The Capitalized Generalized Autoregressive Conditional Heteroskedasticity

被引：1

作者：

Kola, Katlego ^{[1
]}

Sebehela, Tumellano ^{[1
]}

机构：

[1] Univ Witwatersrand, Sch Construct Econ & Management, ZA-2050 Johannesburg, South Africa

来源：

REVIEW OF PACIFIC BASIN FINANCIAL MARKETS AND POLICIES | 2022年 / 25卷 / 03期

关键词：

GARCH; MARKET VOLATILITY; RISK; COMMODITY; RETURNS; UNCERTAINTY; INVESTMENT; DEBT; GOLD;

D O I：

10.1142/S0219091522500175

中图分类号：

F8 [财政、金融];

学科分类号：

0202 ;

摘要：

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.

引用

页数：29

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