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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
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Safe havens, machine learning, and the sources of geopolitical risk : a forecasting analysis using over a century of data
Gupta, Rangan; Karmakar, Sayar; Pierdzioch, Christian - 2022
Persistent link: https://www.econbiz.de/10012794059
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Forecasting realized gold volatility : is there a role of geopolitical risks?
Gillas, Konstantinos Gkillas; Gupta, Rangan; … - In: Finance research letters 35 (2020), pp. 1-6
Persistent link: https://www.econbiz.de/10012438328
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Safe havens, machine learning, and the sources of geopolitical risk : a forecasting analysis using over a century of data
Gupta, Rangan; Karmakar, Sayar; Pierdzioch, Christian - In: Computational economics 64 (2024) 1, pp. 487-513
Persistent link: https://www.econbiz.de/10015078039
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On the intraday return curves of Bitcoin : predictability and trading opportunities
Bouri, Elie; Lau, Chi Keung; Saeed, Tareq; Wang, Shixuan; … - In: International review of financial analysis 76 (2021), pp. 1-12
Persistent link: https://www.econbiz.de/10012804738
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Cryptocurrency uncertainty and volatility forecasting of precious metal futures markets
Wei, Yu; Wang, Yizhi; Lucey, Brian M.; Vigne, Samuel A. - In: Journal of commodity markets 29 (2023), pp. 1-16
Persistent link: https://www.econbiz.de/10014277412
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Can Security Analyst Forecasts Predict Gold Returns?
Mihaylov, George - 2017
This paper examines whether security analyst earnings forecasts for firms primarily operating in the gold market can be … utilised to predict returns on the price of gold.We first demonstrate that analysts are at least in part basing their earnings … forecasts for gold firms on the return expectations of the gold commodity market.We show this by providing evidence that analyst …
Persistent link: https://www.econbiz.de/10012967299
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Boosting Cryptocurrency Return Prediction
Filippou, Ilias; Rapach, David; Thimsen, Christoffer - 2021
We use boosted decision trees to generate daily out-of-sample forecasts of excess returns for Bitcoin and Ethereum, the two best-known and largest cryptocurrencies. The decision trees incorporate information from 39 predictors, including variables relating to cryptocurrency fundamentals,...
Persistent link: https://www.econbiz.de/10013213970
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Trend-based Forecast of Cryptocurrency Returns
Tan, Xilong; Tao, Yubo - 2022
We systematically re-examine the efficacy of trend-based technical indicators in predicting cryptocurrency market returns at daily, weekly, and monthly horizons. It shows that the price-based signals are more effective than the volume-based signals in the short horizon (daily and weekly), while...
Persistent link: https://www.econbiz.de/10014239497
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Forecasting Cryptocurrency Returns
Chakraborty, Nilanjana - 2023
This paper studies two cryptocurrencies and finds that their prices can be estimated or forecasted better than their returns because returns being ratios of prices, do not always exhibit the economic relationship that may exist between two price series. However, average returns use multiple...
Persistent link: https://www.econbiz.de/10014350724