Market Microstructure Daniel Sungyeon Kim

1. Market MicrostructureDaniel Sungyeon Kim

2. Types of Arbitrage • I’ll give you some examples of arbitrage and you tell me what type of arbitrage they are (pure arbvs. speculative arb, etc.) • Arbs buy low, sell high  profit on the price difference Ex: TSE GM = $35.20  sell high (converted to US $) NYSE GM = $35.00buy low profit = $0.20 • Ex: Corn in France = $7.00 / bushel  sell Corn in US = $6.00 / bushel  buy, ship Shipping cost = $0.60 / bushel Profit = $0.40 / bushel • Q: What kind are they: pure arb or speculative arb?

3. More on Types of Arbitrage • Here is an example of speculative arb • Pairs trading: • GM is underpriced (your value > market price) • Ford is overpriced (your value < market price) • Spec arb = (+$1 million) in GM & (-$1 million) in Ford •  if correct: GM up and Ford down  profit • Q: How much marketwiderisk does this bet have?

4. More on Types of Arbitrage • Here is an example of speculative arb • Pairs trading: • GM is underpriced (your value > market price) • Ford is overpriced (your value < market price) • Spec arb = (+$1 million) in GM & (-$1 million) in Ford •  if correct: GM up and Ford down  profit • Q: How much auto industry risk?

5. More on Types of Arbitrage • Here is an example of speculative arb • Pairs trading: • GM is underpriced (your value > market price) • Ford is overpriced (your value < market price) • Spec arb = (+$1 million) in GM & (-$1 million) in Ford •  if correct: GM up and Ford down  profit

6. More on Types of Arbitrage • Portfolio generalization: • Low tech stocks are underpriced (your value > market price) • High tech stocks are overpriced (your value < market price) • speculative arb= (+$1 million) in low tech portfolio and . (-$1 million) in high tech portfolio • Q: How much marketwide risk does this bet have?

7. Application to the Flash Crash Suppose heavy selling pressure on S&P 500 stocks that pushes the price down but no selling pressure in mid-cap and small-cap stocks Q: What should speculative arbitrageurs do?

8. More on Types of Arbitrage Q: Going back to the first two examples (GM and Corn), are they cross-instrument arbor intermarketarb?

9. More on Types of Arbitrage Here is an example of Cross-instrument arb: Soybean crush = beans can be crushed and made into oil and meal tight relationship: beans and oil & meal cost to crush Q: How do you arb, if beans are cheap?

10. More on Types of Arbitrage Here is an example of Cross-instrument arb: Soybean crush = beans can be crushed and made into oil and meal tight relationship: beans and oil & meal cost to crush Q: How do you arb, if beans are expensive?

11. More on Types of Arbitrage • Index arbitrage • Based ontight relationship: S&P 500 Stock Index • S&P 500 Stock Index Futures Price • “Cost of Carry” = “Spot-Futures Parity” – this pricing equation tells us the relationship should be: • (S&P 500 Stock Index Futures Price) = (S&P 500 Stock Index) * (1 + Riskfree Rate)^(Time to Maturity) • based on the Time to Maturity of the Futures contract • Deviations from Cost of Carry arbopportunity

12. Price Convergence At maturity, the Time to Maturity = 0,  S&P 500 Stock Index Futures Price = S&P 500 Stock Index called Price Convergence Price Stock Index Futures Price Stock Index Time Maturity

14. Index Arbitage • If cost of carry deviation before maturity is greater than transaction costs, then initiate arbitrage  gain profit • At maturity, close out position  zero profit at maturity because of Price Convergence • Q: Is this pure arbor speculative arb?

15. Price Vs. Quantity Characterization • Price characterization: arbitrageurs buy low and sell high  brings prices together • Quantity characterization: arbs move assets and liquidity from one market to another • Going back to our earlier examples: • Arbsmove GM shares from NYSE to TSE • Arbs move corn from US to France • Connecting two markets that would otherwise be separate •  combines the liquidity of the two markets

16. Gatev, Goetzmann, and Rouwenhorst Q: What is their “pairs” investment strategy?

18. Kennecott and Uniroyal • Kennecott = cooper mining company • Uniroyal = variety of industrial products, particularly tires • Not clear why they should tract each other • Day 8 = open position • Q: Which do you buy and which do you sell on day 8? • Buy Uniroyal and sell Kennecott • Buying “loser” and selling “winner”  contrarian strategy • Day 33 = prices converged  close position • Do many times over 6 months (sometimes Uniroyal is lowest, so you buy Uniroyal and sometimes Kennecott is lowest, so you buy Kennecott) • Q: Is this fundamental analysis or technical analysis?

19. Pairs Trading Pairs traders might be disciplined investors who exploit undisciplined over-reaction by other investors “Self-financing” strategy = sell short stock A, use proceeds to buy stock B strategy pays for itself with no extra money needed typical of what hedge funds do

25. Bowen, Hutchinson, and O’Sullivan Universe: FTSE 100 stocks on the London Stock Exchange Q: What is their “intra-daypairs” trading strategy?

27. Exhibit 1 Clearly Barclays and the Lloyds Banking Group are moving together. Q: Does this make sense? Q: What units of time are graph here?

29. Exhibit 2 Q: At the first opportunity, which stock do you buy vs. sell?

30. Exhibit 2 The gap opens and closes three times – spec arb hopes to exploit transitory price deviations – due to “overreaction” or to temporary imbalance of buyers and sellers The fourth time big negative shock to Lloyds and no tendency to close the gap –might be permanent price shock – due to news  gap might never close

32. Exhibit 3 Comparing gap to open = 2 stddev vs. 3 stddev  average price deviation is smaller, but average round trips is larger

34. Exhibit 4 Returns with 2 stddev triggers Q: How sensitive are the returns to transaction costs?

36. Exhibit 5 Returns with 3 stddev triggers Q: How sensitive are the returns to transaction costs?

38. Exhibit 6 Returns to waiting one houron 3 stddev triggers Q: How sensitive are the returns to waiting one hour and transaction costs?

39. Summary Returns on high-frequency pairs trading is very sensitive to speed and to transaction costs

40. Informed Trading We know that insider information= Illegal to trade on Q: What private information is legalto trade on?

41. Informed Trader Types Q: What are the four types of informed trading, what they trade on, and the impact that eachtype has on prices

42. Impact on Market Efficiency • Q: What impact does legal informed trading have on market efficiency? Eugene Fama, developed Market Efficiency theory and evidence

43. Bessembinder, Maxwell, and Venkataraman • Q: What is TRACE? • Financial Industry Regulatory Authority

44. TRACE • Corporate bonds trade in a fragmented dealer market • Before TRACE: the market was very opaque price were not reported publicly • After TRACE: Must report bond price to NASD within 75 minutes of trade info was published on NASD web site with a 4 hour delay (not exactly “real time”!) • Applies to all bonds with issuance size = $1 billion or greater • Implemented July 1, 2002

45. Half Spreads on TRACE Bonds • Data: 6 months before and 6 months afterimplementation • Bonds covered by TRACE and those not • Don’t observe bid-ask prices, but DO know which are buys vs. sells  imply transaction costs from regression • Change in price = Change in Q + other factors • Q = 1 for a buy at implied ask • = -1 for a sell at implied bid • Coefficient on Delta Q =effective half spread

48. Spill-over Effect on Non-TRACE Bonds Table 3 (not included) Spill-over effect on Non-TRACE bonds 15% reduction in trading costs

49. Edwards, Harris, and Piwowar • Aggregate value Corporate Bonds = Stocks • By Jan 2003, all OTC bond trades report to TRACE, not just $1Billion or greater • Sample: All TRACE reported trades from Jan 2003 – Jan 2005 • 12.3 million trades worth $9.3 Trillion • Under pressure, NASD phased in “real-time” reporting = within 15 minutes by Jan 2005 • They examine trading costs by size, credit rating, etc. and by transparent vs. opaque