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
1.A Review of the Manipulation Literature Market manipulation is an issue that is almost as old as the earliest speculative market The prevalence of"pump and dump"or"dump and cover"strategies was widely reported in financial press at the beginning of the 17h century when the Amsterdam Stock Exchange was founded.Even though market manipulation might be much more severe in the early years of financial markets,it is too early to say that manipulation is no longer of importance.In modern financial markets,manipulations are often taken in hidden ways that cannot be easily detected and outlawed.In many emerging markets where market regulations are weak,manipulation is still quite rampant.3 Even in the relatively well- regulated US market,Aggarwal and Wu (2003)have documented hundreds of cases of price manipulation in the 1990s. Following Allen and Gale (1992),we classify manipulation into three categories: information-based manipulation,action-based manipulation,and trade-based manipulation. Information-based manipulation is taken by releasing false information or spreading misleading rumors.The operation of"trading pools"in the United States during the 1920s gives examples of information-based manipulation.A group of investors would combine to form a pool:first to buy a stock,then to spread favorable rumors about the firm,and finally to sell out at a profit.The striking cases of Enron and the Worldcom in 3 For example,China's worst stock-market crime in 2002 was a scheme by seven people, including two former China Venture Capital executives,accused of using $700 million and 1,500 brokerage accounts nationwide to manipulate the company share price. 4 An example of information-based manipulation is the case of Texas Gulf Sulphur Company in the 1960s(Jaffe 1974).In late 1963 drillings by its engineers struck huge mineral deposits. Between November 1963 and mid-April 1964,company officials tried hard to convince the public that the opposite was true,by falsifying evidence,while accumulating company shares and options.On April 12,1964,the company even issued a press release stating that the technical 5
5 1. A Review of the Manipulation Literature Market manipulation is an issue that is almost as old as the earliest speculative market. The prevalence of “pump and dump” or “dump and cover” strategies was widely reported in financial press at the beginning of the 17th century when the Amsterdam Stock Exchange was founded. Even though market manipulation might be much more severe in the early years of financial markets, it is too early to say that manipulation is no longer of importance. In modern financial markets, manipulations are often taken in hidden ways that cannot be easily detected and outlawed. In many emerging markets where market regulations are weak, manipulation is still quite rampant.3 Even in the relatively wellregulated US market, Aggarwal and Wu (2003) have documented hundreds of cases of price manipulation in the 1990s. Following Allen and Gale (1992), we classify manipulation into three categories: information-based manipulation, action-based manipulation, and trade-based manipulation. Information-based manipulation is taken by releasing false information or spreading misleading rumors. The operation of “trading pools” in the United States during the 1920s gives examples of information-based manipulation. A group of investors would combine to form a pool: first to buy a stock, then to spread favorable rumors about the firm, and finally to sell out at a profit.4 The striking cases of Enron and the Worldcom in 3 For example, China's worst stock-market crime in 2002 was a scheme by seven people, including two former China Venture Capital executives, accused of using $700 million and 1,500 brokerage accounts nationwide to manipulate the company share price. 4 An example of information-based manipulation is the case of Texas Gulf Sulphur Company in the 1960s (Jaffe 1974). In late 1963 drillings by its engineers struck huge mineral deposits. Between November 1963 and mid-April 1964, company officials tried hard to convince the public that the opposite was true, by falsifying evidence, while accumulating company shares and options. On April 12, 1964, the company even issued a press release stating that the technical
2001 might also be related to information-based manipulation.Van Bommel (2003) shows the role of rumors in facilitating prce manipulation. Benabou and Laroque (1992)show that if an opportunistic individual has privileged information and his statements are to certain extent viewed as credible by investors,he can profitably manipulate asset markets through strategically distorted announcements. As privileged information is noisy and learning remains incomplete,opportunistic individuals (corporate officers,financial journalists,or "gurus")can manipulate the market repeatedly,even though their manipulation power is limited in the long run by public's constant reassessment of their credibility.In a related article,John and Narayanan(1997)discuss market manipulation through inside information and the role of insider trading regulations.They show that the existing disclosure rule of the Securities and Exchange Commission (SEC)creates incentives for an informed insider to manipulate the stock market by sometimes trading in wrong direction (i.e.,buying with bad news and selling with good news about the firm).By doing so,the insider can effectively reduce the informativeness of his subsequent trade disclosure because the market is not sure whether an insider's buying (selling)indicates good (bad)news. Consequently,the insider maintains his information superiority for a longer period of time and uses it to reap large profits in later periods by trading in the "right"direction. These profits more than make up for the losses suffered by trading in the wrong direction initially.5 Action-based manipulation is based on actions (other than trading)that change the actual evidence was inconclusive;four days-and a large number of shares-later,the company admitted that deposits had in fact been found.Mahoney (1999),however,question the empirical validity of the existence of manipulation in the 1920s. 3 In addition,Vila(1989)presents an example of information-based manipulation where the manipulator shorts the stock,releases false information and then buys back the stock at a lower price. 6
6 2001 might also be related to information-based manipulation. Van Bommel (2003) shows the role of rumors in facilitating price manipulation. Benabou and Laroque (1992) show that if an opportunistic individual has privileged information and his statements are to certain extent viewed as credible by investors, he can profitably manipulate asset markets through strategically distorted announcements. As privileged information is noisy and learning remains incomplete, opportunistic individuals (corporate officers, financial journalists, or “gurus”) can manipulate the market repeatedly, even though their manipulation power is limited in the long run by public’s constant reassessment of their credibility. In a related article, John and Narayanan (1997) discuss market manipulation through inside information and the role of insider trading regulations. They show that the existing disclos ure rule of the Securities and Exchange Commission (SEC) creates incentives for an informed insider to manipulate the stock market by sometimes trading in wrong direction (i.e., buying with bad news and selling with good news about the firm). By doing so, the insider can effectively reduce the informativeness of his subsequent trade disclosure because the market is not sure whether an insider’s buying (selling) indicates good (bad) news. Consequently, the insider maintains his information superiority for a longer period of time and uses it to reap large profits in later periods by trading in the “right” direction. These profits more than make up for the losses suffered by trading in the wrong direction initially.5 Action-based manipulation is based on actions (other than trading) that change the actual evidence was inconclusive; four days— and a large number of shares— later, the company admitted that deposits had in fact been found. Mahoney (1999), however, question the empirical validity of the existence of manipulation in the 1920s. 5 In addition, Vila (1989) presents an example of information-based manipulation where the manipulator shorts the stock, releases false information and then buys back the stock at a lower price
or perceived value of the assets.Bagnoli and Lipman (1996)investigate action-based manipulation using take-over bids.In their model,a manipulator acquires stock in a firm and then announces a take-over bid.This leads to a price run up of the firm's stock.The manipulator therefore is able to sell his stock at the higher price.Of course,the bid is dropped eventually The Securities Exchange Act of 1934 established extensive provisions aimed at eliminating manipulation.By regulating information disclosure and restricting and monitoring the trading activities of the directors,managers,and insiders,the Act has successfully made market manipulation more difficult.The types of manipulation that the Act effectively outlawed are mainly information-based and action-based.As a matter of fact,regulating information disclosure of public companies has now become one of the most important tasks of virtually all securities regulation bodies across the world. Trade-based manipulation,however,is much more difficult to eradicate.It occurs when a large trader or a group of traders attempt to manipulate the price of an asset simply by buying and then selling,without taking any publicly observable action to alter the asset value or releasing false information to change the price.This type of manipulation could be of great importance empirically.Hedge funds often buy and then sell substantial blocks of stock,even though they are apparently not interested in taking over the firm.In our opinion,these large buying/selling activities could be taken sometimes for the purpose of trade-based manipulation. Allen and Gale (1992)build a model showing that trade-based manipulation is possible in a rational expectations framework.The Allen and Gale model has three trading dates (indexed by t=1,2,3)and three types of traders,a continuum of identical rational investors,a large informed trader who enters the market at date 1 if and only if he has 7
7 or perceived value of the assets. Bagnoli and Lipman (1996) investigate action-based manipulation using take-over bids. In their model, a manipulator acquires stock in a firm and then announces a take -over bid. This leads to a price run up of the firm’s stock. The manipulator therefore is able to sell his stock at the higher price. Of course, the bid is dropped eventually. The Securities Exchange Act of 1934 established extensive provisions aimed at eliminating manipulation. By regulating information disclosure and restricting and monitoring the trading activities of the directors, managers, and insiders, the Act has successfully made market manipulation more difficult. The types of manipulation that the Act effectively outlawed are mainly information-based and action-based. As a matter of fact, regulating information disclosure of public companies has now become one of the most important tasks of virtually all securities regulation bodies across the world. Trade-based manipulation, however, is much more difficult to eradicate. It occurs when a large trader or a group of traders attempt to manipulate the price of an asset simply by buying and then selling, without taking any publicly observable action to alter the asset value or releasing false information to change the price. This type of manipulation could be of great importance empirically. Hedge funds often buy and then sell substantial blocks of stock, even though they are apparently not interested in taking over the firm. In our opinion, these large buying/selling activities could be taken sometimes for the purpose of trade-based manipulation. Allen and Gale (1992) build a model showing that trade -based manipulation is possible in a rational expectations framework. The Allen and Gale model has three trading dates (indexed by t =1，2，3) and three types of traders, a continuum of identical rational investors, a large informed trader who enters the market at date 1 if and only if he has
private information,and a large manipulator who observes whether the informed trader has the private information.The manipulator has a small but positive probability to enter the market and to mimic the informed trader's action when the informed trader actually has no private information.The manipulator is able to achieve a positive profit under certain conditions because there can exist a pooling equilibrium in which the investors are uncertain whether a large trader who buys shares is a manipulator or an informed trader.6 Aggarwal and Wu (2003)present a theory and some empirical evidence on stock price manipulation in the United States.Extending the framework of Allen and Gale (1992), they consider what happens when a manipulator can trade in the presence of other rationaltraders who seek out information about the stock's true value.In a market with manipulators,they show more information seekers imply a greater competition for shares, making it easier for a manipulator to enter the market and potentially worsening market efficiency. There are several other articles investigating manipulation.Camerer (1998)tests whether naturally occurring markets can be strategically manipulated using a field experiment with racetrack betting.Kumar and Seppi (1992)develop a model of manipulation in futures markets.Hart (1977)investigates the conditions of equilibrium price process under which manipulation is possible.He considers conditions under which profitable 6 Allen and Gale made several assumptions to make the trade-based manipulation possible in their model.First,the small investors must be much more risk averse than the large traders.The manipulation may not be possible if the informed trader is as risk averse as or even more risk averse than the small rational investors.Second,the probability of manipulation shall be sufficiently small.Third,private information still plays a crucial role in the model.Fourth,the informed trader's trading decision depends on whether he receives the private information,but not on the content of his private information.Namely,when the informed trader receives his private information,he will purchase the same quantity of the stock no matter what he receives is good news or bad news;when he does not receive the private information,he will not enter the market even though he is risk neutral and the expected asset return is positive.To some extent,the informed trader himself seems to be less than fully rational. 8
8 private information, and a large manipulator who observes whether the informed trader has the private information. The manipulator has a small but positive probability to enter the market and to mimic the informed trader’s action when the informed trader actually has no private information. The manipulator is able to achieve a positive profit under certain conditions because there can exist a pooling equilibrium in which the investors are uncertain whether a large trader who buys shares is a manipulator or an informed trader.6 Aggarwal and Wu (2003) present a theory and some empirical evidence on stock price manipulation in the United States. Extending the framework of Allen and Gale (1992), they consider what happens when a manipulator can trade in the presenc e of other rational traders who seek out information about the stock’s true value. In a market with manipulators, they show more information seekers imply a greater competition for shares, making it easier for a manipulator to enter the market and potentially worsening market efficiency. There are several other articles investigating manipulation. Camerer (1998) tests whether naturally occurring markets can be strategically manipulated using a field experiment with racetrack betting. Kumar and Seppi (1992) develop a model of manipulation in futures markets. Hart (1977) investigates the conditions of equilibrium price process under which manipulation is possible. He considers conditions under which profitable 6 Allen and Gale made several assumptions to make the trade-based manipulation possible in their model. First, the small investors must be much more risk averse than the large traders. The manipulation may not be possible if the informed trader is as risk averse as or even more risk averse than the small rational investors. Second, the probability of manipulation shall be sufficiently small. Third, private information still plays a crucial role in the model. Fourth, the informed trader’s trading decision depends on whether he receives the private information, but not on the content of his private information. Namely, when the informed trader receives his private information, he will purchase the same quantity of the stock no matter what he receives is good news or bad news; when he does not receive the private information, he will not enter the market even though he is risk neutral and the expected asset return is positive. To some extent, the informed trader himself seems to be less than fully rational
speculation is possible in an infinite horizon deterministic economy.He finds that manipulation is possible if the economy is dynamically unstable or if demand functions are non-linear and satisfy some technical conditions.Jarrow (1992)extends Hart's analysis to a stochastic setting with time dependent price process.He shows that profitable manipulation is possible if the manipulator can corner the market.He also demonstrates the manipulator can achieve a positive profit if he is able to establish a price trend and trade against it.To conserve space,we are sorry to skip many other important articles in this literature. Our investigation of manipulation is based on a different setup and generates several new insights.First,because our model does not rest on information asymmetry or fundamental risk,manipulation investigated here is therefore purely trade-based.This makes our distinct from information based model such as DSSW.7 Second,our model does not depend on various market frictions discussed in the literature (e.g.,Jarrow 1992),such as corners,short squeezes,etc.Third,and most importantly,we derive the equilibrium price process endogenously by constructing manipulator's trading strategies based on certain well-documented behavioral biases of investors.Theoretically,the large trader can manipulate the price process repeatedly and frequently as long as there are investors who have those behavioral biases specified in the model. The contributions of our work are multi-fold.First,the paper provides an application of behavioral theor ies documented in the literature to endogenously derive several well-known asset pricing anomalies.Second,we provide an additional example of trade-based manipulation,distinct from the model of Allen and Gale (1992)--that does not impose assumptions on information asymmetry or the probability of manipulation. Third,we illustrate a possibility of trade-based manipulation based on realistic 7 See section 4 for a detailed comparison between our model and De Long et al.(DSSW,1990). 9
9 speculation is possible in an infinite horizon deterministic economy. He finds that manipulation is possible if the economy is dynamically unstable or if demand functions are non-linear and satisfy some technical conditions. Jarrow (1992) extends Hart’s analysis to a stochastic setting with time dependent price process. He shows that profitable manipulation is possible if the manipulator can corner the market. He also demonstrates the manipulator can achieve a positive profit if he is able to establish a price trend and trade against it. To conserve space, we are sorry to skip many other important articles in this literature. Our investigation of manipulation is based on a different setup and generates several new insights. First, because our model does not rest on information asymmetry or fundamental risk, manipulation investigated here is therefore purely trade -based. This makes our distinct from information based model such as DSSW. 7 Second, our model does not depend on various market frictions discussed in the literature (e.g., Jarrow 1992), such as corners, short squeezes, etc. Third, and most importantly, we derive the equilibrium price process endogenously by constructing manipulator’s trading strategies based on certain well-documented behavioral biases of investors. Theoretically, the large trader can manipulate the price process repeatedly and frequently as long as there are investors who have those behavioral biases specified in the model. The contributions of our work are multi-fold. First, the paper provides an application of behavioral theories documented in the literature to endogenously derive several well-known asset pricing anomalies. Second, we provide an additional example of trade-based manipulation, distinct from the model of Allen and Gale (1992)--that does not impose assumptions on information asymmetry or the probability of manipulation. Third, we illustrate a possibility of trade-based manipulation based on realistic 7 See section 4 for a detailed comparison between our model and De Long et al. (DSSW, 1990)