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Accurate forecasting of tourism demand and income holds paramount importance for both the tourism industry and the national economy. This study aims to address several objectives: (1) specify the best forecasting model in the prediction of tourist arrival volumes and tourism income for Turkey; (2) assess the degree of impact exerted by various determinants on the tourism forecasts; (3) generate forecasts for tourist arrival volumes and tourism income using the most suitable models; and (4) examine potential scenarios illustrating the ramifications of the Russia-Ukraine war on tourist arrival volumes and tourism income. The forecasting models employed in this study encompass a comprehensive set of statistical methods, including ETS, ARIMA, TRAMO-SEATS, X13, X11, STL, Grey, and their combinations with ANN. In the ANN models, exogenous variables such as the global financial crisis, the Turkey-Russia warplane crash crisis, the COVID-19 pandemic, and USD/TRY exchange rates are incorporated. The results unveil the identification of five superior models: ETS, Grey, hybrid ETS-ANN, hybrid Grey-ANN, and hybrid ARIMA-ANN models, which exhibit the lowest MAPE and sMAPE values. Forecasts for the forthcoming quarters are examined under two scenarios: assuming the continuity or cessation of the Russia-Ukraine war. Comparative analysis of the relative effects of exogenous variables indicates that COVID-19 has the most substantial impact on tourist arrival volumes, and tourism income is primarily influenced by the USD/TRY exchange rate. [ABSTRACT FROM AUTHOR]

Our investigation strives to unearth the best portfolio hedging strategy for the G7 stock indices through Bitcoin and gold using daily data relevant to the period 2 January 2016 to 5 January 2023. This study uses the DVECH-GARCH model to model dynamic correlation and then compute optimal hedge ratios and hedging effectiveness. The empirical findings show that Bitcoin and gold were rather effective hedge assets before COVID-19 and diversifiers during the pandemic and Russia–Ukraine war. From hedging effectiveness perspectives, gold and Bitcoin are safe-haven assets, and the investment risk of G7 stock indices could be hedged by taking a short position during thepandemic period and war except for the pair Nikkei/Gold. Additionally, gold beats Bitcoin in terms of hedging efficiency. We thus demonstrate the central role of Bitcoin and gold as financial market participants, particularly during market turmoil and downward movements. Our findings can be of interest to investors, regulators, and governments to take into consideration the role of Bitcoin in financial markets. [ABSTRACT FROM AUTHOR]

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Objective: The aim of this study was to predict the number of patients infected with coronavirus disease (COVID-19) by the end of year 2020 by using the number of infections in Turkey between the dates 11.3.2020-9.9.2020 and exponential smoothing model. Material and Methods: Different versions of the exponential smoothing model were applied and compared by using the data published and upgraded on the web by the Turkish Republic Ministry of Health, and near future predictions were performed after the determination of two models (containing additive method model: Model 1 and containing multiplicative method model: Model 2) producing the best estimates. Results: The first proposed model (Model 1) estimated that there would be 374,842, 427,672 and 482,263 infected patients in Turkey by the date 31 October 2020, 30 November 2020, and 31 December 2020, respectively. For the same dates, it was calculated that there would be 391,992, 472,782, and 573,811 infected patients, respectively for the second model (Model 2). The model 2 was evaluated to produce more realistic results considering that the number of patients infected with COVID-19 will increase even more with the effect of winter. Conclusion: It was thought that the models proposed in this study could also be used to predict the number of infected patients in international studies in the upcoming period. At the same time, it was evaluated that these models not only for infections but could also be used to estimate the number of deaths and recoveries due to coronavirus disease 2019. [ABSTRACT FROM AUTHOR]