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Analysing Time-frequency Relationship between Oil price and Sectoral Indices in India using Wavelet Techniques

Author

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  • Koushik Mandal

    (Indian Institute of Foreign Trade, India)

  • Radhika Prosad Datta

    (Indian Institute of Foreign Trade, India)

Abstract

Oil is considered an essential factor of any economy. This paper examines the time-varying correlation between oil price return, BSE SENSEX, and 14 sectoral indexes in India using multiscale wavelet decomposition and wavelet coherence analysis. The maximal wavelet discrete wavelet transform analysis shows a feedback relationship between 13 sectors at higher time horizons (dC4, dC5, and dC6). Based on the wavelet coherence plot, the oil price and sectoral index return show a high co-movement at 32 to 128 weeks. The wavelet coherence plot shows that the oil price and sectoral index return show a high co-movement during the period of Mar-May 2020 (especially during the period of financial crisis widely spread due to the COVID19 pandemic and nationwide lockdown notification announced by the Government of India). We discuss the implications of these studies in detail.

Suggested Citation

  • Koushik Mandal & Radhika Prosad Datta, 2022. "Analysing Time-frequency Relationship between Oil price and Sectoral Indices in India using Wavelet Techniques," International Journal of Energy Economics and Policy, Econjournals, vol. 12(5), pages 192-201, September.
    • Handle: RePEc:eco:journ2:2022-05-23
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    More about this item

    Keywords

    Wavelet Coherence; Multiscale decomposition; Lead Lag Relationship; Sectoral indices;
    All these keywords.

    JEL classification:

    • L93 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Air Transportation
    • P18 - Political Economy and Comparative Economic Systems - - Capitalist Economies - - - Energy; Environment
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • Q57 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Ecological Economics
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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