New Economics Papers
on Market Microstructure
Issue of 2007‒08‒18
four papers chosen by
Thanos Verousis

  1. Estimating Quadratic Variation When Quoted Prices Change by a Constant Increment By Jeremy Large
  2. How Frequently Does the Stock Price Jump? – An Analysis of High-Frequency Data with Microstructure Noises By Jin-Chuan Duan; András Fülöp
  3. Expiration-Day Effects ¡V An Asian Twist By Joseph K.W. Fung; Haynes H.M. Yung
  4. Order Imbalance and the Dynamics of Index and Futures Prices By Joseph K.W. Fung; Philip Yu

  1. By: Jeremy Large
    Abstract: For financial assets whose best quotes almost always change by jumping by the market`s price tick size (one cent, five cents, etc.), this paper proposes an estimator of Quadratic Variation which controls for microstructure effects. It measures the prevalence of alternations, where quotes jump back to their just-previous price. It defines a simple property called "uncorrelated alternation", which under conditions implies that the estimator is consistent in an asymptotic limit theory, where jumps become very frequent and small. Feasible limit theory is developed, and in simulations works well.
    Keywords: Realized Volatility, Realized Variance, Quadratic Variation, Market Microstructure, High-Frequency Data, Prue Jump Process
    JEL: C10 C22 C80
    Date: 2007
  2. By: Jin-Chuan Duan (Joseph L. Rotman School of Management, University of Toronto); András Fülöp (ESSEC Paris and CREST.)
    Abstract: The stock price is assumed to follow a jump-diffusion process which may exhibit time-varying volatilities. An econometric technique is then developed for this model and applied to high-frequency time series of stock prices that are subject to microstructure noises. Our method is based on first devising a localized particle filter and then employing fixed-lag smoothing in the Monte Carlo EM algorithm to perform the maximum likelihood estimation and inference. Using the intra-day IBM stock prices, we find that high-frequency data are crucial to disentangling frequent small jumps from infrequent large jumps. During the trading sessions, jumps are found to be frequent but small in magnitude, which is in sharp contrast to infrequent but large jumps when the market is closed. We also find that at the 5- or 10-minute sampling frequency, the conclusion will critically depend on whether heavy-tailed microstructure noises have been accounted for. Ignoring microstructure noises can, for example, lead to an overestimation of the jump intensity of 50% or more.
    Keywords: Particle filtering, jump-diffusion, maximum likelihood, EM-algorithm.
    JEL: C22
    Date: 2007
  3. By: Joseph K.W. Fung (Hong Kong Baptist University); Haynes H.M. Yung (Open University of Hong Kong)
    Abstract: This is an examination of the intraday trading activities of index stocks on the common expiration day of index derivatives. In Hong Kong, index futures and index options use an Asian-style settlement procedure. All contracts are settled against the estimated average settlement (EAS) price, which is the arithmetic average of the underlying cash index taken every five minutes on the expiration day. Trading volume and total trade count on the expiration day are found to both be higher than normal. Most important, trading intensifies in terms of both volume and frequency at times close to the five-minute time marks. Significant order imbalance and price reversal patterns are not found. That there is no systematic order imbalance pattern explains the absence of a price reversal pattern.
    Keywords: Asian-style settlement, index derivatives, expiration-day effects.
    Date: 2007–01
  4. By: Joseph K.W. Fung (Hong Kong Baptist University); Philip Yu (University of Hong Kong)
    Abstract: This study uses transaction records of index futures and the index stocks, with bid/ask price quotes, to examine the impact of stock market order imbalance on the dynamic behavior of index futures and cash index prices. Spurious correlation in the index is purged by using an estimate of the ¡§true¡¨ index with highly synchronous and active quotes of individual stocks. A smooth transition autoregressive errorcorrection model (STAECM) is used to describe the nonlinear dynamics of the index and futures prices. Order imbalance in the cash stock market is found to significantly affect the error-correction dynamics of index and futures prices. Order imbalance impedes error-correction particularly when the market impact of order imbalance works against the error-correction force of the cash index, explaining why real potential arbitrage opportunity may persist over some time. Incorporating order imbalance in the framework significantly improves its explanatory power. The findings indicate that a stock market microstructure that allows a quick resolution of order imbalance promotes dynamic arbitrage efficiency between futures and the underlying stocks.
    Date: 2007–04

This issue is ©2007 by Thanos Verousis. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
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