New Economics Papers
on Market Microstructure
Issue of 2013‒08‒31
seven papers chosen by
Thanos Verousis

  1. Learning and Evolution of Trading Strategies in Limit Order Markets By Carl Chiarella; Xue-Zhong He; Lijian Wei
  2. Volatility and Liquidity Costs By Selma Chaker
  3. Which continuous-time model is most appropriate for exchange rates? By Deniz Erdemlioglu; Sébastien Laurent; Christopher J. Neely
  4. The impact of jumps and thin trading on realized hedge ratios By Dungey, Mardi; Henry, Olan T; Hvodzdyk, Lyudmyla
  5. ECB monetary policy surprises: identification through cojumps in interest rates By Lars winkelmann; Markus Bibinger; Tobias Linzert;
  6. Intermediating Adverse Selection By Vincent Glode; Christian Opp
  7. The Microstructure of Exchange Rate Management: FX Intervention and Capital Controls in Brazil By Calebe de Roure; Steven Furnagiev; Stefan Reitz

  1. By: Carl Chiarella (Finance Discipline Group, UTS Business School, University of Technology, Sydney); Xue-Zhong He (Finance Discipline Group, UTS Business School, University of Technology, Sydney); Lijian Wei (Finance Discipline Group, UTS Business School, University of Technology, Sydney)
    Abstract: How do traders process and learn from market information, what trading strategies should they use, and how does learning affect the market? This paper proposes a learning model of an articial limit order market with asymmetric information to address these issues. Using a genetic algorithm as a learning mechanism, we show that learning, in particular the learning from uninformed traders, improves market informational efficiency and has a significant impact on the stylized facts of limit order markets, order submission, liquidity supply and consumption, the hump shaped order book near the quote, and the bid-ask spread. Moreover, the learning affects the evolution process of the trading strategies for all traders. The model provides some insights into market efficiency, the interaction of traders, the dynamics of limit order books, and the evolution of trading strategies.
    Keywords: Limit order book; evolution; genetic algorithm learning; asymmetric information; trading strategy
    JEL: G14 C63 D82
    Date: 2013–08–01
  2. By: Selma Chaker
    Abstract: Observed high-frequency prices are contaminated with liquidity costs or market microstructure noise. Using such data, we derive a new asset return variance estimator inspired by the market microstructure literature to explicitly model the noise and remove it from observed returns before estimating their variance. The returns adjusted for the estimated liquidity costs are either totally or partially free from noise. If the liquidity costs are fully removed, the sum of squared high-frequency returns – which would be inconsistent for return variance when based on observed returns – becomes a consistent variance estimator when based on adjusted returns. This novel estimator achieves the maximum possible rate of convergence. However, if the liquidity costs are only partially removed, the residual noise is smaller and closer to an exogenous white noise than the original noise. Therefore, any volatility estimator that is robust to noise relies on weaker noise assumptions if it is based on adjusted returns than if it is based on observed returns.
    Keywords: Econometric and statistical methods; Financial markets; Market structure and pricing
    JEL: G20 C14 C51 C58
    Date: 2013
  3. By: Deniz Erdemlioglu; Sébastien Laurent; Christopher J. Neely
    Abstract: This paper attempts to realistically model the underlying exchange rate data generating process. We ask what types of diffusion or jump features are most appropriate. The most plausible model for 1-minute data features Brownian motion and Poisson jumps but not infinite activity jumps. Modeling periodic volatility is necessary to accurately identify the frequency of jump occurrences and their locations. We propose a two-stage method to capture the effects of these periodic volatility patterns. Simulations show that microstructure noise does not significantly impair the statistical tests for jumps and diffusion behavior.>
    Keywords: Foreign exchange ; Time-series analysis
    Date: 2013
  4. By: Dungey, Mardi; Henry, Olan T; Hvodzdyk, Lyudmyla (School of Economics and Finance, University of Tasmania)
    Abstract: The use of intradaily data to produce daily variance measures has resulted in increased forecast accuracy and better hedging for many markets. However, this paper shows that improved hedging ratios can depend on the behavior of price disruptions in the assets. When spot and future prices for the same asset do not jump simultaneously inferior hedging outcomes can be observed. This problem dominates potential bias from thin trading. Using US Treasury data we demonstrate how the extent of non-synchronized jumping leads to the ?nding that optimal hedging ratios are not improved with intradaily data in this market.
    Keywords: US US Treasury bonds; Futures; Realized hedge ratios; Jumps; Thin trading
    JEL: C01 C32 G11 G17
    Date: 2013–03–28
  5. By: Lars winkelmann; Markus Bibinger; Tobias Linzert;
    Abstract: This paper proposes a new econometric approach to disentangle two distinct response patterns of the yield curve to monetary policy announcements. Based on cojumps in intraday tick-data of a short and long term interest rate, we develop a day-wise test that detects the occurrence of a significant policy surprise and identifies the market perceived source of the surprise. The new test is applied to 133 policy announcements of the European Central Bank (ECB) in the period from 2001-2012. Our main findings indicate a good predictability of ECB policy decisions and remarkably stable perceptions about the ECB’s policy preferences.
    Keywords: Central bank communication; yield curve; spectral cojump estimator; high frequency tick-data
    JEL: E58 C14 C58
    Date: 2013–08
  6. By: Vincent Glode (Wharton School); Christian Opp (University of Pennsylvania)
    Abstract: We propose a parsimonious model of over-the-counter trading under asymmetric information to study the presence of intermediary chains that stand between well informed parties and uninformed market participants. Multiple moderately informed intermediaries can fulfill an important economic role of "smoothing" adverse selection. Informed market participants may prefer to trade through these intermediary chains as they improve trade efficiency but also reduce the surplus accruing to uninformed traders. Our model makes novel predictions about optimal network formation when adverse selection problems impede the efficiency of trade.
    Date: 2013
  7. By: Calebe de Roure; Steven Furnagiev; Stefan Reitz
    Abstract: This paper uses a microstructure approach to analyze the effectiveness of capital controls introduced in Brazil to counter an appreciation of the Real. Based on a rich data set from the Brazilian foreign exchange market, we estimate a reduced-form VAR to characterize the interaction of the central bank, financial and commercial customers in times of regulatory policy measures. Controlling for regular FX interventions we find that capital controls change market participants' behavior. Referring to thesource of order flow, we find no evidence that the appreciation of the Real is driven by financial customers’ activity. Instead, commercial customers seem to be a primary driver of the Real within our model. To the extent that capital controls influence commercial customers' order flow, this is the likely channel policy makers use to respond to a perceived loss of international competitiveness
    Keywords: Foreign Exchange,Sterilized Intervention, Macroprudential Policies, Market Microstructure
    JEL: F31 E58 G14 G15
    Date: 2013–08

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