Market Microstructure Daniel Sungyeon Kim

1. Market MicrostructureDaniel Sungyeon Kim

2. Block Traders Q: What is a block trade?

3. Block Traders • Q: Why don’t these large trades automatically get handled by the specialist or dealer who has quoted bid and ask prices?

4. More on Block Trades • “Latent demand problem” = hard to find a counterparty to trade a block • Q: Why doesn’t block initiator post on Craig’s list? FOR SALE 80,000 Shares of GE

5. More on Block Trades Suppose Ask = $39.60 for 800 shares Bid = $39.50 for 500 shares Q: Why don’t profit-seekers submit a limit buy? WILLING TO BUY 50,000 shares at $39.30

7. Submission to an Exchange Now let’s consider an example to see what happens next after the buyer and seller are matched Fidelity wants to sell 20,000 Upstairs Broker finds CALPERS who agrees to buy 20,000 at $30.00 Next: Deal is submitted to an exchange in the form of matched limit orders Fidelity = limit sell for 20,000 shares at $30.00 CALPERS = limit buy for 20,000 shares at $30.00

8. More on Submission to an Exchange • Example #1: Need to determine which exchange • NYSE: Limit buy for 1,000 at $30.00 – has time priority • Boston: no limit buys – could by-pass the NYSE limit buy by trading here • Q: How can the NYSE avoid losing block business to Boston?

9. More on Submission to an Exchange • Example #2: Suppose there is a Limit buy for 4,000 at $30.02, which is a better price • Q: How would Fidelity’s limit sell execute in this case?

10. Angel, Harris, and Splat • Section 4: Classic Trading Problems: • Buyers need to find sellers and sellers need to find buyers = “latent demand problem” • Avoid trading with informed traders = “asymmetric information problem” • Problems associated with large traders: • Front-running = “order exposure problem” • Quote-matching • Naïve larger trader: Limit buy for 40,000 shares at $30.00 • Quote matcher: limit buy for 2,000 shares at $30.01  it executes • If prices rise to $32.00  $2.01 profit • If prices fall to $28.00, quote matcher submits market sell which executes against naïve large trader at $30.00  only a $.01 loss • Requires quote matcher to react faster than naïve large trader • Price discrimination = “price discrimination problem”

11. Innovative Solutions • Order routing to exchanges – electronic routing lead to national and regional consolidation of exchanges • ECNs (Electronic exchanges) – • fast updating of orders and automatic execution  competed well in NASDAQ securities • Faced long wait (15 seconds) to avoid trading through floor-based exchanges  competed poorly in NYSE and AMEX securities • Hidden order size – • On large limit orders, most is hidden and tiny amount is displayed • Avoids front-running and quote-matching • Hidden orders are executed via market orders or marketable limits • Dark pool – POSIT • Buy orders and sell orders are submitted, but keep totally dark • Market is called every hour • Matched shares are executed at quote midpoint of NYSE

12. More Innovative Solutions • Dark pool – Liquidnet • Customers share buy and sell order info • Liquidnet notifies customers with opposite trading interest • They negotiate price and size annoymously • Dark pool – Actionable indications of interest • Customer indicates a willingness to buy or to sell • Info only goes to trustworthy people • Algorithms • Large demands are broken up into many small orders that are spaced out over time • Execution is dynamically managed to meet customer needs • Proprietary trading • High-frequency market making and arbitrage strategies

13. More Innovative Solutions • Co-location • High-frequency traders locate their servers in the same room as exchange servers  get information and submit orders as fast possible

14. Market Performance during Financial Crisis The markets performed smoothly during the high volatility and high volume of the 2008 financial crisis Vs. 1987 crash where the printing of orders fell 1 hour behind, trade reporting fell 2 hours behind, and NASDAQ dealers refused to answer the phone Short selling was temporarily banned in the US and in many countries around the world – we will examine this in more detail in a later class

15. Comparison with Other Markets US: Open architecture  competition  lower costs Some countries: Monopoly exchanges  fallen behind Europe: Moved to competitive structure  show a decline in legacy exchanges

16. Recommendations for SEC Rulemaking Make-or-take pricing: example: BATS charges a fee of $0.0025 per share for any order that takes liquidity = demandsliquidity = market order or marketable limit order And provides a rebate of $0.0024 per share for any order that makes liquidity = suppliesliquidity = nonmarketable limit order that is submitted and then executes All fees and rebates are less than one cent Regulation NMS capped the fees at $0.0030

17. Price of Liquidity Tape A = New York Stock Exchange-listed stocks Tape B = Regional Stock Exchange-listed stocks (including AMEX, NYSE ARCA) Tape C = NASDAQ-listed stocks Routing Fee = when the order is rerouted to another exchange to get a better price

18. Make-or-take pricing Concern: Making rebates and taking fees distort broker routing decision – most brokers keep the rebates, so customer doesn’t benefit – may route retail market orders to brokers who internalize orders to avoid the fee Recommendations: Require brokers to pass both fees and rebates to customer Require brokers to route orders to NBBO based on net prices: Making order: net price = price + rebate Taking order: net price = price - fee

19. Naked Sponsored Access When the broker does NOT examine and verify that customer orders are reasonable before submitting them to an exchange  customer’s computer can submit orders at electronic speed to broker and sent to exchange at electronic speed Concern: programming error or unanticipated situation  unintended orders  settlement failure Example: customer wants 10,000 shares, but submits orders for 10,000,000 shares Example: during 2009 “Flash Crash,” Accenture stock had been trading for $38, suddenly traded for $0.01  the NYSE nullified such trades after the fact Recommendation: prohibit naked sponsored access  must be a broker-dealer with plenty of capital to directly access the market

20. Misfiring Algorithms Concern: Trading algorithms go out-of-control and submit unintended orders for large quantities Recommendation: Examine the risk and take appropriate action

21. Flash Orders Suppose: Then a market buy for 5,000 shares arrives at BATS BATS will execute $1,000 shares at $30.10 Reg NMS requires that after 1 second, the remaining market buy for 4,000 shares be routed to DirectEdge to fill at $30.11 But within that 1 second window, BATS will “flash” a new Bid price of $30.10 for 4,000 shares If a high-frequency trader is willing to sell 4,000 shares at $30.10, then the market buy executes on BATS at $30.10 Otherwise, the remaining market buy gets routed to DirectEdge to execute at $30.11

22. Flash Orders Concern: Creates a “two-tier” system because only high-frequency traders can observe the flashed bid price and respond with an opposite side order in less than 1 second SEC: considering a ban on flash orders Recommendation: make sure use of flash orders is voluntary for customers Concern: A high-frequency trader who observes a flash order may front-run the order in less than 1 second Recommendation: Prohibit front-running for a 1 second period

23. Front-Running Orders in Correlated Markets Broker-dealer receives a market buy  can’t buy on own account until market buy executes Broker-dealer receives a limit buy  can buy on own account at one penny higher price until limit buy executes Concern: Nothing stops a broker-dealer from buying highly correlated assets (futures on that stock, options on that stock, stocks in same industry) while handling a customer buy order No evidence that this is happening now, but … Recommendation: Prohibit buying highly correlated assets while handling a customer buy order

24. Sub-penny pricing Tick size reductions: $1/8 to $1/16  lower spreads and lower depths $1/16 to 1 penny  lower spreads and lower depths How about 1 penny to 1 mil (1/10 penny)? Benefit: lower spreads Costs: lower depths; more trading shifted to dark pools; clutter trading screen with more data, but less info

25. Consumer Disclosures of Broker Quality Rule 605: Exchanges must disclose info on effective spreads, % of orders executed, time to execution, etc. Rule 606: Brokers must disclose info about where orders are routed and if they receive payment for order flow from that venue Recommendation: Brokers should be required to disclose statistics about the effective spreads, % of order executed, time to execution, etc. of orders that they handle

26. SOES Bandits • 1987 market crash – NASDAQ dealers escaped from supposedly “firm quotes” by not answering the phone • Response: Small Order Execution System (SOES) automatic execution of orders up to 1,000 shares • Gave rise to what become called “SOES Bandits” • If there are 20 dealers and 5 dealers start moving price up, then send buy orders to the remaining 15 dealers and then sell a few minutes later when everyone’s prices have increase • “Monster buttons” that with a single click will send the maximum 1,000 share orders to those dealers who have not changed their price

27. SOES Bandits • What started as a small problem became huge when Harvey Houtkin of AllTech started recruiting people to become SOES bandits – give them a one week seminar, set them up with a NASDAQ level II screen and trading software, act as the broker charging a modest commission  huge amount of SOES bandit trading

28. More on SOES Bandits • NASDAQ felt they were destroying the whole dealership market at the expense of the general public – NASDAQ tried to prohibit “professional traders” from using SOES – Houtkin took them to court and won • A study of SOES Bandit profits showed that 2/3 lost money, but 1/3 made money – key to profitability was exiting your position using limit orders on Instinet • This was really the start of something much bigger – the whole day trading phenomena

29. Day Trader Training Classes Q: Focus more on day trader training classes. What do they teach you?

30. NASAA Report North American Securities Administrators Associations (NASAA) = Securities regulators NASDAQ has proposed to regulated day trading firms and require the same “appropriateness” or “suitability” rules that applies to brokers who are licensed by the SEC

31. NASAA Report Q: First considering the business practices of the day trading training firms, what complaints do they have?

32. More on NASAA Report Q: What did they find when they analyzed day trader accounts?

33. More on NASAA Report • NASAA recommends: • “suitability” requirements for candidates to be trained in day trading • disclosure of risks for these training businesses

34. More on NASAA Report • No “suitability” or disclosure requirements have ever been adopted – it is still the “wild west” out there!

35. Barber and Odean Even if one doesn’t go to Barton’s extremes, if day traders are losing money, there’s one obvious question: Q: Why don’t they just stop?

36. Behavioral Vs. Traditional Finance This brings us to an emerging area of finance: Behavioral Finance – psychological reasons, including cognitive biases and irrational behavior Vs. Traditional Finance – economic reasons – strictly rational behavior

37. Barber and Odean • Charles Schwab data on 64,465 households • These are “ordinary investors,” not day traders • Investigate the relationship between how much you trade and your investment returns

39. Trading is Hazardous to Your Wealth • Separated into five groups by turnover (amount of trading) • 25% turnover / month = 3 times / year (vs. 278 times / year for day traders) • Grey bars show turnover for five groups • White bars  roughly the same gross return • Black bars  declining performance the more you trade  burn up your money in trading costs • Consistent with overconfidence

40. More Trading is Hazardous to Your Wealth • Now extend the grey bars (turnover) from active investor turnover of 3 to a day trader turnover of 278 • the grey bars would have to go up to the roof! • Similarly extend the black bars (net returns) from active investor low returns to day trader very negative returns • the black bars would go down a couple floors into the bedrock! •  Day trading is a good way to lose a lot of money