1. Best Execution ITG Inc., Member NASD, SIPC © 2003 ITG Inc., All Rights Reserved, Not to be reproduced without permission 91603-82599 Transactions Costs and Trading Zhiwu Chen, Yale School of Management Note: This presentation is mostly adapted from the slides prepared by Ian Domowitz, Managing Director of ITG, for his talk at Yale on Oct. 1, 2003. His work is gratefully acknowldged.

2. 2 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Successful Implementation Strategies  Trade data  Organization  Performance vs. benchmarks  Sorted and organized  Access to all liquidity sources  Logical participation trading strategies Portfolio Management Pre-Trade AnalysisPost-Trade Analysis Trading Trade Blotter  Trading cost  Risk analysis  Optimal horizon  Risk analysis  Optimization  Fair value pricing

3. 3 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Who’s Got the Alpha?*  Two funds:  Large Cap Value Gross Alpha=13.1%  Small Cap GrowthGross Alpha=17.8%  Both Incur Trading Costs * John Bogle Jr.. “Transaction Cost and Growth of Assets”

4. 4 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Will the Real Return (and Risk) Please Stand up?

5. 5 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Trading Costs Impact Fund Rankings Top 25 funds more pronounced: Average 8.5 bps between ranks Next 75 funds: Average 0.6 bps between ranks 16 bps would move the #50 Fund to #20.

6. 6 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Three Step Program  Measurement  Regular pre-trade and post-trade measurement  Focus on implicit costs of the entire trade  Analysis  Compare trades to appropriate benchmarks  Aggregate pre-trade and post-trade trade results by meaningful categories to see hidden costs  Control  Trading as a source of value  Logical participation  Control the attributes of residual portfolios throughout the execution process

7. 7 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Measurement  Trading costs are more than commissions and spreads  Implicit costs, including market impact, are significant...  But do not omit delay and opportunity costs midpoint BIDASK EXECUTION COST Market Impact Spread

8. 8 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Measure Indirect Trading Costs Paper Returns Returns if all trades were executed instantaneously and with zero cost at the decision price Real Returns Trades partially or fully executed at prices achievable in the market, or not executed at all Implementation Shortfall Direct Costs Commissions, Ticket charges,Taxes Indirect Costs Delay Cost, Timing Gain/Loss Market Impact Opportunity cost

9. 9 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Types of Costs PM Decision Price Release Price B/O Midpoint at Execution time Executed Price (Assumed) Executed Price (Actual) Delay Timing Gain/LossMarket Impact Opportunity Cost Executed Orders Unexecuted Orders TIME

10. 10 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Arbitrageur Price Anomalies

11. 11 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission The organization of stock exchange makes a difference to price impact

12. 12 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission On Benchmarks  So many choices, so much confusion  What benchmarks to use?  Miscommunication between traders and portfolio managers symptomatic of benchmark issues  Traders may perform well versus VWAP benchmark ...but portfolio managers are dissatisfied  Pursuing a VWAP benchmark encourages traders to parcel out their trades over several days, missing the opportunity to obtain alpha

13. 13 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Typical Example Original Order: Buy 100,000 INTL 1/10/01 10:46 Executed as follows: 1/10/01 30,000 @ $8.00 1/11/01 20,000 @ $8.75 1/12/01 30,000@ $9.50 1/16/01 20,000@$10.00

14. 14 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Benchmarks Results But Using Decision Price Cost is 14.25% Using Multi-Day, Order-Level VWAP Benchmark Cost is Negligible

15. 15 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission A Study in Timing: an example  The head trader believes costs are too high for relatively liquid stocks  Goal: identify the cost drivers  The trade order management system has time stamps for:  When the order was released by the PM to the desk  When the desk released the order to the broker  When the broker executed the trade

16. 16 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission The Scenario Trading Desk Places Trade Exec Price (Actual) Opportunity Cost (Slippage) Overall transaction costs were 52 bp from order release to execution Costs from order release by the PM’s to the Trading Desk equaled 38 bp per share Total Cost 52 bp Order Received By Broker DelayTiming Gain/Loss Market Impact Cost 38 bp Cost 14 bp PM Releases Order Decision Price Costs from when the trade was placed by the desk to the Broker were 14 bp per share.

17. 17 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Costs By Order Size / Market / Side

18. 18 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Costs By Time Delay

19. 19 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Costs By Time Delay & Order Size

20. 20 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Back to the Head Trader  Not just large orders  Timing study might suggest excess costs for larger orders when sufficient liquidity was unavailable  Instead, presentation of a coherent set of results elicits:  desk has been holding small and large orders to package together as part of programs  the packaging has adverse consequences  opportunity costs were incurred when the markets moved against the trade

21. 21 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Analysis  Building a narrative  Aggregate pre-trade and post-trade trade results by meaningful categories to see hidden costs

22. 22 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Periodic Reviews Add Value  Head of Trading performs periodic post-trade analysis to detect trends and refine investment style  Classify by market, sector, etc.  Post-trade analysis indicates mediocre trading performance  Costs are 135 basis points overall, relative to an order-level, mid-point benchmark

23. 23 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Outcome  Improve trading strategy and performance by synchronizing PM and trader goals  Use implementation shortfall as the trader’s benchmark  Incorporate this benchmark in the PM’s stock selection process  Traders incented to obtain target price close to target price of the PM  Traders may be willing to pay up in some cases to get the trade done  PM’s are more aware of the liquidity characteristics of their trades and potential costs

24. 24 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Delay Costs: consider an example  Trader is concerned that his firm’s DOT executions are too costly  DOT flow is routed through one major broker  From the time the trade was released to the desk to the time of execution, costs averaged 35 basis points (buy-ask, sell-bid)  In dollar terms, this was about 9.5 cents  Given the volume of DOT orders, this represents a significant cost  Should the broker be fired?

25. 25 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Decomposition PM Releases Order Desk Places Trade Broker Gets Order Executed Price Desk Delay Time DelayMarket Impact Delay Costs = 26 bps Total Cost = 35 bps Executed Orders TIME

26. 26 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Results of Decomposition  Approach  Obtain time-stamp from TOMS to figure out time when order was first sent from the PM desk, client’s trading desk.  Broker has time it received order  Of the 35 bps cost  26 bps is attributable to delays/slippage Of which, 3 bps is noise due to time stamp mismatches  9 bps is the cost Measured from when the broker received the order Benchmark is buy at ask, sell at bid

27. 27 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission “9 bps is still too high!”  Maybe  Further analysis finds that some trades are sent prior to the open  Cost computation uses previous quotes, which might be considered to be misleading

28. 28 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Illustration for Sell Order Portfolio managers have a systematic tendency to generate sell orders prior to open if market is likely to decline 9:30 AM Previous Bid (Benchmark for sell) Opening Price Incorrect Attribution of Cost (5 bps)  Broker Executes at Opening Price 

29. 29 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Resolution  For orders received pre-open, use opening price as benchmark; otherwise buy at ask, sell at bid  Results: Broker cost falls to 4 bps  Outcome  No change in broker  Methodology adopted to measure other brokers  Approach to creating program trades reviewed

30. 30 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Now, what can you do to control price impact costs?  The real name of the game  Identify means of reducing price impacts  Example: liquidity monitoring possibilities  Larger sizes in an environment characterized by more trades  Larger sizes with smaller spreads

31. 31 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Size Liquidity low high Cost Size Liquidity States and Costs

32. 32 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Price Impact and Upstairs Trades

33. 33 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Horizon Managers  Given a strategy, trading over extended horizons depends on characteristics  For a particular stock, logical participation depends on strategy

34. 34 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Different Stocks /Different Strategies To Reduce Costs

35. 35 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Trade Distribution Example Aggressive: high volatility, small percentage ADV Passive: low volatility, high percentage ADV

36. 36 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Traditional Index Strategy v. Logical Participation

37. 37 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Another way to manage costs: trading over Longer Horizons  Two objectives  match the desired trading distribution/benchmark closely  obtain favorable execution prices  Objectives achieved by  Placing and correcting limit orders to maximize opportunities to earn the spread  Sending marketable orders as necessary to keep on schedule  Design for large trade sizes in portfolio trading applications  Next generation VWAP

38. 38 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission A Server for Horizon Trading  Intelligent autopilot for portfolio trading  Continuously monitor progress and urgency  Bands define leeway for straying from the distribution in search of better executions  To price orders appropriately according to market conditions 100% 0% 50% Percent Completed 9:30 4:00 Time Horizon Fills

39. 39 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Pitfalls in Pegging and Discretion Strategies  Typical pegging algorithm errors  contribute to momentum by instantaneously adjusting price to match all quote changes  pegged orders typically leave an obvious information trail  Typical discretion order type errors  excess time and effort required to make informed discretion range judgements  constancy of discretion range over life of order, although aggressiveness should be a function of urgency, which may change

40. 40 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Pegging and Discretion Revisited  Enhanced pegging  peg an order loosely to the inside market  react conditionally, determining whether each quote change merits an order price correction  randomize and blend in with the crowd  Dynamic discretion  automatically choose appropriate discretion range for each order independently  continuously adjust range over life of order, recalculating the trigger price that demands liquidity  Adjust based on market conditions

41. 41 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Beyond Simple Pegs  Blended passive/aggressive strategy for price performance with on-time completion.  Supply liquidity to obtain favorable fills  Use carefully-timed aggressive orders to stay on schedule  Multiple electronic agents working in concert One agent provides liquidity, pegging a piece of the order loosely to the inside market. Objective: to maintain exposure to the inside market without driving prices or leaking information Second agent trades opportunistically using carefully-timed orders at marketable prices. Discretion range adjusts dynamically based on current urgency level. Objective: to complete trade on schedule Quoted Spread

42. 42 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Automating the Short Horizon  Watch every name individually  Update information continuously  Forecast quote movements:  Width of Spread  Direction of Market  Bid/Ask Volatility  If the model predicts favorable market movement  trade to capture a portion of the spread  If the market looks to move against the order  trade aggressively, based on the horizon

43. 43 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission The ITG View of Logical Participation NYSE AMEX Regionals DOT SuperMontage ECNs / ADF Market Makers ITG OTC Router TriAct™POSIT ® SPI Small Orders 5-30 min Time Horizon activePeg ™ All Order Sizes 10-240 min Time Horizon Horizon  Large Orders 30-390 min Time Horizon ITG Order Filter ITG Client Inbound Orders ITG SmartServer  Family ITG Desk Expert Manual Attention

44. 44 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Incorporate Risk  Use a pre-trade model that incorporates a daily risk model to quantify opportunity cost  Find optimal strategy to minimize impact costs while balancing delay costs

45. 45 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission The Typical Tradeoff Picture

46. 46 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission The Right Risk Model: Horizon Does Make a Difference Short-term volatility can differ significantly from longer-term volatility S&P is a registered trademark of McGraw Hill Inc.

47. 47 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Market & Specific Risk Matters More at Daily Levels S&P is a registered trademark of McGraw-Hill, Inc.

48. 48 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission A Complementary View  Two opposing forces  reduce market impact  reduce risk  a portfolio that behaves like the target portfolio as soon as possible  With appropriate cost and risk models  construct waves to implement the transition  analyze tradeoff between predicted cost and risk  same basic tools as the classical Markowitz portfolio problem  Example conclusion  “no wave that completes 15% of the transition, while costing 35 bps, will result in a tracking error lower than 7.8%”

49. 49 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Cost and Risk Tradeoffs

50. 50 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Where Risk Control Meets Cost Control  Benchmarking  Strategy  Max $ traded  Min dollars at risk  Min trading costs  Urgency  Control characteristics that add to cost of trade  $ risk  Tracking error  Sector balance  Liquidity exposure

51. 51 ©2003 ITG Inc. All Rights Reserved, Not to be reproduced without permission Example  This approach was recently used in a $1.2 billion two-sided transition portfolio with 403 names  Original portfolio has aggregate tracking error of 3.5%  Transition instructions permitted the list to be traded in “waves” subject to constraints  Analysis shows can trade a 25% “wave” of $307MM that cuts risk to 2.7%  Trade 81 of the 403 names  This wave improves liquidity of residual positions; order size drops from 18.7% to 14.7% of average daily volume  Successive application yields the optimal transition strategy