Title: TARCH model-based dynamic hedging strategy of ADR portfolios

Authors: Haochen Guo; Zdeněk Zmeškal

Addresses: Faculty of Economics, VŠB-Technical University of Ostrava, Czech Republic; School of Economics and Management, Southeast University, China ' Faculty of Economics, VŠB-Technical University of Ostrava, Czech Republic

Abstract: Traditional hedging is only applied to minimise uncertainty about the financial asset's value at some particular future time when the hedge is closed, and it is only concerned with one scenario. However, dynamic hedging is used with simulation techniques to value the financial assets and to measure risk. The framework relies on solving the traditional hedging strategy, but it is used to simulate various multi-scenarios for the portfolio value. The purpose of this paper is to apply Monte Carlo to simulate the threshold autoregressive conditionally heteroschedastic (TARCH) process to determine the dynamic hedging strategy of the proposed American depositary receipt (ADR) stock portfolios. The empirical study examines Germany and the UK ADR portfolios to reduce China's ADR portfolio risk in the US equity market. It contributes to solving investing in foreign stocks to hedge risky stocks in the US equity market. The result presents that using Germany and the UK's ADR portfolios could lead against the risk of investment of China's ADRs in the US equity market. It can improve the investor's portfolio allocation and protects the profit.

Keywords: TARCH model; dynamic hedging strategy; value at risk; Monte Carlo simulation; volatility model; American depositary receipt; ADR; the US equity market.

DOI: 10.1504/IJEA.2022.124141

International Journal of Economics and Accounting, 2022 Vol.11 No.2, pp.199 - 211

Received: 16 Mar 2021
Accepted: 11 Aug 2021
Published online: 14 Jul 2022 *

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