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Forecasting the price of gold
Hassani, Hossein; Silva, Emmanuel Sirimal; Gupta, Rangan; … - In: Applied economics 47 (2015) 37/39, pp. 4141-4152
Persistent link: https://www.econbiz.de/10011294643
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Date-stamping US housing market explosivity
Balcilar, Mehmet; Katzke, Nico; Gupta, Rangan - 2018
In this paper the authors set out to date-stamp periods of US housing price explosivity for the period 1830–2013. They make use of several robust techniques that allow them to identify such periods by determining when prices start to exhibit explosivity with respect to its past behaviour and...
Persistent link: https://www.econbiz.de/10011812671
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Date-stamping US housing market explosivity
Balcilar, Mehmet; Katzke, Nico; Gupta, Rangan - 2017
In this paper, the authors set out to date-stamp periods of US housing price explosivity for the period 1830-2013. They make use of several robust techniques that allow them to identify such periods by determining when prices start to exhibit explosivity with respect to its past behaviour and...
Persistent link: https://www.econbiz.de/10011674010
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Exchange rate predictability with nine alternative models for BRICS countries
Salisu, Afees A.; Gupta, Rangan; Kim, Won Joong - In: Journal of macroeconomics 71 (2022), pp. 1-20
Persistent link: https://www.econbiz.de/10013328218
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Modeling and forecasting carbon dioxide emission allowance spot price volatility : multifractal vs. GARCH-type volatility models
Segnon, Mawuli; Lux, Thomas; Gupta, Rangan - 2015
This paper applies Markov-switching multifractal (MSM) processes to model and forecast carbon dioxide (CO2) emission … price volatility, and compares their forecasting performance to the standard GARCH, fractionally integrated GARCH (FIGARCH … criteria and forecast horizons, while MS-GARCH mostly comes out as the least successful model. Applying various VaR backtesting …
Persistent link: https://www.econbiz.de/10011296114
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Forecasting volatility of commodity, currency, and stock markets : evidence from Markov switching multifractal models
Liu, Ruipeng; Segnon, Mawuli; Cepni, Oguzhan; Gupta, Rangan - 2023
Persistent link: https://www.econbiz.de/10014448138
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Do precious metal prices help in forecasting South African inflation?
Balcilar, Mehmet; Katzke, Nico; Gupta, Rangan - In: The North American journal of economics and finance : a … 40 (2017), pp. 63-72
Persistent link: https://www.econbiz.de/10011878788
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Structural breaks and GARCH models of stock return volatility : the case of South Africa
Babikir, Ali; Gupta, Rangan; Mwabutwa, Chance; … - In: Economic modelling 29 (2012) 6, pp. 2435-2443
Persistent link: https://www.econbiz.de/10009673703
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Forecasting Realized Stock-Market Volatility : Do Industry Returns Have Predictive Value?
Demirer, Riza; Gupta, Rangan; Pierdzioch, Christian - 2021
bad) stock market volatility, we show that incorporating the information in lagged industry returns can help improve out …-of sample forecasts of aggregate stock market volatility. While the predictive contribution of industry level returns is not … crisis, highlighting the informational value of real economic activity on stock market volatility dynamics. Finally, we show …
Persistent link: https://www.econbiz.de/10013249490
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A note on investor happiness and the predictability of realized volatility of gold
Bonato, Matteo; Gillas, Konstantinos Gkillas; Gupta, Rangan - In: Finance research letters 39 (2021), pp. 1-6
Persistent link: https://www.econbiz.de/10012805333