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The Capitalized Generalized Autoregressive Conditional Heteroskedasticity

Author

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  • Katlego Kola

    (School of Construction Economics & Management, WITS University, Johannesburg 2050, South Africa)

  • Tumellano Sebehela

    (School of Construction Economics & Management, WITS University, Johannesburg 2050, South Africa)

Abstract

The aim of this paper is to shed new light on hedging discrete volatilities, in particular when using the generalized autoregressive conditional heteroskedasticity (thereafter GARCH) model. Despite its elegance, GARCH does not account for (i) correlation coefficients of debt and equity, (ii) equity parameter, (iii) risk premium, (iv) interest rates, and (v) shocks-stock markets. The unaccounted listed parameters are included into the GARCH(1,1) and the paper inverts a new model, expanded GARCH, called the capitalized GARCH. The results show that the capitalized GARCH convergences in a similar manner to the GARCH(1,1) in modeling volatility of bonds, commodities, equities, and real estate indices.

Suggested Citation

  • Katlego Kola & Tumellano Sebehela, 2022. "The Capitalized Generalized Autoregressive Conditional Heteroskedasticity," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 25(03), pages 1-29, September.
    • Handle: RePEc:wsi:rpbfmp:v:25:y:2022:i:03:n:s0219091522500175
    DOI: 10.1142/S0219091522500175
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    Keywords

    GARCH;

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