Securities exchange micro-structure part 1 - NYSE, NASDAQ, CBOE, LSE, EuroNext, ASX

NYSE: order-driven. NASDAQ: quote-driven. LSE: quote-driven. ASX: order-driven.

NYSE faster for market orders. NASDAQ is faster overall (25 seconds). NYSE slower (50 seconds) because of manual execution & auction.

Liquidity

Liquidity has U-shape pattern: high at open and close. Trade while liquidity is high. Prices are more informative in liquid parcels.

NYSE orders are consolidated. NASDAQ orders are fragmented because NASDAQ has different trading locations.

Switch from NASDAQ to NYSE: liquidity & price efficiency improved, volatility reduced. Consolidation is more valuable for less liquid stocks.

Spreads

NASDAQ: spreads are stable through out the day but narrow near close.

NASDAQ spreads remain constant during first hour. NYSE spreads decline.

NASDAQ spreads narrow near close, NYSE spreads widen near close.

CBOE options: spread high at open, narrows after open, lowest at close.

NYSE: reversed-J spread shape.

Inverse relationship between spreads and activity. Relationship between risk and spreads. Relationship between spreads and information coming to market. Inverse relationship between spreads and competition.

Switch from NASDAQ to NYSE: quoted spreads & effective spreads decrease.

Institutional Trading

70% trading volume on NYSE is by member firms & institutional investors.

Large block institutional sale: perceived as liquidity motivation. Block purchase: perceived as containing favorable information, especially for small stocks.

Seller-initiated: down then slightly up, price effect is temporary. Buy-initiated: up then slightly down, price effect is permanent.

Seller-initiated: price reaches equilibrium after 3 trades, most adjustments in the first trade. Buy-initiated: equilibrium after 1 trade.

Downticks: price effect is largely permanent. Upticks: permanent price effect dominates.

Brokers do short to accommodate block purchase.

Anonymity

Spreads decline. Aggressiveness decline. Orderbook depth increases.

Limit order traders are more willing to expose under anonymity.

Anonymity attracts order flow from non-anonymous markets, but only for large stocks.

Anonymity has few benefits to inactive stocks, and higher benefits in presence of information asymmetry.

Increase in spreads foreshadows increase in volatility.

Positive relationship between spreads in one parcel and magnitude of price change in the subsequent.

Exchanges in fragmented markets should consider anonymous trading to improve price competition and liquidity.

Bibliography

Bennett & Wei, 2006, Market structure, fragmentation, and market quality

Admati & Pfleiderer, 1998, A theory of intraday patterns: volume and price variability

Chan, Christie & Schultz, 1995, Market structure and the intraday pattern of bid-ask spread for NASDAQ securities

Chan, Chung & Johnson, 1995, The intraday behavior of bid-ask spreads for NYSE stocks and CBOE options

Chan & Lakonishok, 1992, Institutional trades and intraday stock price behavior

Comerton-Forde & Tang, 2009, Anonymity, liquidity and fragmentation

Foucault, Moinas & Theissen, 2005, Does anonymity matter in electronic limit order markets?

Holthausen & Leftwich, 1987, The effect of large block transactions on security prices

Holthausen, Leftwich & Mayers, 1990, Large-block transactions, the speed of response, and temporary and permanent stock-price effect

McInish & Wood, 1992, An analysis of intraday patterns in bid/ask spreads for NYSE stocks

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