Sentiment hedging: Trending stocks on reddit

dc.contributorTer Horst , Enrique Alejandro
dc.contributorMantilla, Daniel
dc.contributorRiascos Villegas, Alvaro José
dc.creatorNova Orozco, Germán Andrés
dc.date.accessioned2023-06-22T12:51:11Z
dc.date.accessioned2023-09-07T00:20:49Z
dc.date.available2023-06-22T12:51:11Z
dc.date.available2023-09-07T00:20:49Z
dc.date.created2023-06-22T12:51:11Z
dc.date.issued2023-05-31
dc.identifierhttp://hdl.handle.net/1992/67769
dc.identifierinstname:Universidad de los Andes
dc.identifierreponame:Repositorio Institucional Séneca
dc.identifierrepourl:https://repositorio.uniandes.edu.co/
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8727319
dc.description.abstractThe present document studies the hedging of portfolios in the face of social media sentiment. To do this, a portfolio of stocks is constructed whose returns are correlated with innovations in social media sentiment. To estimate sentiment, two approaches are presented: the first with supervised analysis using the Multinomial Inverse Regression (MNIR) model (Taddy, 2013a) and the second with the lexicon-based Valence Aware Dictionary for Sentiment Reasoning (VADER) model (Hutto and Gilbert, 2014). To estimate sentiment, a database of 56.5 million comments and posts from Reddit is used. To generate the hedging asset allocation, Deep Reinforcement Learning is implemented, specifically the Adaptive Deep Deterministic Policy Gradient (Adaptive DDPG) algorithm (Li et al., 2019). It is found that the way sentiment is estimated determines the algorithm¿s hedging performance to a large extent. For the portfolio that is covered against sentiment estimated by MNIR, notable out-of-sample results are achieved. To highlight the versatility of the methodology, algorithm performance is presented by focusing on maximizing returns. In summary, the best performing portfolios, in terms of return, were those that incorporated social media sentiment analysis. Additionally, portfolios utilizing the Adaptive DDPG algorithm showed a better Sharpe ratio compared to an Equal Weighted Portfolio and individual stock investments.
dc.languageeng
dc.publisherUniversidad de los Andes
dc.publisherMaestría en Economía
dc.publisherFacultad de Economía
dc.relationBarnes, K., Riesenmy, T., Trinh, M., Lleshi, E., Balogh, N., Molontay, R. (2021). Dank or not? Analyzing and predicting the popularity of memes on Reddit. Applied Network Science, 6:21. https://doi.org/10.1007/s41109-021-00358-7
dc.relationBaumgartner, J., Zannettou, S., Keegan, B., Squire, M., Blackburn, J. (2020). The Pushshift Reddit Dataset. In Proceedings of the International AAAI Conference on Web and Social Media (Vol. 14, pp. 830-839). arXiv:2001.08435
dc.relationBaur, D. and Smales, L. (2020). Hedging geopolitical risk with precious metals. Journal of Banking & Finance, Volume 117, 105823, ISSN 0378-4266, https://doi.org/10.1016/j.jbankfin.2020.105823
dc.relationBlack, F. (1986). Noise. The Journal of Finance, Jul., 1986, Vol. 41, No. 3, Papers and Proceedings of the Forty-Fourth Annual Meeting of the America Finance Association, New York, New York, December 28-30, 1985 (Jul., 1986), pp. 529-543
dc.relationBowman, J. (2022). Why Bed Bath & Beyond Stock Skyocketed 89% in August. The Motley Fool. Retrieved from https://www.fool.com/investing/2022/09/01/why-bed-bath-beyond-stock-skyocketed-89-in-august/
dc.relationCaldara, D., and Iacoviello, M. (2018). Measuring geopolitical risk. International Finance Discussion Paper 1222, Board of Governors of the Federal Reserve
dc.relationCamargo, J., González, M., Guzmán, A., ter Horst, E., Trujillo, A. (2018). Topics and Methods in Economics, Finance, and Business Journals: A Content Analysis Enquiry, Heliyon, Volume 4, Issue 12, https://doi.org/10.1016/j.heliyon.2018.e01062.
dc.relationCasarin, R., Correa, J. C., Camargo, J. E., Dakduk, S., ter Horst, E., Molina, G. (2019). What makes a tweet be retweeted? A Bayesian trigram analysis of tweet propagation during the 2015 Colombian political campaign. Journal of Information Science, 47(3), 297-305. https://doi.org/10.1177/0165551519886056
dc.relationChacon, R., Morillon, T., Wang, R (2023). Will the reddit rebellion take you to themoon? Evidence from WallStreetBets. Financial Markets and Portfolio Management 37:1-25, https://doi.org/10.1007/s11408- 022-00415-w
dc.relationChaouki, A. Hardiman, S., Schmidt, C., Sérié, E., Lataillade, J. (2020). Deep deterministic portfolio optimization. The Journal of Finance and Data Science 6 (2020) 16e30. https://doi.org/10.1016/j.jfds.2020.06.002
dc.relationChung, J. (2021). Melvin capital lost 53% in january, hurt by gamestop and other bets. Wall Street J. O Retrieved from https://www.wsj.com/.
dc.relationCostola, M., Iacopini, M., Santagiustina, C. (2021). On the "mementum" of meme stocks. Economics Letters, 207, https://doi.org/10.1016/j.econlet.2021.110021
dc.relationDhaoui, A. and Bensalah, N. (2016). Asset valuation impact of investor sentiment: A revised Fama¿French five-factor model. Journal of Asset Management Vol. 18, 1, 16-28, https://doi.org/10.1057/s41260-016- 0027-2
dc.relationDong, H. and Gil-Bazo, J. (2020). Sentiment stocks. International Review of Financial Analysis Volume 72, November 2020, 101573. https://doi.org/10.1016/j.irfa.2020.101573
dc.relationEngle, R., Giglio, S., Kelly, B., Lee, H., Stroebel, J. (2020). Hedging Climate Change News, The Review of Financial Studies, Volume 33, Issue 3, March 2020, Pages 1184-1216, https://doi.org/10.1093/rfs/hhz072
dc.relationFama, E. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, Vol. 25, No. 2, Papers and Proceedings of the Twenty-Eighth Annual Meeting of the American Finance Association New York. 25. pp 383-417.
dc.relationFama, E. and French, K. (2015). A five-factor asset pricing model. Journal of Financial Economics 116 1-22. http://dx.doi.org/10.1016/j.jfineco.2014.10.010
dc.relationFottner, A., Okhrin, Y., Pfahler, J., Wustl, J. (2022). Reddit financial image post sentiment dataset. Data in Brief 45 (2022) 108759. https://doi.org/10.1016/j.dib.2022.108759
dc.relationHasso, T., Müller, D., Pelster, M., Warkulat, S. (2021). Who participated in the GameStop frenzy? Evidence from brokerage accounts, Finance Research Letters, https://doi.org/10.1016/j.frl.2021.102140.
dc.relationHerbst-Bayliss, S. (2022). Melvin Capital to shut after heavy losses on meme stocks, market slump. Thomson Reuters. Retrieved from https://www.reuters.com/markets/us/hedge-fund-melvin-capital-tellsinvestors- it-plans-shut-down-letter-2022-05-18/
dc.relationHoulihan, P., Creamer, G. (2017). Risk Premium of Social Media Sentiment. The Journal of Investing, 26(3), 21-28, https://doi.org/10.3905/joi.2017.26.3.021
dc.relationHughes, J. (2023). Meme-stock 2.0: Wall Street¿s retail trading boom is back. Financial Times. Retrieved from https://www.ft.com/content/0ffaea2b-ba38-4dbc-bb52-499cdb0e1662
dc.relationHutto, C., Gilbert, E. (2014). VADER: A Parsimonious Rule-based Model for Sentiment Analysis of Social Media Text. Proceedings of the Eighth International AAAI Conference on Weblogs and Social Media. https://doi.org/10.1609/icwsm.v8i1.14550
dc.relationJang, J., Seong, N. (2023). Deep reinforcement learning for stock portfolio optimization by connecting with modern portfolio theory. Expert Systems With Applications 218 (2023) 119556. https://doi.org/10.1016/j.eswa.2023.119556
dc.relationJung, S. and Jeong, Y. (2021). Examining stock markets and societal mood using Internet memes. Journal of Behavioral and Experimental Finance 32 (2021) 100575. https://doi.org/10.1016/j.jbef.2021.100575
dc.relationKlein, Tony. (2021). A note on GameStop, short squeezes, and autodidactic herding: An evolution in financial literacy?, Finance Research Letters, https://doi.org/10.1016/j.frl.2021.102229.
dc.relationKoratamaddi, P., Wadhwani, K., Gupta, M. y Sanjeevi, S. (2021). Market sentiment-aware deep reinforcement learning approach for stock portfolio allocation. Engineering Science and Technology, an International Journal Volume 24, Issue 4, August 2021, Pages 848-859, https://doi.org/10.1016/j.jestch.2021.01.007
dc.relationLamont, Owen. (2001). Economic tracking portfolios. Journal of Econometrics, Volume 105, Issue 1, Pages 161-184, ISSN 0304-4076. https://doi.org/10.1016/S0304-4076(01)00074-4
dc.relationLefebvre, G., Lebreton, M., Mayniel, F., Bourgeois-Gironde, S., Palminteri, S. (2017). Behavioural and neural characterization of optimistic reinforcement learning. NATURE HUMAN BEHAVIOUR 1, 0067. DOI: 10.1038/s41562-017-0067
dc.relationLi, X., Li, Y., Zhan, Y., Liu, X. (2019) Optimistic Bull or Pessimistic Bear: Adaptive Deep Reinforcement Learning for Stock Portfolio Allocation. ArXiv. https://doi.org/10.48550/arXiv.1907.01503
dc.relationLillicrap, P., Hunt, J., Pritzel , A., Heess, N., Erez, T., Tassa, Y., Silver, D., Wierstra, D. (2015). Continuous Control with Deep Reinforcement Learning. arXiv preprint arXiv:1509.02971.
dc.relationLyócsa, S., Baumöhl, E., Výrost, T. (2019). YOLO trading: Riding with the herd during the GameStop episode. Finance Research Letters https://doi.org/10.1016/j.frl.2021.102359
dc.relationMalladi, R., Fabozzi, F. (2016). Equal-weighted strategy: Why it outperforms value-weighted strategies? Theory and evidence. Journal of Asset Management Vol. 18, 3, 188¿208. doi:10.1057/s41260-016-0033-4
dc.relationMarkowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1):77-91.
dc.relationMcCrank, J., Ahmed, S., Delevigne, L. (2021). Analysis: New meme stocks swing as shorts and retail investors face off again. Thomson Reuters. Retrieved from https://www.reuters.com/article/us-usa-stocksretail- investors-analysis-idCAKBN2CH2C3
dc.relationMcGurk, Z., Nowak, A., Hall, J.C. (2020). Stock returns and investor sentiment: textual analysis and social media. J Econ Finan 44, 458-485. https://doi.org/10.1007/s12197-019-09494-4
dc.relationMelton, C., Olusanya, O., Ammar, N., Shaban-Nejad, A. (2021). Public sentiment analysis and topic modeling regarding COVID-19 vaccines on the Reddit social media platform: A call to action for strengthening vaccine confidence. Journal of Infection and Public Health 14 (2021) 1505-1512. https://doi.org/10.1016/j.jiph.2021.08.010
dc.relationNobanee, H. and Ellili, N. (2023) What do we know about meme stocks? A bibliometric and systematic review, current streams, developments, and directions for future research. International Review of Economics and Finance 85 (2023) 589-602, https://doi.org/10.1016/j.iref.2023.02.012
dc.relationNobre, R., Nascimento, K., Vargas, P., Baria, A., Pessin, G., Villas, L., Rocham G. (2021). AURORA: an autonomous agent-oriented hybrid trading service. Neural Computing and Applications (2022) 34:2217-2232. https://doi.org/10.1007/s00521-021-06508-3
dc.relationPellegrino, F., Coupe, C. y Marsico, E. (2011). A cross-language perspective on speech information rate. Language; 87(3): 539-558
dc.relationRanco, G., Aleksovski, D., Caldarelli, G., Grcar, M., y Mozetic, I. (2015). The Effects of Twitter Sentiment on Stock Price Returns. PLoS ONE 10(9): e0138441
dc.relationRenault, T. (2020). Sentiment analysis and machine learning in finance: a comparison of methods and models on one million messages. Digit Finance 2, 1-13, https://doi.org/10.1007/s42521-019-00014-x
dc.relationScharfstein, D. and Stein, J. (1990). Herd Behavior and Investment. The American Economic Review, Jun., 1990, Vol. 80, No. 3 (Jun., 1990), pp. 465-479
dc.relationSilver, D., Lever, G., Heess, N., Degris, T., Wierstra, D., Riedmiller, M. (2014). Deterministic policy gradient algorithms. In ICML
dc.relationSujata, R. (2021). Losses on short positions in U.S. firms top $70 billion - Ortex data. Thomson Reuters. Retrieved from Http:// https://www.reuters.com/
dc.relationSutto, R. and Barto, A. (2018). Reinforcement Learning an Introduction. The MIT Press
dc.relationTaddy, M. (2013). Multinomial Inverse Regression for Text Analysis. Journal of the American Statistical Association, 108(503), 755-770. http://www.jstor.org/stable/24246859
dc.relationTaddy, M. (2013). Measuring Political Sentiment on Twitter: Factor Optimal Design for Multinomial Inverse Regression. Technometrics, 55(4), 415-425. http://www.jstor.org/stable/24586996
dc.relationUhlenbeck, G., and Ornstein, L. (1930). On the theory of the brownian motion. Physical review, 36(5):823
dc.relationUmar, Z., Gubareva, M., Yousaf, I., Ali, S. (2021). A tale of company fundamentals vs sentiment driven pricing: The case of GameStop. Journal of Behavioral and Experimental Finance 30 (2021) 100501 https://doi.org/10.1016/j.jbef.2021.100501
dc.relationUmar, Z., Yousaf, I., Zaremba, A. (2021). Comovements between heavily shorted stocks during a market squeeze: Lessons from the GameStop trading frenzy, Research in International Business and Finance, Volume 58, https://doi.org/10.1016/j.ribaf.2021.101453
dc.relationWankhade, M., Sekhara, A., Kulkarni, C. (2022). A survey on sentiment analysis methods, applications, and challenges. Vol.:(0123456789) Artificial Intelligence Review (2022) 55:5731-5780. https://doi.org/10.1007/s10462-022-10144-1
dc.relationYang L., Liyan, H., Yang, X. (2021). The impact of geopolitical uncertainty on energy volatility. International Review of Financial Analysis, Volume 75, 101743, ISSN 1057-5219, https://doi.org/10.1016/j.irfa.2021.101743
dc.relationYousaf, I., Pham, L., Goodell, J. (2023). The connectedness between meme tokens, meme stocks, and other asset classes: Evidence from a quantile connectedness approach. J. Int. Financ. Markets Inst. Money 82 (2023) 101694. https://doi.org/10.1016/j.intfin.2022.101694
dc.relationZhou, H. and Yu, B. (2020). Information Quality of Reddit Link Posts on Health News. A. Sundqvist et al. (Eds.): iConference 2020, LNCS 12051, pp. 186-197, 2020
dc.rightshttps://repositorio.uniandes.edu.co/static/pdf/aceptacion_uso_es.pdf
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.titleSentiment hedging: Trending stocks on reddit
dc.typeTrabajo de grado - Maestría


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