The Components of the Bid-Ask Spread: A General Approach

Abstract

A simple time-series market microstructure model is constructed within which existing models of spread components are reconciled. We show that existing models fail to decompose the spread into all its components. Two alternative extensions of the simple model are developed to identify all the components of the spread and to estimate the spread at which trades occur. The empirical results support the presence of a large order processing component and smaller, albeit significant, adverse selection and inventory components. The spread components differ significantly according to trade size and are also sensitive to assumptions about the relation between orders and trades. The difference between the ask and the bid quotesthe spread-has long been of interest to traders, regulators, and researchers. While acknowledging that the bid-ask spread must cover the order processing costs incurred by the providers of market liquidity, researchers have focused on two additional costs of market making that must also be reflected in the spread.

Is Best Really Better? Internalization of Orders in an Open Limit Order Book

“…For that purpose, we modify the Glosten and Harris (1988) approach to account for the specific dual market structure under scrutiny. We also estimate a restricted 11 version of the model which is similar to the models considered by Huang and Stoll (1997) and Madhavan, Richardson and Roomans (1997).…”

“…Given that our data allows identification of trades as buyer-initiated or seller-initiated, yet do not contain quote information, it is natural to employ a spread decompostion model along the lines of Glosten and Harris (1988), Huang and Stoll (1997) and Madhavan, Richardson and Roomans (1997) for a comparison and decompostion of transaction costs in Xetra and Xetra BEST. In the context of the present paper, the Glosten and Harris (1988) model is the most suitable framework.…”

End-User Order Flow and Exchange Rate Dynamics

“…The statistically insignificant deal size parameters may be due to traders' response to the strategy of dealers inferring information from order flow (Huang and Stoll, 1997). As informed traders' profits would surely decrease in the presence of learning dealers, there is a strong incentive to camouflage private information by splitting up orders into a number of (smaller) standardized transactions.…”

“…Huang and Stoll, 1997;Madhavan and Smidt, 1991). Independently of the dealer's decision on which market segment to choose in order to benefit from his private information, the logic of information aggregation on FX markets implies that customer order flow will consistently be more important in the determination of exchange rates than interdealer flow (Sager and Taylor, 2005).…”

Liquidity Cost Determinants in the Saudi Market

“…Bid-ask spread as a measure of liquidity was decomposed, using the model of Huang and Stoll (1997) to infer the information asymmetry patterns in the market. We use quoted spread (QBAS), relative spread (RBAS) and effective spread (EBAS) as three proxies for liquidity in the market.…”