New Economics Papers
on Market Microstructure
Issue of 2013‒01‒26
four papers chosen by
Thanos Verousis

  1. Non-Fundamental Information and Market-Makers' Behavior during the NASDAQ Preopening Session By Lescourret, Laurence
  2. Estimating the efficient price from the order flow: a Brownian Cox process approach By Sylvain Delattre; Christian Y. Robert; Mathieu Rosenbaum
  3. Which Short-Selling Regulation is the Least Damaging to Market Efficiency? Evidence from Europe By Oscar Bernal Diaz; Astrid Herinckx; Ariane Szafarz
  4. A Model-Free Measure of Aggregate Idiosyncratic Volatility and the Prediction of Market Returns By René Garcia; Daniel Mantilla-Garcia; Lionel Martellini

  1. By: Lescourret, Laurence (ESSEC Business School)
    Abstract: This paper examines whether NASDAQ dealers' preopening quotes might be related to non-fundamental information, that is, information about transient trading pressure un- related to fundamentals. Preopening quotes posted by wholesalers (dealers specialized in market-making and thus presumably more exposed to inventory risks) are strongly related to opening price reversals, a measure of transitory price pressure. Wholesalers are more likely to post preopening quotes on days characterized by large liquidity shocks or days following larger order imbalances, but not on days of strong informational asymmetry about fundamentals (days of analyst recommendation releases, earnings announcements or merger announcements). These patterns do not hold for other intermediaries, namely institutional brokers providing sell-side coverage. I also nd that daily order imbalances (another trading pressure measure) are strongly related to the preopening activity of wholesalers but not to any other groups of market-makers with more diversied banking activities. Overall, I interpret this as evidence that non-fundamental information matters during the preopening session and impacts intermediaries' preopening behavior.
    Keywords: Market Microstructure; Preopen; NASDAQ; Non-fundamental Information; Price Reversals; Order Imbalances
    JEL: D82 G12 G14
    Date: 2012–12
  2. By: Sylvain Delattre; Christian Y. Robert; Mathieu Rosenbaum
    Abstract: At the ultra high frequency level, the notion of price of an asset is very ambiguous. Indeed, many different prices can be defined (last traded price, best bid price, mid price,...). Thus, in practice, market participants face the problem of choosing a price when implementing their strategies. In this work, we propose a notion of efficient price which seems relevant in practice. Furthermore, we provide a statistical methodology enabling to estimate this price form the order flow.
    Date: 2013–01
  3. By: Oscar Bernal Diaz; Astrid Herinckx; Ariane Szafarz
    Abstract: Exploiting cross-sectional and time-series variations in European regulations during the July 2008 – June 2009 period, we show that: 1) Prohibition on covered short selling raises bid-ask spread and reduces trading volume, 2) Prohibition on naked short selling raises both volatility and bid-ask spread, 3) Disclosure requirements raise volatility and reduce trading volume, and 4) No regulation is effective against price decline. Overall, all short-sale regulations harm market efficiency. However, naked short-selling prohibition is the only regulation that leaves volumes unchanged while addressing the failure to deliver. Therefore, we argue that this is the least damaging to market efficiency.
    Keywords: short selling; disclosure requirement; market efficiency; regulation; volatility
    JEL: G18 G14 G00 K20 O52
    Date: 2013–01–09
  4. By: René Garcia; Daniel Mantilla-Garcia; Lionel Martellini
    Abstract: In this paper, we formally show that the cross-sectional variance of stock returns is a consistent and asymptotically efficient estimator for aggregate idiosyncratic volatility. This measure has two key advantages: it is model-free and observable at any frequency. Previous approaches have used monthly model based measures constructed from time series of daily returns. The newly proposed cross-sectional volatility measure is a strong predictor for future returns on the aggregate stock market at the daily frequency. Using the cross-section of size and book-to-market portfolios, we show that the portfolios’ exposures to the aggregate idiosyncratic volatility risk predict the cross-section of expected returns. <P>
    Keywords: Aggregate idiosyncratic volatility, cross-sectional dispersion, prediction of market returns,
    Date: 2013–01–01

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