Machine learning sentiment analysis, COVID-19 news and stock market reactions
Author
Abstract
Suggested Citation
DOI: 10.1016/j.ribaf.2023.101881
Download full text from publisher
As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.
Other versions of this item:
- Costola, Michele & Nofer, Michael & Hinz, Oliver & Pelizzon, Loriana, 2020. "Machine learning sentiment analysis, Covid-19 news and stock market reactions," SAFE Working Paper Series 288, Leibniz Institute for Financial Research SAFE.
References listed on IDEAS
- Ahmed, Shamima & Alshater, Muneer M. & Ammari, Anis El & Hammami, Helmi, 2022.
"Artificial intelligence and machine learning in finance: A bibliometric review,"
Research in International Business and Finance, Elsevier, vol. 61(C).
- Shamima Ahmed & Muneer Alshater & Anis El Ammari & Helmi Hammami, 2022. "Artificial intelligence and machine learning in finance: A bibliometric review," Post-Print hal-03697290, HAL.
- Daniele Bianchi & Matthias Büchner & Tobias Hoogteijling & Andrea Tamoni, 2021. "Corrigendum: Bond Risk Premiums with Machine Learning [Bond risk premiums with machine learning]," The Review of Financial Studies, Society for Financial Studies, vol. 34(2), pages 1090-1103.
- Sanjiv R. Das & Mike Y. Chen, 2007. "Yahoo! for Amazon: Sentiment Extraction from Small Talk on the Web," Management Science, INFORMS, vol. 53(9), pages 1375-1388, September.
- Ahmad, Wasim & Kutan, Ali M. & Gupta, Smarth, 2021. "Black swan events and COVID-19 outbreak: Sector level evidence from the US, UK, and European stock markets," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 546-557.
- Joshua Zoen Git Hiew & Xin Huang & Hao Mou & Duan Li & Qi Wu & Yabo Xu, 2019. "BERT-based Financial Sentiment Index and LSTM-based Stock Return Predictability," Papers 1906.09024, arXiv.org, revised Jul 2022.
- Tom Marty & Bruce Vanstone & Tobias Hahn, 2020. "News media analytics in finance: a survey," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(2), pages 1385-1434, June.
- Yarovaya, Larisa & Matkovskyy, Roman & Jalan, Akanksha, 2021.
"The effects of a “black swan” event (COVID-19) on herding behavior in cryptocurrency markets,"
Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
- Larisa Yarovaya & Roman Matkovskyy & Akanksha Jalan, 2021. "The effects of a “black swan” event (COVID-19) on herding behavior in cryptocurrency markets," Post-Print hal-03512931, HAL.
- Jiang, Zhi-Qiang & Zhou, Wei-Xing & Sornette, Didier & Woodard, Ryan & Bastiaensen, Ken & Cauwels, Peter, 2010.
"Bubble diagnosis and prediction of the 2005-2007 and 2008-2009 Chinese stock market bubbles,"
Journal of Economic Behavior & Organization, Elsevier, vol. 74(3), pages 149-162, June.
- Zhi-Qiang Jiang & Wei-Xing Zhou & D. Sornette & Ryan Woodard & Ken Bastiaensen & Peter Cauwels, "undated". "Bubble Diagnosis and Prediction of the 2005-2007 and 2008-2009 Chinese stock market bubbles," Working Papers CCSS-09-008, ETH Zurich, Chair of Systems Design.
- Zhi-Qiang Jiang & Wei-Xing Zhou & Didier Sornette & Ryan Woodard & Ken Bastiaensen & Peter Cauwels, 2009. "Bubble Diagnosis and Prediction of the 2005-2007 and 2008-2009 Chinese stock market bubbles," Papers 0909.1007, arXiv.org, revised Oct 2009.
- Zhi-Qiang JIANG & Wei-Xing ZHOU & Didier SORNETTE & Ryan WOODARD & Ken BASTIAENSEN & Peter CAUWELS, 2009. "Bubble Diagnosis and Prediction of the 2005-2007 and 2008-2009 Chinese stock market bubbles," Swiss Finance Institute Research Paper Series 09-39, Swiss Finance Institute.
- Ankur Sinha & Satishwar Kedas & Rishu Kumar & Pekka Malo, 2022. "SEntFiN 1.0: Entity‐aware sentiment analysis for financial news," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(9), pages 1314-1335, September.
- Roberto Casarin & Flaminio Squazzoni, 2013. "Being on the Field When the Game Is Still Under Way. The Financial Press and Stock Markets in Times of Crisis," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-14, July.
- Susan Athey & Guido W. Imbens, 2019. "Machine Learning Methods That Economists Should Know About," Annual Review of Economics, Annual Reviews, vol. 11(1), pages 685-725, August.
- Mitchell, Mark L & Mulherin, J Harold, 1994. "The Impact of Public Information on the Stock Market," Journal of Finance, American Finance Association, vol. 49(3), pages 923-950, July.
- Lyócsa, Štefan & Baumöhl, Eduard & Výrost, Tomáš & Molnár, Peter, 2020.
"Fear of the coronavirus and the stock markets,"
Finance Research Letters, Elsevier, vol. 36(C).
- Lyócsa, Štefan & Baumöhl, Eduard & Výrost, Tomáš & Molnár, Peter, 2020. "Fear of the coronavirus and the stock markets," EconStor Preprints 219336, ZBW - Leibniz Information Centre for Economics.
- Alexander W. Butler & Gustavo Grullon & James P. Weston, 2005. "Can Managers Forecast Aggregate Market Returns?," Journal of Finance, American Finance Association, vol. 60(2), pages 963-986, April.
- Niels Joachim Gormsen & Ralph S J Koijen & Nikolai Roussanov, 0.
"Coronavirus: Impact on Stock Prices and Growth Expectations,"
The Review of Asset Pricing Studies, Society for Financial Studies, vol. 10(4), pages 574-597.
- Koijen, Ralph & Gormsen, Niels Joachim, 2020. "Coronavirus: Impact on Stock Prices and Growth Expectations," CEPR Discussion Papers 14875, C.E.P.R. Discussion Papers.
- Niels J. Gormsen & Ralph S. J. Koijen, 2020. "Coronavirus: Impact on Stock Prices and Growth Expectations," NBER Working Papers 27387, National Bureau of Economic Research, Inc.
- Ghoddusi, Hamed & Creamer, Germán G. & Rafizadeh, Nima, 2019. "Machine learning in energy economics and finance: A review," Energy Economics, Elsevier, vol. 81(C), pages 709-727.
- Daniele Bianchi & Matthias Büchner & Andrea Tamoni, 2021. "Bond Risk Premiums with Machine Learning [Quadratic term structure models: Theory and evidence]," The Review of Financial Studies, Society for Financial Studies, vol. 34(2), pages 1046-1089.
- Diego García, 2013. "Sentiment during Recessions," Journal of Finance, American Finance Association, vol. 68(3), pages 1267-1300, June.
- Michele Costola & Matteo Iacopini & Carlo R. M. A. Santagiustina, 2020. "Public Concern and the Financial Markets during the COVID-19 outbreak," Papers 2005.06796, arXiv.org.
- Chiah, Mardy & Zhong, Angel, 2020. "Trading from home: The impact of COVID-19 on trading volume around the world," Finance Research Letters, Elsevier, vol. 37(C).
- Haroon, Omair & Rizvi, Syed Aun R., 2020. "COVID-19: Media coverage and financial markets behavior—A sectoral inquiry," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
- Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2023.
"Machine learning advances for time series forecasting,"
Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 76-111, February.
- Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2020. "Machine Learning Advances for Time Series Forecasting," Papers 2012.12802, arXiv.org, revised Apr 2021.
- Zhang, Qi & Cai, Charlie X. & Keasey, Kevin, 2013. "Market reaction to earnings news: A unified test of information risk and transaction costs," Journal of Accounting and Economics, Elsevier, vol. 56(2), pages 251-266.
- Huynh, Toan Luu Duc & Foglia, Matteo & Nasir, Muhammad Ali & Angelini, Eliana, 2021. "Feverish sentiment and global equity markets during the COVID-19 pandemic," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 1088-1108.
- Taylan Kabbani & Ekrem Duman, 2022. "Deep Reinforcement Learning Approach for Trading Automation in The Stock Market," Papers 2208.07165, arXiv.org.
- Pekka Malo & Ankur Sinha & Pekka Korhonen & Jyrki Wallenius & Pyry Takala, 2014.
"Good debt or bad debt: Detecting semantic orientations in economic texts,"
Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(4), pages 782-796, April.
- Pekka Malo & Ankur Sinha & Pyry Takala & Pekka Korhonen & Jyrki Wallenius, 2013. "Good Debt or Bad Debt: Detecting Semantic Orientations in Economic Texts," Papers 1307.5336, arXiv.org, revised Jul 2013.
- Alessandro Rebucci & Jonathan S. Hartley & Daniel Jiménez, 2022.
"An Event Study of COVID-19 Central Bank Quantitative Easing in Advanced and Emerging Economies,"
Advances in Econometrics, in: Essays in Honor of M. Hashem Pesaran: Prediction and Macro Modeling, volume 43, pages 291-322,
Emerald Group Publishing Limited.
- Alessandro Rebucci & Jonathan S. Hartley & Daniel Jiménez, 2020. "An Event Study of COVID-19 Central Bank Quantitative Easing in Advanced and Emerging Economies," NBER Working Papers 27339, National Bureau of Economic Research, Inc.
- Rebucci, Alessandro & Hartley, Jonathan, 2020. "An Event Study of COVID-19 Central Bank Quantitative Easing in Advanced and Emerging Economies," CEPR Discussion Papers 14841, C.E.P.R. Discussion Papers.
- Salisu, Afees A. & Vo, Xuan Vinh, 2020. "Predicting stock returns in the presence of COVID-19 pandemic: The role of health news," International Review of Financial Analysis, Elsevier, vol. 71(C).
- Akhtaruzzaman, Md & Boubaker, Sabri & Sensoy, Ahmet, 2021.
"Financial contagion during COVID–19 crisis,"
Finance Research Letters, Elsevier, vol. 38(C).
- Md Akhtaruzzaman & Sabri Boubaker & Ahmet Sensoy, 2021. "Financial contagion during COVID–19 crisis," Post-Print hal-04455600, HAL.
- Scott R Baker & Nicholas Bloom & Steven J Davis & Kyle Kost & Marco Sammon & Tasaneeya Viratyosin & Jeffrey Pontiff, 0. "The Unprecedented Stock Market Reaction to COVID-19," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 10(4), pages 742-758.
- Jan De Spiegeleer & Dilip B. Madan & Sofie Reyners & Wim Schoutens, 2018. "Machine learning for quantitative finance: fast derivative pricing, hedging and fitting," Quantitative Finance, Taylor & Francis Journals, vol. 18(10), pages 1635-1643, October.
- Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, June.
- repec:bla:jfinan:v:59:y:2004:i:3:p:1259-1294 is not listed on IDEAS
- Xu, Yongan & Liang, Chao & Li, Yan & Huynh, Toan L.D., 2022. "News sentiment and stock return: Evidence from managers’ news coverages," Finance Research Letters, Elsevier, vol. 48(C).
- Nofer, Michael & Hinz, Oliver, 2015. "Using Twitter to Predict the Stock Market: Where is the Mood Effect?," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 77140, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
- Athey, Susan & Imbens, Guido W., 2019.
"Machine Learning Methods Economists Should Know About,"
Research Papers
3776, Stanford University, Graduate School of Business.
- Susan Athey & Guido Imbens, 2019. "Machine Learning Methods Economists Should Know About," Papers 1903.10075, arXiv.org.
- Biktimirov, Ernest N. & Sokolyk, Tatyana & Ayanso, Anteneh, 2021. "Sentiment and hype of business media topics and stock market returns during the COVID-19 pandemic," Journal of Behavioral and Experimental Finance, Elsevier, vol. 31(C).
- Xin Huang, 2018. "Macroeconomic news announcements, systemic risk, financial market volatility, and jumps," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(5), pages 513-534, May.
- J. Bradford De Long & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1987. "The Economic Consequences of Noise Traders," NBER Working Papers 2395, National Bureau of Economic Research, Inc.
- Xingchen Wan & Jie Yang & Slavi Marinov & Jan-Peter Calliess & Stefan Zohren & Xiaowen Dong, 2020. "Sentiment Correlation in Financial News Networks and Associated Market Movements," Papers 2011.06430, arXiv.org, revised Feb 2021.
- Bledar Fazlija & Pedro Harder, 2022. "Using Financial News Sentiment for Stock Price Direction Prediction," Mathematics, MDPI, vol. 10(13), pages 1-20, June.
- Smales, L.A., 2021. "Investor attention and global market returns during the COVID-19 crisis," International Review of Financial Analysis, Elsevier, vol. 73(C).
- Carlini, Federico & Cucinelli, Doriana & Previtali, Daniele & Soana, Maria Gaia, 2020. "Don't talk too bad! stock market reactions to bank corporate governance news," Journal of Banking & Finance, Elsevier, vol. 121(C).
- Dey, Asim K. & Hoque, G.M. Toufiqul & Das, Kumer P. & Panovska, Irina, 2022. "Impacts of COVID-19 local spread and Google search trend on the US stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
- Michael Nofer & Oliver Hinz, 2015. "Using Twitter to Predict the Stock Market," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 57(4), pages 229-242, August.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Ali Asgarov, 2023. "Predicting Financial Market Trends using Time Series Analysis and Natural Language Processing," Papers 2309.00136, arXiv.org.
- Ullah, Rafid & Ismail, Hishamuddin Bin & Islam Khan, Mohammad Tariqul & Zeb, Ali, 2024. "Nexus between Chat GPT usage dimensions and investment decisions making in Pakistan: Moderating role of financial literacy," Technology in Society, Elsevier, vol. 76(C).
- Vecchi, Edoardo & Berra, Gabriele & Albrecht, Steffen & Gagliardini, Patrick & Horenko, Illia, 2023. "Entropic approximate learning for financial decision-making in the small data regime," Research in International Business and Finance, Elsevier, vol. 65(C).
- Abdollahi, Hooman & Fjesme, Sturla L. & Sirnes, Espen, 2024. "Measuring market volatility connectedness to media sentiment," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
- Riahi, Rabeb & Bennajma, Amel & Jahmane, Abderrahmane & Hammami, Helmi, 2024. "Investing in cryptocurrency before and during the COVID-19 crisis: Hedge, diversifier or safe haven?," Research in International Business and Finance, Elsevier, vol. 67(PB).
- Ahelegbey, Daniel Felix & Cerchiello, Paola & Scaramozzino, Roberta, 2022.
"Network based evidence of the financial impact of Covid-19 pandemic,"
International Review of Financial Analysis, Elsevier, vol. 81(C).
- Daniel Felix Ahelegbey & Paola Cerchiello & Roberta Scaramozzino, 2021. "Network Based Evidence of the Financial Impact of Covid-19 Pandemic," DEM Working Papers Series 198, University of Pavia, Department of Economics and Management.
- Cai, Yi & Tang, Zhenpeng & Chen, Ying, 2024. "Can real-time investor sentiment help predict the high-frequency stock returns? Evidence from a mixed-frequency-rolling decomposition forecasting method," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
- Marcus Vinicius Santos & Fernando Morgado-Dias & Thiago C. Silva, 2023. "Oil Sector and Sentiment Analysis—A Review," Energies, MDPI, vol. 16(12), pages 1-29, June.
- Wang, Lu & Guan, Li & Ding, Qian & Zhang, Hongwei, 2023. "Asymmetric impact of COVID-19 news on the connectedness of the green energy, dirty energy, and non-ferrous metal markets," Energy Economics, Elsevier, vol. 126(C).
- Thavavel Vaiyapuri & Sharath Kumar Jagannathan & Mohammed Altaf Ahmed & K. C. Ramya & Gyanendra Prasad Joshi & Soojeong Lee & Gangseong Lee, 2023. "Sustainable Artificial Intelligence-Based Twitter Sentiment Analysis on COVID-19 Pandemic," Sustainability, MDPI, vol. 15(8), pages 1-15, April.
- Szczygielski, Jan Jakub & Charteris, Ailie & Bwanya, Princess Rutendo & Brzeszczyński, Janusz, 2023. "Which COVID-19 information really impacts stock markets?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 84(C).
- Hong, Yun & Jiang, Yanhui & Su, Xiaojian & Deng, Chao, 2024. "Extreme state media reporting and the extreme stock market during COVID-19: A multi-quantile VaR Granger causality approach in China," Research in International Business and Finance, Elsevier, vol. 67(PA).
- Wasim ul Rehman & Omur Saltik & Faryal Jalil & Suleyman Degirmen, 2024. "Viral decisions: unmasking the impact of COVID-19 info and behavioral quirks on investment choices," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-20, December.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Szczygielski, Jan Jakub & Charteris, Ailie & Bwanya, Princess Rutendo & Brzeszczyński, Janusz, 2024. "Google search trends and stock markets: Sentiment, attention or uncertainty?," International Review of Financial Analysis, Elsevier, vol. 91(C).
- Dash, Saumya Ranjan & Maitra, Debasish, 2022. "The COVID-19 pandemic uncertainty, investor sentiment, and global equity markets: Evidence from the time-frequency co-movements," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
- Möller, Rouven & Reichmann, Doron, 2023. "COVID-19 related TV news and stock returns: Evidence from major US TV stations," The Quarterly Review of Economics and Finance, Elsevier, vol. 87(C), pages 95-109.
- Huynh, Toan Luu Duc & Foglia, Matteo & Nasir, Muhammad Ali & Angelini, Eliana, 2021. "Feverish sentiment and global equity markets during the COVID-19 pandemic," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 1088-1108.
- Kang, Yong Joo & Park, Dojoon & Eom, Young Ho, 2024. "Global contagion of US COVID-19 panic news," Emerging Markets Review, Elsevier, vol. 59(C).
- Szczygielski, Jan Jakub & Charteris, Ailie & Bwanya, Princess Rutendo & Brzeszczyński, Janusz, 2023. "Which COVID-19 information really impacts stock markets?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 84(C).
- Qing Liu & Hosung Son, 2024. "Data selection and collection for constructing investor sentiment from social media," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
- Hoang, Daniel & Wiegratz, Kevin, 2022. "Machine learning methods in finance: Recent applications and prospects," Working Paper Series in Economics 158, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
- Daniele Ballinari & Simon Behrendt, 2021. "How to gauge investor behavior? A comparison of online investor sentiment measures," Digital Finance, Springer, vol. 3(2), pages 169-204, June.
- Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Bonsu, Christiana Osei & Karikari, Nana Kwasi & Hammoudeh, Shawkat, 2022. "The effects of public sentiments and feelings on stock market behavior: Evidence from Australia," Journal of Economic Behavior & Organization, Elsevier, vol. 193(C), pages 443-472.
- Niculaescu, Corina E. & Sangiorgi, Ivan & Bell, Adrian R., 2023. "Does personal experience with COVID-19 impact investment decisions? Evidence from a survey of US retail investors," International Review of Financial Analysis, Elsevier, vol. 88(C).
- Sergio Consoli & Luca Tiozzo Pezzoli & Elisa Tosetti, 2022. "Neural forecasting of the Italian sovereign bond market with economic news," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(S2), pages 197-224, December.
- Akhtaruzzaman, Md & Boubaker, Sabri & Umar, Zaghum, 2022. "COVID–19 media coverage and ESG leader indices," Finance Research Letters, Elsevier, vol. 45(C).
- Szczygielski, Jan Jakub & Charteris, Ailie & Bwanya, Princess Rutendo & Brzeszczyński, Janusz, 2022. "The impact and role of COVID-19 uncertainty: A global industry analysis," International Review of Financial Analysis, Elsevier, vol. 80(C).
- Xie, Wen-Jie & Li, Mu-Yao & Zhou, Wei-Xing, 2021. "Learning representation of stock traders and immediate price impacts," Emerging Markets Review, Elsevier, vol. 48(C).
- Zhang, Xiaotao & Li, Guoran & Li, Yishuo & Zou, Gaofeng & Wu, Ji George, 2023. "Which is more important in stock market forecasting: Attention or sentiment?," International Review of Financial Analysis, Elsevier, vol. 89(C).
- Hanauer, Matthias X. & Kononova, Marina & Rapp, Marc Steffen, 2022. "Boosting agnostic fundamental analysis: Using machine learning to identify mispricing in European stock markets," Finance Research Letters, Elsevier, vol. 48(C).
- Andrew J. Patton & Yasin Simsek, 2023. "Generalized Autoregressive Score Trees and Forests," Papers 2305.18991, arXiv.org.
- Hasan, Md. Tanvir, 2022. "The sum of all SCARES COVID-19 sentiment and asset return," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 332-346.
- Mustafa, Andy Ali & Lin, Ching-Yang & Kakinaka, Makoto, 2022. "Detecting market pattern changes: A machine learning approach," Finance Research Letters, Elsevier, vol. 47(PA).
More about this item
Keywords
COVID-19 news; Sentiment analysis; Stock markets;All these keywords.
JEL classification:
- G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
- G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
- G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:riibaf:v:64:y:2023:i:c:s0275531923000077. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ribaf .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.