Regulatory Responses to Short Selling

Regulatory Responses to Short SellingAbstractIt is commonly believed that unessential market legal injurys is non just a side show up beca persona they contain education that facilitates the efficient tryst of resources. The feedback loop to a real investiture decisions al first gears a brusk marketer to make a moolah even in the absence of a fundamental information. This paper analyzes the regulation of manipulative goldbrick make ou put forwardg is to cut down a cost on short sales. Through setting the short merchandising cost at an appropriate level, regulators may be able to drive the untaught diver, but not the negatively informed speculator, out of the market, and, thus mitigate the investment efficiency.One of the most fundamental roles of prices is to facilitate the efficient allocation of incomparable resouces (Hayek, 1945). A pecuniary market is a place where many speculators with different pieces of infomation meet to share, attempting to profit from their information. Prices aggregate there diverse pieces of information and ultimately reflect an accurate assessment of soused rate. Real decision clerics (such as managers, not bad(p) providers, directors, customers, regulators, employees, etc.) will learn from this information and use it to guide their decisions, in turn bear upon crocked cash flows and values (Baumol 1965). In an efficient market, at any point in time market prices of securities provide accurate signals for resource allocation that is, firms can make production-investment decisions according to note price (Fama Miller 1972).Unlike the traditional models where prices only reflect judge cash flows, in the new models that interconnected feedback military unit prices both happen upon and reflect firm cash flow. The feedback effect can explain this by two expressions, several papers in the belles-lettres generate related implication based on models with exogenous feedback, i.e., where firm value or fir ms investment decison is assumed to be mechanically tied to the price (Khanna Sonti 2004 and Ozdenoren Yuan 2008). However, our focus here is on models that exhibit endogenous feedback, i.e, via learning or incentives. The latter one is through which financail markets may draw real cause is by affecting a decision makers incentives to take real decisions, this is most relevant for firm managers, whose compensation is tied to the firms sh atomic number 18 price, in some feel is a way to discourage agency problem. Particularly, the former one is what we interested here, real decision makers learn from stock price and use it to affect real decision.The theoretical research on financial markets traditionally treats the real side of the firm as exogenous. Milgrom Stokey (1982) consider that if cash flows ar exogenous, the only way to generate trade is to introduce noise traders in the model. Grossman Stiglitz (1980) Hellwig (1980) developed rational expectations pitiser models of financial market, in which prices preform a well-articulated role in transferral information from the informed to the uninformed. Kyle (1985) developed a model that is closer to a game-theoretic approch, where the equilibrium concept is similar to the Bayesian-Nash Equilibrium, the information of speculator gets partially reflected in the stock price. However, Fishman Hagerty (1992) Leland (1992) Khanna, Slezak Bradley (1994) and Bernhardt, Hollifield Hughson (1995) arrange models where different types of speculators-insiders and outsiders-trade on their information, in these models, real decison makers learn from price, but, there is a conflict between limiting insider art reduces price efficiency and supporting(a) outsider profession reduces adverse selection. Similarly, Boot Thakor (1997) and Subrahmanyam Titman (1999) use the feedback effect to rationalize a firms choice to issue publicly traded securities, rather than receving private financing (e.g., from a bank). The traditional view of financial market is stock price has no real effect, thus speculator cannot manipulate stock price to get profit. It is very much hard to generate manipulation as an equilibrium phenomennon, given that price impact will cause a manpulator to sell at a low price and buy at a high price and hence lose money overall (Jarrow 1992). Goldstein Guembel (2008) consider a model where the manager of firm learns from the stock price about the profitability of an investment project, thus, manipulation arise as an equilibrium phenomenon. Even the speculator has no information, she can drriven the price kill to make the manager belive that there exist negative information, and led to cancel the investment, thus, she can get profit from her short position. Edmans, Goldstein Jiang (2014) extent their model to show that informed speculators are less likely to trade on bad news rather than good news. Consider a speculator who has negative information, if she short sell to l ower the stock price, the manager will learn from it to take corrective action such as reducing investment, downsizing the firm makes it efficient and improve the firms fundamental value, but this reducing the profitability of speculators short position. Thus, the informed speculator must consider this and refrain her short selling in the first place.The feedback effect has also some empirical supports. Luo (2005) show the companies seem to learn from the market during MA. Companies are more likely to learn in pre-agreement deals than in agreement deals. Companies are more likely to learn in non-high-tech deals than in high-tech deals. Smaller bidders are more likely to learn than are larger bidders. Kau, Linck Rubin (2008) extend his epitome and show that such learning is more likely when governance mechanisms are in place to reduce the agency problem between manager and the shareholders. Chen, Goldstein Jiang (2007) show that the sensitivity of investment to price is stronger w hen there is more private information incorporate into price.Our paper is continue the research question raised by Goldstein Guembel (2008), they provid an asymmetrical model to explaine the uninformed speculator can manipulate the stock price to make profit and they suggest by impose a cost on short sales may eliminate this phenomenon, but they didnt anaysis the impact of short selling cost. Conditional the speculator being uninformed, the speculator can make profit for two reasons. First, he knows that the market will not improve the allocation of resources. Thus, he can sell at a price that is higher than the expected value. Second, the speculator can profit by establishing a short position in the stock and subsequently driving down the firms stock price by kick upstairs short sales. In our analysis of short selling cost can deter the second sources of the uninformed speculators profit.The remainder of the paper is structured as follows. Section 2 gives a brief summary of regu latory response to short selling during the financial crises of 2007-2009 and the European monarch debt crisis of 2011. Section 3 present the model set-up. Section 4 we derive the benchmark equilibrium when absent the feedback. Section 5 derive the equilibrium when the feedback present. Section 6 concludes. All proofs are in the Appendix.2 Recent regulatory response to short sellingAs a go of the financial market turmoil in 2008, the due south and a number of international financial market regulators put in effect a number of new rules regarding short selling. In July the SEC issued an mite order banning so-called naked short sellingIn a naked short-sale transaction, the short seller does not borrow the share before entering the short position. In our model, we can consider the short selling cost is zero is a naked short-sale. in the securities of Fannie Mae, Freddie Mac, and primary dealers at commercial and investment banks. In total 18 stocks were included in the ban, which t ook effect on Monday July 21 and was in effect until August 12.On September 19 2008, the SEC illegalise all short selling of stocks of financial companies. This much broader ban initially included a total of 799 firms, and more firms were added to this list over time. In a introducement regarding the ban, SEC Chairman Christopher Cox said, The Commission is committed to using every weapon in its arsenal to combat market manipulation that threatens investors and capital markets. The emergency order temporarily banning short selling of financial stocks will restore equilibrium to markets. This action, which would not be necessary in a well-functioning market, is temporary in nature and part of the comprehensive set of steps being taken by the Federal Reserve, the Treasury, and the Congress. This broad ban of all short selling in financial institutions was initially set to expire on October 2, but was extended until Wednesday October 9, i.e., three days after the emergency legislatio n (the bailout package) was passed.In addition to measures taken by the SEC, a number of international financial regulators also acted in response to short selling. On September 21 2008, Australia temporarily banned all forms of short selling, with only market makers in options markets allowed to take covered short positions to hedge. In Great Britain, the Financial Services Authority (FSA) enacted a moratorium on short selling of 29 financial institutions from September 18 2008 until January 16 2009. Also Germany, Ireland, Switzerland and Canada banned short selling of some financial stocks, plot of land France, the Netherlands and Belgium banned naked short selling of financial companies.International restrictions on short selling of financial stocks reappeared in 2011. In August of 2011, market regulators in France, Spain, Italy and Belgium imposed temporary restrictions on the short selling of certain financial stocks as European banks came under increasing pressure as part of the sovereign debt crisis in Europe. For example, both Spain and Italy imposed a temporary bans on new short positions, or increases in existing short positions, for a number of financial shares. France temporarily restricted short selling for 11 companies, including Axa, BNP Paribas and Credit Agricole. On August 26, France, Italy and Spain extended their temporary bans on short selling until at to the lowest degree the end of September.Of course, measures against short selling are not exclusive to these recent episodes. In response to the market crash of 1929, the SEC enacted the uptick rule, which restricts traders from selling short on a downtick. In 1940, legislation was passed that banned mutual funds from short selling. Both of these restriction were in effect until 2007. Going back even further in time, the UK banned short selling in the 1630s in response to the Dutch tulip mania.We revisit the model in Goldstein Guembel (2008). Consider an economy with four dates tin0,1,2 ,3and a firm whose stock is traded in the financial market. The firms manager needs to take an investment decision. In t=0, a risk-neutral speculator may learn private information about the state of the world omegathat determines the profitability of the firms investment opportunity. Trading in the financial market occurs in t=1and t=2.The speculator may suffers a short selling cost c(c0)when he short sales. In addition to the speculator, two different types of agents participate in the financial market noise traders whose trades are unrelated to the realization of omegaand a risk-neutral market maker. The latter collects the orders from the speculator and the noise traders and sets a price at which he executes the order out of his inventory. The information of the speculator may get reflected in the price via the trading process. In t=3,the managers takes the investment decision, which may be affected by the stock price realizations. Finally, all uncertainty is realized and pay-of fs are made.Suppose that the firm has an investment opportunity that requires a fixed investment at the amount of K.There are two possible states omegainl,hthat occur with equal probabilities. Firm valueTo simplifier the model, we do not include the assets in place in the expressions for the value of the firm, even including it will not affect our analysis. can be expressed as a function V(omega,k)of the underlying state omegaand the investment decision kin0,KThere is one speculator in the model. In t=0,with probability alpha,the speculator receives a perfectly informative private signal sinl,hregarding the state of the world omega.With probability 1-alphahe receives no signal, which we denote as s=phi.There are two trading dates t=1,2.In individually trading date, the speculator submits orders u_tin-1,0,1to a market maker. There is a exogenous noise trader who submits orders n_t=-1,0,1with equal probabilities. The market maker only observes total order flow Q_t=n_t+u_t,and theref ore possible order flows are Q_t=-2,-1,0,1,2.Moreover, it is assumed that a market maker faces Bertrand competition and thus sets the price for an asset equal to its expected value, given his information set p_1(Q_1)=EVmid Q_1and p_2(Q_1,Q_2)=EVmid Q_1,Q_2.In our model, the price is a function of total order flows, thus, to ease the exposition, we assume that the speculator observes Q_1,and therefore can directly condition his t=2trade on Q_1instead of p_1.Similarly, the firm manager observes Q_1and Q_2, and may use them in his investment decision. The equilibrium concept we use is the Perfect Bayesian Nash equilibrium. Here, it is defined as follows A trading schema by the speculator u_1(s)and u_2(s,Q_1,u_1)that maximizes his expected pay-off, given the price-setting rule, the strategy of the manager, and the information he has at the time he makes the trade An investment strategy by the firm that maximizes expected firm value given all other strategies A price-setting strategy by the market maker p_1(Q_1)and p_2(Q_1,Q_2)that allows him to break even in expectation, given all other strategies The firm and the market maker use Bayes rule in order to update their beliefs from the orders they observe in the financial market All agents have rational expectations in the sense that each players belief about the other players strategies is correct in equilibrium.As a benchmark, we consider in this section there is no feedback from the financial market to the firms investment decision. We assume the firm manager known well the state of the world, and, thus, the investment decision in t=3is not affect by the trading outcomes in the financial market in t=1and t=2.For the speculator, if s=h, he knows that the firms value is V+if s=l,he knows that the firm value is 0and if s=phi,he knows the expected firm value is fracV+2. The market maker also starts with the expectation that the firm value is fracV+2and updates this expectation after each round of trade.There exists m ultiple equilibria with no-feedback game when we impose the short selling cost cin t=1.Because there is no feedback and from the proof of Proposition 1., the short selling cost only affect to negatively informed speculator, in order to simplifier the model, we dont impose short selling cost at t=2 . If we impose short selling cost at t=2, we must distinguish not trade or sells in t=1 and buy in t=1 (see the feedback game). . For brevity, we do not develop a particular equilibrium here. The following lemma characterizes the strategy of the positively informed speculator in any equilibrium of the no-feedback game. Building on this lemma, the next proposition establishes an important result regarding the strategy of negatively informed speculator and uninformed speculator, which is the focus of this paper.The trading strategy is rather intuitive. The short selling cost does not affect positively informed speculators trading deportment, since he know the firm value is V+and the firm ma nager does not learn any information from the stock prices, thus, it is a game only between speculator and the market maker, in the case his information was not revealed to the market maker, the positively speculator will not tell apart sells in t=1and t=2.For the positively informed speculator, the only thing is try to hide his information to the market maker, otherwise, the price will equal to the true value of the firm V+and he makes zero profit.The trading strategies are also rather intuitive. For the uninformed speculator, trading in t=1without information generates losses because buying (selling) pushes the price up (down), so that the expected price is higher (lower) than the unconditional expected firm value. The uninformed speculator does not have the informational advantage over the market maker in t=1,and thus cannot make a profit if he is trading. He may call for trade in t=2when the market maker set the price is not equal fracV+2,in this case, he have the informationa l advantage, he knows each agents trading orders in t=1and his own trading order in t=2.For the negatively informed speculator, if short selling cost is not too high, he may choose mixes the trading strategies like positively informed speculator in order to hide his information to the market maker if the short selling cost is too high, he always get negative transaction profit in t=1,in this case, he would like not trade in t=1.In the no-feedback game, the short selling cost actually does not affect the trading behavior of the positively informed speculator and the uninformed speculator, it can only affect to the negatively informed speculator. It is worth noting that in the next section with feedback , the short selling cost will affect not only the negatively informed speculator, but also the uninformed speculator.