IDEAS home Printed from https://ideas.repec.org/r/pre/wpaper/201943.html
   My bibliography  Save this item

Forecasting Realized Gold Volatility: Is there a Role of Geopolitical Risks?

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Asai, Manabu & Gupta, Rangan & McAleer, Michael, 2020. "Forecasting volatility and co-volatility of crude oil and gold futures: Effects of leverage, jumps, spillovers, and geopolitical risks," International Journal of Forecasting, Elsevier, vol. 36(3), pages 933-948.
  2. Nonejad, Nima, 2021. "Predicting equity premium using news-based economic policy uncertainty: Not all uncertainty changes are equally important," International Review of Financial Analysis, Elsevier, vol. 77(C).
  3. Bouri, Elie & Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2021. "Forecasting power of infectious diseases-related uncertainty for gold realized variance," Finance Research Letters, Elsevier, vol. 42(C).
  4. Christos Floros & Konstantinos Gkillas & Christoforos Konstantatos & Athanasios Tsagkanos, 2020. "Realized Measures to Explain Volatility Changes over Time," JRFM, MDPI, vol. 13(6), pages 1-19, June.
  5. Xiafei Li & Dongxin Li & Xuhui Zhang & Guiwu Wei & Lan Bai & Yu Wei, 2021. "Forecasting regular and extreme gold price volatility: The roles of asymmetry, extreme event, and jump," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1501-1523, December.
  6. Rangan Gupta & Christian Pierdzioch & Wing-Keung Wong, 2021. "A Note on Forecasting the Historical Realized Variance of Oil-Price Movements: The Role of Gold-to-Silver and Gold-to-Platinum Price Ratios," Energies, MDPI, vol. 14(20), pages 1-12, October.
  7. Salisu, Afees A. & Gupta, Rangan & Karmakar, Sayar & Das, Sonali, 2022. "Forecasting output growth of advanced economies over eight centuries: The role of gold market volatility as a proxy of global uncertainty," Resources Policy, Elsevier, vol. 75(C).
  8. Yang, Jianlei & Yang, Chunpeng, 2021. "The impact of mixed-frequency geopolitical risk on stock market returns," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 226-240.
  9. Mehmet Balcilar & Elie Bouri & Rangan Gupta & Christian Pierdzioch, 2021. "El Niño, La Niña, and the Forecastability of the Realized Variance of Heating Oil Price Movements," Sustainability, MDPI, vol. 13(14), pages 1-23, July.
  10. Li, Yingli & Huang, Jianbai & Chen, Jinyu, 2021. "Dynamic spillovers of geopolitical risks and gold prices: New evidence from 18 emerging economies," Resources Policy, Elsevier, vol. 70(C).
  11. Salisu, Afees A. & Cuñado, Juncal & Gupta, Rangan, 2022. "Geopolitical risks and historical exchange rate volatility of the BRICS," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 179-190.
  12. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2022. "A moving average heterogeneous autoregressive model for forecasting the realized volatility of the US stock market: Evidence from over a century of data," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 384-400, January.
  13. Lu, Xinjie & Ma, Feng & Wang, Jianqiong & Dong, Dayong, 2022. "Singlehanded or joint race? Stock market volatility prediction," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 734-754.
  14. Cheng, Sheng & Zhang, Zongyou & Cao, Yan, 2022. "Can precious metals hedge geopolitical risk? Fresh sight using wavelet coherence analysis," Resources Policy, Elsevier, vol. 79(C).
  15. Gkillas, Konstantinos & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2022. "Spillovers in Higher-Order Moments of Crude Oil, Gold, and Bitcoin," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 398-406.
  16. Faheem Aslam & Paulo Ferreira & Haider Ali & Ana Ercília José, 2022. "Application of Multifractal Analysis in Estimating the Reaction of Energy Markets to Geopolitical Acts and Threats," Sustainability, MDPI, vol. 14(10), pages 1-23, May.
  17. Shahbaz, Muhammad & Khan, Asad ul Islam & Mubarak, Muhammad Shujaat, 2023. "Roling-window bounds testing approach to analyze the relationship between oil prices and metal prices," The Quarterly Review of Economics and Finance, Elsevier, vol. 87(C), pages 388-395.
  18. Zhang, Hongwei & Demirer, Riza & Huang, Jianbai & Huang, Wanjun & Tahir Suleman, Muhammad, 2021. "Economic policy uncertainty and gold return dynamics: Evidence from high-frequency data," Resources Policy, Elsevier, vol. 72(C).
  19. Li, Xiafei & Liao, Yin & Lu, Xinjie & Ma, Feng, 2022. "An oil futures volatility forecast perspective on the selection of high-frequency jump tests," Energy Economics, Elsevier, vol. 116(C).
  20. Aysan, Ahmet Faruk & Polat, Ali Yavuz & Tekin, Hasan & Tunalı, Ahmet Semih, 2022. "The Ascent of Geopolitics: Scientometric Analysis and Ramifications of Geopolitical Risk," MPRA Paper 112741, University Library of Munich, Germany.
  21. Będowska-Sójka, Barbara & Demir, Ender & Zaremba, Adam, 2022. "Hedging Geopolitical Risks with Different Asset Classes: A Focus on the Russian Invasion of Ukraine," Finance Research Letters, Elsevier, vol. 50(C).
  22. Rangan Gupta & Sayar Karmakar & Christian Pierdzioch, 2022. "Safe Havens, Machine Learning, and the Sources of Geopolitical Risk: A Forecasting Analysis Using Over a Century of Data," Working Papers 202201, University of Pretoria, Department of Economics.
  23. Zaremba, Adam & Cakici, Nusret & Demir, Ender & Long, Huaigang, 2022. "When bad news is good news: Geopolitical risk and the cross-section of emerging market stock returns," Journal of Financial Stability, Elsevier, vol. 58(C).
  24. Bonato, Matteo & Çepni, Oğuzhan & Gupta, Rangan & Pierdzioch, Christian, 2021. "Do oil-price shocks predict the realized variance of U.S. REITs?," Energy Economics, Elsevier, vol. 104(C).
  25. Zhou, Mei-Jing & Huang, Jian-Bai & Chen, Jin-Yu, 2020. "The effects of geopolitical risks on the stock dynamics of China's rare metals: A TVP-VAR analysis," Resources Policy, Elsevier, vol. 68(C).
  26. Cheng, Sheng & Han, Lingyu & Cao, Yan & Jiang, Qisheng & Liang, Ruibin, 2022. "Gold-oil dynamic relationship and the asymmetric role of geopolitical risks: Evidence from Bayesian pdBEKK-GARCH with regime switching," Resources Policy, Elsevier, vol. 78(C).
  27. Sisa Shiba & Goodness C. Aye & Rangan Gupta & Samrat Goswami, 2022. "Forecastability of Agricultural Commodity Futures Realised Volatility with Daily Infectious Disease-Related Uncertainty," JRFM, MDPI, vol. 15(11), pages 1-15, November.
  28. Gong, Xu & Xu, Jun, 2022. "Geopolitical risk and dynamic connectedness between commodity markets," Energy Economics, Elsevier, vol. 110(C).
  29. Ahdi Noomen Ajmi & Roula Inglesi-Lotz, 2021. "Revisiting the Kuznets Curve Hypothesis for Tunisia: Carbon Dioxide vs. Ecological Footprint," Working Papers 202171, University of Pretoria, Department of Economics.
  30. Kamal, Javed Bin & Wohar, Mark & Kamal, Khaled Bin, 2022. "Do gold, oil, equities, and currencies hedge economic policy uncertainty and geopolitical risks during covid crisis?," Resources Policy, Elsevier, vol. 78(C).
  31. Bonato, Matteo & Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2021. "A note on investor happiness and the predictability of realized volatility of gold," Finance Research Letters, Elsevier, vol. 39(C).
  32. Pattnaik, Debidutta & Hassan, M. Kabir & DSouza, Arun & Ashraf, Ali, 2023. "Investment in gold: A bibliometric review and agenda for future research," Research in International Business and Finance, Elsevier, vol. 64(C).
  33. Li, Songsong & Zhang, Weiqian & Zhang, Wei, 2023. "Dynamic time-frequency connectedness and risk spillover between geopolitical risks and natural resources," Resources Policy, Elsevier, vol. 82(C).
  34. Wang, Lu & Wu, Jiangbin & Cao, Yang & Hong, Yanran, 2022. "Forecasting renewable energy stock volatility using short and long-term Markov switching GARCH-MIDAS models: Either, neither or both?," Energy Economics, Elsevier, vol. 111(C).
  35. Luo, Jiawen & Demirer, Riza & Gupta, Rangan & Ji, Qiang, 2022. "Forecasting oil and gold volatilities with sentiment indicators under structural breaks," Energy Economics, Elsevier, vol. 105(C).
  36. Riza Demirer & Rangan Gupta & Christian Pierdzioch & Syed Jawad Hussain Shahzad, 2021. "A note on oil price shocks and the forecastability of gold realized volatility," Applied Economics Letters, Taylor & Francis Journals, vol. 28(21), pages 1889-1897, December.
  37. Gupta, Rangan & Pierdzioch, Christian, 2022. "Climate risks and forecastability of the realized volatility of gold and other metal prices," Resources Policy, Elsevier, vol. 77(C).
  38. Chen, Wang & Lu, Xinjie & Wang, Jiqian, 2022. "Modeling and managing stock market volatility using MRS-MIDAS model," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 625-635.
  39. Li, Yingli & Huang, Jianbai & Gao, Wang & Zhang, Hongwei, 2021. "Analyzing the time-frequency connectedness among oil, gold prices and BRICS geopolitical risks," Resources Policy, Elsevier, vol. 73(C).
  40. Nonejad, Nima, 2022. "Predicting equity premium out-of-sample by conditioning on newspaper-based uncertainty measures: A comparative study," International Review of Financial Analysis, Elsevier, vol. 83(C).
  41. Theophilus Teye Osah & Andre Varella Mollick, 2023. "Stock and oil price returns in international markets: Identifying short and long-run effects," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 47(1), pages 116-141, March.
  42. Choi, Sun-Yong, 2022. "Evidence from a multiple and partial wavelet analysis on the impact of geopolitical concerns on stock markets in North-East Asian countries," Finance Research Letters, Elsevier, vol. 46(PB).
  43. Salisu, Afees A. & Gupta, Rangan & Bouri, Elie & Ji, Qiang, 2020. "The role of global economic conditions in forecasting gold market volatility: Evidence from a GARCH-MIDAS approach," Research in International Business and Finance, Elsevier, vol. 54(C).
  44. Văn, Lê & Bảo, Nguyễn Khắc Quốc, 2022. "The relationship between global stock and precious metals under Covid-19 and happiness perspectives," Resources Policy, Elsevier, vol. 77(C).
  45. Phan, Dinh Hoang Bach & Tran, Vuong Thao & Iyke, Bernard Njindan, 2022. "Geopolitical risk and bank stability," Finance Research Letters, Elsevier, vol. 46(PB).
  46. Shang, Yue & Wei, Yu & Chen, Yongfei, 2022. "Cryptocurrency policy uncertainty and gold return forecasting: A dynamic Occam's window approach," Finance Research Letters, Elsevier, vol. 50(C).
  47. Riza Demirer & Rangan Gupta & Christian Pierdzioch, 2020. "Forecasting Realized Stock-Market Volatility: Do Industry Returns have Predictive Value?," Working Papers 2020107, University of Pretoria, Department of Economics.
  48. Xu, Yahua & Bouri, Elie & Saeed, Tareq & Wen, Zhuzhu, 2020. "Intraday return predictability: Evidence from commodity ETFs and their related volatility indices," Resources Policy, Elsevier, vol. 69(C).
  49. Hu, Min & Zhang, Dayong & Ji, Qiang & Wei, Lijian, 2020. "Macro factors and the realized volatility of commodities: A dynamic network analysis," Resources Policy, Elsevier, vol. 68(C).
  50. Salisu, Afees A. & Adediran, Idris & Omoke, Philip C. & Tchankam, Jean Paul, 2023. "Gold and tail risks," Resources Policy, Elsevier, vol. 80(C).
  51. Zhou, Mei-Jing & Huang, Jian-Bai & Chen, Jin-Yu, 2022. "Time and frequency spillovers between political risk and the stock returns of China's rare earths," Resources Policy, Elsevier, vol. 75(C).
  52. Evrim Mandaci, Pınar & Azimli, Asil & Mandaci, Nazif, 2023. "The impact of geopolitical risks on connectedness among natural resource commodities: A quantile vector autoregressive approach," Resources Policy, Elsevier, vol. 85(PA).
  53. Fiorillo, Paolo & Meles, Antonio & Pellegrino, Luigi Raffaele & Verdoliva, Vincenzo, 2023. "Geopolitical risk and stock liquidity," Finance Research Letters, Elsevier, vol. 54(C).
  54. Li, Xiafei & Guo, Qiang & Liang, Chao & Umar, Muhammad, 2023. "Forecasting gold volatility with geopolitical risk indices," Research in International Business and Finance, Elsevier, vol. 64(C).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.