × 0.4 = 0.04
M · momentum0.80 × 0.15 = 0.12
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.