Understanding Price Pressures and Realized Hedge Values in Financial Markets

1. Price Pressuresby Terence Hendeshott and Albert J Menkveld Discussant: Jeremy Large, AHL and Oxford-Man Institute at Oxford University 1 May 2009

2. Overview • Price pressures: price deviations from fundamentals when: • A risk-averse intermediary supplies liquidity • Asynchronously arriving investors have differing trading requirements • Theoretical model illustrates the inefficiencies of price pressures • They are caused by the intermediary’s response to bearing inventory risk • They cause investors not to complete valuable trades • Throughout paper, focus is on (2): “lowering of realized hedge values” • Numerical analysis of theoretical model, following Ho and Stoll (1981) • shows that illiquidity exacerbates the lowering of realized hedge values • Econometric model quantifies the effect(s) • Structural state-space model with unique dataset of daily overnight positions of NYSE specialists, ‘94 – ’05 (also ssfpack for ox)

3. Theoretical model • Lowering of realized hedge values: • Price pressures cause inefficiency because they present distorted prices to investors, which preclude some investors from completing valuable trades • A theoretical model quantifies this inefficiency, finding it to be the product of: • the variance of specialists’ inventories (in dollars) • one minus the (1st order) autocorrelation of inventory (this quantifies the effect on signed order flow of the price pressure) • sensitivity of prices to specialists’ inventories • This is the case under parametric structural assumptions.

4. Empirical model • Empirical section uses a unique dataset consisting of daily reported NYSE specialist positions, and a state space model (ssfpack for ox) to quantify • transitory volatility and show it is larger for small stocks • the effect on the price of shocks to the specialist’s position • the dollar value of the “lowering of realized hedge values” • (median ~$4m / stock / yr) • Model for a single market: • Underlying price, mt, is a random walk: • mt = mt-1 + (βγt + wt) • Observed price, pt, deviates from underlying price by a ‘Price Pressure’ of st : • pt = mt + st • ‘Price Pressure’ term depends on specialist’s inventory and lagged terms, plus an innovation εt.

5. Main Comments • Method should let you quantify the total realized gains from trade in the market?! (‘Total hedge value rate’) • A benefit to more specification testing? (e.g. are the inventory residuals autocorrelated?) • Other researchers call st ‘market microstructure noise’, caused by e.g. price discreteness. Do you / can we disentangle this from price pressure? • Remark that specialists are of declining importance

6. Secondary Comments • Are you the first to identify how price pressures can lower realized hedge values? • Purging systemic movements from the econometric analysis introduces complications such as lagged-gammas in one equation. • Would be simpler, hence informative/complementary also to present results with systemic returns in? • Could we have an explicit time-line over the day, of inventory samples, price samples? Could inventories be lagging rather than leading price pressures?