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Nikolaos Vlastakis

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Megaritis, Anastasios & Vlastakis, Nikolaos & Triantafyllou, Athanasios, 2020. "Stock market volatility and jumps in times of uncertainty," Essex Finance Centre Working Papers 29200, University of Essex, Essex Business School.

    Cited by:

    1. Gong, Xue & Zhang, Weiguo & Wang, Junbo & Wang, Chao, 2022. "Investor sentiment and stock volatility: New evidence," International Review of Financial Analysis, Elsevier, vol. 80(C).
    2. Peng-Fei Dai & Xiong Xiong & Zhifeng Liu & Toan Luu Duc Huynh & Jianjun Sun, 2021. "Preventing crash in stock market: The role of economic policy uncertainty during COVID-19," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-15, December.
    3. Li, Zhao-Chen & Xie, Chi & Zeng, Zhi-Jian & Wang, Gang-Jin & Zhang, Ting, 2023. "Forecasting global stock market volatilities in an uncertain world," International Review of Financial Analysis, Elsevier, vol. 85(C).
    4. Grobys, Klaus & Huynh, Toan Luu Duc, 2022. "When Tether says “JUMP!” Bitcoin asks “How low?”," Finance Research Letters, Elsevier, vol. 47(PA).
    5. Xue Gong & Weiguo Zhang & Weijun Xu & Zhe Li, 2022. "Uncertainty index and stock volatility prediction: evidence from international markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-44, December.
    6. Khalfaoui, Rabeh & Stef, Nicolae & Wissal, Ben Arfi & Sami, Ben Jabeur, 2022. "Dynamic spillover effects and connectedness among climate change, technological innovation, and uncertainty: Evidence from a quantile VAR network and wavelet coherence," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    7. Hitz, Lukas & Mustafi, Ismail H. & Zimmermann, Heinz, 2022. "The pricing of volatility risk in the US equity market," International Review of Financial Analysis, Elsevier, vol. 79(C).

Articles

  1. Megaritis, Anastasios & Vlastakis, Nikolaos & Triantafyllou, Athanasios, 2021. "Stock market volatility and jumps in times of uncertainty," Journal of International Money and Finance, Elsevier, vol. 113(C).
    See citations under working paper version above.
  2. Chronopoulos, Dimitris K. & Papadimitriou, Fotios I. & Vlastakis, Nikolaos, 2018. "Information demand and stock return predictability," Journal of International Money and Finance, Elsevier, vol. 80(C), pages 59-74.

    Cited by:

    1. Aharon, David Y. & Qadan, Mahmoud, 2020. "When do retail investors pay attention to their trading platforms?," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    2. Ramos, Sofia B. & Latoeiro, Pedro & Veiga, Helena, 2020. "Limited attention, salience of information and stock market activity," Economic Modelling, Elsevier, vol. 87(C), pages 92-108.
    3. Chundakkadan, Radeef & Nedumparambil, Elizabeth, 2022. "In search of COVID-19 and stock market behavior," Global Finance Journal, Elsevier, vol. 54(C).
    4. Xin-Lan Fu & Xing-Lu Gao & Zheng Shan & Zhi-Qiang Jiang & Wei-Xing Zhou, 2018. "Multifractal characteristics and return predictability in the Chinese stock markets," Papers 1806.07604, arXiv.org.
    5. Gianna Figà-Talamanca & Marco Patacca, 2020. "Disentangling the relationship between Bitcoin and market attention measures," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 47(1), pages 71-91, March.
    6. Chundakkadan, Radeef & Sasidharan, Subash, 2019. "Liquidity pull-back and predictability of government security yield volatility," Economic Modelling, Elsevier, vol. 77(C), pages 124-132.
    7. F. Henrique Castro & Marcelo Guzella, 2021. "Individual investor attention and the predictability of stock market volatility and returns," Economics Bulletin, AccessEcon, vol. 41(3), pages 1418-1424.
    8. Shailesh Rana & William H. Bommer & G. Michael Phillips, 2020. "Predicting Returns for Growth and Value Stocks: A Forecast Assessment Approach Using Global Asset Pricing Models," International Journal of Economics and Financial Issues, Econjournals, vol. 10(4), pages 88-106.
    9. Afees A. Salisu & Ahamuefula E. Ogbonna & Tirimisiyu F. Oloko & Idris A. Adediran, 2021. "A New Index for Measuring Uncertainty Due to the COVID-19 Pandemic," Sustainability, MDPI, vol. 13(6), pages 1-18, March.
    10. Lyócsa, Štefan & Plíhal, Tomáš, 2022. "Russia’s ruble during the onset of the Russian invasion of Ukraine in early 2022: The role of implied volatility and attention," Finance Research Letters, Elsevier, vol. 48(C).
    11. Nikkinen, Jussi & Rothovius, Timo, 2019. "The EIA WPSR release, OVX and crude oil internet interest," Energy, Elsevier, vol. 166(C), pages 131-141.
    12. Radeef Chundakkadan & Subash Sasidharan, 2021. "Central bank's money market operations and daily stock returns," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 136-152, January.
    13. Jaydip Sen & Sidra Mehtab & Abhishek Dutta, 2021. "Volatility Modeling of Stocks from Selected Sectors of the Indian Economy Using GARCH," Papers 2105.13898, arXiv.org.
    14. Geng, Yuedan & Ye, Qiang & Jin, Yu & Shi, Wen, 2022. "Crowd wisdom and internet searches: What happens when investors search for stocks?," International Review of Financial Analysis, Elsevier, vol. 82(C).
    15. Gang Chu & Xiao Li & Dehua Shen & Yongjie Zhang, 2021. "Stock Crashes and Jumps Reactions to Information Demand and Supply: An Intraday Analysis," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(3), pages 397-427, September.
    16. Bleher, Johannes & Dimpfl, Thomas, 2022. "Knitting Multi-Annual High-Frequency Google Trends to Predict Inflation and Consumption," Econometrics and Statistics, Elsevier, vol. 24(C), pages 1-26.
    17. Awijen, Haithem & Ben Zaied, Younes & Ben Lahouel, Béchir & Khlifi, Foued, 2023. "Machine learning for US cross-industry return predictability under information uncertainty," Research in International Business and Finance, Elsevier, vol. 64(C).
    18. Basistha, Arabinda & Kurov, Alexander & Wolfe, Marketa Halova, 2019. "Volatility Forecasting: The Role of Internet Search Activity and Implied Volatility," MPRA Paper 111037, University Library of Munich, Germany.
    19. Katsiampa, Paraskevi & Moutsianas, Konstantinos & Urquhart, Andrew, 2019. "Information demand and cryptocurrency market activity," Economics Letters, Elsevier, vol. 185(C).
    20. Sherif, Mohamed, 2020. "The impact of Coronavirus (COVID-19) outbreak on faith-based investments: An original analysis," Journal of Behavioral and Experimental Finance, Elsevier, vol. 28(C).
    21. Chen, Zhongdong & Schmidt, Adam & Wang, Jin’ai, 2021. "Retail investor risk-seeking, attention, and the January effect," Journal of Behavioral and Experimental Finance, Elsevier, vol. 30(C).
    22. Qu, Hui & Li, Guo, 2023. "Multi-perspective investor attention and oil futures volatility forecasting," Energy Economics, Elsevier, vol. 119(C).
    23. v{S}tefan Ly'ocsa & Tom'av{s} Pl'ihal, 2022. "Russia's Ruble during the onset of the Russian invasion of Ukraine in early 2022: The role of implied volatility and attention," Papers 2205.09179, arXiv.org.
    24. Behrendt, Simon & Prange, Philipp, 2021. "What are you searching for? On the equivalence of proxies for online investor attention," Finance Research Letters, Elsevier, vol. 38(C).
    25. Arnold, Ivo J.M., 2020. "Internet search volumes of UK banks during the crisis: The role of banking structure and business model," Global Finance Journal, Elsevier, vol. 45(C).
    26. Papadamou, Stephanos & Fassas, Athanasios & Kenourgios, Dimitris & Dimitriou, Dimitrios, 2020. "Direct and Indirect Effects of COVID-19 Pandemic on Implied Stock Market Volatility: Evidence from Panel Data Analysis," MPRA Paper 100020, University Library of Munich, Germany.

  3. George Dotsis & Nikolaos Vlastakis, 2016. "Corridor Volatility Risk and Expected Returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(5), pages 488-505, May.

    Cited by:

    1. Dudley Gilder & Leonidas Tsiaras, 2020. "Volatility forecasts embedded in the prices of crude‐oil options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(7), pages 1127-1159, July.
    2. Xingzhi Yao & Marwan Izzeldin, 2018. "Forecasting using alternative measures of model‐free option‐implied volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(2), pages 199-218, February.
    3. Chen, Yu-Lun & Tsai, Wei-Che, 2017. "Determinants of price discovery in the VIX futures market," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 59-73.
    4. Jiangze Du & Shaojie Lai & Kin Keung Lai & Shifei Zhou, 2021. "A novel term structure stochastic model with adaptive correlation for trend analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5485-5498, October.
    5. Shan Lu, 2019. "Testing the Predictive Ability of Corridor Implied Volatility Under GARCH Models," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 26(2), pages 129-168, June.

  4. Vlastakis, Nikolaos & Markellos, Raphael N., 2012. "Information demand and stock market volatility," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1808-1821.

    Cited by:

    1. Falik Shear & Badar Nadeem Ashraf & Mohsin Sadaqat, 2020. "Are Investors’ Attention and Uncertainty Aversion the Risk Factors for Stock Markets? International Evidence from the COVID-19 Crisis," Risks, MDPI, vol. 9(1), pages 1-15, December.
    2. Artem Meshcheryakov & Stoyu I Ivanov, 2017. "Investor's sentiment in predicting the Effective Federal Funds Rate," Economics Bulletin, AccessEcon, vol. 37(4), pages 2767-2796.
    3. Marmora, Paul, 2022. "Does monetary policy fuel bitcoin demand? Event-study evidence from emerging markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    4. Aharon, David Y. & Qadan, Mahmoud, 2020. "When do retail investors pay attention to their trading platforms?," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    5. Tihana Škrinjarić, 2019. "Time Varying Spillovers between the Online Search Volume and Stock Returns: Case of CESEE Markets," IJFS, MDPI, vol. 7(4), pages 1-30, October.
    6. Francesco Capozza & Ingar Haaland & Christopher Roth & Johannes Wohlfart, 2021. "Studying Information Acquisition in the Field: A Practical Guide and Review," ECONtribute Discussion Papers Series 124, University of Bonn and University of Cologne, Germany.
    7. Chen Gu & Ann Marie Hibbert, 2021. "Expectations and financial markets: Lessons from Brexit," The Financial Review, Eastern Finance Association, vol. 56(2), pages 279-299, May.
    8. Ramos, Sofia B. & Latoeiro, Pedro & Veiga, Helena, 2020. "Limited attention, salience of information and stock market activity," Economic Modelling, Elsevier, vol. 87(C), pages 92-108.
    9. Lansing, Kevin J. & LeRoy, Stephen F. & Ma, Jun, 2022. "Examining the sources of excess return predictability: Stochastic volatility or market inefficiency?," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 50-72.
    10. Dai, Zhifeng & Chang, Xiaoming, 2021. "Forecasting stock market volatility: Can the risk aversion measure exert an important role?," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    11. Amal Aouadi & Mohamed Arouri & David Roubaud, 2018. "Information demand and stock market liquidity: International evidence," Post-Print hal-02011044, HAL.
    12. Theologos Dergiades & Costas Milas & Theodore Panagiotidis, 2013. "Tweets, Google Trends and Sovereign Spreads in the GIIPS," GreeSE – Hellenic Observatory Papers on Greece and Southeast Europe 78, Hellenic Observatory, LSE.
    13. Smales, L.A., 2021. "Investor attention and global market returns during the COVID-19 crisis," International Review of Financial Analysis, Elsevier, vol. 73(C).
    14. Chundakkadan, Radeef & Nedumparambil, Elizabeth, 2022. "In search of COVID-19 and stock market behavior," Global Finance Journal, Elsevier, vol. 54(C).
    15. Rho Caterina & Fernández Raúl & Palma Brenda, 2021. "A Sentiment-based Risk Indicator for the Mexican Financial Sector," Working Papers 2021-04, Banco de México.
    16. Melissa S. Kearney & Phillip B. Levine, 2015. "Media Influences on Social Outcomes: The Impact of MTV's 16 and Pregnant on Teen Childbearing," American Economic Review, American Economic Association, vol. 105(12), pages 3597-3632, December.
    17. Chen, Shuning & Zhang, Wei & Feng, Xu & Xiong, Xiong, 2020. "Asymmetry of retail investors’ attention and asymmetric volatility: Evidence from China," Finance Research Letters, Elsevier, vol. 36(C).
    18. Symitsi, Efthymia & Markellos, Raphael N. & Mantrala, Murali K., 2022. "Keyword portfolio optimization in paid search advertising," European Journal of Operational Research, Elsevier, vol. 303(2), pages 767-778.
    19. Martina Halouskov'a & Daniel Stav{s}ek & Mat'uv{s} Horv'ath, 2022. "The role of investor attention in global asset price variation during the invasion of Ukraine," Papers 2205.05985, arXiv.org, revised Aug 2022.
    20. Ballinari, Daniele & Audrino, Francesco & Sigrist, Fabio, 2022. "When does attention matter? The effect of investor attention on stock market volatility around news releases," International Review of Financial Analysis, Elsevier, vol. 82(C).
    21. Agarwal, Shweta & Kumar, Shailendra & Goel, Utkarsh, 2019. "Stock market response to information diffusion through internet sources: A literature review," International Journal of Information Management, Elsevier, vol. 45(C), pages 118-131.
    22. Huang, Jianbai & Tang, Jing & Zhang, Hongwei, 2020. "The effect of investors’ information search behaviors on rebar market return dynamics using high frequency data," Resources Policy, Elsevier, vol. 66(C).
    23. Desagre, Christophe & D’Hondt, Catherine, 2021. "Googlization and retail trading activity," Journal of Behavioral and Experimental Finance, Elsevier, vol. 29(C).
    24. D Aromi & A Clements, 2018. "Media attention and crude oil volatility: Is there any 'new' news in the newspaper?," NCER Working Paper Series 118, National Centre for Econometric Research.
    25. Salisu, Afees A. & Vo, Xuan Vinh, 2021. "Firm-specific news and the predictability of Consumer stocks in Vietnam," Finance Research Letters, Elsevier, vol. 41(C).
    26. Anh Dang & Trung Nguyen, 2021. "Valuation Effect of Emotionality in Corporate Philanthropy," Journal of Business Ethics, Springer, vol. 173(1), pages 47-67, September.
    27. K. Lebedeva, 2015. "An Empirical Analysis of the Russian Financial Markets’ Liquidity and Returns," Review of Business and Economics Studies // Review of Business and Economics Studies, Финансовый Университет // Financial University, vol. 3(3), pages 5-31.
    28. Astaiza-Gómez, José Gabriel, 2021. "Investors' Information Choice," MPRA Paper 110008, University Library of Munich, Germany.
    29. Konstantinos N. Konstantakis & Despoina Paraskeuopoulou & Panayotis G. Michaelides & Efthymios G. Tsionas, 2021. "Bank deposits and Google searches in a crisis economy: Bayesian non‐linear evidence for Greece (2009–2015)," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5408-5424, October.
    30. Prashant Das & Alan Ziobrowski & N. Coulson, 2015. "Online Information Search, Market Fundamentals and Apartment Real Estate," The Journal of Real Estate Finance and Economics, Springer, vol. 51(4), pages 480-502, November.
    31. Semen Son-Turan, 2016. "The Impact of Investor Sentiment on the "Leverage Effect"," International Econometric Review (IER), Econometric Research Association, vol. 8(1), pages 4-18, April.
    32. Jain, Anshul & Biswal, Pratap Chandra, 2019. "Does internet search interest for gold move the gold spot, stock and exchange rate markets? A study from India," Resources Policy, Elsevier, vol. 61(C), pages 501-507.
    33. Toni Ahnert & Christoph Bertsch, 2015. "A Wake-Up-Call Theory of Contagion," Staff Working Papers 15-14, Bank of Canada.
    34. Kojima, Fuhito & Pathak, Parag & Roth, Alvin E., 2013. "Matching with Couples: Stability and Incentives in Large Markets," Scholarly Articles 30831454, Harvard University Department of Economics.
    35. Peltomäki, Jarkko & Vähämaa, Emilia, 2015. "Investor attention to the Eurozone crisis and herding effects in national bank stock indexes," Finance Research Letters, Elsevier, vol. 14(C), pages 111-116.
    36. Halousková, Martina & Stašek, Daniel & Horváth, Matúš, 2022. "The role of investor attention in global asset price variation during the invasion of Ukraine," Finance Research Letters, Elsevier, vol. 50(C).
    37. Nikoletta Poutachidou & Stephanos Papadamou, 2021. "The Effect of Quantitative Easing through Google Metrics on US Stock Indices," IJFS, MDPI, vol. 9(4), pages 1-19, October.
    38. Huang, Tzu-Lun, 2018. "The puzzling media effect in the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 49(C), pages 129-146.
    39. Gang Chu & John W. Goodell & Dehua Shen & Yongjie Zhang, 2022. "Machine learning to establish proxies for investor attention: evidence of improved stock-return prediction," Annals of Operations Research, Springer, vol. 318(1), pages 103-128, November.
    40. Thomas Dimpfl & Stephan Jank, 2016. "Can Internet Search Queries Help to Predict Stock Market Volatility?," European Financial Management, European Financial Management Association, vol. 22(2), pages 171-192, March.
    41. Hervé, Fabrice & Zouaoui, Mohamed & Belvaux, Bertrand, 2019. "Noise traders and smart money: Evidence from online searches," Economic Modelling, Elsevier, vol. 83(C), pages 141-149.
    42. Chu, Gang & Dowling, Michael & Shen, Dehua & Zhang, Yongjie, 2023. "Information demand density matters: Evidence from the post-earnings announcement drift," International Review of Financial Analysis, Elsevier, vol. 86(C).
    43. Amal Aouadi & Mohamed Arouri & Frédéric Teulon, 2014. "Investor Following and Volatility: A GARCH Approach," Working Papers 2014-286, Department of Research, Ipag Business School.
    44. Smales, L.A., 2022. "Investor attention in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 79(C).
    45. Böhme, Marcus H. & Gröger, André & Stöhr, Tobias, 2020. "Searching for a better life: Predicting international migration with online search keywords," Journal of Development Economics, Elsevier, vol. 142(C).
    46. Omer N. Gokalp & Sami Keskek & Abdullah Kumas & Marshall A. Geiger, 2020. "Insider trading around auto recalls: Does investor attention matter?," Review of Quantitative Finance and Accounting, Springer, vol. 55(3), pages 1003-1033, October.
    47. Jung, Alexander & Kühl, Patrick, 2021. "Can central bank communication help to stabilise inflation expectations?," Working Paper Series 2547, European Central Bank.
    48. Gabriele Ranco & Ilaria Bordino & Giacomo Bormetti & Guido Caldarelli & Fabrizio Lillo & Michele Treccani, 2014. "Coupling news sentiment with web browsing data improves prediction of intra-day price dynamics," Papers 1412.3948, arXiv.org, revised Dec 2015.
    49. Gabriele Ranco & Ilaria Bordino & Giacomo Bormetti & Guido Caldarelli & Fabrizio Lillo & Michele Treccani, 2016. "Coupling News Sentiment with Web Browsing Data Improves Prediction of Intra-Day Price Dynamics," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-14, January.
    50. Ana Brochado, 2016. "Investor attention and Portuguese stock market volatility: We’ll google it for you!," EcoMod2016 9345, EcoMod.
    51. Afkhami, Mohamad & Cormack, Lindsey & Ghoddusi, Hamed, 2017. "Google search keywords that best predict energy price volatility," Energy Economics, Elsevier, vol. 67(C), pages 17-27.
    52. Li, Shouwei & Zhuang, Yangyang & He, Jianmin, 2016. "Stock market stability: Diffusion entropy analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 462-465.
    53. Chundakkadan, Radeef & Sasidharan, Subash, 2019. "Liquidity pull-back and predictability of government security yield volatility," Economic Modelling, Elsevier, vol. 77(C), pages 124-132.
    54. Xiao, Jihong & Wang, Yudong, 2021. "Investor attention and oil market volatility: Does economic policy uncertainty matter?," Energy Economics, Elsevier, vol. 97(C).
    55. Anenberg, Elliot & Kung, Edward, 2015. "Information technology and product variety in the city: The case of food trucks," Journal of Urban Economics, Elsevier, vol. 90(C), pages 60-78.
    56. Al Guindy, Mohamed, 2021. "Cryptocurrency price volatility and investor attention," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 556-570.
    57. Georgios Bampinas & Theodore Panagiotidis & Christina Rouska, 2018. "Volatility persistence and asymmetry under the microscope: The role of information demand for gold and oil," Working Paper series 18-13, Rimini Centre for Economic Analysis.
    58. Perroni, Carlo & Scharf, Kimberley & Talavera, Oleksandr & Vi, Linh, 2022. "Does online salience predict charitable giving? Evidence from SMS text donations," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 134-149.
    59. Owain Ap Gwilym & Iftekhar Hasan & Qingwei Wang & Ru Xie, 2016. "In Search of Concepts: The Effects of Speculative Demand on Stock Returns," European Financial Management, European Financial Management Association, vol. 22(3), pages 427-449, June.
    60. Mohamed Arouri & Amal Aouadi & Philippe Foulquier & Frédéric Teulon, 2013. "Can Information Demand Help to Predict Stock Market Liquidity ? Google it !," Working Papers 2013-24, Department of Research, Ipag Business School.
    61. Hamid, Alain & Heiden, Moritz, 2015. "Forecasting volatility with empirical similarity and Google Trends," Journal of Economic Behavior & Organization, Elsevier, vol. 117(C), pages 62-81.
    62. Grace Weishi Gu & Zachary R. Stangebye, 2023. "Costly Information And Sovereign Risk," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(4), pages 1397-1429, November.
    63. In Huh & Ju Hyun Pyun, 2018. "Does Nuclear Uncertainty Threaten Financial Markets? The Attention Paid to North Korean Nuclear Threats and Its Impact on South Korea's Financial Markets," Asian Economic Journal, East Asian Economic Association, vol. 32(1), pages 55-82, March.
    64. Chang, Young Bong & Kwon, YoungOk, 2018. "Ambiguities in valuing information technology firms: Do internet searches help?," Journal of Business Research, Elsevier, vol. 92(C), pages 260-269.
    65. Karanasos, M. & Yfanti, S., 2021. "On the Economic fundamentals behind the Dynamic Equicorrelations among Asset classes: Global evidence from Equities, Real estate, and Commodities," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    66. Chen, Hong-Yi & Chen, Hsuan-Chi & Lai, Christine W., 2021. "Internet search, fund flows, and fund performance," Journal of Banking & Finance, Elsevier, vol. 129(C).
    67. Sun, Hang, 2016. "Crisis-Contingent Dynamics of Connectedness: An SVAR-Spatial-Network “Tripod” Model with Thresholds," Research Memorandum 032, Maastricht University, Graduate School of Business and Economics (GSBE).
    68. Christophe Desagre & Catherine D'Hondt, 2020. "Googlization and retail investors' trading activity," LIDAM Discussion Papers LFIN 2020004, Université catholique de Louvain, Louvain Finance (LFIN).
    69. Matthias Bank & Martin Larch & Georg Peter, 2011. "Google search volume and its influence on liquidity and returns of German stocks," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 25(3), pages 239-264, September.
    70. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2023. "Discovering the drivers of stock market volatility in a data-rich world," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    71. Vighneswara Swamy & M. Dharani, 2020. "RETRACTED ARTICLE: Google Search Intensity and the Investor Attention Effect: A Quantile Regression Approach," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(2), pages 403-423, June.
    72. Alexander F. McQuoid & Charles Moore & Stephen Sawyer & David C. Vitt, 2017. "Trigger Warning: The Causal Impact of Gun Ownership on Suicide," Departmental Working Papers 55, United States Naval Academy Department of Economics.
    73. Bonaparte, Yosef & Bernile, Gennaro, 2023. "A new “Wall Street Darling?” effects of regulation sentiment in cryptocurrency markets," Finance Research Letters, Elsevier, vol. 52(C).
    74. Massimo Guidolin & Alexei G. Orlov & Manuela Pedio, 2018. "How good can heuristic-based forecasts be? A comparative performance of econometric and heuristic models for UK and US asset returns," Quantitative Finance, Taylor & Francis Journals, vol. 18(1), pages 139-169, January.
    75. Wei, He & Guo, Yaoqi & Yu, Zhuling & Cheng, Hui, 2021. "The impact of events on metal futures based on the perspective of Google Trends," Resources Policy, Elsevier, vol. 74(C).
    76. Massimo Guidolin & Manuela Pedio, 2020. "Media Attention vs. Sentiment as Drivers of Conditional Volatility Predictions: An Application to Brexit," BAFFI CAREFIN Working Papers 20145, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    77. Massimiliano Caporin & Francesco Poli, 2017. "Building News Measures from Textual Data and an Application to Volatility Forecasting," Econometrics, MDPI, vol. 5(3), pages 1-46, August.
    78. Li, Xin & Ma, Jian & Wang, Shouyang & Zhang, Xun, 2015. "How does Google search affect trader positions and crude oil prices?," Economic Modelling, Elsevier, vol. 49(C), pages 162-171.
    79. Latoeiro, Pedro & Ramos, Sofía B. & Veiga, Helena, 2013. "Predictability of stock market activity using Google search queries," DES - Working Papers. Statistics and Econometrics. WS ws130605, Universidad Carlos III de Madrid. Departamento de Estadística.
    80. Sifat, Imtiaz Mohammad & Thaker, Hassanudin Mohd Thas, 2020. "Predictive power of web search behavior in five ASEAN stock markets," Research in International Business and Finance, Elsevier, vol. 52(C).
    81. Takayuki Morimoto & Yoshinori Kawasaki, 2017. "Forecasting Financial Market Volatility Using a Dynamic Topic Model," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 24(3), pages 149-167, September.
    82. Smith, Geoffrey Peter, 2012. "Google Internet search activity and volatility prediction in the market for foreign currency," Finance Research Letters, Elsevier, vol. 9(2), pages 103-110.
    83. Klomp, Jeroen, 2020. "The impact of Russian sanctions on the return of agricultural commodity futures in the EU," Research in International Business and Finance, Elsevier, vol. 51(C).
    84. Peri, Massimo & Vandone, Daniela & Baldi, Lucia, 2014. "Internet, noise trading and commodity futures prices," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 82-89.
    85. El Ouadghiri, Imane & Guesmi, Khaled & Peillex, Jonathan & Ziegler, Andreas, 2021. "Public Attention to Environmental Issues and Stock Market Returns," Ecological Economics, Elsevier, vol. 180(C).
    86. Livio Fenga, 2020. "Filtering and prediction of noisy and unstable signals: The case of Google Trends data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 281-295, March.
    87. Tamgac, Unay, 2021. "Emerging market exchange rates during quantitative tapering: The effect of US and domestic news," Research in International Business and Finance, Elsevier, vol. 57(C).
    88. Peri, Massimo & Vandone, Daniela & Baldi, Lucia, 2012. "Information Demand and Agriculture Commodity Prices," 2012 International European Forum, February 13-17, 2012, Innsbruck-Igls, Austria 144973, International European Forum on System Dynamics and Innovation in Food Networks.
    89. Semen Son Turan, 2014. "Internet Search Volume and Stock Return Volatility: The Case of Turkish Companies," Information Management and Business Review, AMH International, vol. 6(6), pages 317-328.
    90. Nikkinen, Jussi & Rothovius, Timo, 2019. "The EIA WPSR release, OVX and crude oil internet interest," Energy, Elsevier, vol. 166(C), pages 131-141.
    91. Perroni, Carlo & Scharf, Kimberley & Talavera, Oleksandr & Vi, Linh, 2021. "Online Salience and Charitable Giving : Evidence from SMS Donations," The Warwick Economics Research Paper Series (TWERPS) 1325, University of Warwick, Department of Economics.
    92. Takeda, Fumiko & Wakao, Takumi, 2014. "Google search intensity and its relationship with returns and trading volume of Japanese stocks," Pacific-Basin Finance Journal, Elsevier, vol. 27(C), pages 1-18.
    93. He, Wenjian & Chen, Xiaoyang & Liu, Zhiyong John, 2022. "Can anti-corruption help realize the “strong” Porter Hypothesis in China? Evidence from Chinese manufacturing enterprises," Journal of Asian Economics, Elsevier, vol. 80(C).
    94. Matheus Pereira Libório & Petr Iakovlevitch Ekel & Carlos Augusto Paiva Martins, 2023. "Economic analysis through alternative data and big data techniques: what do they tell about Brazil?," SN Business & Economics, Springer, vol. 3(1), pages 1-16, January.
    95. Joon Chae & Ryumi Kim & Jaehee Han, 2020. "Investor Attention from Internet Search Volume and Underreaction to Earnings Announcements in Korea," Sustainability, MDPI, vol. 12(22), pages 1-29, November.
    96. Rashid AMIN & Habib AHMAD, 2013. "Does Investor Attention Matter�S?," Journal of Public Administration, Finance and Law, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 4(4), pages 111-125, December.
    97. Bouoiyour, Jamal & Selmi, Refk & Tiwari, Aviral, 2014. "Is Bitcoin business income or speculative bubble? Unconditional vs. conditional frequency domain analysis," MPRA Paper 59595, University Library of Munich, Germany.
    98. Geng, Yuedan & Ye, Qiang & Jin, Yu & Shi, Wen, 2022. "Crowd wisdom and internet searches: What happens when investors search for stocks?," International Review of Financial Analysis, Elsevier, vol. 82(C).
    99. Adachi, Yuta & Masuda, Motoki & Takeda, Fumiko, 2017. "Google search intensity and its relationship to the returns and liquidity of Japanese startup stocks," Pacific-Basin Finance Journal, Elsevier, vol. 46(PB), pages 243-257.
    100. T. Bazhenov & D. Fantazzini, 2019. "Forecasting Realized Volatility of Russian stocks using Google Trends and Implied Volatility," Russian Journal of Industrial Economics, MISIS, vol. 12(1).
    101. Vicente, María Rosalía & López-Menéndez, Ana J. & Pérez, Rigoberto, 2015. "Forecasting unemployment with internet search data: Does it help to improve predictions when job destruction is skyrocketing?," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 132-139.
    102. Piñeiro-Chousa, Juan & Šević, Aleksandar & González-López, Isaac, 2023. "Impact of social metrics in decentralized finance," Journal of Business Research, Elsevier, vol. 158(C).
    103. Lyócsa, Štefan & Halousková, Martina & Haugom, Erik, 2023. "The US banking crisis in 2023: Intraday attention and price variation of banks at risk," Finance Research Letters, Elsevier, vol. 57(C).
    104. Gang Chu & Xiao Li & Dehua Shen & Yongjie Zhang, 2021. "Stock Crashes and Jumps Reactions to Information Demand and Supply: An Intraday Analysis," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(3), pages 397-427, September.
    105. Ladislav Kristoufek, 2015. "Power-law correlations in finance-related Google searches, and their cross-correlations with volatility and traded volume: Evidence from the Dow Jones Industrial components," Papers 1502.00225, arXiv.org.
    106. Ming‐Hung Wu & Wei‐Che Tsai & Pei‐Shih Weng & Dan‐Yi Li, 2021. "Effects of investor attention in China's commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(8), pages 1315-1332, August.
    107. Bampinas, Georgios & Panagiotidis, Theodore & Papapanagiotou, Georgios, 2023. "Oil shocks and investor attention," The Quarterly Review of Economics and Finance, Elsevier, vol. 87(C), pages 68-81.
    108. González-Fernández, Marcos & González-Velasco, Carmen, 2018. "Can Google econometrics predict unemployment? Evidence from Spain," Economics Letters, Elsevier, vol. 170(C), pages 42-45.
    109. Hao, Jing & Xiong, Xiong, 2021. "Retail investor attention and firms' idiosyncratic risk: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 74(C).
    110. Jaroslav Bukovina, 2016. "Social Media and Capital Markets – an Overview," MENDELU Working Papers in Business and Economics 2016-57, Mendel University in Brno, Faculty of Business and Economics.
    111. Fantazzini, Dean & Shangina, Tamara, 2019. "The importance of being informed: forecasting market risk measures for the Russian RTS index future using online data and implied volatility over two decades," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 55, pages 5-31.
    112. Ding Ding & Chong Guan & Calvin M. L. Chan & Wenting Liu, 2020. "Building stock market resilience through digital transformation: using Google trends to analyze the impact of COVID-19 pandemic," Frontiers of Business Research in China, Springer, vol. 14(1), pages 1-21, December.
    113. Nguyen, Cuong & Hoang, Lai & Shim, Jungwook & Truong, Phuong, 2020. "Internet search intensity, liquidity and returns in emerging markets," Research in International Business and Finance, Elsevier, vol. 52(C).
    114. Jang, Hyeonung & Seo, Byoung Ki, 2020. "Monetary policy rate expectation and energy prices during the FOMC announcement period," Finance Research Letters, Elsevier, vol. 32(C).
    115. Koch, Sophia & Dimpfl, Thomas, 2023. "Attention and retail investor herding in cryptocurrency markets," Finance Research Letters, Elsevier, vol. 51(C).
    116. Basistha, Arabinda & Kurov, Alexander & Wolfe, Marketa Halova, 2019. "Volatility Forecasting: The Role of Internet Search Activity and Implied Volatility," MPRA Paper 111037, University Library of Munich, Germany.
    117. Pavel Ciaian & d'Artis Kancs & Miroslava Rajcaniova, 2018. "The Price of BitCoin: GARCH Evidence from High Frequency Data," EERI Research Paper Series EERI RP 2018/14, Economics and Econometrics Research Institute (EERI), Brussels.
    118. Papadamou, Stephanos & Fassas, Athanasios P. & Kenourgios, Dimitris & Dimitriou, Dimitrios, 2021. "Flight-to-quality between global stock and bond markets in the COVID era," Finance Research Letters, Elsevier, vol. 38(C).
    119. Mario Maggi & Pierpaolo Uberti, 2021. "Google search volumes for portfolio management: performances and asset concentration," Annals of Operations Research, Springer, vol. 299(1), pages 163-175, April.
    120. Schmidt, Torsten & Vosen, Simeon, 2012. "Using Internet Data to Account for Special Events in Economic Forecasting," Ruhr Economic Papers 382, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    121. Moussa, Faten & BenOuda, Olfa & Delhoumi, Ezzeddine, 2017. "The use of open source internet to analysis and predict stock market trading volume," Research in International Business and Finance, Elsevier, vol. 41(C), pages 399-411.
    122. Imene Ben El Hadj Said & Skander Slim, 2022. "The Dynamic Relationship between Investor Attention and Stock Market Volatility: International Evidence," JRFM, MDPI, vol. 15(2), pages 1-25, February.
    123. Yu-Fen Chen & Cheng-Few Lee & Fu-Lai Lin, 2023. "The influences of information demand and supply on stock price synchronicity," Review of Quantitative Finance and Accounting, Springer, vol. 61(3), pages 1151-1176, October.
    124. Baur, Dirk G. & Dimpfl, Thomas, 2016. "Googling gold and mining bad news," Resources Policy, Elsevier, vol. 50(C), pages 306-311.
    125. Kao, Lanfeng & Chen, Anlin & Lu, Cheng-Shou, 2022. "Retail investor attention and IPO prices with a pre-IPO market," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 416-432.
    126. Eli Arditi & Eldad Yechiam & Gal Zahavi, 2015. "Association between Stock Market Gains and Losses and Google Searches," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-12, October.
    127. Hasler, Michael & Ornthanalai, Chayawat, 2018. "Fluctuating attention and financial contagion," Journal of Monetary Economics, Elsevier, vol. 99(C), pages 106-123.
    128. Michael Graham & Jussi Nikkinen & Jarkko Peltomäki, 2020. "Web-Based Investor Fear Gauge and Stock Market Volatility: An Emerging Market Perspective," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 19(2), pages 127-153, August.
    129. Erik J. Mayer, 2021. "Advertising, investor attention, and stock prices: Evidence from a natural experiment," Financial Management, Financial Management Association International, vol. 50(1), pages 281-314, March.
    130. Emre Cevik & Buket Kirci Altinkeski & Emrah Ismail Cevik & Sel Dibooglu, 2022. "Investor sentiments and stock markets during the COVID-19 pandemic," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-34, December.
    131. Coble, David & Pincheira, Pablo, 2017. "Nowcasting Building Permits with Google Trends," MPRA Paper 76514, University Library of Munich, Germany.
    132. Chouliaras, Andreas & Grammatikos, Theoharry, 2013. "News Flow, Web Attention and Extreme Returns in the European Financial Crisis," MPRA Paper 51335, University Library of Munich, Germany.
    133. Prakash Ranjan, Ravi & Bhattachharyya, Malay, 2018. "Does investor attention to energy stocks exhibit power law?," Energy Economics, Elsevier, vol. 75(C), pages 573-582.
    134. Aharon, David Y. & Qadan, Mahmoud, 2018. "What drives the demand for information in the commodity market?," Resources Policy, Elsevier, vol. 59(C), pages 532-543.
    135. Massimo PERI & Daniela VANDONE & Lucia BALDI, 2012. "Internet, noise trading and commodity prices," Departmental Working Papers 2012-07, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    136. Liu, Fengqi & Kang, Yuxin & Guo, Kun & Sun, Xiaolei, 2021. "The relationship between air pollution, investor attention and stock prices: Evidence from new energy and polluting sectors," Energy Policy, Elsevier, vol. 156(C).
    137. Ozkan Haykir & Ibrahim Yagli, 2022. "Speculative bubbles and herding in cryptocurrencies," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-33, December.
    138. Ding, Rong & Hou, Wenxuan, 2015. "Retail investor attention and stock liquidity," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 37(C), pages 12-26.
    139. Burcu Kapar & Jose Olmo, 2021. "Analysis of Bitcoin prices using market and sentiment variables," The World Economy, Wiley Blackwell, vol. 44(1), pages 45-63, January.
    140. Thomas Dimpfl & Vladislav Kleiman, 2019. "Investor Pessimism and the German Stock Market: Exploring Google Search Queries," German Economic Review, Verein für Socialpolitik, vol. 20(1), pages 1-28, February.
    141. Bucher, Melk C., 2017. "Investor Attention and Sentiment: Risk or Anomaly?," Working Papers on Finance 1712, University of St. Gallen, School of Finance.
    142. Szczygielski, Jan Jakub & Charteris, Ailie & Obojska, Lidia, 2023. "Do commodity markets catch a cold from stock markets? Modelling uncertainty spillovers using Google search trends and wavelet coherence," International Review of Financial Analysis, Elsevier, vol. 87(C).
    143. Moussa, Faten & Delhoumi, Ezzeddine & Ouda, Olfa Ben, 2017. "Stock return and volatility reactions to information demand and supply," Research in International Business and Finance, Elsevier, vol. 39(PA), pages 54-67.
    144. Caperna, Giulio & Colagrossi, Marco & Geraci, Andrea & Mazzarella, Gianluca, 2020. "Googling Unemployment During the Pandemic: Inference and Nowcast Using Search Data," Working Papers 2020-04, Joint Research Centre, European Commission.
    145. Piotr Skórka & Beata Grzywacz & Dawid Moroń & Magdalena Lenda, 2022. "COVID-19 in Memes: The Adaptive Response of Societies to the Pandemic?," IJERPH, MDPI, vol. 19(19), pages 1-24, October.
    146. Katsiampa, Paraskevi & Moutsianas, Konstantinos & Urquhart, Andrew, 2019. "Information demand and cryptocurrency market activity," Economics Letters, Elsevier, vol. 185(C).
    147. Chen, Zhongdong & Craig, Karen Ann, 2023. "Active attention, retail investor base, and stock returns," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    148. Masaki Mori, 2015. "Information Diffusion in the U.S. Real Estate Investment Trust Market," The Journal of Real Estate Finance and Economics, Springer, vol. 51(2), pages 190-214, August.
    149. ap Gwilym, O. & Kita, A. & Wang, Q., 2014. "Speculate against speculative demand," International Review of Financial Analysis, Elsevier, vol. 34(C), pages 212-221.
    150. Vilma Deltuvaitė & Svatopluk Kapounek & Petr Koráb, 2019. "Impact of Behavioural Attention on the Households Foreign Currency Savings as a Response to the External Macroeconomic Shocks," Prague Economic Papers, Prague University of Economics and Business, vol. 2019(2), pages 155-177.
    151. Goddard, John & Kita, Arben & Wang, Qingwei, 2015. "Investor attention and FX market volatility," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 38(C), pages 79-96.
    152. Daniel Chai & Mengjia Dai & Philip Gharghori & Barbara Hong, 2021. "Internet Search Intensity and Its Relation with Trading Activity and Stock Returns," International Review of Finance, International Review of Finance Ltd., vol. 21(1), pages 282-311, March.
    153. Ronald MacDonald & Xuxin Mao, 2015. "An Alternative way of Predicting the Outcome of the Scottish Independence Referendum: The Information in the Ether," SIRE Discussion Papers 2015-69, Scottish Institute for Research in Economics (SIRE).
    154. Cedric Mbanga & Ali F. Darrat & Jung Chul Park, 2019. "Investor sentiment and aggregate stock returns: the role of investor attention," Review of Quantitative Finance and Accounting, Springer, vol. 53(2), pages 397-428, August.
    155. Vakrman, Tomas & Kristoufek, Ladislav, 2015. "Underpricing, underperformance and overreaction in initial pubic offerings: Evidence from investor attention using online searches," FinMaP-Working Papers 35, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    156. Gao, Yang & Wang, Yaojun & Wang, Chao & Liu, Chao, 2018. "Internet attention and information asymmetry: Evidence from Qihoo 360 search data on the Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 802-811.
    157. Hailiang Huang & Yanhong Li & Yingying Zhang, 2018. "Investors’ attention and overpricing of IPO: an empirical study on China’s growth enterprise market," Information Systems and e-Business Management, Springer, vol. 16(4), pages 761-774, November.
    158. Matija Piv{s}korec & Nino Antulov-Fantulin & Petra Kralj Novak & Igor Mozetiv{c} & Miha Grv{c}ar & Irena Vodenska & Tomislav v{S}muc, 2014. "News Cohesiveness: an Indicator of Systemic Risk in Financial Markets," Papers 1402.3483, arXiv.org.
    159. Zhang, Yongjie & Chu, Gang & Shen, Dehua, 2021. "The role of investor attention in predicting stock prices: The long short-term memory networks perspective," Finance Research Letters, Elsevier, vol. 38(C).
    160. Ana Brochado, 2016. "Retail Investor Sentiment: Can We Google It?," EcoMod2016 9341, EcoMod.
    161. Senarathne, Chamil W., . "The Information Flow Interpretation of Margin Debt Value Data: Evidence from New York Stock Exchange," Asian Journal of Applied Economics, Kasetsart University, Center for Applied Economics Research, vol. 26(1).
    162. Chen, Linda H. & Dyl, Edward A. & Jiang, George J. & Juneja, Januj A., 2015. "Risk, illiquidity or marketability: What matters for the discounts on private equity placements?," Journal of Banking & Finance, Elsevier, vol. 57(C), pages 41-50.
    163. Tang, Wenbin & Zhu, Lili, 2017. "How security prices respond to a surge in investor attention: Evidence from Google Search of ADRs," Global Finance Journal, Elsevier, vol. 33(C), pages 38-50.
    164. Ahundjanov, Behzod B. & Akhundjanov, Sherzod B. & Okhunjanov, Botir B., 2021. "Risk perception and oil and gasoline markets under COVID-19," Journal of Economics and Business, Elsevier, vol. 115(C).
    165. Swamy, Vighneswara & Dharani, M. & Takeda, Fumiko, 2019. "Investor attention and Google Search Volume Index: Evidence from an emerging market using quantile regression analysis," Research in International Business and Finance, Elsevier, vol. 50(C), pages 1-17.
    166. Chronopoulos, Dimitris K. & Papadimitriou, Fotios I. & Vlastakis, Nikolaos, 2018. "Information demand and stock return predictability," Journal of International Money and Finance, Elsevier, vol. 80(C), pages 59-74.
    167. Ramya Rajajagadeesan Aroul & Sanjiv Sabherwal & Sergiy Saydometov, 2022. "FEAR Index, city characteristics, and housing returns," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 50(1), pages 173-205, March.
    168. Xiong Xiong & Zhang Jin & Feng Xu & Jin Xi, 2016. "Review on Financial Innovations in Big Data Era," Journal of Systems Science and Information, De Gruyter, vol. 4(6), pages 489-504, December.
    169. Marmora, Paul, 2021. "Individual investor ownership and the news coverage premium," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 494-507.
    170. Denis Davydov & Jarkko Peltomäki, 2023. "Investor attention and the use of leverage," The Financial Review, Eastern Finance Association, vol. 58(2), pages 287-313, May.
    171. Minjian Ye & Guangzhong Li, 2017. "Internet big data and capital markets: a literature review," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 3(1), pages 1-18, December.
    172. Qadan, Mahmoud & Nama, Hazar, 2018. "Investor sentiment and the price of oil," Energy Economics, Elsevier, vol. 69(C), pages 42-58.
    173. Feng, Jiabao & Wang, Yudong & Yin, Libo, 2017. "Oil volatility risk and stock market volatility predictability: Evidence from G7 countries," Energy Economics, Elsevier, vol. 68(C), pages 240-254.
    174. Hsieh, Shu-Fan & Chan, Chia-Ying & Wang, Ming-Chun, 2020. "Retail investor attention and herding behavior," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 109-132.
    175. Tripathi, Abhinava & Pandey, Ashish, 2021. "Information dissemination across global markets during the spread of COVID-19 pandemic," International Review of Economics & Finance, Elsevier, vol. 74(C), pages 103-115.
    176. Liu, Yang & Han, Liyan & Yin, Libo, 2019. "News implied volatility and long-term foreign exchange market volatility," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 126-142.
    177. Vozlyublennaia, Nadia, 2014. "Investor attention, index performance, and return predictability," Journal of Banking & Finance, Elsevier, vol. 41(C), pages 17-35.
    178. Peltomäki, Jarkko & Graham, Michael & Hasselgren, Anton, 2018. "Investor attention to market categories and market volatility: The case of emerging markets," Research in International Business and Finance, Elsevier, vol. 44(C), pages 532-546.
    179. Mauck, Nathan & Pruitt, Stephen & Zhang, Wenjia, 2022. "Words matter: Market responses to changes in U.S. and Chinese trade-related internet search frequency under different U.S. administrations," Global Finance Journal, Elsevier, vol. 53(C).
    180. Cai, Wenwu & Lu, Jing, 2019. "Investors’ financial attention frequency and trading activity," Pacific-Basin Finance Journal, Elsevier, vol. 58(C).
    181. Zhang, Yongjie & Song, Weixin & Shen, Dehua & Zhang, Wei, 2016. "Market reaction to internet news: Information diffusion and price pressure," Economic Modelling, Elsevier, vol. 56(C), pages 43-49.
    182. Gong, Qiang & Jacoby, Gady & Li, Shi & Lu, Lei, 2021. "Commonality in disagreement," Pacific-Basin Finance Journal, Elsevier, vol. 67(C).
    183. González-Fernández, Marcos & González-Velasco, Carmen, 2020. "A sentiment index to measure sovereign risk using Google data," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 406-418.
    184. Sergiy Saydometov & Sanjiv Sabherwal & Ramya Rajajagadeesan Aroul, 2020. "Sentiment and its asymmetric effect on housing returns," Review of Financial Economics, John Wiley & Sons, vol. 38(4), pages 580-600, October.
    185. Pham, Linh & Cepni, Oguzhan, 2022. "Extreme directional spillovers between investor attention and green bond markets," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 186-210.
    186. Aouadi, Amal & Arouri, Mohamed & Teulon, Frédéric, 2013. "Investor attention and stock market activity: Evidence from France," Economic Modelling, Elsevier, vol. 35(C), pages 674-681.
    187. Kim, Neri & Lučivjanská, Katarína & Molnár, Peter & Villa, Roviel, 2019. "Google searches and stock market activity: Evidence from Norway," Finance Research Letters, Elsevier, vol. 28(C), pages 208-220.
    188. Jolana Stejskalová, 2017. "The Impact of Attention to News about Tax Changes on the Stock Market," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 65(6), pages 2113-2121.
    189. Feng He & Libo Yin, 2021. "Shocks to the equity capital ratio of financial intermediaries and the predictability of stock return volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 945-962, September.
    190. Guglielmo Maria Caporale & Menelaos Karanasos & Stavroula Yfanti, 2019. "Macro-Financial Linkages in the High-Frequency Domain: The Effects of Uncertainty on Realized Volatility," CESifo Working Paper Series 8000, CESifo.
    191. Lei, Lijun (Gillian) & Li, Yutao & Luo, Yan, 2019. "Production and dissemination of corporate information in social media: A review," Journal of Accounting Literature, Elsevier, vol. 42(C), pages 29-43.
    192. Shen, Lihua & Lu, Xinjie & Luu Duc Huynh, Toan & Liang, Chao, 2023. "Air quality index and the Chinese stock market volatility: Evidence from both market and sector indices," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 224-239.
    193. Tantaopas, Parkpoom & Padungsaksawasdi, Chaiyuth & Treepongkaruna, Sirimon, 2016. "Attention effect via internet search intensity in Asia-Pacific stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 38(C), pages 107-124.
    194. Wang, Chen & Shen, Dehua & Li, Youwei, 2022. "Aggregate Investor Attention and Bitcoin Return: The Long Short-term Memory Networks Perspective," Finance Research Letters, Elsevier, vol. 49(C).
    195. Arnold, Ivo J.M., 2020. "Internet search volumes of UK banks during the crisis: The role of banking structure and business model," Global Finance Journal, Elsevier, vol. 45(C).
    196. Papadamou, Stephanos & Fassas, Athanasios & Kenourgios, Dimitris & Dimitriou, Dimitrios, 2020. "Direct and Indirect Effects of COVID-19 Pandemic on Implied Stock Market Volatility: Evidence from Panel Data Analysis," MPRA Paper 100020, University Library of Munich, Germany.
    197. Sobti, Neharika & Sehgal, Sanjay & Ilango, Balakrishnan, 2021. "How do macroeconomic news surprises affect round-the-clock price discovery of gold?," International Review of Financial Analysis, Elsevier, vol. 78(C).

  5. Nikolaos Vlastakis & George Dotsis & Raphael N. Markellos, 2009. "How efficient is the European football betting market? Evidence from arbitrage and trading strategies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(5), pages 426-444.

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    2. Nikolaos Vlastakis & George Dotsis & Raphael Markellos, 2008. "Nonlinear modelling of European football scores using support vector machines," Applied Economics, Taylor & Francis Journals, vol. 40(1), pages 111-118.
    3. Isabel Abinzano & Luis Muga & Rafael Santamaria, 2017. "Behavioral Biases Never Walk Alone," Journal of Sports Economics, , vol. 18(2), pages 99-125, February.
    4. Lahvicka, Jiri, 2013. "The Fibonacci Strategy Revisited: Can You Really Make Money by Betting on Soccer Draws?," MPRA Paper 47649, University Library of Munich, Germany.
    5. Luca De Angelis & J. James Reade, 2022. "Home advantage and mispricing in indoor sports’ ghost games: the case of European basketball," Economics Discussion Papers em-dp2022-01, Department of Economics, University of Reading.
    6. Li, Yang & Brooks, Robert, 2022. "Evidence of arbitrage trading activity: The case of Chinese metal futures contracts," Emerging Markets Review, Elsevier, vol. 51(PB).
    7. Egon Franck & Erwin Verbeek & Stephan Nüesch, 2013. "Inter-market Arbitrage in Betting," Economica, London School of Economics and Political Science, vol. 80(318), pages 300-325, April.
    8. Giovanni Angelini & Luca De Angelis, 2017. "PARX model for football match predictions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(7), pages 795-807, November.
    9. Egon Franck & Erwin Verbeek & Stephan Nuesch, 2008. "Sentimental Preferences and the Organizational Regime of Betting Markets," Working Papers 0089, University of Zurich, Institute for Strategy and Business Economics (ISU), revised 2010.
    10. Nicos Zafiris, 2016. "Is There Such A Thing As A Safe Bet ?," Journal of Gambling Business and Economics, University of Buckingham Press, vol. 10(1), pages 40-65.
    11. Martin Spann & Bernd Skiera, 2009. "Sports forecasting: a comparison of the forecast accuracy of prediction markets, betting odds and tipsters," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(1), pages 55-72.
    12. Auld, Tom & Linton, Oliver, 2019. "The behaviour of betting and currency markets on the night of the EU referendum," International Journal of Forecasting, Elsevier, vol. 35(1), pages 371-389.
    13. Fischer, Kai & Haucap, Justus, 2020. "Betting market efficiency in the presence of unfamiliar shocks: The case of ghost games during the COVID-19 pandemic," DICE Discussion Papers 349, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    14. Hofer, Vera & Leitner, Johannes, 2017. "Relative pricing of binary options in live soccer betting markets," Journal of Economic Dynamics and Control, Elsevier, vol. 76(C), pages 66-85.
    15. Rebeggiani, Luca & Gross, Johannes, 2018. "Chance or Ability? The Efficiency of the Football Betting Market Revisited," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181563, Verein für Socialpolitik / German Economic Association.
    16. Vincenzo Candila & Antonio Scognamillo, 2019. "On the Longshot Bias in Tennis Betting Markets: The Casco Normalization," Working Papers 3_236, Dipartimento di Scienze Economiche e Statistiche, Università degli Studi di Salerno.
    17. Guy Elaad, 2020. "Home-field advantage and biased prediction markets in English soccer," Applied Economics Letters, Taylor & Francis Journals, vol. 27(14), pages 1170-1174, July.
    18. Adrian Bell & Chris Brooks & David Matthews & Charles Sutcliffe, 2011. "Over the Moon or Sick as a Parrot? The Effects of Football Results on a Club's Share Price," Post-Print hal-00709557, HAL.
    19. Kai Fischer & Justus Haucap, 2022. "Home advantage in professional soccer and betting market efficiency: The role of spectator crowds," Kyklos, Wiley Blackwell, vol. 75(2), pages 294-316, May.
    20. David Winkelmann & Christian Deutscher & Marius Ötting, 2021. "Bookmakers’ mispricing of the disappeared home advantage in the German Bundesliga after the COVID-19 break," Applied Economics, Taylor & Francis Journals, vol. 53(26), pages 3054-3064, June.
    21. Buhagiar, Ranier & Cortis, Dominic & Newall, Philip W.S., 2018. "Why do some soccer bettors lose more money than others?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 18(C), pages 85-93.
    22. Angelini, Giovanni & De Angelis, Luca, 2019. "Efficiency of online football betting markets," International Journal of Forecasting, Elsevier, vol. 35(2), pages 712-721.
    23. Montone, Maurizio, 2021. "Optimal pricing in the online betting market," Journal of Economic Behavior & Organization, Elsevier, vol. 186(C), pages 344-363.
    24. Christian Deutscher & David Winkelmann & Marius Otting, 2020. "Bookmakers' mispricing of the disappeared home advantage in the German Bundesliga after the COVID-19 break," Papers 2008.05417, arXiv.org, revised Aug 2020.
    25. Elaad, Guy & Reade, J. James & Singleton, Carl, 2020. "Information, prices and efficiency in an online betting market," Finance Research Letters, Elsevier, vol. 35(C).
    26. Masahiro Ashiya, 2015. "Lock! Risk-Free Arbitrage in the Japanese Racetrack Betting Market," Journal of Sports Economics, , vol. 16(3), pages 322-330, April.
    27. Leitner, Christoph & Zeileis, Achim & Hornik, Kurt, 2010. "Forecasting sports tournaments by ratings of (prob)abilities: A comparison for the EUROÂ 2008," International Journal of Forecasting, Elsevier, vol. 26(3), pages 471-481, July.
    28. Dominic Cortis & Steve Hales & Frank Bezzina, 2013. "Profiting On Inefficiencies In Betting Derivative Markets: The Case Of Uefa Euro 2012," Journal of Gambling Business and Economics, University of Buckingham Press, vol. 7(1), pages 39-51.
    29. Giovanni Angelini & Luca De Angelis & Carl Singleton, 2019. "Informational efficiency and behaviour within in-play prediction markets," Economics Discussion Papers em-dp2019-20, Department of Economics, University of Reading, revised 01 Apr 2021.
    30. Marius Ötting & Christian Deutscher & Carl Singleton & Luca De Angelis, 2022. "Gambling on Momentum," Economics Discussion Papers em-dp2022-10, Department of Economics, University of Reading.
      • Marius Otting & Christian Deutscher & Carl Singleton & Luca De Angelis, 2022. "Gambling on Momentum," Papers 2211.06052, arXiv.org.
    31. Marius Ötting & Christian Deutscher & Carl Singleton & Luca De Angelis, 2023. "Gambling on Momentum in Contests," Economics Discussion Papers em-dp2023-08, Department of Economics, University of Reading.
    32. Pascal Flurin Meier & Raphael Flepp & Egon Franck, 2021. "Are sports betting markets semistrong efficient? Evidence from the COVID-19 pandemic," Working Papers 387, University of Zurich, Department of Business Administration (IBW).
    33. Goto, Shingo & Yamada, Toru, 2023. "What drives biased odds in sports betting markets: Bettors’ irrationality and the role of bookmakers," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 252-270.
    34. Babatunde Buraimo & David Peel & Rob Simmons, 2013. "Systematic Positive Expected Returns in the UK Fixed Odds Betting Market: An Analysis of the Fink Tank Predictions," IJFS, MDPI, vol. 1(4), pages 1-15, December.
    35. Dimic, Nebojsa & Neudl, Manfred & Orlov, Vitaly & Äijö, Janne, 2018. "Investor sentiment, soccer games and stock returns," Research in International Business and Finance, Elsevier, vol. 43(C), pages 90-98.
    36. David Winkelmann & Marius Ötting & Christian Deutscher & Tomasz Makarewicz, 2024. "Are Betting Markets Inefficient? Evidence From Simulations and Real Data," Journal of Sports Economics, , vol. 25(1), pages 54-97, January.
    37. Philip W. S. Newall & Dominic Cortis, 2021. "Are Sports Bettors Biased toward Longshots, Favorites, or Both? A Literature Review," Risks, MDPI, vol. 9(1), pages 1-9, January.
    38. Lessmann, Stefan & Sung, Ming-Chien & Johnson, Johnnie E.V. & Ma, Tiejun, 2012. "A new methodology for generating and combining statistical forecasting models to enhance competitive event prediction," European Journal of Operational Research, Elsevier, vol. 218(1), pages 163-174.
    39. Carlos Gomez-Gonzalez & Julio del Corral, 2018. "The betting market over time: overround and surebets in European football," Economics and Business Letters, Oviedo University Press, vol. 7(4), pages 129-136.
    40. Jinook Jeong & Jee Young Kim & Yoon Jae Ro, 2017. "On the Efficiency of Racetrack Betting Market: A New Test for the Favorite-Longshot Bias," Working papers 2017rwp-106, Yonsei University, Yonsei Economics Research Institute.
    41. Colantonio Emiliano, 2013. "Betting Markets: Opportunities For Many?," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(2), pages 200-208, December.
    42. Salvatore Caruso & Giuseppe Pernagallo, 2021. "On the efficiency of online soccer betting markets: a new methodology based on symbolic series," Economics Bulletin, AccessEcon, vol. 41(3), pages 1451-1460.
    43. Andrew Grant & Anastasios Oikonomidis & Alistair C. Bruce & Johnnie E. V. Johnson, 2018. "New entry, strategic diversity and efficiency in soccer betting markets: the creation and suppression of arbitrage opportunities," The European Journal of Finance, Taylor & Francis Journals, vol. 24(18), pages 1799-1816, December.
    44. Fry, John & Serbera, Jean-Philippe & Wilson, Rob, 2021. "Managing performance expectations in association football," Journal of Business Research, Elsevier, vol. 135(C), pages 445-453.
    45. Luca De Angelis & J. James Reade, 2023. "Home advantage and mispricing in indoor sports’ ghost games: the case of European basketball," Annals of Operations Research, Springer, vol. 325(1), pages 391-418, June.

  6. Nikolaos Vlastakis & George Dotsis & Raphael Markellos, 2008. "Nonlinear modelling of European football scores using support vector machines," Applied Economics, Taylor & Francis Journals, vol. 40(1), pages 111-118.

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    3. Xianning Wang & Zhengang Ma & Jiusheng Chen & Jingrong Dong, 2023. "Can Regional Eco-Efficiency Forecast the Changes in Local Public Health: Evidence Based on Statistical Learning in China," IJERPH, MDPI, vol. 20(2), pages 1-19, January.
    4. S Lessmann & M-C Sung & J E V Johnson, 2011. "Towards a methodology for measuring the true degree of efficiency in a speculative market," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(12), pages 2120-2132, December.
    5. Hassanniakalager, Arman & Sermpinis, Georgios & Stasinakis, Charalampos & Verousis, Thanos, 2020. "A conditional fuzzy inference approach in forecasting," European Journal of Operational Research, Elsevier, vol. 283(1), pages 196-216.
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