Informed Manipulation

In asymmetric information models of financial markets, prices imperfectly reveal the private information held by traders. Informed insiders thus have an incentive not only to trade less aggressively but also to manipulate the market by trading in the wrong direction and undertaking short-term losses, thereby increasing the noise in the trading process. In this paper we show that when the market faces uncertainty about the existence of the insider in the market and when there is a large number of trading periods before all private information is revealed, long-lived informed traders will manipulate in every equilibrium

Essays on Market Microstructure

This dissertation studies topics on market microstructure. The first chapter theoretically studies market manipulation in stock markets in a linear equilibrium. The second chapter empirically examines the presence of opportunities for liquidity arbitrage. The last chapter develops and examines a method to capture a co-movement of informed trading. In chapter 1, I study a theory of trade-based price manipulation in markets. I compare two different types of price manipulation studied in previous literature, uninformed and informed manipulation, in the same linear equilibrium model. I show that the presence of positive-feedback traders creates an incentive for the informed trader to bluff, but the opportunity is absent if a sufficient number of uninformed traders behave strategically. Numerical comparable statics results show that informed manipulation is more likely and more profitable when the noise trading is more volatile and that market efficiency could become worse under the presence of manipulation. A financial transaction tax can not prevent informed manipulation, but it reduces the liquidity of the market. Chapter 2 empirically investigates intra-day price manipulation in a stock market. My microstructure model is specifically designed to define the conditions under which a manipulation opportunity arises from the variation in liquidity as measured by price impact. My empirical analysis using data from the Tokyo Stock Exchange suggests that while there is a significant chance of uninformed manipulation across time and stock codes, it is not profitable enough to affect price fluctuations. Analysis of intraday price and trade sizes shows that the opportunity begins to disappear shortly. Chapter 3 studies contagion in a financial market by using a market microstructure model. We extend the Easley, Kiefer, and O'Hara (1997) model to a multiple-asset framework. The model allows us to identify whether the driving forces of informed trading common or idiosyncratic information events are. We apply the method to three groups of stocks listed on the New York Stock Exchange: American Depositary Receipts (ADRs) of developed and emerging countries, and blue chips. We find contagion among emerging-country ADRs during the Asian Financial Crisis of 1997, in the sense that informed trades were mostly driven by common information events

The Hegelian Inquiring System and Critical Triangulation Tools for the Internet Information Slave

This paper discusses informing, i.e. increasing people’s understanding of reality by providing representations of this reality. The Hegelian inquiry system is used to explain the nature of informing. Understanding the Hegelian inquiry system is essential for making informed decisions where the reality can be ambiguous and where sources of bias and manipulation have to be understood for increasing the level of free-informed choice. This inquiry system metaphorically identifies information masters and slaves, and we propose critical dialectic information triangulation (CDIT) tools for information slaves (i.e. non-experts) in dialect interactions with informative systems owned by supposed information masters. The paper concludes with suggestions for further research on informative triangulation tools for the internet and management information systems

Stock Price Manipulation, Market Microstructure and Asymmetric Information

In recent years, there has been a large literature on how stock exchange specialists set prices when there are investors who know more about the stock than they do. An important assumption in this literature is that there are *liquidity traders* who are equally likely to buy or sell for exogenous reasons. It is plausible that some buyers have cash needs and are forced to sell their stock. However, buyers will usually be able to choose the time at which they trade. It will be optimal for them to minimize the probability of trading with informed investors by choosing an appropriate time to trade and clustering at that time. This asymmetry means that when liquidity buyers are not clustering, purchases are more likely to be by an informed trader than sales so the price movement resulting from a purchase is larger than for a sale. As a result, profitable manipulation by uninformed investors may occur. A model where the specialist takes account of the possibility of manipulation in equilibrium is presented.

Market Manipulation: A Comprehensive Study of Stock Pools

Using a hand collected new data set, this paper examines in detail a classic account of stock market manipulation—the “stock pools” of the 1920s, which prompted the current anti-manipulation rules in the United States. We examine abnormal turnover and returns and the relationship between them, as well as the long-term performance of the selected stocks. We conclude that the evidence suggests informed trading rather than manipulation. Our findings have implications for regulatory policy as well as the investigation and prosecution of manipulation cases

Insider trading with partially informed traders

The single auction equilibrium of Kyle's (1985) is studied, in which noise traders may be partially informed, or alternatively they can be manipulated. Unlike Kyle's assumption that the quantity traded by the noise traders is independent of the asset value, we assume that the noise traders are able to correlate their trade with the true price. This has several implications for the equilibrium, one being that the insider's expected profits decrease as the noise traders' ability to correlate positively improve. In the limit, the noise traders do not lose on average, and the insider makes zero expected profits. When the correlation is negative, we interpret this as manipulation. In this case the insider makes the highest expected profits, and the informativeness of prices is at its minimum.Insider trading; asymmetric information; strategic trade; correlated trade; partially informed noise traders

Batch Informed Trees (BIT*): Sampling-based Optimal Planning via the Heuristically Guided Search of Implicit Random Geometric Graphs

In this paper, we present Batch Informed Trees (BIT*), a planning algorithm based on unifying graph- and sampling-based planning techniques. By recognizing that a set of samples describes an implicit random geometric graph (RGG), we are able to combine the efficient ordered nature of graph-based techniques, such as A*, with the anytime scalability of sampling-based algorithms, such as Rapidly-exploring Random Trees (RRT). BIT* uses a heuristic to efficiently search a series of increasingly dense implicit RGGs while reusing previous information. It can be viewed as an extension of incremental graph-search techniques, such as Lifelong Planning A* (LPA*), to continuous problem domains as well as a generalization of existing sampling-based optimal planners. It is shown that it is probabilistically complete and asymptotically optimal. We demonstrate the utility of BIT* on simulated random worlds in $\mathbb{R}^2$ and $\mathbb{R}^8$ and manipulation problems on CMU's HERB, a 14-DOF two-armed robot. On these problems, BIT* finds better solutions faster than RRT, RRT*, Informed RRT*, and Fast Marching Trees (FMT*) with faster anytime convergence towards the optimum, especially in high dimensions.Comment: 8 Pages. 6 Figures. Video available at http://www.youtube.com/watch?v=TQIoCC48gp

Guidelines for the practice and performance of manipulation under anesthesia

BACKGROUND: There are currently no widely accepted guidelines on standards for the practice of chiropractic or manual therapy manipulation under anesthesia, and the evidence base for this practice is composed primarily of lower-level evidence. The purpose of this project was to develop evidence-informed and consensus-based guidelines on spinal manipulation under anesthesia to address the gaps in the literature with respect to patient selection and treatment protocols. METHODS: An expert consensus process was conducted from August-October 2013 using the Delphi method. Panelists were first provided with background literature, consisting of three review articles on manipulation under anesthesia. The Delphi rounds were conducted using the widely-used and well-established RAND-UCLA consensus process methodology to rate seed statements for their appropriateness. Consensus was determined to be reached if 80% of the 15 panelists rated a statement as appropriate. Consensus was reached on all 43 statements in two Delphi rounds. RESULTS: The Delphi process was conducted from August-October 2013. Consensus was reached on recommendations related to all aspects of manipulation under anesthesia, including patient selection; diagnosis and establishing medical necessity; treatment and follow-up procedures; evaluation of response to treatment; safety practices; appropriate compensation considerations; and facilities, anesthesia and nursing standards. CONCLUSIONS: A high level of agreement was achieved in developing evidence-informed recommendations about the practice of chiropractic/manual therapy manipulation under anesthesia