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Intraday and interday volatility in the Japanese stock market. (2000). Bollerslev, Tim ; Andersen, Torben ; Cai, Jun.
In: Journal of International Financial Markets, Institutions and Money.
RePEc:eee:intfin:v:10:y:2000:i:2:p:107-130.

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  2. Intraday and overnight tail risks and return predictability in the crude oil market: Evidence from oil-related regular news and extreme shocks. (2023). Bouri, Elie ; Wang, Cheng ; Zhang, Dingsheng ; Xu, Yahua.
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  3. Intraday Price Discovery between Spot and Futures Markets of NIFTY 50: An Empirical Study during the Times of COVID-19. (2022). Alhumoudi, Hamad A ; Bansal, Rohit ; Atif, Mohd ; Pervez, Asif ; Hussain, Md Mobashshir ; Khan, Mohammed Arshad ; Chen, Miaochao.
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  5. Oil price volatility forecasts: What do investors need to know?. (2022). Filis, George ; Degiannakis, Stavros.
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  8. Intraday Patterns in Returns on the Romanian and Bulgarian Stock Markets. (2020). Dragot, Victor ; Ilic, Elena Valentina ; Anghel, Dan Gabriel.
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  9. What Can Machine Learning Tell Us About Intraday Price Patterns in a Frontier Stock Market?. (2020). Anghel, Dan Gabriel.
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  12. Time-of-day periodicities of trading volume and volatility in Bitcoin exchange: Does the stock market matter?. (2020). Hsu, Yuan-Teng ; Liu, Hung-Chun ; Wang, Jying-Nan.
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  17. Black swan events in Chinas stock markets: Intraday price behaviors on days of volatility. (2019). Lin, Wen-Yuan ; Tsai, I-Chun ; I-Chun Tsai, .
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  18. Heterogeneous component multiplicative error models for forecasting trading volumes. (2019). Storti, Giuseppe ; Naimoli, Antonio.
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  19. Monday mornings: Individual investor trading on days of the week and times within a day. (2019). Willows, Gizelle D ; Richards, Daniel W.
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  20. Jockeying for Position in CEO Letters: Impression Management and Sentiment Analytics. (2019). Boudt, Kris ; Thewissen, James.
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  21. Intraday realised volatility forecasting and announcements. (2018). Vortelinos, Dimitrios I.
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  22. The Twitter myth revisited: Intraday investor sentiment, Twitter activity and individual-level stock return volatility. (2018). Behrendt, Simon ; Schmidt, Alexander .
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  23. Volatility connectedness in the Chinese banking system: Do state-owned commercial banks contribute more?. (2018). Wang, Gang-Jin ; Jiang, Zhi-Qiang ; Zhao, Longfeng ; Xie, Chi.
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  24. The intraday volatility spillover index approach and an application in the Brexit vote. (2018). Nishimura, Yusaku ; Sun, Bianxia.
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  25. Persistence of announcement effects on the intraday volatility of stock returns: Evidence from individual data. (2017). Uctum, Remzi ; Prat, Georges ; Lecarpentiermoyal, Sylvie ; Renoumaissant, Patricia.
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  26. Intraday Periodicity and Volatility Forecasting: Evidence from Indian Crude Oil Futures Market. (2017). .
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  27. Stylized facts of intraday precious metals. (2017). lucey, brian ; Batten, Jonathan ; Urquhart, Andrew ; Peat, Maurice ; McGroarty, Frank.
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  28. Estimating Financial Volatility with High-Frequency Returns. (2017). Vo, Long.
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  29. Financial Market Integration: Evidence from Cross-Listed French Firms. (2017). Mehanaoui, Mohamed .
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  30. Persistence of announcement effects on the intraday volatility of stock returns: Evidence from individual data. (2017). Uctum, Remzi ; Lecarpentier-Moyal, Sylvie ; Prat, Georges ; Renou-Maissant, Patricia.
    In: Review of Financial Economics.
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  31. Volatility and public information flows: Evidence from disclosure and media coverage in the Japanese stock market. (2017). Aman, Hiroyuki ; Moriyasu, Hiroshi.
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  32. Decoupling the short- and long-term behavior of stochastic volatility. (2017). Bennedsen, Mikkel ; Pakkanen, Mikko S ; Lunde, Asger.
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  33. Limit-order book resiliency after effective market orders: Spread, depth and intensity. (2017). Xu, Hai-Chuan ; Zhou, Wei-Xing ; Zhang, Wei ; Xiong, Xiong ; Chen, Wei.
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  34. Decoupling the short- and long-term behavior of stochastic volatility. (2017). Pakkanen, Mikko S ; Lunde, Asger ; Bennedsen, Mikkel.
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  35. The Chinese Stock Market Does not React to the Japanese Market: Using Intraday Data to Analyse Return and Volatility Spillover Effects. (2016). Tsutsui, Yoshiro ; Nishimura, Yusaku ; Hirayama, Kenjiro.
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  36. Does U.S. Macroeconomic News Make the South African Stock Market Riskier?. (2016). GUPTA, RANGAN ; Cakan, Esin.
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  38. Intra-day realized volatility for European and USA stock indices. (2016). Floros, Christos ; Degiannakis, Stavros.
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  39. The Boats That Did Not Sail: Asset Price Volatility in a Natural Experiment. (2016). Koudijs, Peter.
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  40. The Chinese Stock Market Does not React to the Japanese Market: Using Intraday Data to Analyse Return and Volatility Spillover Effects. (2016). Tsutsui, Yoshiro ; Nishimura, Yusaku ; Hirayama, Kenjiro .
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  42. Intra-Day Realized Volatility for European and USA Stock Indices. (2015). Floros, Christos ; Degiannakis, Stavros.
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  43. Nonlinearity in high-frequency stock returns: Evidence from the Athens Stock Exchange. (2015). Emmanouilides, Christos ; Anagnostidis, Panagiotis .
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  45. Public information arrival and investor reaction during a period of institutional change: An episode of early years of a newly independent central bank. (2015). Kutan, Ali ; Brzeszczynski, Janusz ; Brzeszczyski, Janusz.
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  46. Search for the periodicity of the prime Indian and American stock exchange indices using date-compensated discrete Fourier transformAuthor-Name: Samadder, Swetadri. (2015). Basu, Tapasendra ; Ghosh, Koushik.
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  47. Intraday Return and Volatility Spillover Mechanism from Chinese to Japanese Stock Market. (2014). Tsutsui, Yoshiro ; Nishimura, Yusaku ; Hirayama, Kenjiro.
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  51. Circuit Breakers on the London Stock Exchange: Do they improve subsequent market quality?. (2014). Brugler, James ; Linton, Oliver.
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  53. Expiration‐Day Effects and the Impact of Short Trading Breaks on Intraday Volatility: Evidence from the Indian Market. (2013). Pandey, Ajay ; Agarwalla, Sobhesh Kumar.
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  54. Double-conditional smoothing of high-frequency volatility surface in a spatial multiplicative component GARCH with random effects. (2013). Feng, Yuanhua.
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  55. Persistence of announcement effects on the intraday volatility of stock returns: evidence from individual data. (2013). Renou-Maissant, Patricia ; Lecarpentier-Moyal, Sylvie ; Uctumd, Remzi .
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  56. Persistence of announcement effects on the intraday volatility of stock returns: evidence from individual data. (2013). Uctum, Remzi ; Prat, Georges ; Moyal, Sylvie Lecarpentier ; Maissant, Patricia Renou .
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  57. Persistence of announcement effects on the intraday volatility of stock returns: evidence from individual data. (2013). Renou-Maissant, Patricia ; Lecarpentier-Moyal, Sylvie ; Uctumd, Remzi .
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  58. Persistence of announcement effects on the intraday volatility of stock returns: evidence from individual data. (2013). Uctum, Remzi ; Renou-Maissant, Patricia ; Prat, Georges ; Lecarpentier-Moyal, Sylvie.
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  59. Persistence of announcement effects on the intraday volatility of stock returns: evidence from individual data. (2013). Uctum, Remzi ; Renou-Maissant, Patricia ; Prat, Georges ; Lecarpentier-Moyal, Sylvie.
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  60. Do FOMC minutes matter to markets? An intraday analysis of FOMC minutes releases on individual equity volatility and returns. (2013). Jubinski, Daniel ; Tomljanovich, Marc.
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  62. Persistence of announcement effects on the intraday volatility of stock returns: evidence from individual data. (2013). Uctum, Remzi ; Prat, Georges ; Renou-Maissant, Patricia ; Lecarpentier-Moyal, Sylvie.
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  64. Return and Volatility Spillovers between Japanese and Chinese Stock Markets FAn Analysis of Overlapping Trading Hours with High-frequency Data. (2012). Tsutsui, Yoshiro ; Nishimura, Yusaku ; Hirayama, Kenjiro.
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  75. International macroeconomic announcements and intraday euro exchange rate volatility. (2010). Speight, Alan ; Evans, Kevin .
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  76. Dynamic news effects in high frequency Euro exchange rates. (2010). Evans, Kevin P. ; Speight, Alan E. H., .
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  77. HOW FAST DO TOKYO AND NEW YORK STOCK EXCHANGES RESPOND TO EACH OTHER? AN ANALYSIS WITH HIGH-FREQUENCY DATA. (2010). Tsutsui, Yoshiro ; Hirayama, Kenjiro.
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  78. Modeling and Forecasting the Volatility of the Nikkei 225 Realized Volatility Using the ARFIMA-GARCH Model. (2009). Ishida, Isao ; Be, Toshiaki Watana ; Watanabe, Toshiaki .
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  79. The reaction of asset prices to macroeconomic announcements in new EU markets: Evidence from intraday data. (2009). Kutan, Ali ; Kočenda, Evžen ; Hanousek, Jan.
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  80. The distribution of realized variances: Marginal behaviors, asymmetric dependence and contagion effects. (2009). Metais, Carole ; Ane, Thierry .
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  81. Modeling and Forecasting the Volatility of the Nikkei 225 Realized Volatility Using the ARFIMA-GARCH Model. (2009). Ishida, Isao ; Be, Toshiaki Watana ; Watanabe, Toshiaki .
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  83. How Fast Do Tokyo and New York Stock Exchanges Respond to Each Other?: An Analysis with High-Frequency Data. (2008). Tsutsui, Yoshiro ; Hirayama, Kenjiro.
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