Measuring Market Liquidity

1. Measuring Market Liquidity

2. Market liquidity Being able to trade the quantity you want to trade with minimal price impact and minimal cost Can measure liquidity for individual stocks and then aggregate across the market We can get direct measures: Price impact of trades Transaction costs Trade sizes

3. Comparing liquidity But how do we compare liquidity across stocks? Or within the same stock across time? Suppose we see the following quoted % spreads GPS = 15 bps; ANF = 20 bps Is ANF less liquid? Maybe on this dimension… Is the specialist for GPS doing a better job? Depends on the factors that influence the spread. In order to make relative comparisons of liquidity we need to understand and control for factors that influence spreads. Note both GPS and ANF are NYSE-listed, so differences in market structure are not an issue in this case.

4. Spreads and Spread Components

5. The bid/ask spread The spread is the price impatient traders pay to immediately buy or sell The spread is the compensation market makers (MMs) and limit order traders earn for offering liquidity Understanding spreads, and their drivers, is important to: Optimize order submission strategies given current market conditions – market vs. limit order strategies Maximizing dealer profitability Learning about how changes in market structure should change liquidity

6. Spreads and MMs Spreads are crucial to MM profits If a monopolist, MMs would set spreads to maximize profits Spread must be wide enough to cover costs of doing business Spreads can’t be too wide, or else order flow will be too weak to cover costs MM profit a function of: Effective spread earned on their round-trip transactions Number of round-trip transactions Losses due to market movements against their inventory positions

7. Spread components

8. Overview of spread components If the spread constitutes all (or the majority) of a market makers revenue, then it needs to cover the costs of doing business These costs are typically broken into two components: Transaction Cost (Inventory Cost) Component Inventory Risk Order-Processing Costs (normal business costs) Adverse Selection Cost Component Risk due to asymmetric information - MMs will lose on transactions with informed traders. Note that some economists break spread down into the three components with the pink bullets above.

9. Market Maker Inventories Dealers and Specialists have inventories of stock from which they trade They can control their inventories by adjusting the aggressiveness of their quotes If inventory is too low: May have to bypass profitable trades May be in violation of capital requirements To fix: Bid aggressively, ask away from market Increases probability that MM buys If inventory is too high: Position is expensive to finance At increasing risk to drop in stock price Specialists rarely (if ever) hedge their positions. Why? To fix: Ask aggressively, bid away from market Increases probability that MM sells

10. Inventory Risk MMs gain when markets move with their inventory position, and lose when markets move against their inventory position Diversifiable inventory risk Due to firm-specific (unsystematic) events no one can predict If movements are uncorrelated across stocks, then this risk is diversifiable in the specialist portfolio Return volatility (idiosyncratic risk) is therefore a factor influencing inventory risk – especially so if the MM is not well-diversified

11. Inventory Risk Non-diversifiable inventory risk Due to correlated (systematic) adverse market movements on stocks with similar inventory positions Regardless of diversification of portfolio, systematic market movements can decrease value of MMs inventory Historical Note: about 1/3rd of NYSE specialist firms were essentially put in bankruptcy after market crash of October 1987.

12. Transaction Cost or Inventory Component of the Spread A component of spread needs to cover: Risk premium MMs may require for bearing inventory risk Normal costs of doing business Cost of capital for assets (inventory) Staff wages Exchange memberships/dues Technology investments Office space, utilities, other overhead This component is sometimes also called the “transitory spread component” If these were the only costs of market making, equilibrium spread would straddle true value, and we would observe ‘bid ask bounce’ in transaction prices (transitory price changes)

13. Adverse Selection Risk The risk of trading with informed traders MMs know they always lose when trading against a truly informed trader When informed traders buy, MM inventory falls, and prices subsequently rise When informed traders sell, MM inventory rises, and prices subsequently fall

14. How to deal with adverse selection? The best method for the MM to deal with this risk is to adjust quotes such that order flow is two-sided (flowing to both bid and ask equally) This means the quotes are currently close to what the market believes is the true value Widen quotes so that order flow and trade is limited on both sides of market (equally) This limits losses by simply limiting trading MM’s typically do not try to figure out true fundamental values of securities they trade. They instead focus on order flow and quote adjustments to make a two-sided market.

15. Adverse selection spread component MM’s adjust quotes based on the probability of informed trade Greater probability of informed trade, should lead to wider spreads, all else constant This change in spread due to this risk is called the “adverse selection component” of the spread This component is sometimes called the ‘permanent spread component’ (as opposed to ‘transitory’) Top of pg 300 Price changes due to adverse selection do not systematically reverse Instead, price changes reflect MMs inference of true stock value given the direction of order flow if done correctly, the sequence of resulting price changes should be random

16. Total Spread (see pg 301) V0 is current value estimate V0B is estimated value given that next trader is a buyer V0S is estitmated value given that next trader is a seller

17. Total spread on next trade If trade at t=1 is a buyer:

18. Many studies estimate spread components Econometricians can estimate the size of the components because they predict different price movements TC component should yield transitory ‘bounce’ Adverse selection component should yield a random walk Most studies have found the adverse selection component to be more important

19. Some empirical evidence Ho and Macris (1984) find that an option specialist’s quotes are influenced by his inventory position, consistent with inventory-based models of market making. Glosten and Harris (1988) decompose bid-ask spreads into 2 parts, and find that adverse selection component rises in importance with trade size. Stoll (1989) decomposes spreads into 3 parts, and finds: 43% Adverse Information Costs 10% Inventory Holding Costs 47% Order Processing Costs Hasbrouck (1988) using different method, also find significant inventory and adverse selection components, with much stronger adverse selection components Madhavan and Smidt (1991) use specialist inventory data and also finds a much stronger adverse selection component. Lin, Sanger, and Booth (1995) further analyze spread components by time of day, trade size, and market venue (see next 2 slides)

20. Some empirical evidence

21. Some empirical evidence

22. Cross-sectional liquidity predictions

23. Some cross-sectional spread predictions Stocks with greater probability of informed trade will have higher spreads and lower liquidity, all else constant. Stocks whose characteristics make it more difficult to manage inventory will have wider spreads. What proxies to use?

24. Cross-sectional proxies Volatility Stocks with greater return volatility (idiosyncratic and systematic) should have greater inventory cost components, all else constant. Also, greater volatility leads to more uncertainty about estimate of V0 Thus, volatility should also exacerbate asymmetric information problems

25. Cross-sectional proxies Utilitarian Trading Interest Recall that they trade for reasons unrelated to profit; we often call them ‘liquidity motivated traders’ Stocks with stronger utilitarian trading interest tend to be more actively traded, which in turn, causes spreads to narrow through competition for immediacy allows inventories to be more easily adjusted More opportunities for MM to adjust inventory causes a dilution of the probability of informed trade in the order flow, lowering the adverse selection component

26. Cross-sectional proxies Size of the firm Larger firms have more information production Increase utilitarian interest Decrease prob of informed trade Number of analysts Stocks with more reporting analysts should have lower spreads – again due to information production Press coverage Stocks with greater press coverage (good or bad) should have lower spreads – due to information production Conglomorates Holding size of the firm constant, firms with more business units should have lower spreads due to lower inventory and adverse selection risks Industry or product age Firms in ‘old’ industries should be more easily valued than firms in ‘new’ industries Firm Age Old firms should be more easily valued, all else constant, lowering adverse selection Material information releases Probability of informed trade should increase immediately prior to earnings releases, or other announcements

27. Fragmentation issues? Market fragmentation is the degree that a stock’s order flow is spread across various market centers How should that alter spreads? Greater fragmentation might increase competition between traders and lower spreads Christie and Schultz (1994)… Greater fragmentation might fail to bring buyers and sellers together, leaving each center with a larger spread than one concentrated trading center might achieve Seems to be a question that only evidence can answer… we come back to this one next week.

28. Cross-Sectional Prediction Summary Spreads are positively related to: Return volatility Spreads are negatively related to: Trading interest Firm size Number of analysts Degree of press coverage Number of business units Firm age Industry age

29. How do we measure market liquidity?

30. Common liquidity measures Quoted bid-ask spreads Effective bid-ask spreads Price impact Amihud (2002), others ILLIQ = Absolute return / dollar volume PIN – econometric methods of estimating the probability of informed trade

31. Spread comparisons Given that we can imagine what factors influence spreads, we can compare spreads across firms with different market structures while attempting to hold constant various factors known to influence spreads. Huang and Stoll, 1996, “A Paired Comparison…” Bessembinder, 1999, “Trade Execution Costs on NYSE…” Think about how market design issues influence spreads and liquidity Coughenour and Deli, 2002, “On the Organizational Form…” Corwin and Coughenour, 2008, “Limited Attention…”

32. Assignment 1B For same stock, gather Consolidated Quote Data for same day in 2004 and 2009 in Excel These will be bigger files… By sorting, eliminate quotes with prices of zero and share quantities of zero By sorting, eliminate quotes with dollar spread > $5. These are probably errors Calculate dollar and percentage quoted spreads for each remaining quote What is the distribution of each spread across whole day? What is the distribution of each spread for just Ex=‘N’? What is the mean spread at each half-hour interval? What is the Amihud (2002) ILLIQ measure each half-hour? Absolute return / dollar volume of trade Need to use both data sets. See page 2 of his paper linked on webpage (last day of class)