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Moritz Heiden

Personal Details

First Name:Moritz
Middle Name:
Last Name:Heiden
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RePEc Short-ID:phe600
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Affiliation

Fakultät für Wirtschaftswissenschaften
Universität Augsburg

Augsburg, Germany
http://www.wiwi.uni-augsburg.de/
RePEc:edi:fwaugde (more details at EDIRC)

Research output

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Jump to: Articles

Articles

  1. D. Schneller & S. Heiden & M. Heiden & A. Hamid, 2018. "Home is Where You Know Your Volatility – Local Investor Sentiment and Stock Market Volatility," German Economic Review, Verein für Socialpolitik, vol. 19(2), pages 209-236, May.
  2. Schneller D. & Heiden S. & Hamid A. & Heiden M., 2018. "Home is Where You Know Your Volatility – Local Investor Sentiment and Stock Market Volatility," German Economic Review, De Gruyter, vol. 19(2), pages 209-236, May.
  3. E. C. Brechmann & M. Heiden & Y. Okhrin, 2018. "A multivariate volatility vine copula model," Econometric Reviews, Taylor & Francis Journals, vol. 37(4), pages 281-308, April.
  4. 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.

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.

Articles

  1. D. Schneller & S. Heiden & M. Heiden & A. Hamid, 2018. "Home is Where You Know Your Volatility – Local Investor Sentiment and Stock Market Volatility," German Economic Review, Verein für Socialpolitik, vol. 19(2), pages 209-236, May.

    Cited by:

    1. Phan, Thi Nha Truc & Bertrand, Philippe & Phan, Hong Hai & Vo, Xuan Vinh, 2023. "The role of investor behavior in emerging stock markets: Evidence from Vietnam," The Quarterly Review of Economics and Finance, Elsevier, vol. 87(C), pages 367-376.
    2. Jiang, Shangwei & Jin, Xiu, 2021. "Effects of investor sentiment on stock return volatility: A spatio-temporal dynamic panel model," Economic Modelling, Elsevier, vol. 97(C), pages 298-306.
    3. N. Banholzer & S. Heiden & D. Schneller, 2019. "Exploiting investor sentiment for portfolio optimization," Business Research, Springer;German Academic Association for Business Research, vol. 12(2), pages 671-702, December.
    4. Papadamou, Stephanos & Fassas, Athanasios P. & Kenourgios, Dimitris & Dimitriou, Dimitrios, 2023. "Effects of the first wave of COVID-19 pandemic on implied stock market volatility: International evidence using a google trend measure," The Journal of Economic Asymmetries, Elsevier, vol. 28(C).
    5. Stefan Abrantes Costa & Pedro Manuel Nogueira Reis & Antonio Pedro Soares Pinto, 2020. "Subjective/ Behavioural Factors Influence the PSI 20 and IBEX 35," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 11(5), pages 13-27, October.
    6. S., Glogger & S., Heiden & D., Schneller, 2019. "Bearing the bear: Sentiment-based disagreement in multi-criteria portfolio optimization," Finance Research Letters, Elsevier, vol. 31(C), pages 47-53.

  2. Schneller D. & Heiden S. & Hamid A. & Heiden M., 2018. "Home is Where You Know Your Volatility – Local Investor Sentiment and Stock Market Volatility," German Economic Review, De Gruyter, vol. 19(2), pages 209-236, May.

    Cited by:

    1. Jiang, Shangwei & Jin, Xiu, 2021. "Effects of investor sentiment on stock return volatility: A spatio-temporal dynamic panel model," Economic Modelling, Elsevier, vol. 97(C), pages 298-306.
    2. N. Banholzer & S. Heiden & D. Schneller, 2019. "Exploiting investor sentiment for portfolio optimization," Business Research, Springer;German Academic Association for Business Research, vol. 12(2), pages 671-702, December.
    3. Papadamou, Stephanos & Fassas, Athanasios P. & Kenourgios, Dimitris & Dimitriou, Dimitrios, 2023. "Effects of the first wave of COVID-19 pandemic on implied stock market volatility: International evidence using a google trend measure," The Journal of Economic Asymmetries, Elsevier, vol. 28(C).

  3. E. C. Brechmann & M. Heiden & Y. Okhrin, 2018. "A multivariate volatility vine copula model," Econometric Reviews, Taylor & Francis Journals, vol. 37(4), pages 281-308, April.

    Cited by:

    1. Jorge V. Pérez-Rodríguez, 2020. "Another look at the implied and realised volatility relation: a copula-based approach," Risk Management, Palgrave Macmillan, vol. 22(1), pages 38-64, March.
    2. Nikolaus Hautsch & Ostap Okhrin & Alexander Ristig, 2023. "Maximum-Likelihood Estimation Using the Zig-Zag Algorithm," Journal of Financial Econometrics, Oxford University Press, vol. 21(4), pages 1346-1375.
    3. Erniel B. Barrios & Paolo Victor T. Redondo, 2021. "Nonparametric Test for Volatility in Clustered Multiple Time Series," Papers 2104.14412, arXiv.org, revised May 2024.
    4. Wanling Huang & André Varella Mollick & Khoa Huu Nguyen, 2017. "Dynamic responses and tail-dependence among commodities, the US real interest rate and the dollar," Empirical Economics, Springer, vol. 53(3), pages 959-997, November.
    5. Wenjing Wang & Minjing Tao, 2020. "Forecasting Realized Volatility Matrix With Copula-Based Models," Papers 2002.08849, arXiv.org.
    6. Czado, Claudia & Ivanov, Eugen & Okhrin, Yarema, 2019. "Modelling temporal dependence of realized variances with vines," Econometrics and Statistics, Elsevier, vol. 12(C), pages 198-216.
    7. Demetrescu, Matei & Golosnoy, Vasyl & Titova, Anna, 2020. "Bias corrections for exponentially transformed forecasts: Are they worth the effort?," International Journal of Forecasting, Elsevier, vol. 36(3), pages 761-780.
    8. Xu, Chi & Zheng, Chunling & Wang, Donghua & Ji, Jingru & Wang, Nuan, 2019. "Double correlation model for operational risk: Evidence from Chinese commercial banks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 327-339.

  4. 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.

    Cited by:

    1. 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.
    2. 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.
    3. 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).
    4. Schaer, Oliver & Kourentzes, Nikolaos & Fildes, Robert, 2019. "Demand forecasting with user-generated online information," International Journal of Forecasting, Elsevier, vol. 35(1), pages 197-212.
    5. Qadan, Mahmoud & Zoua’bi, Maher, 2019. "Financial attention and the demand for information," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 82(C).
    6. Hasanzadeh, Samira & Alishahi, Modjgan, 2020. "COVID-19 Pounds: Quarantine and Weight Gain," MPRA Paper 103074, University Library of Munich, Germany.
    7. Anastasiou, Dimitris & Ballis, Antonis & Drakos, Konstantinos, 2022. "Constructing a positive sentiment index for COVID-19: Evidence from G20 stock markets," International Review of Financial Analysis, Elsevier, vol. 81(C).
    8. Geri Skenderi & Christian Joppi & Matteo Denitto & Marco Cristani, 2024. "Well googled is half done: Multimodal forecasting of new fashion product sales with image‐based google trends," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 1982-1997, September.
    9. Christophe Desagre & Catherine D'Hondt, 2020. "Googlization and retail investors' trading activity," LIDAM Discussion Papers LFIN 2020004, Université catholique de Louvain, Louvain Finance (LFIN).
    10. 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.
    11. France, Stephen L. & Shi, Yuying & Kazandjian, Brett, 2021. "Web Trends: A valuable tool for business research," Journal of Business Research, Elsevier, vol. 132(C), pages 666-679.
    12. Dimitrios Anastasiou & Zacharias Bragoudakis & Stelios Giannoulakis, 2020. "Perceived vs actual financial crisis and bank credit standards: is there any indication of self-fulfilling prophecy?," Working Papers 277, Bank of Greece.
    13. 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.
    14. Siliverstovs, Boriss & Wochner, Daniel S., 2018. "Google Trends and reality: Do the proportions match?," Journal of Economic Behavior & Organization, Elsevier, vol. 145(C), pages 1-23.
    15. 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.
    16. D. Schneller & S. Heiden & M. Heiden & A. Hamid, 2018. "Home is Where You Know Your Volatility – Local Investor Sentiment and Stock Market Volatility," German Economic Review, Verein für Socialpolitik, vol. 19(2), pages 209-236, May.
    17. María José Ayala & Nicolás Gonzálvez-Gallego & Rocío Arteaga-Sánchez, 2024. "Google search volume index and investor attention in stock market: a systematic review," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-29, December.
    18. Jiang, Shangrong & Li, Yuze & Lu, Quanying & Wang, Shouyang & Wei, Yunjie, 2022. "Volatility communicator or receiver? Investigating volatility spillover mechanisms among Bitcoin and other financial markets," Research in International Business and Finance, Elsevier, vol. 59(C).
    19. Wei Zhang & Kai Yan & Dehua Shen, 2021. "Can the Baidu Index predict realized volatility in the Chinese stock market?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-31, December.
    20. Caperna, Giulio & Colagrossi, Marco & Geraci, Andrea & Mazzarella, Gianluca, 2020. "Googling Unemployment During the Pandemic: Inference and Nowcast Using Search Data," JRC Working Papers in Economics and Finance 2020-04, Joint Research Centre, European Commission.
    21. Emmanuel Sirimal Silva & Hossein Hassani & Dag Øivind Madsen & Liz Gee, 2019. "Googling Fashion: Forecasting Fashion Consumer Behaviour Using Google Trends," Social Sciences, MDPI, vol. 8(4), pages 1-23, April.
    22. de Castro, Jessica & Piccoli, Pedro, 2023. "Do online searches actually measure future retail investor trades?," International Review of Financial Analysis, Elsevier, vol. 86(C).
    23. Papadamou, Stephanos & Fassas, Athanasios P. & Kenourgios, Dimitris & Dimitriou, Dimitrios, 2023. "Effects of the first wave of COVID-19 pandemic on implied stock market volatility: International evidence using a google trend measure," The Journal of Economic Asymmetries, Elsevier, vol. 28(C).
    24. Dimitrios Anastasiou & Konstantinos Drakos, 2021. "Nowcasting the Greek (semi‐) deposit run: Hidden uncertainty about the future currency in a Google search," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1133-1150, January.
    25. 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.
    26. Liu, Yuanyuan & Niu, Zibo & Suleman, Muhammad Tahir & Yin, Libo & Zhang, Hongwei, 2022. "Forecasting the volatility of crude oil futures: The role of oil investor attention and its regime switching characteristics under a high-frequency framework," Energy, Elsevier, vol. 238(PA).
    27. Stephen L. France & Yuying Shi, 2017. "Aggregating Google Trends: Multivariate Testing and Analysis," Papers 1712.03152, arXiv.org, revised Mar 2018.
    28. Philippas, Dionisis & Dragomirescu-Gaina, Catalin & Goutte, Stéphane & Nguyen, Duc Khuong, 2021. "Investors’ attention and information losses under market stress," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 1112-1127.
    29. Caperna, Giulio & Colagrossi, Marco & Geraci, Andrea & Mazzarella, Gianluca, 2022. "A babel of web-searches: Googling unemployment during the pandemic," Labour Economics, Elsevier, vol. 74(C).
    30. Yongjie Zhang & Yue Li & Dehua Shen, 2022. "Investor Attention and the Carbon Emission Markets in China: A Nonparametric Wavelet-Based Causality Test," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 29(1), pages 123-137, March.
    31. 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.
    32. Foglia, Matteo & Miglietta, Federica, 2024. "Does every cloud (bubble) have a silver lining? An investigation of ESG financial markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 42(C).
    33. Ritika Chopra & Gagan Deep Sharma, 2021. "Application of Artificial Intelligence in Stock Market Forecasting: A Critique, Review, and Research Agenda," JRFM, MDPI, vol. 14(11), pages 1-34, November.
    34. Desagre, Christophe & D’Hondt, Catherine, 2021. "Googlization and retail trading activity," Journal of Behavioral and Experimental Finance, Elsevier, vol. 29(C).
    35. 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).
    36. Behera, Sarthak & Sadana, Divya, 2022. "The Impact of Visibility on School Athletic Finances: An Empirical Analysis using Google Trends," MPRA Paper 114818, University Library of Munich, Germany.
    37. Chaiyuth Padungsaksawasdi & Sirimon Treepongkaruna & Robert Brooks, 2019. "Investor Attention and Stock Market Activities: New Evidence from Panel Data," IJFS, MDPI, vol. 7(2), pages 1-19, June.
    38. Fernando Díaz & Pablo A Henríquez, 2021. "Social sentiment segregation: Evidence from Twitter and Google Trends in Chile during the COVID-19 dynamic quarantine strategy," PLOS ONE, Public Library of Science, vol. 16(7), pages 1-29, July.
    39. 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.
    40. Patrick Houlihan & Germán G. Creamer, 2017. "Can Sentiment Analysis and Options Volume Anticipate Future Returns?," Computational Economics, Springer;Society for Computational Economics, vol. 50(4), pages 669-685, December.
    41. 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.
    42. Kyoto Yono & Hiroki Sakaji & Hiroyasu Matsushima & Takashi Shimada & Kiyoshi Izumi, 2020. "Construction of Macroeconomic Uncertainty Indices for Financial Market Analysis Using a Supervised Topic Model," JRFM, MDPI, vol. 13(4), pages 1-18, April.
    43. Ouyang, Zi-sheng & Yang, Xi-te & Lai, Yongzeng, 2021. "Systemic financial risk early warning of financial market in China using Attention-LSTM model," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    44. Lyócsa, Štefan & Baumöhl, Eduard & Výrost, Tomáš, 2022. "YOLO trading: Riding with the herd during the GameStop episode," Finance Research Letters, Elsevier, vol. 46(PA).
    45. 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).
    46. Anastasiou, Dimitrios & Drakos, Konstantinos, 2021. "European depositors’ behavior and crisis sentiment," Journal of Economic Behavior & Organization, Elsevier, vol. 184(C), pages 117-136.
    47. Zhang, Tonghui & Yuan, Ying & Wu, Xi, 2020. "Is microblogging data reflected in stock market volatility? Evidence from Sina Weibo," Finance Research Letters, Elsevier, vol. 32(C).
    48. Paravee Maneejuk & Woraphon Yamaka, 2019. "Predicting Contagion from the US Financial Crisis to International Stock Markets Using Dynamic Copula with Google Trends," Mathematics, MDPI, vol. 7(11), pages 1-29, November.
    49. 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.
    50. Behrendt, Simon & Peter, Franziska J. & Zimmermann, David J., 2020. "An encyclopedia for stock markets? Wikipedia searches and stock returns," International Review of Financial Analysis, Elsevier, vol. 72(C).
    51. James Alm & Weizheng Lai & Xun Li, 2021. "Housing Market Regulations and Strategic Divorce Propensity in China," Working Papers 2119, Tulane University, Department of Economics.
    52. Alomari, Mohammad & Al Rababa’a, Abdel Razzaq & El-Nader, Ghaith & Alkhataybeh, Ahmad & Ur Rehman, Mobeen, 2021. "Examining the effects of news and media sentiments on volatility and correlation: Evidence from the UK," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 280-297.
    53. Fu, Tong & Huang, Dasen & Feng, Lingbing & Tang, Xiaoping, 2024. "More is better? The impact of predictor choice on the INE oil futures volatility forecasting," Energy Economics, Elsevier, vol. 134(C).
    54. Krzysztof DRACHAL, 2020. "Forecasting the Inflation Rate in Poland and U.S. Using Dynamic Model Averaging (DMA) and Google Queries," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 18-34, July.
    55. Lin, Boqiang & Wei, Kai, 2024. "Does investor attitude toward carbon neutrality affect stock returns in China?," International Review of Financial Analysis, Elsevier, vol. 93(C).
    56. Audrino, Francesco & Sigrist, Fabio & Ballinari, Daniele, 2020. "The impact of sentiment and attention measures on stock market volatility," International Journal of Forecasting, Elsevier, vol. 36(2), pages 334-357.

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