Wavelet Decomposition Approach for Understanding Time-varying Relationship of Financial Sector Variables: a Study of the Indian Stock Market

• Autorzy: Indranil Ghosh , Tamal Datta Chaudhuri
• Języki publikacji: EN

Abstrakty

EN

In this paper, we study the effect of overall stock market sentiment in India on sectoral indices and on individual stock prices in terms of co movement, dependence and volatility transmission along with the magnitude and persistence of the effects. The study uses wavelet decomposition framework for breaking down different financial time series into time varying components. Quantile Regression, Wavelet Multiple Correlation and Cross Correlation analysis, and Diebold Yilmaz spillover analysis are then applied to investigate the nature of dependence, association, and spillover dynamics. For further focus, we have considered different time periods separately to identify the effect of market phases. Interesting results are obtained with respect to persistence of shocks, both across and within time periods. These have implications with respect to understanding market behavior and also perception of sectors and stocks. (original abstract)

Słowa kluczowe

EN

Equity market; Wavelet transform; Quantile regression

PL

Rynek akcji; Transformacja falkowa; Regresja kwantylowa

• Czasopismo: Multiple Criteria Decision Making / University of Economics in Katowice
• Rocznik: 2020
• Tom: 15
• Strony: 36--65

Twórcy

autor

Indranil Ghosh

• Institute of Management Technology, Hyderabad, India

autor

Tamal Datta Chaudhuri

• Centre for Knowledge, Ideas and Development Studies, KnIDS, Kolkata, India,

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Identyfikatory

DOI

10.22367/mcdm/2020.15.03