nep-mst New Economics Papers
on Market Microstructure
Issue of 2007‒12‒08
four papers chosen by
Thanos Verousis
University of Wales (Aberystwyth)

  1. Exchange rate volatility, macro announcements and the choice of intraday seasonality filtering method By Laakkonen, Helinä
  2. "Estimating Stochastic Volatility Models Using Daily Returns and Realized Volatility Simultaneously" By Makoto Takahashi; Yasuhiro Omori; Toshiaki Watanabe
  3. Some mathematical properties of the futures market platform By LAIB, Fodil; RADJEF, M.S.
  4. The Paris financial market in the 19th century: an efficient multi-polar organization? By Pierre-Cyrille Hautcoeur; Angelo Riva

  1. By: Laakkonen, Helinä (University of Jyväskylä)
    Abstract: Filtering intraday seasonality in volatility is crucial for using high frequency data in econometric analysis. This paper studies the effects of filtering on statistical inference concerning the impact of news on exchange rate volatility. The properties of different methods are studied using a 5-minute frequency USD/EUR data set and simulated returns. The simulation results suggest that all the methods tend to produce downward-biased estimates of news coefficients, some more than others. The study supports the Flexible Fourier Form method as the best for seasonality filtering.
    Keywords: high-frequency; volatility; macro announcements; seasonality
    JEL: C22 C49 C52 E44
    Date: 2007–11–28
  2. By: Makoto Takahashi (Graduate School of Economics, University of Tokyo); Yasuhiro Omori (Faculty of Economics, University of Tokyo); Toshiaki Watanabe (Institute of Economic Research, Hitotsubashi University)
    Abstract: Realized volatility, which is the sum of squared intraday returns over a certain interval such as a day, has recently attracted the attention of financial economists and econometricians as an accurate measure of the true volatility. In the real market, however, the presence of non-trading hours and market microstructure noise in transaction prices may cause the bias in the realized volatility. On the other hand, daily returns are less subject to the noise and therefore may provide additional information on the true volatility. From this point of view, we propose modeling realized volatility and daily returns simultaneously based on well-known stochastic volatility model. Using intraday data of Tokyo stock price index, we show that this model can estimate realized volatility biases and parameters simultaneously.We take a Bayesian approach and propose an efficient sampling algorithm to implement the Markov chain Monte Carlo method for our simultaneous model. The result of the model comparison between the simultaneous models using both naive and scaled realized volatilities indicates that the effect of non-trading hours is more essential than that of microstructure noise but still the latter has to be considered for better fitting. Our Bayesian approach has an advantage over the conventional two-step correction procedure in that we are able to take the uncertainty in estimation of both biases and parameters into account for the prediction and the evaluation of Value-at-Risk.
    Date: 2007–09
  3. By: LAIB, Fodil; RADJEF, M.S.
    Abstract: This is an introductory work to analytical properties of the futures market platform’s main parameters. The underlying mechanism of this market structure is formulated into a mathematical dynamical model. Some mathematical properties of traders’ positions, their potential and realized wealths, market open interest and average price, are stated and demonstrated.
    Keywords: futures market platform; open interest
    JEL: C02 G13
    Date: 2007–12–04
  4. By: Pierre-Cyrille Hautcoeur; Angelo Riva
    Abstract: The literature in financial history usually considers London as the only centre of the late 19th century's financial globalization, and explains it at least in part by the efficient microstructure (organization) of the London Stock Exchange (LSE). The LSE is characterized as having been a little regulated market, where entry was easy both for traders and issuers [Michie (1998), Neal (2004), White (2006)]. The LSE microstructure is also considered as the natural and optimal one by much of the theoretical literature on stock markets, which argues that free entry decreases transaction costs and increases both liquidity and diversification, resulting in economies of scale attracting traders, issuers and buyers. Our paper tries to explain why the Paris Bourse was able to be so successful in spite of the supposedly inefficient monopoly and regulations that the State imposed it. We focus on the fact that the Paris market actually included several different market places: the Parquet (the official Bourse, organized by the agents de change), the Coulisse, the Marché libre, and inter-bank direct operations. We argue that this multi-polar organization, was efficient, relying on the specialization it allowed, and the complementarities it helped develop among markets. We incorporate in the discussion the recent theoretical literature that shows that no single market can satisfy the heterogeneous preferences of all issuers and investors, so that a multi-polar organization can be a superior solution. We demonstrate our claim by looking not only at the rules but also at the actual functioning of the Parquet thanks to its archives which we recently classified. These archives also allow us to build new statistical series which permit evaluating the performances of the Parquet during the 19th century: volumes traded, seat prices, transaction costs, and operational risks. If one supposes that the Parquet was the least efficient segment of the Parisian market, this will provide us with a lower bound for the global efficiency of that market, which should be compared with other markets on similar concrete grounds.
    Date: 2007

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