Security price adjustment across exchanges: an investigation of common factor components for Dow stocks

Harris, Frederick H. deB.; McInish, Thomas H.; Wood, Robert A.

doi:10.1016/s1386-4181(01)00017-9

Cited by 253 publications

(197 citation statements)

References 36 publications

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“…This relation was discussed by Johansen (1996) (see also Hansen and Johansen 1998, pp. 27-28), and similar arguments were given by de Jong (2002) and Baillie, Booth, Tse, and Zabotina (2002) (see also Harris et al 2002;Lehmann 2002).…”

Section: Common Stochastic Trendsupporting

confidence: 74%

“…(For alternative ways of decomposing the observed price series, see, e.g., Engle and Sun 2005, who used a ACD-GARCH specification where the noise process has a two-component ARMA structure; also see Frijns and Lehnert 2004. ) We use the vector autoregressive framework that was used to analyze price discovery (from multiple markets) by Harris, McInish, Shoesmith, and Wood (1995), Hasbrouck (1995), and Harris, McInish, and Wood (2002), among others. Our analysis differs from this literature because we apply cointegration techniques to quotes and transactions in conjunction, not to transaction prices from different exchanges.…”

Section: Price Decomposition By Cointegration Methodsmentioning

confidence: 99%

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Realized Variance and Market Microstructure Noise

Hansen

Lunde²

2006

Journal of Business & Economic Statistics

1,039

652

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We study market microstructure noise in high-frequency data and analyze its implications for the realized variance (RV) under a general specification for the noise. We show that kernel-based estimators can unearth important characteristics of market microstructure noise and that a simple kernel-based estimator dominates the RV for the estimation of integrated variance (IV). An empirical analysis of the Dow Jones Industrial Average stocks reveals that market microstructure noise is time-dependent and correlated with increments in the efficient price. This has important implications for volatility estimation based on highfrequency data. Finally, we apply cointegration techniques to decompose transaction prices and bid-ask quotes into an estimate of the efficient price and noise. This framework enables us to study the dynamic effects on transaction prices and quotes caused by changes in the efficient price.

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Section: Common Stochastic Trendsupporting

confidence: 74%

Section: Price Decomposition By Cointegration Methodsmentioning

confidence: 99%

Realized Variance and Market Microstructure Noise

Hansen

Lunde²

2006

Journal of Business & Economic Statistics

1,039

652

View full text Add to dashboard Cite

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“…For detailed discussion, we refer readers to Hasbrouck (1995Hasbrouck ( , 2002, Baillie et al (2002), Booth et al (2002), Gonzalo and Granger (1995), Harris et al (2002), Huang (2002), and Lehmann (2002). In contrast to the usual multiple markets setup, we consider two prices, WP 1 and WP 2−10 derived from the same order book.…”

Section: The Hasbrouck and Gonzalo-granger Methodsmentioning

confidence: 99%

The Informational Content of an Open Limit Order Book

Cao

Hansch

Beardsley³

2004

SSRN Journal

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We assess the informational content of an open limit order book from three directions: (1) Does the limit order book allow better inferences about a security's value than simply the best bid and offer prices from the first step of the book? If it does, how much additional information can be gleaned from the book? (2) Are imbalances between the demand and supply schedules informative about future price movements? and (3) Does the shape of the limit order book impact traders' order submission strategies? Our empirical evidence suggests that the order book beyond the first step is informative-its information share is about 30%. The imbalance between demand and supply from step 2 to 10 provides additional power in explaining future short-term returns. Finally, traders do use the available information on the state of the book, not only from the first step, but also from other steps, when developing their order submission strategies. JEL Classification Numbers: G10, G12, G13Keywords: Limit order book, price discovery, order placement strategy, demand and supply schedule A majority of stock markets around the world are organized as electronic limit order books.Among the reasons advanced for their popularity is the greater transparency offered by these systems compared to dealer market settings. A typical limit order book system allows its users to view depth at a number of price levels at and away from the market, while dealer markets usually rely on dissemination of only the dealers' best quotes. In a limit order book, all displayed prices and quantities are typically executable instantaneously, whereas in dealer markets prices for trades beyond the quoted size need to be assessed through negotiations between traders and market makers. Also, market makers may offer price improvement for trades up to quoted size.Although limit order book trading systems have been successful around the world, little research has been done to address the value of the information contained in the order book. 1 In particular, one important question that left unanswered is whether the demand and supply schedules as expressed in the limit orders to buy and sell contain information beyond the best bid and offer prices. Clearly, the immediate benefit of being able to view the book is the ability to assess the cost of buying or selling a certain number of shares. Unlike dealer markets, where orders may receive price improvement or have to be negotiated if they exceed quoted depth, limit order books allow almost perfect assessment of an order's price. 2 The purpose of this paper is to address three related questions. First, does the limit order book allow better inferences about a security's value than simply the best bid and offer prices? If it does, how much additional information can be gleaned from the book? Second, are imbalances between the demand and supply schedules informative about future price movements? Finally, does the shape of the limit order book impact traders' order submission strategies?In the price discovery literatur...

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“…30 Harris et al (2002) report that the influence of the NYSE on price discovery relative to regional exchanges increases as its spreads, compared to those of other exchanges, decrease. In the cross-border context, competitive market making by the TSX versus the NYSE can be inferred by comparing bid-ask spreads on the TSX and the NYSE.…”

Section: Informed Trading and Cross-border Price Discoverymentioning

confidence: 99%