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Forecasting daily exchange rate volatility using intraday returns

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Cited by:

  1. Jui-Cheng Hung & Tien-Wei Lou & Yi-Hsien Wang & Jun-De Lee, 2013. "Evaluating and improving GARCH-based volatility forecasts with range-based estimators," Applied Economics, Taylor & Francis Journals, vol. 45(28), pages 4041-4049, October.
  2. Long H. Vo, 2017. "Estimating Financial Volatility with High-Frequency Returns," Journal of Finance and Economics Research, Geist Science, Iqra University, Faculty of Business Administration, vol. 2(2), pages 84-114, October.
  3. Ané, Thierry & Ureche-Rangau, Loredana & Gambet, Jean-Benoît & Bouverot, Julien, 2008. "Robust outlier detection for Asia-Pacific stock index returns," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(4), pages 326-343, October.
  4. Wong, Woon K. & Tan, Dijun & Tian, Yixiang, 2009. "Informed trading and liquidity in the Shanghai Stock Exchange," International Review of Financial Analysis, Elsevier, vol. 18(1-2), pages 66-73, March.
  5. Isao Ishida & Toshiaki Watanabe, 2009. "Modeling and Forecasting the Volatility of the Nikkei 225 Realized Volatility Using the ARFIMA-GARCH Model," CIRJE F-Series CIRJE-F-608, CIRJE, Faculty of Economics, University of Tokyo.
  6. Abderrazak Ben Maatoug & Rim Lamouchi & Russell Davidson & Ibrahim Fatnassi, 2018. "Modelling Foreign Exchange Realized Volatility Using High Frequency Data: Long Memory versus Structural Breaks," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 10(1), pages 1-25, March.
  7. Barucci, Emilio & Reno, Roberto, 2002. "On measuring volatility and the GARCH forecasting performance," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 12(3), pages 183-200, July.
  8. Wen-Cheng Lu & Fang-Jun Lin, 2010. "An Empirical Study Of Volatility And Trading Volume Dynamics Using High-Frequency Data," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 4(3), pages 93-101.
  9. Marcelo C. Carvalho & Marco Aurélio S. Freire & Marcelo Cunha Medeiros & Leonardo R. Souza, 2006. "Modeling and Forecasting the Volatility of Brazilian Asset Returns: a Realized Variance Approach," Brazilian Review of Finance, Brazilian Society of Finance, vol. 4(1), pages 55-77.
  10. Lien, Donald & Yang, Li, 2005. "Availability and settlement of individual stock futures and options expiration-day effects: evidence from high-frequency data," The Quarterly Review of Economics and Finance, Elsevier, vol. 45(4-5), pages 730-747, September.
  11. Giot, Pierre & Laurent, Sebastien, 2004. "Modelling daily Value-at-Risk using realized volatility and ARCH type models," Journal of Empirical Finance, Elsevier, vol. 11(3), pages 379-398, June.
  12. Ubukata, Masato, 2018. "Dynamic hedging performance and downside risk: Evidence from Nikkei index futures," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 270-281.
  13. Mohammad Al-Shboul & Aktham Maghyereh, 2023. "Did real economic uncertainty drive risk connectedness in the oil–stock nexus during the COVID-19 outbreak? A partial wavelet coherence analysis," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 12(1), pages 1-23, December.
  14. Michael McAleer & Marcelo Medeiros, 2008. "Realized Volatility: A Review," Econometric Reviews, Taylor & Francis Journals, vol. 27(1-3), pages 10-45.
  15. Emilio Barucci & Giancarlo Giuffra Moncayo & Daniele Marazzina, 2022. "Cryptocurrencies and stablecoins: a high-frequency analysis," Digital Finance, Springer, vol. 4(2), pages 217-239, September.
  16. Mendes, Beatriz Vaz de Melo & Accioly, Victor Bello, 2012. "On the dependence structure of realized volatilities," International Review of Financial Analysis, Elsevier, vol. 22(C), pages 1-9.
  17. Bart Frijns & Dimitris Margaritis, 2008. "Forecasting daily volatility with intraday data," The European Journal of Finance, Taylor & Francis Journals, vol. 14(6), pages 523-540.
  18. Koopman, Siem Jan & Jungbacker, Borus & Hol, Eugenie, 2005. "Forecasting daily variability of the S&P 100 stock index using historical, realised and implied volatility measurements," Journal of Empirical Finance, Elsevier, vol. 12(3), pages 445-475, June.
  19. Ying Jiang & Shamim Ahmed & Xiaoquan Liu, 2017. "Volatility forecasting in the Chinese commodity futures market with intraday data," Review of Quantitative Finance and Accounting, Springer, vol. 48(4), pages 1123-1173, May.
  20. Ané, Thierry & Métais, Carole, 2009. "The distribution of realized variances: Marginal behaviors, asymmetric dependence and contagion effects," International Review of Financial Analysis, Elsevier, vol. 18(3), pages 134-150, June.
  21. Jui-Cheng Hung & Ren-Xi Ni & Matthew C. Chang, 2009. "The Information Contents of VIX Index and Range-based Volatility on Volatility Forecasting Performance of S&P 500," Economics Bulletin, AccessEcon, vol. 29(4), pages 2592-2604.
  22. Chortareas, Georgios & Jiang, Ying & Nankervis, John. C., 2011. "Forecasting exchange rate volatility using high-frequency data: Is the euro different?," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1089-1107, October.
  23. Bollerslev, Tim & Zhou, Hao, 2002. "Estimating stochastic volatility diffusion using conditional moments of integrated volatility," Journal of Econometrics, Elsevier, vol. 109(1), pages 33-65, July.
  24. Chu, Carlin C.F. & Lam, K.P., 2011. "Modeling intraday volatility: A new consideration," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(3), pages 388-418, July.
  25. Min Liu & Chien‐Chiang Lee & Wei‐Chong Choo, 2021. "An empirical study on the role of trading volume and data frequency in volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 792-816, August.
  26. Hashimoto, Yuko, 2005. "The impact of the Japanese banking crisis on the intraday FX market in late 1997," Journal of Asian Economics, Elsevier, vol. 16(2), pages 205-222, April.
  27. Eugenie Hol & Siem Jan Koopman, 2002. "Stock Index Volatility Forecasting with High Frequency Data," Tinbergen Institute Discussion Papers 02-068/4, Tinbergen Institute.
  28. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, November.
  29. Jian Zhou, 2017. "Forecasting REIT volatility with high-frequency data: a comparison of alternative methods," Applied Economics, Taylor & Francis Journals, vol. 49(26), pages 2590-2605, June.
  30. Lyócsa, Štefan & Molnár, Peter & Výrost, Tomáš, 2021. "Stock market volatility forecasting: Do we need high-frequency data?," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1092-1110.
  31. Matei, Marius, 2011. "Non-Linear Volatility Modeling of Economic and Financial Time Series Using High Frequency Data," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 116-141, June.
  32. Bertrand B. Maillet & Jean-Philippe R. M�decin, 2010. "Extreme Volatilities, Financial Crises and L-moment Estimations of Tail-indexes," Working Papers 2010_10, Department of Economics, University of Venice "Ca' Foscari".
  33. Yuko Hashimoto, 2004. "The Impact of the Japanese Banking Crisis on the Intraday FX Market," Econometric Society 2004 Far Eastern Meetings 679, Econometric Society.
  34. Anagnostidis, Panagiotis & Emmanouilides, Christos J., 2015. "Nonlinearity in high-frequency stock returns: Evidence from the Athens Stock Exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 473-487.
  35. Alan E. H. Speight & David G. McMillan, 2004. "Daily volatility forecasts: reassessing the performance of GARCH models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(6), pages 449-460.
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