New Economics Papers
on Market Microstructure
Issue of 2011‒11‒01
eleven papers chosen by
Thanos Verousis

  1. Dark Pool Trading Strategies By Sabrina Buti; Barbara Rindi; Ingrid M. Werner
  2. Price impact asymmetry of institutional trading in Chinese stock market By Fei Ren; Li-Xin Zhong
  3. A limit order book model for latency arbitrage By Samuel N. Cohen; Lukasz Szpruch
  4. Dynamics of Bid-ask Spread Return and Volatility of the Chinese Stock Market By Tian Qiu; Guang Chen; Li-Xin Zhong; Xiao-Run Wu
  5. Belief dispersion among household investors and stock trading volume By Dan Li; Geng Li
  6. Competition between Exchanges: A research Agenda By Estelle Cantillon; Pai-Ling Yin
  7. The performance of amateur traders on a public internet site: a case of a stock-exchange contest By Blanchard, michel; Bernard, philippe
  8. Suitability of using technical indicators as potential strategies within intelligent trading systems By Evan Hurwitz; Tshilidzi Marwala
  9. Endogenous Liquidity Constraints in a Dynamic Contest By Martin Grossmann
  10. Memory effects in stock price dynamics: evidences of technical trading By Federico Garzarelli; Matthieu Cristelli; Andrea Zaccaria; Luciano Pietronero
  11. A Quantum-like Approach to the Stock Market By Diederik Aerts; Bart D'Hooghe; Sandro Sozzo

  1. By: Sabrina Buti; Barbara Rindi; Ingrid M. Werner
    Abstract: We model a financial market where traders have access both to a fully transparent limit order book (LOB) and to an opaque Dark Pool (DP). When a DP is introduced to a LOB market,orders migrate to the DP from the LOB, but overall trading volume increases. Moreover, inside quoted depth in the LOB decreases, but quoted spreads tend to narrow in deep books and widen in shallow ones. DP market share is higher when LOB depth is high, when LOB spread is narrow, when the tick size is large and when traders seek protection from price impact. When depth decreases on one side of the LOB, liquidity is drained from the DP. When Flash orders provide select traders with information about the state of the DP, more orders migrate from the LOB to the DP but overall market quality improves.
    Date: 2011
  2. By: Fei Ren; Li-Xin Zhong
    Abstract: The asymmetric price impact between the institutional purchases and sales of 32 liquid stocks in Chinese stock markets in year 2003 is carefully studied. We analyze the price impact in both drawup and drawdown trends with consecutive positive and negative daily price changes, and test the dependence of the price impact asymmetry on the market condition. For most of the stocks institutional sales have a larger price impact than institutional purchases, and larger impact of institutional purchases only exists in few stocks with primarily increasing tendencies. We further study the mean return of trades surrounding institutional transactions, and find the asymmetric behavior also exists before and after institutional transactions. A new variable is proposed to investigate the order book structure, and it can partially explain the price impact of institutional transactions. A linear regression for the price impact of institutional transactions further confirms our finding that institutional sales primarily have a larger price impact than institutional purchases in the bearish year 2003.
    Date: 2011–10
  3. By: Samuel N. Cohen; Lukasz Szpruch
    Abstract: We consider a single security market based on a limit order book and two investors, with different speeds of trade execution. If the fast investor can front-run the slower investor, we show that this allows the fast trader to obtain risk free profits, but that these profits cannot be scaled. We derive the fast trader's optimal behaviour when she has only distributional knowledge of the slow trader's actions, with few restrictions on the possible prior distributions. We also consider the slower trader's response to the presence of a fast trader in a market, and the effects of the introduction of a `Tobin tax' on financial transactions. We show that such a tax can lead to the elimination of profits from front-running strategies. Consequently, a Tobin tax can both increase market efficiency and attract traders to a market.
    Date: 2011–10
  4. By: Tian Qiu; Guang Chen; Li-Xin Zhong; Xiao-Run Wu
    Abstract: Bid-ask spread is taken as an important measure of the financial market liquidity. In this article, we study the dynamics of the spread return and the spread volatility of four liquid stocks in the Chinese stock market, including the memory effect and the multifractal nature. By investigating the autocorrelation function and the Detrended Fluctuation Analysis (DFA), we find that the spread return is lack of long-range memory, while the spread volatility is long-range time correlated. Moreover, by applying the Multifractal Detrended Fluctuation Analysis (MF-DFA), the spread return is observed to possess a strong multifractality, which is similar to the dynamics of a variety of financial quantities. Differently from the spread return, the spread volatility exhibits a weak multifractal nature.
    Date: 2011–10
  5. By: Dan Li; Geng Li
    Abstract: We study the effects of belief dispersion on stock trading volume. Unlike most of the existing work on the subject, our paper focuses on how household investors' disagreements on macroeconomic variables influence market-wide trading volume. We show that greater belief dispersion among household investors is associated with significantly higher trading volume, even after controlling for the disagreements among professional forecasters. Further, we find that the belief dispersion among household investors who are more likely to own stocks has more pronounced effects on trading volume, suggesting a causal relationship. Finally, we show that greater "belief jumbling," or the dispersion of belief changes over a given period, is also related to more active trading during the same period.
    Date: 2011
  6. By: Estelle Cantillon; Pai-Ling Yin
    Abstract: This paper describes open research questions related to the competition and market structure of financial exchanges and argues that only a combination of industrial organization and finance can satisfactorily attack these questions. Two examples are discussed to illustrate how the combination of these two approaches can significantly enrich the analysis: the “network externality puzzle”, which refers to the question of why trading for the same security is often split across trading venues, and the impact of the multi-sided character of financial exchanges on pricing and profitability.
    Keywords: network effects; two-sided market; tipping; competition; market structure; market microstructure
    JEL: G29 L13 L40 L15
    Date: 2011–05
  7. By: Blanchard, michel; Bernard, philippe
    Abstract: We analyze a very thorough data base, including all of the bid/ask orders and daily portfolio values of more than 600 on-line amateur traders from February 2007 to June 2009. These traders were taking part in a stock-exchange contest proposed by the French Internet stock-exchange site Zonebourse. More than 80% of traders lose relative to the market. Their relative average annual performance varies from -38% to -60%, depending on the method used. In absolute, more than 99% of traders lose and face drastic losses: on average, portfolio values fall from an initial value of 100 to a terminal value of 7 in the 29 months covered here. When we include the rewards offered by the contest, average performance becomes -13% a year. However, only two deciles continue to beat the market. From an initial value of 100 the final value is 28 including rewards, but 95% of traders still lose in absolute. There is no clear performance persistence for traders. Are the best traders just lucky then? Focusing on contest winners, the long-term transition analysis suggests a long-term probability of staying in the best decile which is greater than chance. We thus cannot reject a “star effect” of staying in the best decile. However, the great majority of amateurs do seem to be e-pigeons. Online trading may just be costly entertainment, like casino gambling.
    Keywords: Behavioral finance; finance; online trading; amateur traders ; e-pigeons; trade losses
    JEL: G11 G10
    Date: 2011–10–24
  8. By: Evan Hurwitz; Tshilidzi Marwala
    Abstract: The potential of machine learning to automate and control nonlinear, complex systems is well established. These same techniques have always presented potential for use in the investment arena, specifically for the managing of equity portfolios. In this paper, the opportunity for such exploitation is investigated through analysis of potential simple trading strategies that can then be meshed together for the machine learning system to switch between. It is the eligibility of these strategies that is being investigated in this paper, rather than application. In order to accomplish this, the underlying assumptions of each trading system are explored, and data is created in order to evaluate the efficacy of these systems when trading on data with the underlying patterns that they expect. The strategies are tested against a buy-and-hold strategy to determine if the act of trading has actually produced any worthwhile results, or are simply facets of the underlying prices. These results are then used to produce targeted returns based upon either a desired return or a desired risk, as both are required within the portfolio-management industry. Results show a very viable opportunity for exploitation within the aforementioned industry, with the Strategies performing well within their narrow assumptions, and the intelligent system combining them to perform without assumptions.
    Date: 2011–10
  9. By: Martin Grossmann (Department of Business Administration, University of Zurich)
    Abstract: In this article, I analyze the effects of future liquidity constraints on the investment behavior of two contestants with asymmetric prize valuations in a dynamic contest model. Contestants compete in two consecutive Tullock contests in order to win a contest prize in each period. The loser of the first-period contest can be liquidity constraint in the second period. The model reveals the following four main results: (i) Future liquidity constraints marginally affect today's intensity of competition but rather influence tomorrow's contest. (ii) A higher contest prize in both periods surprisingly decreases aggregate second-period investment in a symmetric contest. (iii) Counterintuitively, a higher asymmetry with respect to the contest prize valuations increases the first-period investment of both contestants.(iv) The effect of a higher asymmetry on second-period investment depends on which contestant won the first-period contest. Further results are derived with respect to the existence and uniqueness of the equilibrium, competitive balance and expected total profits.
    Keywords: Dynamic contest, liquidity constraint, competitive balance
    JEL: C72 C73 D43 D72 L13
    Date: 2011–10
  10. By: Federico Garzarelli; Matthieu Cristelli; Andrea Zaccaria; Luciano Pietronero
    Abstract: Technical trading represents a class of investment strategies for Financial Markets based on the analysis of trends and recurrent patterns of price time series. According standard economical theories these strategies should not be used because they cannot be profitable. On the contrary it is well-known that technical traders exist and operate on different time scales. In this paper we investigate if technical trading produces detectable signals in price time series and if some kind of memory effect is introduced in the price dynamics. In particular we focus on a specific figure called supports and resistances. We first develop a criterion to detect the potential values of supports and resistances. As a second step, we show that memory effects in the price dynamics are associated to these selected values. In fact we show that prices more likely re-bounce than cross these values. Such an effect is a quantitative evidence of the so-called self-fulfilling prophecy that is the self-reinforcement of agents' belief and sentiment about future stock prices' behavior.
    Date: 2011–10
  11. By: Diederik Aerts; Bart D'Hooghe; Sandro Sozzo
    Abstract: Modern approaches to stock pricing in quantitative finance are typically founded on the 'Black-Scholes model' and the underlying 'random walk hypothesis'. Empirical data indicate that this hypothesis works well in stable situations but, in abrupt transitions such as during an economical crisis, the random walk model fails and alternative descriptions are needed. For this reason, several proposals have been recently forwarded which are based on the formalism of quantum mechanics. In this paper we apply the 'SCoP formalism', elaborated to provide an operational foundation of quantum mechanics, to the stock market. We argue that a stock market is an intrinsically contextual system where agents' decisions globally influence the market system and stocks prices, determining a nonclassical behavior. More specifically, we maintain that a given stock does not generally have a definite value, e.g., a price, but its value is actualized as a consequence of the contextual interactions in the trading process. This contextual influence is responsible of the non-Kolmogorovian quantum-like behavior of the market at a statistical level. Then, we propose a 'sphere model' within our 'hidden measurement formalism' that describes a buying/selling process of a stock and shows that it is intuitively reasonable to assume that the stock has not a definite price until it is traded. This result is relevant in our opinion since it provides a theoretical support to the use of quantum models in finance.
    Date: 2011–10

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