SEARCH

SEARCH BY CITATION

REFERENCES

  • Admati, A.R. and P.C. Pfleiderer (2001), ‘Disclosing Information on the Internet: Is It Noise or Is It News?’, Technical Report (Graduate School of Business, Stanford University).
  • Aggarwal, R.K. and G. Wu (2006), ‘Stock Market Manipulations’, Journal of Business, Vol. 79, No. 4, pp. 191553.
  • Antweiler, W. and M.Z. Frank (2004), ‘Is all that Talk Just Noise? The Information Content of Internet Stock Message Boards’,Journal of Finance, Vol. 59, No. 3, pp. 125995.
  • Brock, W., J. Lakonishok and B. LeBaron (1992), ‘Simple Technical Trading Rules and the Stochastic Properties of Stock Returns’, Journal of Finance, Vol. 47, No. 5, pp. 173164.
  • Chan, W.S. (2003), ‘Stock Price Reaction to News and No-news: Drift and Reversal after Headlines’, Journal of Financial Economics, Vol. 70, No. 2, pp. 22360.
  • Cook, D.O. and X. Lu (2009), ‘Information Matters, Noises Don’t: Internet Message Boards Affect Stock Returns’, Working Paper (University of Alabama).
  • Cowan, A.R. (1992), ‘Nonparametric Event Study Tests’, Review of Quantitative Finance and Accounting, Vol. 2, No. 4, pp. 34358.
  • Cowan, A.R., N. Nayar and A.K. Singh (1990), ‘Stock Returns Before and After Calls of Convertible Bonds’, Journal of Financial and Quantitative Analysis, Vol. 25, No. 4, pp. 54954.
  • Daniel, K. and S. Titman (1997), ‘Evidence on the Characteristics of Cross Sectional Variation in Stock Returns’, Journal of Finance, Vol. 52, No. 1, pp. 133.
  • Daniel, K., D. Hirshleifer and A. Subrahmanyam (1998), ‘Investor Psychology and Security Market Under- and Over-Reactions’, Journal of Finance, Vol. 53, No. 6, pp. 183985.
  • Das, S.R. and M.Y. Chen (2007), ‘Yahoo! For Amazon: Sentiment Extraction from Small Talk on the Web’, Management Science, Vol. 53, No. 9, pp. 137588.
  • Das, S.R., A. Fa. De. Martinez-Jerez and P. Tufano (2005), ‘eInformation: A Clinical Study of Investor Discussion and Sentiment’, Financial Management, Vol. 34, No. 3, pp. 10337.
  • DeMarzo, P., D. Vayanos and J. Zwiebel (2003), ‘Persuasion Bias, Social Influence, and Uni-dimensional Opinions’, Quarterly Journal of Economics, Vol. 118, No. 3, pp. 90967.
  • Eren, N., H.N. Ozsoylev and P.E. Street (2009), ‘Hype and Dump Manipulation’, Working Paper (University of Minnesota).
  • Estabrooks, A., T. Jo and N. Japkowicz (2004), ‘A Multiple Resampling Method for Learning from Imbalances Data Sets’, Computational Intelligence, Vol. 20, No. 1, pp. 1836.
  • Fama, E.F. and K.R. French (1992), ‘The Cross-Section of Expected Stock Returns’, Journal of Finance, Vol. 47, No. 2, pp. 42765.
  • George, T.J. and C.Y. Hwang (2004), ‘The 52-week High and Momentum Investing’, Journal of Finance, Vol. 59, No. 5, pp. 214575.
  • Gu, B., P. Konana, A. Liu, B. Rajagopalan and J. Ghosh (2006), ‘Predictive Value of Stock Message Board Sentiments’, Working Paper (University of Texas at Austin).
  • Hirschey, M., V.J. Richardson and S. Scholz (2000), ‘Stock-Price Effects of Internet Buy-Sell Recommendations: The Motley Fool Case’, Financial Review, Vol. 35, No. 2, pp. 14774.
  • Japkowicz, N. and S. Stephen (2002), ‘The Class Imbalance Problem: A Systematic Study’, Intelligent Data Analysis Journal, Vol. 6, No. 5, pp. 42950.
  • Jiang, G., P.G. Mahoney and J. Mei (2005), ‘Market Manipulation: A Comprehensive Study of Stock Pools’, Journal of Financial Economics, Vol. 77, No. 1, pp. 14770.
  • Jones, C.M, G. Kaul and M.L. Lipson (1994), ‘Transactions, Volume and Volatility’, Review of Financial Studies, Vol. 7, No. 4, pp. 63151.
  • Keasler, T.R. and C.R. McNeil (2010), ‘Mad Money Stock Recommendations: Market Reaction and Performance’, Journal of Economics and Finance, Vol. 34. No. 1, pp. 122.
  • Khwaja, A.I. and A. Mian (2005), ‘Unchecked Intermediaries: Price Manipulation in an Emerging Stock Market’, Journal of Financial Economics, Vol. 78, No. 1, pp. 20341.
  • Klibanoff, P., O. Lamont and T.A. Wizman (1998), ‘Investor Reaction to Salient News in Closed-End Country Funds’, Journal of Finance, Vol. 53, No. 2, pp. 67399.
  • Korczak, A., P. Korczak and M. Lasfer (2010), ‘To Trade or Not to Trade: The Strategic Trading of Insiders Around News Announcements’, Journal of Business Finance & Accounting, Vol. 37, Nos. 3 & 4, pp. 36907.
  • Koski, J.L, E.M. Rice and A. Tarhouni (2007), ‘Noise Trading and Volatility: Evidence from Day Trading and Message Boards’, Working Paper (University of Washington).
  • Kumar A. and C.M.C. Lee (2003), ‘Individual Investor Sentiment and Comovement in Small Stock Returns’, Working Paper (Cornell University).
  • Kyle, A.S. and S. Viswanathan (2008), ‘How to Define Illegal Price Manipulation’, American Economic Review, Vol. 98, No. 2, pp. 27479.
  • Lakonishok, J. and S. Smidt (1986), ‘Volume for Winners and Losers: Taxation and Other Motives for Stock Trading’, Journal of Finance, Vol. 41, No. 4, pp. 95174.
  • Lee, C.M.C. and B. Radhakrishna (2000), ‘Inferring Investor Behavior: Evidence from TORQ Data’, Journal of Financial Markets, Vol. 3, No. 2, pp. 83111.
  • Lewis. D.D. (1998), ‘Naive Bayes at Forty: The Independence Assumption in Information Retrieval’, In Proceedings of the European Conference on Machine Learning, pp. 415.
  • MacKinlay, A. C. (1997), ‘Event Studies in Economics and Finance’, Journal of Economic Literature, Vol. 35, No. 1, pp. 1339.
  • McCallum, A.K. (1996), ‘Bow: A Toolkit for Statistical Language Modeling, Text Retrieval, Classification and Clustering’ (http://www.cs.cmu.edu/~mccallum/bow).
  • McCallum, A.K. and K. Nigam (1998), ‘A Comparison of Event Models for Naive Bayes Text Classification’, in Proceedings of the AAAI-98 Workshop on Learning for Text Categorization, pp. 4148.
  • Orens, R., W. Aerts and D. Cormier (2010), ‘Web-Based Non-Financial Disclosure and Cost of Finance’, Journal of Business Finance & Accounting, Vol. 37, Nos. 9 & 10, pp. 105793.
  • Neumann, J.J. and P.M. Kenny (2007), ‘Does Mad Money Make the Market go Mad? Quarterly Review of Economics and Finance, Vol. 47, No. 5, pp. 60215.
  • Patell, J.M. (1976), ‘Corporate Forecasts of Earnings per Share and Stock Price Behavior: Empirical Test’, Journal of Accounting Research, Vol. 14, No. 2, pp. 24676.
  • Rubin, A. and E. Rubin (2010), ‘Informed Investors and The Internet’, Journal of Business Finance & Accounting, Vol. 37, Nos. 7 & 8, pp. 84165.
  • Scholes, M. and J. Williams (1977), ‘Estimating Betas from Nonsynchronous Data’, Journal of Financial Economics, Vol. 5, No. 3, pp. 30927.
  • Sebastiani, F. (2002), ‘Machine Learning in Automated Text Categorization’, ACM Computing Surveys, Vol. 34, No. 1, pp. 147.
  • Shiller, R.J. (1995), ‘Conversation, Information, and Herd Behavior’, American Economic Review, Vol. 85, No. 2, pp. 18185.
  • Strong, N. (1992), ‘Modelling Abnormal Returns: A Review Article’, Journal of Business Finance & Accounting, Vol. 19, No. 4, pp. 53353.
  • Tumarkin, R. (2002), ‘Internet Message Board Activity and Market Efficiency: A Case Study of The Internet Service Sector using RagingBull.com’, Financial Markets, Institutions and Instruments, Vol. 11, No. 4, pp. 31335.
  • Tumarkin, R. and R.F. Whitelaw (2001), ‘News or Noise? Internet Message Board Activity and Stock Prices’, Financial Analyst Journal, Vol. 57, No. 3, pp. 4151.
  • van Bommel, J. (2003), ‘Rumors’, Journal of Finance, Vol. 58, No. 4, pp. 1499520.
  • Vilardo, M.F. (2004), ‘Online Impersonation in Securities Scams’, IEEE Security and Privacy, Vol. 2, No. 3, pp. 8285.
  • White, H.L. (1980), ‘A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity’, Econometrica, Vol. 48, No. 4, pp. 81738.
  • Wysocki, P.D. (1999), ‘Cheap Talk on the Web: The Determinants of Postings on Stock Message Boards’, Working Paper (University of Michigan).
  • Wysocki, P.D. (2000), ‘Private Information, Earnings Announcements and Trading Volume’, Working Paper (MIT Sloan School of Management).
  • Zhang, Y. and P.E. Swanson (2010), ‘Are Day Traders Bias Free? Evidence from Internet Stock Message Boards’, Journal of Economics and Finance, Vol. 34, No. 1, pp. 96112.