Efficiency Check Using Cointegration and Machine Learning Approach: Crude Oil Futures Markets

Bakshi, Siddak Singh; Jaiswal, Raj Kumar; Jaiswal, Ritika

doi:10.1016/j.procs.2021.07.038

Cited by 5 publications

(1 citation statement)

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“…Further, there is an existence of information flow and a long-term relationship exists between Indian and US crude oil futures (Sharma, 2017). Moreover, the volume of crude oil granger causes the prices or absolute returns in India (Biswas, S. and Rajib, 2011) and there is a lack of cointegration relationship between crude oil futures and the stock market in India (Bakshi et al ,2021). Crude oil shocks have a significant negative impact on economic development in India (Sreenu, 2018) and a fall in crude oil price gives positive signs to FMCG sector 2 (Business Standard, 2020) whereas rise in crude oil would have a negative impact on Auto sector 3 (Business Standard, 2021).…”

Section: Introductionmentioning

confidence: 99%

Linkages Between Crude Oil Futures and Selected Sectoral Indices: Evidence From Causality Approach

Ammar¹,

Khan²

2022

EFMR

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The aim of this study is to empirically show the dynamic causal relationship between crude oil future prices and sectoral indices of India using daily data from November 30 th , 2011 to November 18 th , 2021 and its subsets. First, we apply ADF, P-P and KPSS unit root tests and then Johansen tests for estimating the cointegration. We use Granger Causality to find linkages and further VAR and VECM as per cointegration. VAR results are supported by Impulse Response whereas Wald tests ascertain the shortterm relationship for insignificant coefficients. The study found that crude oil futures and sectoral indices are integrated of order one in subset 2 whereas subset 1 and full data period doesn't show cointegration. The overall result for the full data period shows the metal sector and crude oil futures have bidirectional causality with significant impact on the metal sector. The Metal Index also has symmetric results on different time horizons. Subdata 2 shows long term relations between crude oil futures and all the sectors except FMCG and Health. Subdata 1 shows the lag of crude oil futures influences the metal sector only in the short term. The study is conducted for a period of ten years and based in India, which is an oil importing country. The availability of commodity derivatives data is also limited in India, hence the study cannot be generalized for all the countries. No study has been done considering crude oil futures and sectoral indices of India, hence providing the gap for the study.

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Section: Introductionmentioning

confidence: 99%

Linkages Between Crude Oil Futures and Selected Sectoral Indices: Evidence From Causality Approach

Ammar¹,

Khan²

2022

EFMR

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Price forecasting through neural networks for crude oil, heating oil, and natural gas

Jin,

2024

Measurement: Energy

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A deep connection among the natural resources, technical progress, efficient energy and sustainability: The mediating role of governance

Chen,

Xie

2024

Resources Policy

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Efficiency Check Using Cointegration and Machine Learning Approach: Crude Oil Futures Markets

Cited by 5 publications

References 25 publications

Linkages Between Crude Oil Futures and Selected Sectoral Indices: Evidence From Causality Approach

Linkages Between Crude Oil Futures and Selected Sectoral Indices: Evidence From Causality Approach

Price forecasting through neural networks for crude oil, heating oil, and natural gas

A deep connection among the natural resources, technical progress, efficient energy and sustainability: The mediating role of governance

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