Behavior Based Manipulation Chunsheng Zhou Peking University & Jianping Mei New York University This Version:October 03 Zhou is from Guanghua School of Management,Peking University,Beijing 100871,China. E-Mail:zhoucs@gsm.pku.edu.cn.Mei is from Department of Finance,Stern School of Business, New York University,44 West 4th Street,New York,NY 10012-1126,(212)998-0354, jmei@stern.nyu.edu.We are grateful to helpful discussions with Franklin Allen and Wei Xiong. We also thank Bin Liu and Jiagi Tang for able research assistance. 0
0 Behavior Based Manipulation Chunsheng Zhou Peking University & Jianping Mei New York University * This Version: October 03 * Zhou is from Guanghua School of Management, Peking University, Beijing 100871, China. E-Mail: zhoucs@gsm.pku.edu.cn. Mei is from Department of Finance, Stern School of Business, New York University, 44 West 4th Street, New York, NY 10012-1126, (212) 998-0354, jmei@stern.nyu.edu. We are grateful to helpful discussions with Franklin Allen and Wei Xiong. We also thank Bin Liu and Jiaqi Tang for able research assistance
Behavior Based Manipulation Abstract If investors are not fully rational,what can smart money do?This paper provides an example in which smart money can strategically take advantage of investors'behavioral biases and manipulate the price process to make profit.The paper considers three types of traders,behavior-driven investors who have two behavioral biases(momentum trading and dispositional effect),arbitrage urs,and a manipulator who can influence asset prices. We show that,due to the investors'behavioral biases and the limit of arbitrage,the manipulator can profit from a "pump and dump"trading strategy by accumulating the speculative asset while pushing the asset price up,and then selling the asset at high prices. Since nobody has private information,manipulation investigated here is completely trade-based.The paper also endogenously derives several asset pricing anomalies, including excess volatility of asset prices,momentum and reversal. JEL:G12,G18 1
1 Behavior Based Manipulation Abstract If investors are not fully rational, what can smart money do? This paper provides an example in which smart money can strategically take advantage of investors’ behavioral biases and manipulate the price process to make profit. The paper considers three types of traders, behavior-driven investors who have two behavioral biases (momentum trading and dispositional effect), arbitrage urs, and a manipulator who can influence asset prices. We show that, due to the investors’ behavioral biases and the limit of arbitrage, the manipulator can profit from a “pump and dump” trading strategy by accumulating the speculative asset while pushing the asset price up, and then selling the asset at high prices. Since nobody has private information, manipulation investigated here is completely trade-based. The paper also endogenously derives several asset pricing anomalies, including excess volatility of asset prices, momentum and reversal. JEL: G12, G18
Behavioral studies in economics and finance,such as Kahneman and Tversky (1974, 1979,2000),Tversky and Kahneman (1986),Barberis,Shleifer,and Vishny (1998), Thaler(1999),suggest that economic agents are less than fully rational.They are often psychologically biased.Their psychological biases,together with "limits of arbitrage", lead to asset price'deviations from fundamental values and may generate a large number of anomalies that cannot be easily explained in the rational expectations paradigm. While it is important to identify plausible causes for asset pricing anomalies,most investors would be more interested in knowing how to take advantage of other people's behavioral biases to make money.In this paper,we build an equilibrium model to demonstrate how "smart money"can profit from other investors'irrational behaviors. The model has three classes of investors:a manipulator,behavior-driven investors,and arbitrageurs.Behavior-driven investors are not fully rational,whose behavioral biases used in the model are momentum trading and unwillingness to sell losers.These two psychological biases are supported by many theoretical and empirical studies,including Hong and Stein(1999),Odean (1998),Shefrin and Statman(1985),among others. Arbitrageurs play a critical role in preventing large price jumps and market crash,but because of the limits of arbitrage,they cannot fully eliminate asset price's deviation from fundamental value. The manipulator is a large investor who is a price setter rather than a price taker.As a deep-pocket investor,he lures momentum investors into the market by pumping up the stock price and then dumps the stock to make a profit by taking advantage of the disposition effect and the limits of arbitrage. Barberis and Thaler(2003)and Hirshleifer(2001)provide detailed surveys of the behavior literature. 2
2 Behavioral studies in economics and finance, such as Kahneman and Tversky (1974, 1979, 2000), Tversky and Kahneman (1986), Barberis, Shleifer, and Vishny (1998) , Thaler (1999), suggest that economic agents are less than fully rational1 . They are often psychologically biased. Their psychological biases, together with “limits of arbitrage”, lead to asset price’ deviations from fundamental values and may generate a large number of anomalies that cannot be easily explained in the rational expectations paradigm. While it is important to identify plausible causes for asset pricing anomalies, most investors would be more interested in knowing how to take advantage of other people’s behavioral biases to make money. In this paper, we build an equilibrium model to demonstrate how “smart money” can profit from other investors’ irrational behaviors. The model has three classes of investors: a manipulator, behavior-driven investors, and arbitrageurs. Behavior-driven investors are not fully rational, whose behavioral biases used in the model are momentum trading and unwillingness to sell losers. These two psychological biases are supported by many theoretical and empirical studies, including Hong and Stein (1999), Odean (1998), Shefrin and Statman (1985), among others. Arbitrageurs play a critical role in preventing large price jumps and market crash, but because of the limits of arbitrage, they cannot fully eliminate asset price’s deviation from fundamental value. The manipulator is a large investor who is a price setter rather than a price taker. As a deep-pocket investor, he lures momentum investors into the market by pumping up the stock price and then dumps the stock to make a profit by taking advantage of the disposition effect and the limits of arbitrage. 1 Barberis and Thaler (2003) and Hirshleifer (2001) provide detailed surveys of the behavior literature
Numerous empirical studies suggest that there exist trading strategies that can yield positive abnormal returns presumably because of asset pricing errors.For example, Jegadeesh and Titman(1993)report that investors can make substantial abnormal profits by buying past winners and selling past losers2.These studies have several common characteristics.First,they are based all on observed or realized prices.Naturally,the realized prices are the result of interactions among a large number of investors.Therefore, it is difficult to rely only on the empirical studies to identify the roles played by different investors in price determination.Second,the trading strategies such as the momentum trading documented in the empirical literature usually takes the price process as exogenous.This methodology is valid only if the investors who follow these strategies,in total,are price-takers.Investors cannot actively affect price processes for profit-making purpose. A distinctive feature of our model is its explicit investigation of how smart money (the manipulator)interacts with irrational traders and what profit the manipulator makes from exploiting other investors'behavioral biases.In other words,the manipulator in our model manipulates the price process to create more chances for the irrational investors to make mistakes.This is an important feature,but largely assumed away in the existing behavioral finance literature.For instance,Barberis,Shleifer,and Vishny (1998,BSV henceforth)have a representative agent model in which trading does not occur.Daniel, Hirshleifer,and Subrahmanyam(1998,DHS henceforth)consider two classes of traders, the informed (I)and the uninformed (U).However,since prices in their model are set by the risk-neutral informed traders,the formal role of the uninformed is minimal there. Hong and Stein also model two classes of traders--news-watchers and momentum traders. News-watchers only care about what news they observe,while momentum traders make 2 Lesmond,Schill,and Zhou(2003)argue that the profit of the momentum strategy documented by Jegadeesh and Titman is illusory because of transactions costs.Lesmond,Schill and Zhou's result therefore provides positive evidence for the argument of limits of arbitrage." 3
3 Numerous empirical studies suggest that there exist trading strategies that can yield positive abnormal returns presumably because of asset pricing errors. For example , Jegadeesh and Titman (1993) report that investors can make substantial abnormal profits by buying past winners and selling past losers2 . These studies have several common characteristics. First, they are based all on observed or realized prices. Naturally, the realized prices are the result of interactions among a large number of investors. Therefore, it is difficult to rely only on the empirical studies to identify the roles played by different investors in price determination. Second, the trading strategies such as the momentum trading documented in the empirical literature usually takes the price process as exogenous. This methodology is valid only if the investors who follow these strategies, in total, are price-takers. Investors cannot actively affect price processes for profit-making purpose. A distinctive feature of our model is its explicit investigation of how smart money (the manipulator) interacts with irrational traders and what profit the manipulator makes from exploiting other investors’ behavioral biases. In other words, the manipulator in our model manipulates the price process to create more chances for the irrational investors to make mistakes. This is an important feature, but largely assumed away in the existing behavioral finance literature. For instance, Barberis, Shleifer, and Vishny (1998, BSV henceforth) have a representative agent model in which trading does not occur. Daniel, Hirshleifer, and Subrahmanyam (1998, DHS henceforth) consider two classes of traders, the informed (I) and the uninformed (U). However, since prices in their model are set by the risk-neutral informed traders, the formal role of the uninformed is minimal there. Hong and Stein also model two classes of traders--news-watchers and momentum traders. News-watchers only care about what news they observe, while momentum traders make 2 Lesmond, Schill, and Zhou (2003) argue that the profit of the momentum strategy documented by Jegadeesh and Titman is illusory because of transactions costs. Lesmond, Schill and Zhou’s result therefore provides positive evidence for the argument of “limits of arbitrage
decisions based only on price changes.No trader purposefully chooses a trading strategy to take advantage of other people's behavioral biases. Moreover,the price movement in our model is completely trade based.It neither resorts to information asymmetry nor depends on the fundamental risk of the asset.Almost all other behavior-based asset pricing theories,however,depend on fundamental-related information or news in some ways.Here lies the main distinction of our model from De Long,Shleifer,Summers,and Waldmann(1990,DSSW thereafter).As we will discuss subsequently,this feature allows us to investigate purely trade based market manipulation. Finally,our model produces somewhat similar correlations among prices,turnover,and volatility to the model of investor overconfidence by Scheinkman and Xiong (2003).In our model,the manipulator's strategic action,together with other investors'behavioral biases,not only brings the manipulator himself profit,but also brings about excess volatility,excess trading,short-term price continuation,and long-term price reversal.This feature helps us to further understand why investors trade and why asset prices sometimes fluctuate continually without any significant news on earnings and other fundamental variables.It also provides a purely trade-based explanation on some well known empirical anomalies,such as price momentum and reversal. The rest of the paper is structured as follows.The next section reviews the literature of manipulation.Section 2 sets up the theoretical model.Section 3 solves the model for the “pump and dump”strategy and then extends the model to include the“dump and cover” strategy..Section 4 investigates the implications of the model on several well-known asset pricing anomalies.Section 5 provides some empirical evidence from recent studies of market manipulation that is consistent with our model.Section 6 concludes
4 decisions based only on price changes. No trader purposefully chooses a trading strategy to take advantage of other people’s behavioral biases. Moreover, the price movement in our model is completely trade based. It neither resorts to information asymmetry nor depends on the fundamental risk of the asset. Almost all other behavior-based asset pricing theories, however, depend on fundamental-related information or news in some ways. Here lies the main distinction of our model from De Long, Shleifer, Summers, and Waldmann (1990, DSSW thereafter). As we will discuss subsequently, this feature allows us to investigate purely trade based market manipulation. Finally, our model produces somewhat similar correlations among prices, turnover, and volatility to the model of investor overconfidence by Scheinkman and Xiong (2003). In our model, the manipulator’s strategic action, together with other investors’ behavioral biases, not only brings the manipulator himself profit, but also brings about excess volatility, excess trading, short-term price continuation, and long-term price reversal. This feature helps us to further understand why investors trade and why asset prices sometimes fluctuate continually without any significant news on earnings and other fundamental variables. It also provides a purely trade-based explanation on some well known empirical anomalies, such as price momentum and reversal. The rest of the paper is structured as follows. The next section reviews the literature of manipulation. Section 2 sets up the theoretical model. Section 3 solves the model for the “pump and dump” strategy and then extends the model to include the “dump and cover” strategy.. Section 4 investigates the implications of the model on several well-known asset pricing anomalies. Section 5 provides some empirical evidence from recent studies of market manipulation that is consistent with our model. Section 6 concludes