New Economics Papers
on Market Microstructure
Issue of 2007‒09‒09
five papers chosen by
Thanos Verousis


  1. Order Flows, News, and Exchange Rate Volatility By M. FRÖMMEL; A. MENDE; L. MENKHOFF
  2. Capturing Common Components in High-Frequency Financial Time Series: A Multivariate Stochastic Multiplicative Error Model By Nikolaus Hautsch
  3. The Microstructure of the Bond Market in the 20th Century By BIAIS, Bruno; GREEN, Richard
  4. Liquidity, Competition & Price Discovery in the European Corporate Bond Market By BIAIS, Bruno; DECLERCK, Fany
  5. Time-varying contributions by the corporate bond and CDS markets to credit risk price discovery By Dötz, Niko

  1. By: M. FRÖMMEL; A. MENDE; L. MENKHOFF
    Abstract: This paper examines the roles of order flow (reflecting private information) and news (reflecting public information) in explaining exchange rate volatility. Analyzing four months of a bank’s high frequency US dollar-euro trading, three different kinds of order flow are used in addition to seasonal patterns in explaining volatility. We find that only larger sized order flows from financial customers and banks – indicating informed trading – contribute to explaining volatility, whereas flows from commercial customers do not. The result is robust when we control for news and other measures of market activity. This strengthens the view that exchange rate volatility reflects information processing.
    Keywords: exchange rate, market microstructure, order flow, financial customer orders, volatility patterns
    JEL: F G15
    Date: 2007–06
    URL: http://d.repec.org/n?u=RePEc:rug:rugwps:07/474&r=mst
  2. By: Nikolaus Hautsch
    Abstract: We introduce a multivariate multiplicative error model which is driven by component- specific observation driven dynamics as well as a common latent autoregressive factor. The model is designed to explicitly account for (information driven) common factor dynamics as well as idiosyncratic effects in the processes of high-frequency return volatilities, trade sizes and trading intensities. The model is estimated by simulated maximum likelihood using efficient importance sampling. Analyzing five minutes data from four liquid stocks traded at the New York Stock Exchange, we find that volatilities, volumes and intensities are driven by idiosyncratic dynamics as well as a highly persistent common factor capturing most causal relations and cross-dependencies between the individual variables. This confirms economic theory and suggests more parsimonious specifications of high-dimensional trading processes. It turns out that common shocks affect the return volatility and the trading volume rather than the trading intensity.
    Keywords: Multiplicative error models, common factor, efficient importance sampling, intraday trading process.
    JEL: C15 C32 C52
    Date: 2007–09
    URL: http://d.repec.org/n?u=RePEc:hum:wpaper:sfb649dp2007-052&r=mst
  3. By: BIAIS, Bruno; GREEN, Richard
    Date: 2007–08–29
    URL: http://d.repec.org/n?u=RePEc:ide:wpaper:7373&r=mst
  4. By: BIAIS, Bruno; DECLERCK, Fany
    Date: 2007–08
    URL: http://d.repec.org/n?u=RePEc:ide:wpaper:7371&r=mst
  5. By: Dötz, Niko
    Abstract: This paper looks at the dynamic price relationship between spreads in the corporate bond market and credit default swaps (CDS). It picks up where Blanco et al (2005) leave off but is focused on European credit markets. The study is based on companies listed in the iTraxx CDS index and thus on new data on a more liquid CDS market. Unlike previous studies, which look at price formation in a time-invariant context, the contributions of both markets to price discovery are analysed in a timevariant context. We devote particular attention to the question of whether such information input is stable in times of crisis and find that, although the CDS market slightly dominates the price discovery process, its contribution fell visibly during the turbulence on the credit markets in early 2005 in favour of that of the bond market.
    Keywords: price discovery, credit risk, corporate bonds, credit derivatives, Kalman filter
    JEL: C32 G10 G14
    Date: 2007
    URL: http://d.repec.org/n?u=RePEc:zbw:bubdp2:5904&r=mst

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