Skip to content

Behavioral Finance:Two Cases of Stock Price Manipulation

By Nguyen Nguyen–On November 6th, 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 “trade on noise as if it were information”(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 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.

Twitter- Craig’s case

According to SEC, James Alan Craig (“Craig”) committed “securities fraud by making false statement about publicly traded companies in order to manipulate the price of these companies’ exchange-trade securities.” 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’s investigation to Audience, Inc., was all Craig needed to cause Audience’s 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.’s drug trial papers and that “certain trial results were tainted”, causing this company’s stock sharply dropped by 16%. Craig allegedly made profits by buying those companies’ stocks after the false rumors and selling them when the prices were recovered.

PennyStockChaser.com- McKeown and Ryan’s case

In 2010, McKeown and Ryan were accused of using a website called PennyStockChaser.com to “tout 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.” 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.

Market Inefficiency

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:

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!– which should have not been the case in efficient markets.

Second, investors suffer from psychological biases. One of those biases was “the tendency to buy attention-grabbing stocks.” (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’ attention a limited numbers of so-called highly undervalued stocks. When a stock price had been “pumped” after a promotion campaign, it was “dumped” 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 “tulip mania” in the Netherlands in the 1630s when tulip prices were pushed to unprecedented highs (the price of a single flower exceeded a skilled worker’s 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’ minds, calling on them not only to buy those “good stocks” but also to buy them fast. The same analogy applies to the case of Craig’s. 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- “judgment based on stereotypes” (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 naïve in making an investment decision or were suffering from the representativeness effect where they assumed expert’s 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.

Final thought

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: “If human behavior can partly justify the market inefficiency, wouldn’t it be time for it to be formally accepted in traditional finance models?”

 

Nguyen Nguyen
University of St. Thomas–Master of Science in Finance (candidate)

 

References

Barber, Brad M., Terrance Odean, and Ning Zhu. “Systematic noise.” Journal of Financial Markets. 2009. Print.

Barberis, Nicholas, Andrei Shleifer, and Robert Vishny. “A model of investor sentiment.” Journal of Financial Economics. Vol.49. 1998. Print.

Black, Fisher. “Noise.” The Journal of Finance. Vol.44. 1985. Print.

Nofsinger, John R. The psychology of investing. New Jersey: Prentice Hall, 2014. Print.

Shiller, Robert J. “From Efficient Markets Theory to Behavioral Finance.” The Journal of Economic Perspectives. Vol.17. 2003. Print.

Thaler, Richard H. “The End of Behavior Finance.” Financial Analysts Journal. Vol.55. 1999. Print.

U.S. Securities and Exchange Commission. Complaint. Case No.CV-15-. California: GPO, 2015. Print.

U.S. Securities and Exchange Commission. Complaint. Case No.10-80748. Florida: GPO, 2010. Print.

 

 

 

share this post

Community

Discipline

Goodness

Knowledge

Never miss an update...

Subscribe to the CSB Blog!