{"id":459,"date":"2015-12-04T21:55:49","date_gmt":"2015-12-04T21:55:49","guid":{"rendered":"http:\/\/blogs.stthom.edu\/cameron\/?p=459"},"modified":"2017-04-13T20:53:55","modified_gmt":"2017-04-13T20:53:55","slug":"behavioral-financetwo-cases-of-stock-price-manipulation","status":"publish","type":"post","link":"https:\/\/blogs.stthom.edu\/cameron\/behavioral-financetwo-cases-of-stock-price-manipulation\/","title":{"rendered":"Behavioral Finance:Two Cases of Stock Price Manipulation"},"content":{"rendered":"

By Nguyen Nguyen–On November 6th<\/sup>, the financial world was flooded with news of the indictment of a man using Twitter to manipulate stock market prices. It rang the bells of behavioral finance: noise trading, overreaction, and psychological biases. It is not new that individual investors \u201ctrade on noise as if it were information\u201d(Black, 1986). However, the amount of damage that noise trading caused to the market is shocking: more than $1.6 million in the course of two days. If one looks back to five year ago when SEC filed its complaint of a similar case on PennyStockChaser.com<\/a> regarding market manipulation using social media to make an approximate profit of $2.4 millions, it seems that the lessons learned back then had been forgotten. Discussed below are two cases of stock market price manipulation using social media and justifications of these from a behavioral finance perspective.<\/p>\n

Twitter- Craig\u2019s case<\/strong><\/p>\n

According to SEC, James Alan Craig (\u201cCraig\u201d) committed \u201csecurities fraud by making false statement about publicly traded companies in order to manipulate the price of these companies\u2019 exchange-trade securities.\u201d Specifically, in 2013, Craig mimicked the Twitter accounts of two securities research firms: Muddy Watters Research, and Citron Research. On January 2013, ninety minutes and eight phony tweets regarding an undergone Department of Justice\u2019s investigation to Audience, Inc., was all Craig needed to cause Audience\u2019s stock price to plummet approximately 28%. The next day, Craig, again used his fake research firm Twitter accounts, spread a false statement that the Food and Drug Administration had seized the Therapeutics, Inc.\u2019s drug trial papers and that \u201ccertain trial results were tainted\u201d, causing this company\u2019s stock sharply dropped by 16%. Craig allegedly made profits by buying those companies\u2019 stocks after the false rumors and selling them when the prices were recovered.<\/p>\n

PennyStockChaser.com- McKeown and Ryan\u2019s case <\/strong><\/p>\n

In 2010, McKeown and Ryan were accused of using a website called PennyStockChaser.com to \u201ctout United Stated microcap companies, while at the same time clandestinely selling millions of shares of the same companies to profit from the demand they help create through their touting.\u201d According to SEC, McKeown and Ryan claimed that PennyStockChaser.com was a public investment recommendation tool supported by a group of investment experts who conducted thorough market researches and provided individual investors with best buying recommendations. Within the year of 2009, the website touted and successfully sold 74 penny stocks, making at least $2.4 million from this scalping.<\/p>\n

Market Inefficiency<\/strong><\/p>\n

What was observed from the market reaction was not consistent with the efficient market hypothesis, leaving room for some justifications from a behavioral finance perspective. A false statement was capable of causing changes in stock prices as investors updated their beliefs, but the drop of 28% and 16% in the prices within 90 minutes were overly dramatic. If numbers could talk, there would be at least two things they would probably tell us:<\/p>\n

First, investors overreact to bad news. Barberis, Shleifer, and Vishny (1998) consider investor sentiment as one of variables of a stock price evaluation. The more weighted investor sentiment is, the further stock price derives from its intrinsic value. The shocking rising trade volume of 840,000 shares after the phony tweets from 77,000 shares the previous day indicates investor sentiment. People traded too much!\u2013 which should have not been the case in efficient markets.<\/p>\n

Second, investors suffer from psychological biases. One of those biases was \u201cthe tendency to buy attention-grabbing stocks.\u201d (Barber et al, 2009) This bias was partly responsible for the infamous success of PennyStockChaser.com couple years ago. Out of hundred or thousand stocks, this website brought to investors\u2019 attention a limited numbers of so-called highly undervalued stocks. When a stock price had been \u201cpumped\u201d after a promotion campaign, it was \u201cdumped\u201d immediately, making profits for those who were behind the stage curtain. Another bias that tempted individual investors into irrational decision-making process might very well be the irrational exuberance (Shiller, 2003). Let us not forget the \u201ctulip mania\u201d in the Netherlands in the 1630s when tulip prices were pushed to unprecedented highs (the price of a single flower exceeded a skilled worker\u2019s annual income) due to the power of word of mouth. Nearly five decades later, by fraudulently matching Facebook and Twitter stock successes with the stocks it was promoting, PennyStockChaser.com created hype in investors\u2019 minds, calling on them not only to buy those \u201cgood stocks\u201d but also to buy them fast. The same analogy applies to the case of Craig\u2019s. As soon as investors realized the sudden massive trade volume of Audience stock, they rushed into dumping it without considering either the fundamental value of the stock or the authenticity of the news. That was sadly dangerous! Another psychological bias that could be used to explain the shocking market reaction is the representativeness- \u201cjudgment based on stereotypes\u201d (Nofsinger, 2014). The human brain tends to make short cuts in decision-making by simply classifying information into different mental boxes containing a group of similar characteristics. Keep in mind one common factor in our two cases: both claimed to provide information in the name of market researchers and investment experts. It sounds ridiculous to trust a random cyber source because everyone can claim to be anyone on the internet. However, what shocking is that people believed those claims. Even if those claims were true, investors were either too na\u00efve in making an investment decision or were suffering from the representativeness effect where they assumed expert\u2019s advice were better than their own judgments. I choose to believe the second possibility. Professionals are more sophisticated than average people in giving investment advice. There is nothing wrong with getting advice from them. However, this advice should be absorbed through a critical filter of rational thought. The more educated we become, the better chance we have of being able to get past our psychological biases.<\/p>\n

Final thought<\/strong><\/p>\n

Sixteen years ago, Thaler (1999) predicted the essence of behavioral finance. He said there would come a time when we would no longer classify behavioral finance as a separate branch but rather see it in the same light of finance itself. The idea of taking human element into our finance explanation proves its validity over time. Ultimately, the remaining question is: \u201cIf human behavior can partly justify the market inefficiency, wouldn\u2019t it be time for it to be formally accepted in traditional finance models?\u201d<\/p>\n

 <\/p>\n

Nguyen Nguyen<\/a>
\nUniversity of St. Thomas–Master of Science in Finance (candidate)<\/p>\n

 <\/p>\n

References<\/strong><\/p>\n

Barber, Brad M., Terrance Odean, and Ning Zhu. \u201cSystematic noise.\u201d Journal of Financial Markets<\/em>. 2009. Print.<\/p>\n

Barberis, Nicholas, Andrei Shleifer, and Robert Vishny. \u201cA model of investor sentiment.\u201d Journal of Financial Economics<\/em>. Vol.49. 1998. Print.<\/p>\n

Black, Fisher. \u201cNoise.\u201d The Journal of Finance<\/em>. Vol.44. 1985. Print.<\/p>\n

Nofsinger, John R. The psychology of investing<\/em>. New Jersey: Prentice Hall, 2014. Print.<\/p>\n

Shiller, Robert J. \u201cFrom Efficient Markets Theory to Behavioral Finance.\u201d The Journal of Economic Perspectives<\/em>. Vol.17. 2003. Print.<\/p>\n

Thaler, Richard H. \u201cThe End of Behavior Finance.\u201d Financial Analysts Journal<\/em>. Vol.55. 1999. Print.<\/p>\n

U.S. Securities and Exchange Commission. Complaint<\/em>. Case No.CV-15-. California: GPO, 2015. Print.<\/p>\n

U.S. Securities and Exchange Commission. Complaint<\/em>. Case No.10-80748. Florida: GPO, 2010. Print.<\/p>\n

 <\/p>\n

 <\/p>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

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