nep-mst New Economics Papers
on Market Microstructure
Issue of 2018‒05‒14
two papers chosen by
Thanos Verousis

  1. Quotes, Trades and the Cost of Capital By Rosu, Ioanid; Sojli, Elvira; Tham, Wing Wah
  2. Co-impact: Crowding effects in institutional trading activity By Fr\'ed\'eric Bucci; Iacopo Mastromatteo; Zolt\'an Eisler; Fabrizio Lillo; Jean-Philippe Bouchaud; Charles-Albert Lehalle

  1. By: Rosu, Ioanid; Sojli, Elvira; Tham, Wing Wah
    Abstract: We study the quoting activity of market makers in relation with trading, liquidity, and expected returns. Empirically, we find larger quote-to-trade (QT) ratios in small, illiquid or neglected firms, yet large QT ratios are associated with low expected returns. The last result is driven by quotes, not by trades. We propose a model of quoting activity consistent with these facts. In equilibrium, market makers monitor the market faster (and thus increase the QT ratio) in neglected, difficult-to-understand stocks. They also monitor faster when their clients are less risk averse, which reduces mispricing and lowers expected returns.
    Keywords: Liquidity; price discovery; volatility; trading volume; monitoring; neglected stocks; risk aversion; inventory; high frequency trading
    JEL: G12 G14
    Date: 2017–07–01
  2. By: Fr\'ed\'eric Bucci; Iacopo Mastromatteo; Zolt\'an Eisler; Fabrizio Lillo; Jean-Philippe Bouchaud; Charles-Albert Lehalle
    Abstract: This paper is devoted to the important yet unexplored subject of \emph{crowding} effects on market impact, that we call "co-impact". Our analysis is based on a large database of metaorders by institutional investors in the U.S. equity market. We find that the market chiefly reacts to the net order flow of ongoing metaorders, without individually distinguishing them. The joint co-impact of multiple contemporaneous metaorders depends on the total number of metaorders and their mutual sign correlation. Using a simple heuristic model calibrated on data, we reproduce very well the different regimes of the empirical market impact curves as a function of volume fraction $\phi$: square-root for large $\phi$, linear for intermediate $\phi$, and a finite intercept $I_0$ when $\phi \to 0$. The value of $I_0$ grows with the sign correlation coefficient. Our study sheds light on an apparent paradox: How can a non-linear impact law survive in the presence of a large number of simultaneously executed metaorders?
    Date: 2018–04

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