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The importance of oil assets for portfolio optimization: The analysis of firm level stocks

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  • Sarwar, Suleman
  • Shahbaz, Muhammad
  • Anwar, Awais
  • Tiwari, Aviral Kumar

Abstract

This study aimed to analyze the shock transmission and volatility spillover between firm stocks and oil assets by using the BEKK-GARCH model in which a variance and covariance series are used for portfolio optimization. For this purpose, we use the daily data from 107 Pakistani-listed firms covering the period from January 2000 to August 2017. Our overall results confirm the interdependence between firm stocks and oil assets. Additionally, there is strong evidence of volatility spillover from stocks to oil and from oil to stocks. The results from the portfolio optimization show the importance of oil assets in the formation of an optimal portfolio. Moreover, we find that in the case of manufacturing firm stocks, the investors should spend >50% of their total investment to purchase oil assets, while the remaining investment should be used to acquire firm stocks. On the other hand, in the case of investments in oil and gas firm stocks, it is evident that investors can form an optimal portfolio by spending a larger proportion of their investments on firm stocks rather than on oil assets. This research implication can be valuable for portfolio managers and individual investors who are willing to invest in Pakistani stocks.

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  • Sarwar, Suleman & Shahbaz, Muhammad & Anwar, Awais & Tiwari, Aviral Kumar, 2019. "The importance of oil assets for portfolio optimization: The analysis of firm level stocks," Energy Economics, Elsevier, vol. 78(C), pages 217-234.
    • Handle: RePEc:eee:eneeco:v:78:y:2019:i:c:p:217-234
    DOI: 10.1016/j.eneco.2018.11.021
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    More about this item

    Keywords

    Volatility spillover; Portfolio optimization; BEKK-GARCH; Firm level stocks;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • 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
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G19 - Financial Economics - - General Financial Markets - - - Other

    Statistics

    Access and download statistics

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