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Bernardina Algieri, Arturo Leccadito and Pietro Toscano
This study investigates the daily co-movements in commodity prices over the period 2006?2020 using a novel approach based on a time-varying Gerber correlation. The statistic is computed considering a set of probabilities estimated via non-traditional mod...
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Nikoletta Poutachidou and Stephanos Papadamou
The purpose of this study is to investigate the fluctuations that occur in stock returns of US stock indices when there is an increase in the volume of Google internet searches for the phrase ?quantitative easing? in the US. The exponential generalized a...
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Kejin Wu and Sayar Karmakar
Forecasting volatility from econometric datasets is a crucial task in finance. To acquire meaningful volatility predictions, various methods were built upon GARCH-type models, but these classical techniques suffer from instability of short and volatile d...
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Katleho Makatjane and Ntebogang Moroke
During the past decades, seasonal autoregressive integrated moving average (SARIMA) had become one of a prevalent linear models in time series and forecasting. Empirical research advocated that forecasting with non-linear models can be an encouraging alt...
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Faizul Mubarok,Mohammad Masykur Fadhli
Pág. in press
The presence of the stock market has helped to increase economic growth in a country. However, high levels of volatility plus economic uncertainty make investors have to rethink investing in the capital market. This study aims to examine the share of eac...
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