Statistical modelling of Zimbabwe’s international tourist arrivals using both symmetric and asymmetric volatility models

Chikobvu, Delson; Makoni, Tendai

doi:10.4102/jef.v12i1.426

Cited by 6 publications

(2 citation statements)

References 25 publications

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“…(Agiomirgianakis et al 2015) studied the detrimental effect of exchange rate volatility (ERV) on tourist arrivals. (Chikobvu and Makoni 2019) employed the ARMA-GARCH and ARMA-EGARCH models to investigate the symmetric and asymmetric influence of good and negative news on foreign visitor arrivals volatility. Tourist volatility was estimated using GARCH, BJR (TARCH), and EGARCH models by (Çelik 2020).…”

Section: Studies Of Symmetric and Asymmetric Effects Across On The Ne...mentioning

confidence: 99%

Effects of Multiple Financial News Shocks on Tourism Demand Volatility Modelling and Forecasting

Zhang

Choo

Aziz

et al. 2022

JRFM

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Even though both symmetric and asymmetric conceptions of news impacts are well-established in the disciplines of economics and financial markets, the effects of combining multiple news shocks on the volatility of tourism demand have not yet been delved into or gauged in any tourist destination. This work hypothesises and verifies that the news impact curve (NIC), conditional heteroscedastic volatility models, and multiple news shocks are suitable for forecasting the volatility of the Malaysian tourist industry. Among them, three primarily volatility models (GARCH, EGARCH, and GJRGARCH) are used in conjunction with five financial news shocks (FFNSs), namely the Kuala Lumpur Composite Index (KLCI), the United States Dollar Index (DXY), the stock performance of 500 large companies listed on stock exchanges (S&P500), Crude Oil (CO), and Gold Price (GP). Among the most significant findings of this study are the demonstration of monthly seasonality using conditional mean equations, asymmetry effects in EGARCH-FFNSs, and GJRGARCH-FFNSs models in conditional variance equations and 50 NICs, and the GARCH-FFNSs model’s evaluation of the persistence influence of news shocks on monthly visitor arrivals in Malaysia. The GJRGARCH-FFNSs model is the best model for Malaysian tourism demand volatility forecasting accuracy. Furthermore, KLCI and Gold Price have the most substantial impact on the number of tourists to Malaysia. In addition, it should be emphasised that the methodological framework utilised in this study can be a useful tool for creating and forecasting the performance of symmetry and asymmetry impacts on tourism demand volatility.

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Section: Studies Of Symmetric and Asymmetric Effects Across On The Ne...mentioning

confidence: 99%

Effects of Multiple Financial News Shocks on Tourism Demand Volatility Modelling and Forecasting

Zhang

Choo

Aziz

et al. 2022

JRFM

View full text Add to dashboard Cite

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“…In general, model that is capable to handle the asymmetric effect are the Asymmetric Power ARCH (APARCH) model, Threshold GARCH (TGARCH), and Exponential GARCH (EGARCH). These models have been successfully applied in many fields such as model the pathogens at marine recreational sites [6], model the international tourist arrivals [7], and model the stock market prices [8] [9]. Since the world gold price contains asymmetric effects, APARCH, TGARCH, and EGARCH models are considered in this study.…”

Section: Introductionmentioning

confidence: 99%

World Gold Price Forecast using APARCH, EGARCH and TGARCH Model

Irene

Wijaya

Muhayani

2020

InPrime:Ind.Jour.Pure.Applied.Math

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Investment is a process of investing money for profit or material result. One investment commodity is gold. Gold is a precious metal in which the value tends to fluctuate over time. This indicates that there is a non-constant variance called heteroscedasticity. The appropriate time-series model to solve this heteroscedasticity problem is ARCH/GARCH. However, this model can't be applied for the financial cases that have an asymmetric effect (the downward and increase tendency in the level of volatility when returns rise and vice versa). Therefore, in this research, we forecast the world gold prices using APARCH, EGARCH, and TGARCH methods. We use the monthly world gold price data from June 1993 until May 2018. The result shows that the best-fitted model to forecasting the world gold prices is EGARCH (1.1). This model has the smallest error than the other models with a Mean Absolute Percentage Error (MAPE) value of 4.66%.Keywords: return; volatilities; heteroscedasticity; asymmetric effect; APARCH; EGARCH; TGARCH. AbstrakInvestasi adalah proses menginvestasikan uang untuk keuntungan atau hasil material. Salah satu komoditas investasi adalah emas. Emas adalah logam mulia yang nilainya cenderung berfluktuasi dari waktu ke waktu. Ini menunjukkan bahwa ada varian non-konstan yang disebut heteroskedastisitas. Metode deret waktu yang tepat untuk menyelesaikan masalah ini adalah ARCH/GARCH. Namun model ini tidak dapat digunakan untuk kasus keuangan yang memiliki efek asimetris (kecenderungan menurun dan meningkatnya volatilitas ketika nilai return naik dan sebaliknya). Oleh karena itu, dalam penelitian ini, kami memprediksi harga emas dunia menggunakan metode APARCH, EGARCH, dan TGARCH dengan data harga emas dunia bulanan pada bulan Juni 1993 - Mei 2018. Hasilnya menunjukkan bahwa, di antara ketiga metode itu, model terbaik untuk memprediksi harga emas dunia adalah EGARCH (1.1) dengan nilai Mean Absolute Percentage Error (MAPE) sebesar 4,66%.Kata kunci: return; volatilitas; heteroskedastisitas; efek asimetris; APARCH; EGARCH; TGARCH.

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