{"id":73028,"date":"2025-08-17T10:11:10","date_gmt":"2025-08-17T10:11:10","guid":{"rendered":"https:\/\/www.newsbeep.com\/uk\/73028\/"},"modified":"2025-08-17T10:11:10","modified_gmt":"2025-08-17T10:11:10","slug":"research-on-the-impact-of-algorithmic-trading-on-market-volatility","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/uk\/73028\/","title":{"rendered":"Research on the impact of algorithmic trading on market volatility"},"content":{"rendered":"

Hendershott, T. & Moulton, P. C. Automation, speed, and stock market quality: The NYSE\u2019s hybrid. J Financ Markets 14(4), 568\u2013604 (2011).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Hasbrouck, J. & Saar, G. Low-latency trading. J Financ Markets 16(4), 646\u2013679 (2013).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Carrion, A. Very fast money: High-frequency trading on the NASDAQ. J Financ Markets 16(4), 680\u2013711 (2013).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Ramos, H. P. & Perlin, M. S. Does algorithmic trading harm liquidity? Evidence from Brazil. North Am J Econ Finance 54, 101243 (2020).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Boehmer, E., Fong, K. Y. & Wu, J. Algorithmic trading and market quality: International evidence. J Financ Quant Anal 56(8), 2659\u20132688 (2020).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

J. Brogaard, High frequency trading and its impact on market quality, Northwestern University Kellogg School of Management Working Paper (2010).<\/p>\n

Hagstr\u00f6mer, B. & Nord\u00e9n, L. The diversity of high-frequency traders. J Financ Markets 16(4), 741\u2013770 (2013).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

F. Zhang, High-frequency trading, stock volatility, and price discovery, SSRN (2010), 1691679.<\/p>\n

Kirilenko, A., Kyle, A. S., Samadi, M. & Tuzun, T. The flash crash: High-frequency trading in an electronic market. J. Financ. 72(3), 967\u2013998 (2017).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Hirshleifer, D. Investor psychology and asset pricing. J. Financ. 56(4), 1533\u20131597 (2001).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Fu, J., Wu, X., Liu, Y. & Chen, R. Firm-specific investor sentiment and stock price crash risk. Financ. Res. Lett. 38, 101442 (2021).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Venezia, I., Nashikkar, A. & Shapira, Z. Firm specific and macro herding by professional and amateur investors and their effects on market volatility. J. Bank. Finance 35(7), 1599\u20131609 (2011).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Pushpa, N., Silky, V. K., Anand, J. & Ihor, R. Investor sentiment, market volatility, and ESG index dynamics: an empirical analysis. Cogent Economics & Finance 13(1), 13\u201329 (2025).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Elroi, H. & Haim, K. The impact of retail investor sentiment on the conditional volatility of stocks and bonds: Evidence from the Tel-Aviv stock exchange. Int. Rev. Econ. Financ. 89, 1303\u20131313 (2024).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Rengga, M. P., Asep, J., Nandang, N. & Wanta, W. Investor sentiment and herding in Islamic stocks: An exploration of the moderating role of market capitalization. J Account Invest 26(2), 787\u2013802 (2025).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Hendershott, T., Jones, C. M. & Menkveld, A. J. Does algorithmic trading improve liquidity?. J. Financ. 66(1), 1\u201333 (2011).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Faroop, S., Muhammad, I. & Shiraz, K. Herding behavior and its impact on market volatility: Empirical evidence from the Pakistan stock market. Dialogue Soc Sci Rev 2(4), 218\u2013232 (2024).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Servanna, M. F., Christos, A., Vasileios, P., Emmanouil, S. & Thanos, V. Does algorithmic trading induce herding?. Int. J. Financ. Econ. 27, 385\u2013401 (2024).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Menkveld, A. J. The economics of high-frequency trading: Taking stock. Annu. Rev. Financ. Econ. 8, 1\u201324 (2016).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Hayes, A. F. PROCESS: A versatile computational tool for observed variable mediation, moderation, and conditional process modeling 1\u201339 (Guilford Press, Guilford Press, 2012).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Chen, M. G. The rise and latest research progress of algorithmic trading. Secur. Mark. Her. 9, 11\u201317 (2013).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Xia, Z. B. The new challenge of algorithmic trading to the legal recognition logic of false declaration manipulation. Secur. Mark. Her. 10, 61\u201370 (2017).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Wang, F. Has algorithmic trading improved the pricing efficiency of China\u2019s stock market?. Southern Finance 522, 49\u201364 (2022).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Shiller, R. J. From efficient markets theory to behavioral finance. J Econ Perspect 17(1), 83\u2013104 (2003).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Baker, M. & Wurgler, J. Investor sentiment in the stock market. J Econ Perspect 21(2), 129\u2013152 (2007).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Bouteska, A. & Mili, M. The role of investor sentiment and valuation uncertainty in the changes around analyst recommendations: Evidence from US firms. J. Behav. Financ. 1, 1\u201324 (2021).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Lee, W. Y., Jiang, C. X. & Indro, D. C. Stock market volatility, excess returns, and the role of investor sentiment. J. Bank. Finance 26(12), 2277\u20132299 (2002).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Glasserman, P. & Mamaysky, H. Does unusual news forecast market stress?. J Financ Quant Anal 54(5), 1937\u20131974 (2019).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Sprenger, T. O., Tumasjan, A. & Sandner, P. G. Tweets and trades: The information content of stock microblogs. Eur. Financ. Manag. 20(5), 926\u2013957 (2014).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Da, Z., Engelberg, J. & Gao, P. The sum of all FEARS investor sentiment and asset prices. Rev Financ Stud 28(1), 1\u201332 (2015).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Mehra, R. & Sah, R. Mood fluctuations, projection bias, and volatility of equity prices. J. Econ. Dyn. Control 26(5), 869\u2013887 (2002).<\/p>\n

MathSciNet<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Verma, R. & Verma, P. Noise trading and stock market volatility. J. Multinatl. Financ. Manag. 17(3), 231\u2013243 (2007).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Uygur, U. & Tas, O. Modeling the effects of investor sentiment and conditional volatility in international stock markets. J Appl Financ Bank 2(5), 239 (2012).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Yang, C., Gong, X. & Zhang, H. Volatility forecasting of crude oil futures: The role of investor sentiment and leverage effect. Resour. Policy 61, 548\u2013563 (2019).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Bikhchandani, S. & Sharma, S. Herd behavior in financial markets. IMF Staff. Pap. 47(3), 279\u2013310 (2000).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Avramov, D., Chordia, T. & Goyal, A. The impact of trades on daily volatility. Rev Financ Stud 19(4), 1241\u20131277 (2006).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Cai, F., Han, S. & Li, D. Institutional herding and its price impact: Evidence from the corporate bond market. J. Financ. Econ. 131(1), 139\u2013167 (2019).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Szewczyk, S. H. The intra-industry transfer of information inferred from announcements of corporate security offerings. J. Financ. 47(5), 1935\u20131945 (1992).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Faug\u00e8re, C. & Shawky, H. A. Volatility and institutional investor holdings in a declining market: A study of Nasdaq during the year 2000. J. Appl. Financ. 2, 32\u201342 (2003).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Badrinath, S. G., Gay, G. D. & Kale, J. R. Patterns of institutional investment, prudence, and the managerial” safety-net” hypothesis. J Risk Insurance 1, 605\u2013629 (1989).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Choi, N. & Skiba, H. Institutional herding in international markets. J. Bank. Finance 55, 246\u2013259 (2015).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Gokhale, G. M. & Mittal, A. Exploring the nexus of capital market and investor behaviour: A systematic literature review. Int. J. Econ. Financ. Issues 14(2), 65\u201376 (2024).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Barkha, D., Shallu, B., Vaibhav, A., Mahender, Y. & Pankaj, K. Stock market volatility: A systematic review. J. Model. Manag. 19(3), 57\u201363 (2024).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Ruipeng, L. & Rangan, G. Investors\u2019 uncertainty and forecasting stock market volatility. J. Behav. Financ. 23(3), 327\u2013337 (2022).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Brogaard, J., Hendershott, T. & Riordan, R. High-frequency trading and price discovery. Rev Financ Stud 27(8), 2267\u20132306 (2014).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Malceniece, L., Malcenieks, K. & Putni\u0146\u0161, T. J. High frequency trading and comovement in financial markets. J. Financ. Econ. 134(2), 381\u2013399 (2019).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Hendershott, T., Jones, C. M. & Menkveld, A. J. Does algorithmic trading improve liquidity?. J. Financ. 68(1), 137\u2013175 (2011).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Biais, B., Foucault, T. & Moinas, S. Equilibrium fast trading. J. Financ. 70(3), 967\u20131010 (2015).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Jiang, G. & Zhang, J. High-frequency trading and market quality. Financ. Manage. 46(4), 814\u2013842 (2017).<\/p>\n

MathSciNet<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Baker, M. & Wurgler, J. Investor sentiment and the cross-section of stock returns. J. Financ. 61(4), 1645\u20131680 (2006).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Han, X. & Li, Y. Can investor sentiment be a momentum time-series predictor? Evidence from China. J. Empir. Financ. 42, 212\u2013239 (2017).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Rahman, M. L. & Shamsuddin, A. Investor sentiment and the price-earnings ratio in the G7 stock markets. Pac. Basin Financ. J. 55, 46\u201362 (2019).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Kumar, A. & Lee, C. M. Retail investor sentiment and return comovements. J. Financ. 61(5), 2451\u20132486 (2006).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Lakonishok, J., Shleifer, A. & Vishny, R. W. The impact of institutional trading on stock prices. J. Financ. Econ. 32(1), 23\u201343 (1992).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Ha, Y. & Zhang, H. Algorithmic trading for online portfolio selection under limited market liquidity. Eur. J. Oper. Res. 286(3), 1033\u20131051 (2020).<\/p>\n

MathSciNet<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Chordia, T., Sarkar, A. & Subrahmanyam, A. Liquidity dynamics and cross-autocorrelations. J Financ Quant Anal 1, 709\u2013736 (2011).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Jiang, S. & Jin, X. Effects of investor sentiment on stock return volatility: A spatio-temporal dynamic panel model. Econ. Model. 97, 298\u2013306 (2021).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Graham, J. R. Herding among investment newsletters: Theory and evidence. J. Financ. 54(1), 237\u2013268 (1999).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

P. Gomber, B. Arndt, M. Lutat and T. Uhle, High-frequency trading, SSRN (2011), 1858626.<\/p>\n

Siyuan, Y., Xiaoxu, L., Tian, C., Shengqi, H. & Rong, X. Algorithmic trading and challenges on retail investors in emerging markets. J Econ, Finance, Account Stud 4(3), 36\u201341 (2022).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Tao, C. Algorithmic trading and post-earnings-announcement drift: A cross-country study. Int. J. Account. 58(1), 123\u2013132 (2023).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Brogaard, J., Hendershott, T. & Riordan, R. High frequency trading and the 2008 short-sale ban. J. Financ. Econ. 124(1), 22\u201342 (2017).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n","protected":false},"excerpt":{"rendered":"Hendershott, T. & Moulton, P. C. Automation, speed, and stock market quality: The NYSE\u2019s hybrid. J Financ Markets…\n","protected":false},"author":2,"featured_media":73029,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[12],"tags":[37532,84,37533,4230,1284,467,37534,4231,90,37531,7723,56,54,55],"class_list":["post-73028","post","type-post","status-publish","format-standard","has-post-thumbnail","category-markets","tag-algorithmic-trading","tag-business","tag-financial-market","tag-humanities-and-social-sciences","tag-market-volatility","tag-markets","tag-mediation-model","tag-multidisciplinary","tag-science","tag-scientific-data","tag-statistics","tag-uk","tag-united-kingdom","tag-unitedkingdom"],"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/posts\/73028","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/comments?post=73028"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/posts\/73028\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/media\/73029"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/media?parent=73028"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/categories?post=73028"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/tags?post=73028"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}