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Continuous-Time Models, Realized Volatilities, and Testable Distributional Implications for Daily Stock Returns

Citations

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Cited by:

  1. Shaliastovich, Ivan & Tauchen, George, 2011. "Pricing of the time-change risks," Journal of Economic Dynamics and Control, Elsevier, vol. 35(6), pages 843-858, June.
  2. Liao, Yin & Pan, Zheyao, 2022. "Extreme risk connectedness among global major financial institutions: Links to globalization and emerging market fear," Pacific-Basin Finance Journal, Elsevier, vol. 76(C).
  3. Sébastien Laurent & Jeroen V. K. Rombouts & Francesco Violante, 2012. "On the forecasting accuracy of multivariate GARCH models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(6), pages 934-955, September.
  4. Chan, Kam Fong & Gray, Philip & van Campen, Bart, 2008. "A new approach to characterizing and forecasting electricity price volatility," International Journal of Forecasting, Elsevier, vol. 24(4), pages 728-743.
  5. Fengler, Matthias R. & Gisler, Katja I.M., 2015. "A variance spillover analysis without covariances: What do we miss?," Journal of International Money and Finance, Elsevier, vol. 51(C), pages 174-195.
  6. Benoît Sévi & César Baena, 2011. "Brownian motion vs. pure-jump processes for individual stocks," Economics Bulletin, AccessEcon, vol. 31(4), pages 3138-3152.
  7. Carroll, Rachael & Kearney, Colm, 2015. "Testing the mixture of distributions hypothesis on target stocks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 39(C), pages 1-14.
  8. El Ouadghiri, Imane & Uctum, Remzi, 2016. "Jumps in equilibrium prices and asymmetric news in foreign exchange markets," Economic Modelling, Elsevier, vol. 54(C), pages 218-234.
  9. Pattanaporn Chatjuthamard & Pavitra Jindahra & Pattarake Sarajoti & Sirimon Treepongkaruna, 2021. "The effect of COVID‐19 on the global stock market," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(3), pages 4923-4953, September.
  10. Lai, Yu-Sheng, 2022. "Improving hedging performance by using high–low range," Finance Research Letters, Elsevier, vol. 48(C).
  11. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2020. "The contribution of intraday jumps to forecasting the density of returns," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-02505861, HAL.
  12. Nielsen, Morten Ørregaard & Frederiksen, Per, 2008. "Finite sample accuracy and choice of sampling frequency in integrated volatility estimation," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 265-286, March.
  13. Degiannakis, Stavros & Filis, George, 2016. "Forecasting oil price realized volatility: A new approach," MPRA Paper 69105, University Library of Munich, Germany.
  14. Laurent, Sébastien & Lecourt, Christelle & Palm, Franz C., 2016. "Testing for jumps in conditionally Gaussian ARMA–GARCH models, a robust approach," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 383-400.
  15. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220, Elsevier.
  16. Degiannakis, Stavros & Floros, Christos, 2016. "Intra-day realized volatility for European and USA stock indices," Global Finance Journal, Elsevier, vol. 29(C), pages 24-41.
  17. Chevallier, Julien & Sévi, Benoît, 2012. "On the volatility–volume relationship in energy futures markets using intraday data," Energy Economics, Elsevier, vol. 34(6), pages 1896-1909.
  18. Hurvich, Cliiford & Wang, Yi, 2006. "A Pure-Jump Transaction-Level Price Model Yielding Cointegration, Leverage, and Nonsynchronous Trading Effects," MPRA Paper 1413, University Library of Munich, Germany.
  19. Thierry Ane & Carole Metais, 2010. "Jump Distribution Characteristics: Evidence from European Stock Markets," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 9(1), pages 1-22, April.
  20. Nikolaus Hautsch & Lada M. Kyj & Roel C. A. Oomen, 2012. "A blocking and regularization approach to high‐dimensional realized covariance estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(4), pages 625-645, June.
  21. Fengler, Matthias R. & Mammen, Enno & Vogt, Michael, 2013. "Additive modeling of realized variance: tests for parametric specifications and structural breaks," Economics Working Paper Series 1332, University of St. Gallen, School of Economics and Political Science.
  22. Weijia Peng & Chun Yao, 2022. "Co-Jumps, Co-Jump Tests, and Volatility Forecasting: Monte Carlo and Empirical Evidence," JRFM, MDPI, vol. 15(8), pages 1-21, July.
  23. Sergii Pypko, 2015. "Volatility Forecast in Crises and Expansions," JRFM, MDPI, vol. 8(3), pages 1-26, August.
  24. Francesco Audrino & Yujia Hu, 2016. "Volatility Forecasting: Downside Risk, Jumps and Leverage Effect," Econometrics, MDPI, vol. 4(1), pages 1-24, February.
  25. Tetsuya Takaishi, 2016. "Dynamical cross-correlation of multiple time series Ising model," Evolutionary and Institutional Economics Review, Springer, vol. 13(2), pages 455-468, December.
  26. Liu, Zhi & Kong, Xin-Bing & Jing, Bing-Yi, 2018. "Estimating the integrated volatility using high-frequency data with zero durations," Journal of Econometrics, Elsevier, vol. 204(1), pages 18-32.
  27. F. Lilla, 2016. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models," Working Papers wp1084, Dipartimento Scienze Economiche, Universita' di Bologna.
  28. Tetsuya Takaishi, 2014. "Analysis of Spin Financial Market by GARCH Model," Papers 1409.0118, arXiv.org.
  29. Nikolaus Hautsch & Lada M. Kyj & Peter Malec, 2015. "Do High‐Frequency Data Improve High‐Dimensional Portfolio Allocations?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(2), pages 263-290, March.
  30. Timo Dimitriadis & Roxana Halbleib & Jeannine Polivka & Jasper Rennspies & Sina Streicher & Axel Friedrich Wolter, 2022. "Efficient Sampling for Realized Variance Estimation in Time-Changed Diffusion Models," Papers 2212.11833, arXiv.org, revised Dec 2023.
  31. BAUWENS, Luc & STORTI, Giuseppe & VIOLANTE, Francesco, 2012. "Dynamic conditional correlation models for realized covariance matrices," LIDAM Discussion Papers CORE 2012060, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  32. Chatrath, Arjun & Miao, Hong & Ramchander, Sanjay & Villupuram, Sriram, 2014. "Currency jumps, cojumps and the role of macro news," Journal of International Money and Finance, Elsevier, vol. 40(C), pages 42-62.
  33. Song, Shijia & Li, Handong, 2023. "Is a co-jump in prices a sparse jump?," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
  34. Johannes Stübinger & Sylvia Endres, 2018. "Pairs trading with a mean-reverting jump–diffusion model on high-frequency data," Quantitative Finance, Taylor & Francis Journals, vol. 18(10), pages 1735-1751, October.
  35. Aitor Ciarreta & Peru Muniain & Ainhoa Zarraga, 2020. "Realized volatility and jump testing in the Japanese electricity spot market," Empirical Economics, Springer, vol. 58(3), pages 1143-1166, March.
  36. Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil price realized volatility using information channels from other asset classes," Journal of International Money and Finance, Elsevier, vol. 76(C), pages 28-49.
  37. Barunik, Jozef & Vacha, Lukas, 2018. "Do co-jumps impact correlations in currency markets?," Journal of Financial Markets, Elsevier, vol. 37(C), pages 97-119.
  38. Andersen, Torben G. & Bollerslev, Tim & Huang, Xin, 2011. "A reduced form framework for modeling volatility of speculative prices based on realized variation measures," Journal of Econometrics, Elsevier, vol. 160(1), pages 176-189, January.
  39. Minxian Yang, 2014. "The Risk Return Relationship: Evidence from Index Return and Realised Variance Series," Discussion Papers 2014-16, School of Economics, The University of New South Wales.
  40. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Post-Print halshs-01442618, HAL.
  41. Maderitsch, R., 2015. "Information transmission between stock markets in Hong Kong, Europe and the US: New evidence on time- and state-dependence," Pacific-Basin Finance Journal, Elsevier, vol. 35(PA), pages 13-36.
  42. M. Frömmel & X. Han & F. Van Gysegem, 2013. "News, Liquidity Dynamics and Intraday Jumps: Evidence from the HUF/EUR market," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 13/848, Ghent University, Faculty of Economics and Business Administration.
  43. Li, Shaoyu & Zheng, Tingguo, 2017. "Modeling spot rate using a realized stochastic volatility model with level effect and dynamic drift☆," The North American Journal of Economics and Finance, Elsevier, vol. 40(C), pages 200-221.
  44. Kuck, Konstantin & Maderitsch, Robert, 2019. "Intra-day dynamics of exchange rates: New evidence from quantile regression," The Quarterly Review of Economics and Finance, Elsevier, vol. 71(C), pages 247-257.
  45. Jung, R.C. & Maderitsch, R., 2014. "Structural breaks in volatility spillovers between international financial markets: Contagion or mere interdependence?," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 331-342.
  46. Chin Wen CHEONG & Lee Min CHERNG & Grace Lee Ching YAP, 2016. "Heterogeneous Market Hypothesis Evaluations using Various Jump-Robust Realized Volatility," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 50-64, December.
  47. Ahmad, Khurshid & Han, JingGuang & Hutson, Elaine & Kearney, Colm & Liu, Sha, 2016. "Media-expressed negative tone and firm-level stock returns," Journal of Corporate Finance, Elsevier, vol. 37(C), pages 152-172.
  48. Evans, Kevin P., 2011. "Intraday jumps and US macroeconomic news announcements," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2511-2527, October.
  49. repec:wyi:journl:002184 is not listed on IDEAS
  50. Liu, Yi & Liu, Huifang & Zhang, Lei, 2019. "Modeling and forecasting return jumps using realized variation measures," Economic Modelling, Elsevier, vol. 76(C), pages 63-80.
  51. Vortelinos, Dimitrios I., 2010. "The properties of realized correlation: Evidence from the French, German and Greek equity markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 50(3), pages 273-290, August.
  52. Wang, Kent & Liu, Junwei & Liu, Zhi, 2013. "Disentangling the effect of jumps on systematic risk using a new estimator of integrated co-volatility," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1777-1786.
  53. Julien Chevallier & Benoît Sévi, 2011. "On the volatility-volume relationship in energy futures markets using intraday data," Working Papers hal-04140997, HAL.
  54. Chowdhury, Biplob & Jeyasreedharan, Nagaratnam, 2019. "An empirical examination of the jump and diffusion aspects of asset pricing: Japanese evidence," Working Papers 2019-02, University of Tasmania, Tasmanian School of Business and Economics.
  55. Yu‐Sheng Lai, 2022. "High‐frequency data and stock–bond investing," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1623-1638, December.
  56. Vít Bubák & Filip Žikeš, 2009. "Distribution and Dynamics of Central-European Exchange Rates: Evidence from Intraday Data," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 59(4), pages 334-359, Oktober.
  57. Siem Jan Koopman & Marcel Scharth, 2012. "The Analysis of Stochastic Volatility in the Presence of Daily Realized Measures," Journal of Financial Econometrics, Oxford University Press, vol. 11(1), pages 76-115, December.
  58. Gilder, Dudley & Shackleton, Mark B. & Taylor, Stephen J., 2014. "Cojumps in stock prices: Empirical evidence," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 443-459.
  59. Maneesoonthorn, Worapree & Martin, Gael M. & Forbes, Catherine S., 2020. "High-frequency jump tests: Which test should we use?," Journal of Econometrics, Elsevier, vol. 219(2), pages 478-487.
  60. Johannes Stübinger & Lucas Schneider, 2019. "Statistical Arbitrage with Mean-Reverting Overnight Price Gaps on High-Frequency Data of the S&P 500," JRFM, MDPI, vol. 12(2), pages 1-19, April.
  61. Giovanni Masala & Filippo Petroni, 2023. "Drawdown risk measures for asset portfolios with high frequency data," Annals of Finance, Springer, vol. 19(2), pages 265-289, June.
  62. Gong, Xiao-Li & Liu, Jian-Min & Xiong, Xiong & Zhang, Wei, 2022. "Research on stock volatility risk and investor sentiment contagion from the perspective of multi-layer dynamic network," International Review of Financial Analysis, Elsevier, vol. 84(C).
  63. Chorro, Christophe & Ielpo, Florian & Sévi, Benoît, 2020. "The contribution of intraday jumps to forecasting the density of returns," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
  64. Dungey, Mardi & Hvozdyk, Lyudmyla, 2010. "Cojumping: Evidence from the US Treasury Bond and Future Markets (Discussion Paper 2010-06)," Working Papers 10450, University of Tasmania, Tasmanian School of Business and Economics, revised 14 Jul 2010.
  65. repec:dau:papers:123456789/6887 is not listed on IDEAS
  66. Aldrich, Eric M. & Heckenbach, Indra & Laughlin, Gregory, 2016. "A compound duration model for high-frequency asset returns," Journal of Empirical Finance, Elsevier, vol. 39(PA), pages 105-128.
  67. Dungey, Mardi & Hvozdyk, Lyudmyla, 2012. "Cojumping: Evidence from the US Treasury bond and futures markets," Journal of Banking & Finance, Elsevier, vol. 36(5), pages 1563-1575.
  68. Bollerslev, Tim & Todorov, Viktor & Li, Sophia Zhengzi, 2013. "Jump tails, extreme dependencies, and the distribution of stock returns," Journal of Econometrics, Elsevier, vol. 172(2), pages 307-324.
  69. Dion Bongaerts & Richard Roll & Dominik Rösch & Mathijs van Dijk & Darya Yuferova, 2022. "How Do Shocks Arise and Spread Across Stock Markets? A Microstructure Perspective," Management Science, INFORMS, vol. 68(4), pages 3071-3089, April.
  70. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2020. "The contribution of intraday jumps to forecasting the density of returns," Post-Print halshs-02505861, HAL.
  71. Worapree Maneesoonthorn & Gael M Martin & Catherine S Forbes, 2018. "Dynamic price jumps: The performance of high frequency tests and measures, and the robustness of inference," Monash Econometrics and Business Statistics Working Papers 17/18, Monash University, Department of Econometrics and Business Statistics.
  72. Aida Karmous & Heni Boubaker & Lotfi Belkacem, 2021. "Forecasting Volatility for an Optimal Portfolio with Stylized Facts Using Copulas," Computational Economics, Springer;Society for Computational Economics, vol. 58(2), pages 461-482, August.
  73. F. Lilla, 2017. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models - 2nd ed," Working Papers wp1099, Dipartimento Scienze Economiche, Universita' di Bologna.
  74. Olusanya E. Olubusoye & OlaOluwa S. Yaya, 2016. "Time series analysis of volatility in the petroleum pricing markets: the persistence, asymmetry and jumps in the returns series," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 40(3), pages 235-262, September.
  75. Gao, Ya & Han, Xing & Li, Youwei & Xiong, Xiong, 2019. "Overnight momentum, informational shocks, and late informed trading in China," International Review of Financial Analysis, Elsevier, vol. 66(C).
  76. Lucio Maria Calcagnile & Giacomo Bormetti & Michele Treccani & Stefano Marmi & Fabrizio Lillo, 2015. "Collective synchronization and high frequency systemic instabilities in financial markets," Papers 1505.00704, arXiv.org.
  77. Fang, Yan & Ielpo, Florian & Sévi, Benoît, 2012. "Empirical bias in intraday volatility measures," Finance Research Letters, Elsevier, vol. 9(4), pages 231-237.
  78. Chan, Kam Fong & Powell, John G. & Treepongkaruna, Sirimon, 2014. "Currency jumps and crises: Do developed and emerging market currencies jump together?," Pacific-Basin Finance Journal, Elsevier, vol. 30(C), pages 132-157.
  79. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Documents de travail du Centre d'Economie de la Sorbonne 17006, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  80. Cui, Xin & Sensoy, Ahmet & Nguyen, Duc Khuong & Yao, Shouyu & Wu, Yiyao, 2022. "Positive information shocks, investor behavior and stock price crash risk," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 493-518.
  81. BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016. "Multiplicative Conditional Correlation Models for Realized Covariance Matrices," LIDAM Discussion Papers CORE 2016041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  82. Chin, Chang-Chiang & Paphakin, Warinthorn, 2021. "The daily relationship between U.S. asset prices and stock prices of American countries," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
  83. Wanidwaranan, Phasin & Padungsaksawasdi, Chaiyuth, 2020. "The effect of return jumps on herd behavior," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
  84. Clements, Adam & Liao, Yin, 2017. "Forecasting the variance of stock index returns using jumps and cojumps," International Journal of Forecasting, Elsevier, vol. 33(3), pages 729-742.
  85. Rituparna Sen & Pulkit Mehrotra, 2016. "Modeling Jumps and Volatility of the Indian Stock Market Using High-Frequency Data," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 14(1), pages 137-150, June.
  86. Torben G. Andersen & Viktor Todorov, 2009. "Realized Volatility and Multipower Variation," CREATES Research Papers 2009-49, Department of Economics and Business Economics, Aarhus University.
  87. Xinwei Feng & Lidan He & Zhi Liu, 2022. "Large Deviation Principles of Realized Laplace Transform of Volatility," Journal of Theoretical Probability, Springer, vol. 35(1), pages 186-208, March.
  88. Vortelinos, Dimitrios I. & Lakshmi, Geeta, 2015. "Market risk of BRIC Eurobonds in the financial crisis period," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 295-310.
  89. Gongyue Jiang & Gaoxiu Qiao & Feng Ma & Lu Wang, 2022. "Directly pricing VIX futures with observable dynamic jumps based on high‐frequency VIX," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(8), pages 1518-1548, August.
  90. Yingjie Dong & Yiu-Kuen Tse, 2017. "Business Time Sampling Scheme with Applications to Testing Semi-Martingale Hypothesis and Estimating Integrated Volatility," Econometrics, MDPI, vol. 5(4), pages 1-19, November.
  91. Nkwoma, Inekwe John, 2017. "Futures-Based Measures Of Monetary Policy And Jump Risk," Macroeconomic Dynamics, Cambridge University Press, vol. 21(2), pages 384-405, March.
  92. Karmous, Aida & Boubaker, Heni & Belkacem, Lotfi, 2019. "A dynamic factor model with stylized facts to forecast volatility for an optimal portfolio," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
  93. Chen, Yixiang & Ma, Feng & Zhang, Yaojie, 2019. "Good, bad cojumps and volatility forecasting: New evidence from crude oil and the U.S. stock markets," Energy Economics, Elsevier, vol. 81(C), pages 52-62.
  94. Tauchen, George & Zhou, Hao, 2011. "Realized jumps on financial markets and predicting credit spreads," Journal of Econometrics, Elsevier, vol. 160(1), pages 102-118, January.
  95. Ahmed A. A. Khalifa & Hong Miao & Sanjay Ramchander, 2011. "Return distributions and volatility forecasting in metal futures markets: Evidence from gold, silver, and copper," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 31(1), pages 55-80, January.
  96. Jan Novotn?? & Jan Hanousek & Ev??en Ko??enda, 2013. "Price Jump Indicators: Stock Market Empirics During the Crisis," William Davidson Institute Working Papers Series wp1050, William Davidson Institute at the University of Michigan.
  97. Cui, Jing & Zhao, Hua, 2015. "Intraday jumps in China's Treasury bond market and macro news announcements," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 211-223.
  98. Worapree Maneesoonthorn & Gael M. Martin & Catherine S. Forbes, 2017. "Dynamic asset price jumps and the performance of high frequency tests and measures," Monash Econometrics and Business Statistics Working Papers 14/17, Monash University, Department of Econometrics and Business Statistics.
  99. Dario Alitab & Giacomo Bormetti & Fulvio Corsi & Adam A. Majewski, 2019. "A realized volatility approach to option pricing with continuous and jump variance components," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(2), pages 639-664, December.
  100. John Elder, Hong Miao, and Sanjay Ramchander, 2013. "Jumps in Oil Prices: The Role of Economic News," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
  101. Qian, Lihua & Wang, Jiqian & Ma, Feng & Li, Ziyang, 2022. "Bitcoin volatility predictability–The role of jumps and regimes," Finance Research Letters, Elsevier, vol. 47(PB).
  102. 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).
  103. Jiang, George J. & Zhu, Kevin X., 2017. "Information Shocks and Short-Term Market Underreaction," Journal of Financial Economics, Elsevier, vol. 124(1), pages 43-64.
  104. Yang, Minxian, 2019. "The risk return relationship: Evidence from index returns and realised variances," Journal of Economic Dynamics and Control, Elsevier, vol. 107(C), pages 1-1.
  105. Zhi Liu, 2017. "Jump-robust estimation of volatility with simultaneous presence of microstructure noise and multiple observations," Finance and Stochastics, Springer, vol. 21(2), pages 427-469, April.
  106. Fleming, Jeff & Paye, Bradley S., 2011. "High-frequency returns, jumps and the mixture of normals hypothesis," Journal of Econometrics, Elsevier, vol. 160(1), pages 119-128, January.
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