New Economics Papers
on Market Microstructure
Issue of 2010‒08‒28
three papers chosen by
Thanos Verousis

  1. Pre-Averaging Based Estimation of Quadratic Variation in the Presence of Noise and Jumps: Theory, Implementation, and Empirical Evidence By Nikolaus Hautsch; Mark Podolskij
  2. Informed and uninformed traders at work: evidence from the French market By Ferriani, Fabrizio
  3. Nonparametric estimation of the volatility under microstructure noise: wavelet adaptation By Hoffmann, Marc; Munk, Axel; Schmidt-Hieber, Johannes

  1. By: Nikolaus Hautsch (Humboldt-Universität zu Berlin); Mark Podolskij (ETH Zurich and CREATES)
    Abstract: This paper provides theory as well as empirical results for pre-averaging estimators of the daily quadratic variation of asset prices. We derive jump robust inference for pre-averaging estimators, corresponding feasible central limit theorems and an explicit test on serial dependence in microstructure noise. Using transaction data of different stocks traded at the NYSE, we analyze the estimators’ sensitivity to the choice of the pre-averaging bandwidth and suggest an optimal interval length. Moreover, we investigate the dependence of pre-averaging based inference on the sampling scheme, the sampling frequency, microstructure noise properties as well as the occurrence of jumps. As a result of a detailed empirical study we provide guidance for optimal implementation of pre-averaging estimators and discuss potential pitfalls in practice.
    Keywords: Quadratic Variation, MarketMicrostructure Noise, Pre-averaging, Sampling Schemes, Jumps
    JEL: C14 C22 G10
    Date: 2010–07–01
  2. By: Ferriani, Fabrizio
    Abstract: The impact that informed and uninformed agents have on market prices is crucial for informational issues in financial markets. Informed trades are associated with institutional operators while uninformed trades are executed on behalf of retail investors. Using high-frequency data from Euronext Paris, I estimate a model where I take into account traders' identities at transaction level. The results show that when the identities of the traders are different on the two sides of the market, stock prices follow the direction indicated by institutional agents. This means that when the buyer is an informed operator and the seller is a retail one, the former transmits a positive pressure to the market. Conversely, when the seller is an institutional agent and the buyer is an uninformed one market prices depress. There is no significant effect when the agent types are the same on both market sides. Since traders' identities are concealed in Euronext Paris, the last part of the paper discusses the informational content implicitly provided by observed market variables. Institutional trading is found to increase throughout the day, whereas no evidence of informed trading is found during specific time periods of the continuous auction, except for the first thirty minutes of the day where there are more uninformed trades. Institutional trading is more common during periods of low price changes and high frequency of transactions. Price variations show that informed agents are usually able to trade at better price conditions. Finally, the tick-test algorithm strongly confirms that informed traders always act as initiators of market transactions.
    Keywords: High-frequency data; Euronext Paris; informational asymmetries.
    JEL: G14 C22 C25
    Date: 2010–08–18
  3. By: Hoffmann, Marc; Munk, Axel; Schmidt-Hieber, Johannes
    Abstract: We study nonparametric estimation of the volatility function of a diffusion process from discrete data, when the data are blurred by additional noise. This noise can be white or correlated, and serves as a model for microstructure effects in financial modeling, when the data are given on an intra-day scale. By developing pre-averaging techniques combined with wavelet thresholding, we construct adaptive estimators that achieve a nearly optimal rate within a large scale of smoothness constraints of Besov type. Since the underlying signal (the volatility) is genuinely random, we propose a new criterion to assess the quality of estimation; we retrieve the usual minimax theory when this approach is restricted to deterministic volatility.
    Keywords: Adaptive estimation; diffusion processes; high-frequency data; microstructure noise; minimax estimation; semimartingales; wavelets.
    JEL: C14 C0 C22
    Date: 2010–07–27

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