Appendix II-A 

Docket No. PA02-2-000 II-A-1 Price Manipulation in Western Markets 

 

Appendix II-A: Supporting Tables for Analysis of Reliant 

Natural Gas Transactions 

 Table II-A1. EOL Western Gas Spot Trades, November 2000 – June 2001, Counterparties 

With the Greatest Daily Gross Trading (continued on next page) 

Rank Location 

Transaction 

Date Counterparty 

Gross 

Quantity 

(MMBtu)1

1 SoCal Topock EPNG 2/2/01 Reliant Energy Services, Inc. 3,705,000 

2 SoCal Topock EPNG 12/1/00 Reliant Energy Services, Inc. 2,280,000 

3 SoCal Topock EPNG 12/15/00 Reliant Energy Services, Inc. 1,824,000 

4 SoCal Topock EPNG 1/31/01 Reliant Energy Services, Inc. 1,740,000 

5 SoCal Topock EPNG 12/8/00 Reliant Energy Services, Inc. 1,440,000 

6 SoCal Topock EPNG 2/16/01 Reliant Energy Services, Inc. 1,420,000 

7 SoCal Topock EPNG 11/22/00 Reliant Energy Services, Inc. 1,400,000 

8 SoCal Topock EPNG 12/11/00 Reliant Energy Services, Inc. 1,354,000 

9 SoCal Topock EPNG 1/26/01 Reliant Energy Services, Inc. 1,230,000 

10 EPNG SoCal Ehrenberg 3/2/01 Reliant Energy Services, Inc. 1,215,000 

11 SoCal Topock EPNG 3/23/01 Reliant Energy Services, Inc. 1,110,000 

12 SoCal Topock EPNG 1/5/01 Reliant Energy Services, Inc. 1,020,000 

13 SoCal Topock EPNG 12/22/00 Reliant Energy Services, Inc. 925,000 

14 SoCal Topock EPNG 12/5/00 Reliant Energy Services, Inc. 911,000 

15 EPNG SoCal Ehrenberg 3/23/01 Reliant Energy Services, Inc. 900,000 

16 SoCal Topock EPNG 12/6/00 Reliant Energy Services, Inc. 803,000 

17 SoCal Topock EPNG 11/17/00 Reliant Energy Services, Inc. 780,000 

18 SoCal Topock EPNG 12/13/00 Reliant Energy Services, Inc. 773,000 

19 SoCal Topock EPNG 1/3/01 Reliant Energy Services, Inc. 730,000 

20 SoCal Topock EPNG 11/17/00 Aquila Energy Marketing Corporation 720,000 

21 SoCal Topock EPNG 2/13/01 Reliant Energy Services, Inc. 710,000 

22 SoCal Topock EPNG 12/7/00 Reliant Energy Services, Inc. 700,000 

23 SoCal Topock EPNG 12/19/00 Reliant Energy Services, Inc. 670,000 

24 SoCal Topock EPNG 2/23/01 Reliant Energy Services, Inc. 630,000 

25 SoCal Topock EPNG 2/9/01 Reliant Energy Services, Inc. 622,500 

26 PG&E Ctygte Pool 5/25/01 Duke Energy Trading and Marketing, L.L.C. 600,000 

27 SoCal Topock EPNG 11/22/00 Southern California Gas Company 600,000 

28 SoCal Topock EPNG 6/11/01 Reliant Energy Services, Inc. 574,000 

29 SoCal Topock EPNG 12/12/00 Reliant Energy Services, Inc. 570,000 

30 SoCal Topock EPNG 1/12/01 Dynegy Marketing and Trade 560,000 

31 PG&E Ctygte Pool 5/4/01 Duke Energy Trading and Marketing, L.L.C. 555,000 

 

1

Gross quantity is adjusted for the duration of the contract: a 1-day spot contract for 10,000 MMBtu/d would 

contribute 10,000 MMBtu to the gross quantity, while a 3-day weekend spot contract for 10,000 MMBtu/d would 

contribute 30,000 MMBtu to the gross quantity. Almost all spot contracts are for 1 or 3 days, although contracts for 

holiday weekends are generally for 4 days and contracts for the Thanksgiving weekend are for 5 days. 
 Appendix II-A 

Docket No. PA02-2-000 II-A-2 Price Manipulation in Western Markets 

Rank Location 

Transaction 

Date Counterparty 

Gross 

Quantity 

(MMBtu)1

32 SoCal Topock EPNG 2/1/01 Reliant Energy Services, Inc. 550,000 

33 EPNG SoCal Ehrenberg 3/23/01 El Paso Merchant Energy, L.P. 525,000 

34 PG&E Ctygte Pool 11/10/00 Duke Energy Trading and Marketing, L.L.C. 525,000 

35 SoCal Topock EPNG 12/15/00 Dynegy Marketing and Trade 525,000 

36 SoCal Topock EPNG 1/26/01 Duke Energy Trading and Marketing, L.L.C. 525,000 

37 SoCal Topock EPNG 1/12/01 Duke Energy Trading and Marketing, L.L.C. 520,000 

38 SoCal Topock EPNG 12/4/00 Reliant Energy Services, Inc. 513,000 

39 SoCal Topock EPNG 11/30/00 Reliant Energy Services, Inc. 502,000 

40 SoCal Topock EPNG 11/27/00 Reliant Energy Services, Inc. 490,000 
 Appendix II-A 

Docket No. PA02-2-000 II-A-3 Price Manipulation in Western Markets 

Table II-A2. EOL Western Gas Spot Trades, November 2000 – June 2001, 

Counterparties With the Greatest Daily Net Purchases (continued on next page) 

Rank Location 

Transaction 

Date Counterparty 

Gross Quantity 

(MMBtu)2

Net 

Purchases 

(MMBtu) 

1 SoCal Topock EPNG 2/16/01 Reliant Energy Services, Inc. 1,420,000 1,380,000 

2 SoCal Topock EPNG 12/15/00 Reliant Energy Services, Inc. 1,824,000 1,356,000 

3 SoCal Topock EPNG 2/2/01 Reliant Energy Services, Inc. 3,705,000 1,065,000 

4 SoCal Topock EPNG 1/5/01 Reliant Energy Services, Inc. 1,020,000 1,020,000 

5 SoCal Topock EPNG 11/22/00 Reliant Energy Services, Inc. 1,400,000 900,000 

6 SoCal Topock EPNG 12/1/00 Reliant Energy Services, Inc. 2,280,000 780,000 

7 SoCal Topock EPNG 12/22/00 Reliant Energy Services, Inc. 925,000 775,000 

8 SoCal Topock EPNG 1/26/01 Reliant Energy Services, Inc. 1,230,000 690,000 

9 PG&E Ctygte Pool 5/25/01 Duke Energy Trading and Marketing, L.L.C. 600,000 600,000 

10 SoCal Topock EPNG 1/3/01 Reliant Energy Services, Inc. 730,000 570,000 

11 SoCal Topock EPNG 1/12/01 Dynegy Marketing and Trade 560,000 560,000 

12 SoCal Topock EPNG 12/13/00 Reliant Energy Services, Inc. 773,000 557,000 

13 PG&E Ctygte Pool 5/4/01 Duke Energy Trading and Marketing, L.L.C. 555,000 555,000 

14 SoCal Topock EPNG 12/8/00 Reliant Energy Services, Inc. 1,440,000 540,000 

15 EPNG SoCal Ehrenberg 3/2/01 Reliant Energy Services, Inc. 1,215,000 495,000 

16 SoCal Topock EPNG 11/17/00 Reliant Energy Services, Inc. 780,000 480,000 

17 SoCal Topock EPNG 11/27/00 Reliant Energy Services, Inc. 490,000 470,000 

18 SoCal Topock EPNG 12/18/00 Reliant Energy Services, Inc. 480,000 460,000 

19 SoCal Topock EPNG 2/23/01 Reliant Energy Services, Inc. 630,000 450,000 

20 SoCal Topock EPNG 1/16/01 Reliant Energy Services, Inc. 445,000 445,000 

21 SoCal Topock EPNG 4/27/01 Reliant Energy Services, Inc. 420,000 420,000 

22 SoCal Topock EPNG 12/12/00 Reliant Energy Services, Inc. 570,000 410,000 

23 SoCal Topock EPNG 2/12/01 Reliant Energy Services, Inc. 470,000 410,000 

24 SoCal Topock EPNG 2/14/01 Reliant Energy Services, Inc. 430,000 410,000 

25 PG&E Ctygte Pool 11/17/00 Duke Energy Trading and Marketing, L.L.C. 465,000 405,000 

26 SoCal Topock EPNG 2/22/01 Reliant Energy Services, Inc. 470,000 390,000 

27 Waha 11/3/00 Aquila Energy Marketing Corporation 450,000 390,000 

28 SoCal Topock EPNG 5/11/01 Reliant Energy Services, Inc. 390,000 390,000 

29 PG&E Ctygte Pool 1/12/01 Duke Energy Trading and Marketing, L.L.C. 460,000 380,000 

30 SoCal Topock EPNG 12/20/00 Reliant Energy Services, Inc. 400,000 380,000 

31 SoCal Topock EPNG 1/22/01 Reliant Energy Services, Inc. 380,000 380,000 

32 SoCal Topock EPNG 2/13/01 Reliant Energy Services, Inc. 710,000 370,000 

 

2

Gross quantity and net purchases are adjusted for the duration of the contract: buying a 1-day spot contract for 

10,000 MMBtu/d would contribute 10,000 MMBtu to the gross quantity and net purchases, while buying a 3-day 

weekend spot contract for 10,000 MMBtu/d would contribute 30,000 MMBtu to the gross quantity and net 

purchases. Almost all spot contracts are for 1 or 3 days, although contracts for holiday weekends are generally for 4 

days and contracts for the Thanksgiving weekend are for 5 days. 
 Appendix II-A 

Docket No. PA02-2-000 II-A-4 Price Manipulation in Western Markets 

Rank Location 

Transaction 

Date Counterparty 

Gross Quantity 

(MMBtu)2

Net 

Purchases 

(MMBtu) 

33 SoCal Topock EPNG 2/1/01 Reliant Energy Services, Inc. 550,000 370,000 

34 SoCal Topock EPNG 12/29/00 Reliant Energy Services, Inc. 440,000 360,000 

35 SoCal Topock EPNG 1/2/01 Reliant Energy Services, Inc. 340,000 340,000 

36 PG&E Ctygte Pool 1/19/01 Duke Energy Trading and Marketing, L.L.C. 450,000 330,000 

37 PG&E Ctygte Pool 11/3/00 Duke Energy Trading and Marketing, L.L.C. 390,000 330,000 

38 SoCal Topock EPNG 2/15/01 Reliant Energy Services, Inc. 330,000 330,000 

39 SoCal Topock EPNG 2/20/01 Reliant Energy Services, Inc. 345,000 325,000 

40 SoCal Topock EPNG 12/14/00 Reliant Energy Services, Inc. 358,000 322,000 
 Appendix II-A 

Docket No. PA02-2-000 II-A-5 Price Manipulation in Western Markets 

Table II-A3. EOL Western Gas Spot Trades, November 2000 – June 2001, 

Counterparties With the Greatest Daily Net Sales (continued on next page) 

Rank Location 

Transaction 

Date Counterparty 

Gross 

Quantity 

(MMBtu)3

Net Sales 

(MMBtu) 

1 SoCal Topock EPNG 11/22/00 Southern California Gas Company 600,000 600,000 

2 EPNG SoCal Ehrenberg 3/23/01 El Paso Merchant Energy, L.P. 525,000 525,000 

3 SoCal Topock EPNG 12/15/00 Dynegy Marketing and Trade 525,000 525,000 

4 SoCal Topock EPNG 12/15/00 Southern California Gas Company 484,638 484,638 

5 SoCal Topock EPNG 3/23/01 El Paso Merchant Energy, L.P. 480,000 480,000 

6 SoCal Topock EPNG 12/22/00 Dynegy Marketing and Trade 450,000 450,000 

7 SoCal Topock EPNG 2/23/01 El Paso Merchant Energy, L.P. 442,500 442,500 

8 SoCal Topock EPNG 1/12/01 Duke Energy Trading and Marketing, L.L.C. 520,000 440,000 

9 SoCal Topock EPNG 1/5/01 El Paso Merchant Energy, L.P. 435,000 435,000 

10 SoCal Topock EPNG 11/3/00 Aquila Energy Marketing Corporation 420,000 420,000 

11 EPNG SoCal Ehrenberg 3/9/01 El Paso Merchant Energy, L.P. 396,000 396,000 

12 SoCal Topock EPNG 12/1/00 Dynegy Marketing and Trade 390,000 390,000 

13 SoCal Topock EPNG 12/8/00 Dynegy Marketing and Trade 390,000 390,000 

14 SoCal Topock EPNG 2/16/01 El Paso Merchant Energy, L.P. 380,000 380,000 

15 EPNG SoCal Ehrenberg 3/2/01 El Paso Merchant Energy, L.P. 360,000 360,000 

16 SoCal Topock EPNG 11/22/00 Duke Energy Trading and Marketing, L.L.C. 350,000 350,000 

17 SoCal Topock EPNG 1/26/01 Duke Energy Trading and Marketing, L.L.C. 525,000 345,000 

18 SoCal Topock EPNG 11/3/00 Duke Energy Trading and Marketing, L.L.C. 345,000 345,000 

19 SoCal Topock EPNG 11/17/00 Aquila Energy Marketing Corporation 720,000 330,000 

20 EPNG SoCal Ehrenberg 3/30/01 El Paso Merchant Energy, L.P. 330,000 330,000 

21 EPNG SoCal Ehrenberg 5/18/01 Reliant Energy Services, Inc. 330,000 330,000 

22 PG&E Ctygte Pool 3/2/01 Duke Energy Trading and Marketing, L.L.C. 330,000 330,000 

23 SoCal Topock EPNG 11/22/00 Williams Energy Marketing & Trading Company 325,000 325,000 

24 PG&E Ctygte Pool 1/12/01 El Paso Merchant Energy, L.P. 300,000 300,000 

25 SoCal Topock EPNG 11/10/00 Aquila Energy Marketing Corporation 300,000 300,000 

26 SoCal Topock EPNG 12/22/00 Aquila Energy Marketing Corporation 300,000 300,000 

27 EPNG SoCal Ehrenberg 3/16/01 El Paso Merchant Energy, L.P. 285,000 285,000 

28 EPNG SoCal Ehrenberg 6/15/01 Reliant Energy Services, Inc. 285,000 285,000 

29 SoCal Topock EPNG 1/19/01 Duke Energy Trading and Marketing, L.L.C. 285,000 285,000 

30 SoCal Topock EPNG 1/12/01 Williams Energy Marketing & Trading Company 280,000 280,000 

31 PG&E Ctygte Pool 1/19/01 El Paso Merchant Energy, L.P. 270,000 270,000 

32 SoCal Topock EPNG 2/2/01 El Paso Merchant Energy, L.P. 270,000 270,000 

 

3

Gross quantity and net sales are adjusted for the duration of the contract: selling a 1-day spot contract for 10,000 

MMBtu/d would contribute 10,000 MMBtu to the gross quantity and net sales, while selling a 3-day weekend spot 

contract for 10,000 MMBtu/d would contribute 30,000 MMBtu to the gross quantity and net sales. Almost all spot 

contracts are for 1 or 3 days, although contracts for holiday weekends are generally for 4 days and contracts for the 

Thanksgiving weekend are for 5 days. 
 Appendix II-A 

Docket No. PA02-2-000 II-A-6 Price Manipulation in Western Markets 

Rank Location 

Transaction 

Date Counterparty 

Gross 

Quantity 

(MMBtu)3

Net Sales 

(MMBtu) 

33 PG&E Ctygte Pool 5/25/01 Calpine Energy Services, L.P. 260,000 260,000 

34 SoCal Topock EPNG 1/5/01 Duke Energy Trading and Marketing, L.L.C. 255,000 255,000 

35 SoCal Topock EPNG 2/2/01 Duke Energy Trading and Marketing, L.L.C. 255,000 255,000 

36 PG&E Ctygte Pool 11/10/00 Aquila Energy Marketing Corporation 480,000 240,000 

37 EPNG SoCal Ehrenberg 3/2/01 Southern California Gas Company 240,000 240,000 

38 EPNG SoCal Ehrenberg 4/6/01 Reliant Energy Services, Inc. 240,000 240,000 

39 PG&E Ctygte Pool 4/27/01 Enron Energy Services, Inc. 240,000 240,000 

40 SoCal Topock EPNG 12/8/00 Aquila Energy Marketing Corporation 240,000 240,000 
 Appendix II-A 

Docket No. PA02-2-000 II-A-7 Price Manipulation in Western Markets 

Table II-A4. EOL Topock and Ehrenberg Gas Spot Trades, November 2000 – June 2001, 

Largest Net Sellers to Enron by Month (continued on next page) 

Transaction 

Month 

Rank 

Within 

Month 

Counterparty 

Counterparty 

Net Sales 

(MMBtu)4

Gross Volume 

(MMBtu) 

 

Nov-00 1 Aquila Energy Marketing Corporation 2,615,000 3,575,000 

 2 Duke Energy Trading and Marketing, L.L.C. 2,210,000 2,720,000 

 3 Southern California Gas Company 1,375,000 1,405,000 

 4 San Diego Gas & Electric Company 595,000 595,000 

 5 PG&E Energy Trading-Gas Corporation 555,000 785,000 

 

Dec-00 1 Dynegy Marketing and Trade 3,545,000 3,605,000 

 2 Aquila Energy Marketing Corporation 2,110,000 2,140,000 

 3 Southern California Gas Company 1,807,638 1,827,638 

 4 Mirant Americas Energy Marketing, L.P. 1,381,000 1,381,000 

 5 Enserco Energy, Inc. 917,000 917,000 

 

Jan-01 1 Duke Energy Trading and Marketing, L.L.C. 2,720,850 3,280,850 

 2 Williams Energy Marketing & Trading Company 1,020,000 1,020,000 

 3 Coral Energy Resources, L.P. 872,708 892,708 

 4 El Paso Merchant Energy, L.P. 741,000 1,821,000 

 5 Aquila Energy Marketing Corporation 439,000 791,000 

 

Feb-01 1 El Paso Merchant Energy, L.P. 2,806,000 3,086,000 

 2 Duke Energy Trading and Marketing, L.L.C. 1,454,000 1,884,000 

 3 Aquila Energy Marketing Corporation 595,000 935,000 

 4 Mirant Americas Energy Marketing, L.P. 524,000 554,000 

 5 Southern California Gas Company 332,500 332,500 

 

Mar-01 1 El Paso Merchant Energy, L.P. 5,484,000 5,624,000 

 2 Southern California Gas Company 790,000 1,080,000 

 3 Aquila Energy Marketing Corporation 641,000 1,037,000 

 4 Texaco Natural Gas Inc. 391,000 391,000 

 5 Burlington Resources Trading Inc. 215,808 215,808 

 

 

 

4

Net sales and gross quantity are adjusted for the duration of the contract: selling a 1-day spot contract for 10,000 

MMBtu/d would contribute 10,000 MMBtu to the net sales and gross quantity, while buying a 3-day weekend spot 

contract for 10,000 MMBtu/d would contribute 30,000 MMBtu to the net sales and gross quantity. Almost all spot 

contracts are for 1 or 3 days, although contracts for holiday weekends are generally for 4 days and contracts for the 

Thanksgiving weekend are for 5 days. 
 Appendix II-A 

Docket No. PA02-2-000 II-A-8 Price Manipulation in Western Markets 

Transaction 

Month 

Rank 

Within 

Month 

Counterparty 

Counterparty 

Net Sales 

(MMBtu)4

Gross Volume 

(MMBtu) 

Apr-01 1 El Paso Merchant Energy, L.P. 2,653,488 2,763,488 

 2 Duke Energy Trading and Marketing, L.L.C. 1,037,754 1,177,754 

 3 Mirant Americas Energy Marketing, L.P. 944,767 944,767 

 4 Coral Energy Resources, L.P. 941,000 979,000 

 5 Southern California Gas Company 500,000 520,000 

 

May-01 1 El Paso Merchant Energy, L.P. 2,114,222 2,634,222 

 2 Enserco Energy, Inc. 530,000 570,000 

 3 Calpine Energy Services, L.P. 380,500 878,500 

 4 PG&E Energy Trading-Gas Corporation 169,598 169,598 

 5 AEP Energy Services, Inc. 144,022 864,022 

 

Jun-01 1 Duke Energy Trading and Marketing, L.L.C. 888,646 1,158,646 

 2 Mirant Americas Energy Marketing, L.P. 601,238 601,238 

 3 El Paso Merchant Energy, L.P. 566,336 1,056,336 

 4 Aquila Energy Marketing Corporation 523,162 749,262 

 5 BP Energy Company 392,500 432,500 

 

Total 1 El Paso Merchant Energy, L.P. 14,365,046 16,985,046 

 2 Duke Energy Trading and Marketing, L.L.C. 7,486,100 12,420,100 

 3 Aquila Energy Marketing Corporation 7,268,162 10,414,262 

 4 Southern California Gas Company 5,014,188 6,134,188 

 5 Mirant Americas Energy Marketing, L.P. 4,202,889 4,312,889 

 6 Coral Energy Resources, L.P. 2,632,665 4,448,623 

 7 Williams Energy Marketing & Trading Company 2,566,134 4,336,134 

 8 Dynegy Marketing and Trade 1,853,013 11,778,971 

 9 Enserco Energy, Inc. 1,808,500 2,398,500 

 10 BP Energy Company 1,696,000 2,491,000 
 Appendix II-A 

Docket No. PA02-2-000 II-A-9 Price Manipulation in Western Markets 

Table II-A5. EOL Western Gas Spot Trades, November 2000 – June 2001, 

Counterparties With the Greatest Monthly Net Purchases 

Rank Location 

Transaction 

Month Counterparty 

Gross 

Quantity 

(MMBtu)5

Net 

Purchases 

(MMBtu) 

1 SoCal Topock EPNG December 2000 Reliant Energy Services, Inc. 15,296,000 8,024,000 

2 SoCal Topock EPNG February 2001 Reliant Energy Services, Inc. 11,422,500 7,227,500 

3 SoCal Topock EPNG January 2001 Reliant Energy Services, Inc. 8,438,350 6,131,650 

4 PG&E Ctygte Pool May 2001 Duke Energy Trading and Marketing, L.L.C. 2,968,475 2,478,475 

5 SoCal Topock EPNG November 2000 Reliant Energy Services, Inc. 5,172,000 2,188,000 

6 Opal April 2001 BP Energy Company 2,391,266 2,044,942 

7 SoCal Topock EPNG May 2001 Reliant Energy Services, Inc. 1,934,479 1,914,479 

8 PG&E Ctygte Pool January 2001 Duke Energy Trading and Marketing, L.L.C. 2,815,000 1,885,000 

9 PG&E Ctygte Pool November 2000 Duke Energy Trading and Marketing, L.L.C. 3,075,000 1,735,000 

10 SoCal Topock EPNG June 2001 Reliant Energy Services, Inc. 2,635,059 1,542,059 

11 Waha March 2001 BP Energy Company 1,465,000 1,465,000 

12 EPNG SoCal Ehrenberg May 2001 Sempra Energy Trading Corp. 1,295,000 1,275,000 

13 Opal December 2000 Dynegy Marketing and Trade 1,285,000 1,275,000 

14 PGT Malin November 2000 Dynegy Marketing and Trade 1,480,000 1,255,000 

15 PG&E Topock June 2001 PG&E Energy Trading-Gas Corporation 1,243,030 1,199,030 

16 PG&E Ctygte Pool April 2001 Mirant Americas Energy Marketing, L.P. 1,065,000 1,065,000 

17 PG&E Ctygte Pool June 2001 Duke Energy Trading and Marketing, L.L.C. 1,599,500 1,059,500 

18 SoCal Topock EPNG January 2001 Dynegy Marketing and Trade 1,384,000 1,034,000 

19 Waha April 2001 BP Energy Company 960,000 960,000 

20 SoCal Topock EPNG April 2001 Reliant Energy Services, Inc. 1,570,000 950,000 

21 Waha February 2001 BP Energy Company 955,000 935,000 

22 EPNG SoCal Ehrenberg May 2001 Reliant Energy Services, Inc. 2,205,000 915,000 

23 PG&E Ctygte Pool April 2001 Duke Energy Trading and Marketing, L.L.C. 1,290,000 860,000 

24 PG&E Ctygte Pool November 2000 Coast Energy Canada, Inc. 1,055,000 855,000 

25 Waha June 2001 Duke Energy Field Services Marketing, LLC 835,000 835,000 

26 Opal November 2000 Dynegy Marketing and Trade 910,000 820,000 

27 PG&E Ctygte Pool November 2000 Pacific Gas & Electric Company 820,000 820,000 

28 Opal November 2000 Cook Inlet Energy Supply L.L.C. 1,985,000 795,000 

29 PG&E Ctygte Pool March 2001 Duke Energy Trading and Marketing, L.L.C. 1,615,000 675,000 

30 PGT Malin February 2001 Enron Energy Services, Inc. 655,000 655,000 

31 EPNG SoCal Ehrenberg June 2001 Sempra Energy Trading Corp. 677,500 637,500 

32 Opal December 2000 Barrett Resources Corporation 715,000 615,000 

 

5

Gross quantity and net purchases are adjusted for the duration of the contract: buying a 1-day spot contract for 

10,000 MMBtu/d would contribute 10,000 MMBtu to the gross quantity and net purchases, while buying a 3-day 

weekend spot contract for 10,000 MMBtu/d would contribute 30,000 MMBtu to the gross quantity and net sales. 

Almost all spot contracts are for 1 or 3 days, although contracts for holiday weekends are generally for 4 days and 

contracts for the Thanksgiving weekend are for 5 days. 
 Appendix II-A 

Docket No. PA02-2-000 II-A-10 Price Manipulation in Western Markets 

Table II-A6. Trading in EOL Spot Gas, Topock and Ehrenberg Points Only, 

November 2000 – June 2001, Busiest EOL Trading Days for Individual Counterparties 

Rank Transaction Date Counterparty 

Number of 

Transactions 

1 1/31/01 Reliant Energy Services, Inc. 174 

2 12/11/00 Reliant Energy Services, Inc. 136 

3 2/2/01 Reliant Energy Services, Inc. 124 

4 12/5/00 Reliant Energy Services, Inc. 89 

5 12/1/00 Reliant Energy Services, Inc. 76 

6 12/13/00 Reliant Energy Services, Inc. 74 

7 1/3/01 Reliant Energy Services, Inc. 73 

8 12/6/00 Reliant Energy Services, Inc. 72 

9 12/7/00 Reliant Energy Services, Inc. 71 

10 2/13/01 Reliant Energy Services, Inc. 71 

11 12/19/00 Reliant Energy Services, Inc. 67 

12 3/23/01 Reliant Energy Services, Inc. 66 

13 6/11/01 Reliant Energy Services, Inc. 61 

14 12/15/00 Reliant Energy Services, Inc. 58 

15 12/12/00 Reliant Energy Services, Inc. 57 

16 2/1/01 Reliant Energy Services, Inc. 55 

17 12/4/00 Reliant Energy Services, Inc. 52 

18 6/13/01 Reliant Energy Services, Inc. 52 

19 11/30/00 Reliant Energy Services, Inc. 51 

20 11/27/00 Reliant Energy Services, Inc. 48 

21 12/8/00 Reliant Energy Services, Inc. 48 

22 12/18/00 Reliant Energy Services, Inc. 48 

23 2/12/01 Reliant Energy Services, Inc. 47 

24 2/22/01 Reliant Energy Services, Inc. 47 

25 5/22/01 Reliant Energy Services, Inc. 47 

26 2/14/01 Reliant Energy Services, Inc. 45 

27 1/16/01 Reliant Energy Services, Inc. 44 

28 1/26/01 Reliant Energy Services, Inc. 42 

29 3/2/01 Reliant Energy Services, Inc. 42 

30 5/10/01 Reliant Energy Services, Inc. 42 
 Appendix II-A 

Docket No. PA02-2-000 II-A-11 Price Manipulation in Western Markets 

Table II-A7. Purchases and Sales of at Least 100,000 MMBtu/d by Counterparty and Location 

(Topock and Ehrenberg Combined) 

Counterparty Location 

Transaction 

Date 

Number of 

Transactions

Sell 

(MMBtu/d) 

Buy 

(MMBtu/d) 

Gross Volume 

(MMBtu/d) 

Reliant Energy Services, Inc. SoCal Topock 11/1/00 21 100,000 100,000 200,000 

Duke Energy Trading and 

Marketing, LLC 

PG&E Ctygte 11/9/00 34 125,000 185,000 310,000 

Reliant Energy Services, Inc. SoCal Topock 11/13/00 40 190,000 200,000 390,000 

Aquila Energy Marketing 

Corporation 

SoCal Topock 11/16/00 28 170,000 100,000 270,000 

Reliant Energy Services, Inc. SoCal Topock 11/30/00 51 182,000 320,000 502,000 

Reliant Energy Services, Inc. SoCal Topock 12/1/00 76 250,000 510,000 760,000 

Reliant Energy Services, Inc. SoCal Topock 12/4/00 52 203,000 310,000 513,000 

Reliant Energy Services, Inc. SoCal Topock 12/5/00 89 311,000 600,000 911,000 

Reliant Energy Services, Inc. SoCal Topock 12/6/00 72 313,000 490,000 803,000 

Reliant Energy Services, Inc. SoCal Topock 12/7/00 71 220,000 480,000 700,000 

Reliant Energy Services, Inc. SoCal Topock 12/8/00 48 150,000 330,000 480,000 

Reliant Energy Services, Inc. SoCal Topock 12/11/00 136 554,000 800,000 1,354,000 

Reliant Energy Services, Inc. SoCal Topock 12/13/00 74 108,000 665,000 773,000 

Reliant Energy Services, Inc. SoCal Topock 12/19/00 67 200,000 470,000 670,000 

Reliant Energy Services, Inc. SoCal Topock 1/31/01 174 730,000 1,010,000 1,740,000 

Reliant Energy Services, Inc. SoCal Topock 2/2/01 124 440,000 795,000 1,235,000 

Reliant Energy Services, Inc. SoCal Topock 2/13/01 71 170,000 540,000 710,000 

Reliant Energy Services, Inc. SoCal Topock 2/28/01 33 120,000 210,000 330,000 

Reliant Energy Services, Inc. SoCal Topock 3/1/01 31 155,000 160,000 315,000 

Reliant Energy Services, Inc. SoCal Topock 3/2/01 42 120,000 285,000 405,000 

Reliant Energy Services, Inc. SoCal Topock 3/20/01 27 110,000 160,000 270,000 

Reliant Energy Services, Inc. SoCal Topock 3/22/01 23 130,000 100,000 230,000 

Reliant Energy Services, Inc. SoCal Topock 3/23/01 66 320,000 350,000 670,000 

Reliant Energy Services, Inc. SoCal Topock 4/3/01 22 120,000 100,000 220,000 

Reliant Energy Services, Inc. SoCal Topock 6/11/01 61 224,000 400,000 624,000 

Reliant Energy Services, Inc. SoCal Topock 6/13/01 52 110,000 379,479 489,479 
 Appendix II-A 

Docket No. PA02-2-000 II-A-12 Price Manipulation in Western Markets 

 Table II-A8. December 2000 Price Chart, Gas Daily Index and EOL Prices With Churn Day Indication 

Transaction 

Date 

Contracted Flow 

Date or Flow 

Period 

Reliant Gross 

Volume 

(MMBtu/d) 

Gas Daily 

Midpoint 

Price 

($/MMBtu)

EOL 

High 

($/MMBtu)

EOL 

Low 

($/MMBtu)

Weighted 

Price 

($/MMBtu)

EOL 

Opening 

Price 

($/MMBtu) 

EOL 

Closing 

Price 

($/MMBtu)

Reliant 

Churn 

Day 

11/30/00 12/1/00 502,000 18.90 20.25 16.50 18.89 17.00 18.25 Yes 

12/1/00 12/2 – 12/4/00 760,000 18.50 20.25 17.00 18.80 18.50 19.25 Yes 

12/4/00 12/5/00 513,000 21.61 23.25 19.00 21.80 19.00 21.50 Yes 

12/5/00 12/6/00 911,000 26.60 28.00 23.25 26.57 23.25 28.00 Yes 

12/6/00 12/7/00 803,000 36.25 41.00 33.00 38.05 34.50 33.00 Yes 

12/7/00 12/8/00 700,000 42.02 53.00 32.00 43.19 45.00 38.00 Yes 

12/8/00 12/9 – 12/11/00 480,000 54.66 59.00 42.00 55.42 42.00 58.00 Yes 

12/11/00 12/12/00 1,354,000 59.42 68.00 34.00 59.19 58.00 50.00 Yes 

12/12/00 12/13/00 570,000 32.75 47.00 20.00 31.80 47.00 26.00 

12/13/00 12/14/00 773,000 20.26 24.00 14.00 20.16 22.00 19.00 Yes 

12/14/00 12/15/00 358,000 19.03 24.00 15.00 19.23 16.00 15.00 

12/15/00 12/16 – 12/18/00 608,000 17.06 19.50 14.00 16.88 17.00 18.00 

12/18/00 12/19/00 480,000 20.39 22.50 17.00 20.52 17.00 19.50 

12/19/00 12/20/00 670,000 19.56 23.00 15.00 20.11 21.00 17.00 Yes 

12/20/00 12/21/00 400,000 20.36 23.00 19.00 20.91 19.00 21.50 

12/21/00 12/22/00 335,000 18.98 22.00 18.00 18.95 22.00 18.00 

12/22/00 12/23 – 12/27/00 185,000 18.78 19.00 17.00 17.98 18.50 18.50 

12/27/00 12/28/00 220,000 16.64 18.50 15.50 16.76 18.50 15.50 

12/28/00 12/29 – 12/31/00 100,000 14.41 15.50 14.20 14.62 14.50 14.50 
 Appendix II-A 

Docket No. PA02-2-000 II-A-13 Price Manipulation in Western Markets 

Table II-A9. EOL Western Gas Spot Trades, November 2000 – June 2001, 

Most Trades Within a Clock Minute6

 (continued on next page) 

Rank Location 

Transaction 

Date Counterparty 

Number of 

Transactions

1 SoCal Topock EPNG 2/2/01 Reliant Energy Services, Inc. 16 

2 SoCal Topock EPNG 2/2/01 Reliant Energy Services, Inc. 15 

3 SoCal Topock EPNG 2/2/01 Reliant Energy Services, Inc. 13 

4 SoCal Topock EPNG 1/31/01 Reliant Energy Services, Inc. 12 

5 SoCal Topock EPNG 1/31/01 Reliant Energy Services, Inc. 12 

6 SoCal Topock EPNG 2/2/01 Reliant Energy Services, Inc. 12 

7 PGT Malin 5/10/01 Enserco Energy, Inc. 11 

8 SoCal Topock EPNG 1/31/01 Reliant Energy Services, Inc. 11 

9 SoCal Topock EPNG 2/2/01 Reliant Energy Services, Inc. 11 

10 SoCal Topock EPNG 6/11/01 Reliant Energy Services, Inc. 11 

11 EPNG SoCal Ehrenberg 3/2/01 Reliant Energy Services, Inc. 10 

12 SoCal Topock EPNG 12/15/00 Reliant Energy Services, Inc. 10 

13 SoCal Topock EPNG 12/20/00 Reliant Energy Services, Inc. 10 

14 SoCal Topock EPNG 1/31/01 Reliant Energy Services, Inc. 10 

15 SoCal Topock EPNG 2/2/01 Reliant Energy Services, Inc. 10 

16 EPNG SoCal Ehrenberg 4/11/01 Reliant Energy Services, Inc. 9 

17 EPNG SoCal Ehrenberg 4/26/01 Reliant Energy Services, Inc. 9 

18 EPNG SoCal Ehrenberg 5/10/01 Reliant Energy Services, Inc. 9 

19 SoCal Topock EPNG 12/4/00 Reliant Energy Services, Inc. 9 

20 SoCal Topock EPNG 12/5/00 Reliant Energy Services, Inc. 9 

21 SoCal Topock EPNG 12/15/00 Reliant Energy Services, Inc. 9 

22 SoCal Topock EPNG 1/26/01 Reliant Energy Services, Inc. 9 

23 SoCal Topock EPNG 1/31/01 Reliant Energy Services, Inc. 9 

24 SoCal Topock EPNG 1/31/01 Reliant Energy Services, Inc. 9 

25 SoCal Topock EPNG 1/31/01 Reliant Energy Services, Inc. 9 

26 SoCal Topock EPNG 2/1/01 Reliant Energy Services, Inc. 9 

27 SoCal Topock EPNG 2/13/01 Reliant Energy Services, Inc. 9 

28 SoCal Topock EPNG 6/13/01 Reliant Energy Services, Inc. 9 

29 PG&E Ctygte Pool 4/26/01 Enron Energy Services, Inc. 8 

30 SoCal Topock EPNG 12/11/00 Reliant Energy Services, Inc. 8 

31 SoCal Topock EPNG 12/11/00 Reliant Energy Services, Inc. 8 

32 SoCal Topock EPNG 12/11/00 Reliant Energy Services, Inc. 8 

33 SoCal Topock EPNG 12/11/00 Reliant Energy Services, Inc. 8 

34 SoCal Topock EPNG 12/13/00 Reliant Energy Services, Inc. 8 

35 SoCal Topock EPNG 1/4/01 Reliant Energy Services, Inc. 8 

36 SoCal Topock EPNG 1/16/01 Reliant Energy Services, Inc. 8 

 

6

A clock minute is defined as starting at, for example, 8:51:00 and extending to 8:51:59. 
 Appendix II-A 

Docket No. PA02-2-000 II-A-14 Price Manipulation in Western Markets 

Rank Location 

Transaction 

Date Counterparty 

Number of 

Transactions

37 SoCal Topock EPNG 1/31/01 Reliant Energy Services, Inc. 8 

38 SoCal Topock EPNG 2/13/01 Reliant Energy Services, Inc. 8 

39 SoCal Topock EPNG 2/13/01 Reliant Energy Services, Inc. 8 

40 SoCal Topock EPNG 2/16/01 Reliant Energy Services, Inc. 8 
 Appendix II-A 

Docket No. PA02-2-000 II-A-15 Price Manipulation in Western Markets 

Table II-A10. EOL Western Gas Spot Trades, November 2000 – June 2001, 

Most Trades Within 5 Clock Minutes7

 (continued on next page) 

Rank Location 

Transaction 

Date Counterparty 

Number of 

Transactions

1 SoCal Topock EPNG 1/31/01 Reliant Energy Services, Inc. 49 

2 SoCal Topock EPNG 2/2/01 Reliant Energy Services, Inc. 39 

3 SoCal Topock EPNG 2/2/01 Reliant Energy Services, Inc. 34 

4 SoCal Topock EPNG 6/11/01 Reliant Energy Services, Inc. 32 

5 SoCal Topock EPNG 1/31/01 Reliant Energy Services, Inc. 25 

6 SoCal Topock EPNG 1/31/01 Reliant Energy Services, Inc. 25 

7 SoCal Topock EPNG 12/11/00 Reliant Energy Services, Inc. 24 

8 SoCal Topock EPNG 12/1/00 Reliant Energy Services, Inc. 23 

9 SoCal Topock EPNG 1/31/01 Reliant Energy Services, Inc. 23 

10 SoCal Topock EPNG 11/27/00 Reliant Energy Services, Inc. 22 

11 SoCal Topock EPNG 12/11/00 Reliant Energy Services, Inc. 21 

12 SoCal Topock EPNG 2/2/01 Reliant Energy Services, Inc. 21 

13 SoCal Topock EPNG 6/13/01 Reliant Energy Services, Inc. 21 

14 SoCal Topock EPNG 11/17/00 Reliant Energy Services, Inc. 20 

15 SoCal Topock EPNG 12/5/00 Reliant Energy Services, Inc. 20 

16 SoCal Topock EPNG 1/3/01 Reliant Energy Services, Inc. 20 

17 SoCal Topock EPNG 1/31/01 Reliant Energy Services, Inc. 20 

18 SoCal Topock EPNG 2/2/01 Reliant Energy Services, Inc. 20 

19 SoCal Topock EPNG 12/11/00 Reliant Energy Services, Inc. 19 

20 SoCal Topock EPNG 12/19/00 Reliant Energy Services, Inc. 19 

21 SoCal Topock EPNG 12/20/00 Reliant Energy Services, Inc. 19 

22 SoCal Topock EPNG 2/22/01 Reliant Energy Services, Inc. 19 

23 SoCal Topock EPNG 12/4/00 Reliant Energy Services, Inc. 18 

24 SoCal Topock EPNG 12/15/00 Reliant Energy Services, Inc. 18 

25 SoCal Topock EPNG 1/22/01 Reliant Energy Services, Inc. 18 

26 SoCal Topock EPNG 1/31/01 Reliant Energy Services, Inc. 18 

27 SoCal Topock EPNG 2/1/01 Reliant Energy Services, Inc. 18 

28 SoCal Topock EPNG 2/13/01 Reliant Energy Services, Inc. 18 

29 EPNG SoCal Ehrenberg 3/2/01 Reliant Energy Services, Inc. 17 

30 SoCal Topock EPNG 1/17/01 Reliant Energy Services, Inc. 17 

31 SoCal Topock EPNG 11/13/00 Reliant Energy Services, Inc. 16 

32 SoCal Topock EPNG 12/13/00 Reliant Energy Services, Inc. 16 

33 EPNG SoCal Ehrenberg 5/10/01 Reliant Energy Services, Inc. 15 

34 SoCal Topock EPNG 12/13/00 Reliant Energy Services, Inc. 15 

35 SoCal Topock EPNG 12/15/00 Reliant Energy Services, Inc. 15 

 

7

A period of 5 clock minutes is defined as starting at, for example, 8:51:00 and extending to 8:55:59. 
 Appendix II-A 

Docket No. PA02-2-000 II-A-16 Price Manipulation in Western Markets 

Rank Location 

Transaction 

Date Counterparty 

Number of 

Transactions

36 SoCal Topock EPNG 2/21/01 Reliant Energy Services, Inc. 15 

37 EPNG SoCal Ehrenberg 6/15/01 Reliant Energy Services, Inc. 14 

38 PGT Malin 5/10/01 Enserco Energy, Inc. 14 

39 SoCal Topock EPNG 11/22/00 Reliant Energy Services, Inc. 14 

40 SoCal Topock EPNG 12/1/00 Reliant Energy Services, Inc. 14 
 Appendix II-A 

Docket No. PA02-2-000 II-A-17 Price Manipulation in Western Markets 

Table II-A11. EOL Western Gas Spot Trades, November 2000 – June 2001, 

Most Consecutive Transactions by One Firm8

 (continued on next page) 

Rank Location Transaction 

Date 

Counterparty Consecutive 

Transactions 

1 SoCal Topock EPNG 1/31/01 Reliant Energy Services, Inc. 43 

2 SoCal Topock EPNG 2/2/01 Reliant Energy Services, Inc. 34 

3 SoCal Topock EPNG 11/27/00 Reliant Energy Services, Inc. 23 

4 SoCal Topock EPNG 1/31/01 Reliant Energy Services, Inc. 22 

5 SoCal Topock EPNG 2/2/01 Reliant Energy Services, Inc. 20 

6 SoCal Topock EPNG 3/23/01 Reliant Energy Services, Inc. 18 

7 EPNG SoCal Ehrenberg 5/10/01 Reliant Energy Services, Inc. 16 

8 SoCal Topock EPNG 1/31/01 Reliant Energy Services, Inc. 16 

9 SoCal Topock EPNG 12/11/00 Reliant Energy Services, Inc. 15 

10 EPNG SoCal Ehrenberg 6/15/01 Reliant Energy Services, Inc. 14 

11 SoCal Topock EPNG 1/31/01 Reliant Energy Services, Inc. 14 

12 SoCal Topock EPNG 1/31/01 Reliant Energy Services, Inc. 14 

13 SoCal Topock EPNG 12/11/00 Reliant Energy Services, Inc. 14 

14 SoCal Topock EPNG 2/2/01 Reliant Energy Services, Inc. 13 

15 SoCal Topock EPNG 1/4/01 Reliant Energy Services, Inc. 13 

16 SoCal Topock EPNG 12/1/00 Reliant Energy Services, Inc. 13 

17 Waha 3/16/01 BP Energy Company 13 

18 SoCal Topock EPNG 1/31/01 Reliant Energy Services, Inc. 12 

19 Waha 3/19/01 BP Energy Company 12 

20 SoCal Topock EPNG 6/11/01 Reliant Energy Services, Inc. 11 

21 SoCal Topock EPNG 2/5/01 El Paso Merchant Energy, L.P. 11 

22 SoCal Topock EPNG 1/31/01 Reliant Energy Services, Inc. 11 

23 SoCal Topock EPNG 12/11/00 Reliant Energy Services, Inc. 11 

24 SoCal Topock EPNG 12/11/00 Reliant Energy Services, Inc. 11 

25 SoCal Topock EPNG 12/11/00 Reliant Energy Services, Inc. 11 

26 SoCal Topock EPNG 11/3/00 Aquila Energy Marketing 

Corporation 

11 

27 EPNG SoCal Ehrenberg 4/26/01 Reliant Energy Services, Inc. 10 

28 EPNG SoCal Ehrenberg 4/11/01 Reliant Energy Services, Inc. 10 

29 EPNG SoCal Ehrenberg 4/5/01 Reliant Energy Services, Inc. 10 

30 EPNG SoCal Ehrenberg 3/23/01 El Paso Merchant Energy, L.P. 10 

31 EPNG SoCal Ehrenberg 3/8/01 El Paso Merchant Energy, L.P. 10 

32 SoCal Topock EPNG 6/11/01 Reliant Energy Services, Inc. 10 

33 SoCal Topock EPNG 5/11/01 Reliant Energy Services, Inc. 10 

34 SoCal Topock EPNG 2/21/01 Reliant Energy Services, Inc. 10 

 

8

These are the longest sequences of transactions for spot gas at a single location that are buy or sell transactions by a 

single firm. 
 Appendix II-A 

Docket No. PA02-2-000 II-A-18 Price Manipulation in Western Markets 

Rank Location Transaction 

Date 

Counterparty Consecutive 

Transactions 

35 SoCal Topock EPNG 2/2/01 Reliant Energy Services, Inc. 10 

36 SoCal Topock EPNG 1/18/01 Reliant Energy Services, Inc. 10 

37 SoCal Topock EPNG 12/11/00 Reliant Energy Services, Inc. 10 

38 EPNG SoCal Ehrenberg 3/26/01 Reliant Energy Services, Inc. 9 

39 EPNG SoCal Ehrenberg 3/2/01 Reliant Energy Services, Inc. 9 

40 SoCal Topock EPNG 6/13/01 Reliant Energy Services, Inc. 9 
 Appendix II-A 

Docket No. PA02-2-000 II-A-19 Price Manipulation in Western Markets 

Table II-A12. EOL Western Gas Spot Trades, November 2000 – June 2001, 

Most Consecutive “Buy” Transactions By One Firm9

 (continued on next page) 

Rank Location Transaction 

Date 

Counterparty Consecutive 

Transactions 

1 SoCal Topock EPNG 11/27/00 Reliant Energy Services, Inc. 23 

2 SoCal Topock EPNG 3/23/01 Reliant Energy Services, Inc. 18 

3 EPNG SoCal Ehrenberg 5/10/01 Reliant Energy Services, Inc. 16 

4 SoCal Topock EPNG 2/2/01 Reliant Energy Services, Inc. 13 

5 SoCal Topock EPNG 1/4/01 Reliant Energy Services, Inc. 13 

6 Waha 3/16/01 BP Energy Company 13 

7 Waha 3/19/01 BP Energy Company 12 

8 SoCal Topock EPNG 6/11/01 Reliant Energy Services, Inc. 11 

9 SoCal Topock EPNG 1/31/01 Reliant Energy Services, Inc. 11 

10 SoCal Topock EPNG 5/11/01 Reliant Energy Services, Inc. 10 

11 SoCal Topock EPNG 2/21/01 Reliant Energy Services, Inc. 10 

12 SoCal Topock EPNG 2/2/01 Reliant Energy Services, Inc. 10 

13 SoCal Topock EPNG 1/18/01 Reliant Energy Services, Inc. 10 

14 SoCal Topock EPNG 12/11/00 Reliant Energy Services, Inc. 10 

15 SoCal Topock EPNG 6/11/01 Reliant Energy Services, Inc. 9 

16 SoCal Topock EPNG 4/27/01 Reliant Energy Services, Inc. 9 

17 SoCal Topock EPNG 2/12/01 Reliant Energy Services, Inc. 9 

18 SoCal Topock EPNG 2/1/01 Reliant Energy Services, Inc. 9 

19 SoCal Topock EPNG 1/26/01 Reliant Energy Services, Inc. 9 

20 SoCal Topock EPNG 1/25/01 Reliant Energy Services, Inc. 9 

21 SoCal Topock EPNG 1/18/01 Reliant Energy Services, Inc. 9 

22 SoCal Topock EPNG 1/16/01 Reliant Energy Services, Inc. 9 

23 SoCal Topock EPNG 1/3/01 Reliant Energy Services, Inc. 9 

24 SoCal Topock EPNG 11/21/00 Reliant Energy Services, Inc. 9 

25 Waha 11/6/00 Aquila Energy Marketing Corporation 9 

26 SoCal Topock EPNG 6/13/01 Reliant Energy Services, Inc. 8 

27 SoCal Topock EPNG 6/13/01 Reliant Energy Services, Inc. 8 

28 SoCal Topock EPNG 4/23/01 Reliant Energy Services, Inc. 8 

29 SoCal Topock EPNG 4/16/01 Dynegy Marketing and Trade 8 

30 SoCal Topock EPNG 2/15/01 Reliant Energy Services, Inc. 8 

31 SoCal Topock EPNG 2/1/01 Reliant Energy Services, Inc. 8 

32 SoCal Topock EPNG 2/1/01 Reliant Energy Services, Inc. 8 

33 SoCal Topock EPNG 1/31/01 Reliant Energy Services, Inc. 8 

34 SoCal Topock EPNG 1/31/01 Reliant Energy Services, Inc. 8 

35 SoCal Topock EPNG 1/31/01 Reliant Energy Services, Inc. 8 

 

9

These are the longest sequences of transactions for spot gas at a single location that are buy transactions by a single 

firm. 
 Appendix II-A 

Docket No. PA02-2-000 II-A-20 Price Manipulation in Western Markets 

Rank 

 

Location Transaction 

Date 

Counterparty Consecutive 

Transactions 

36 SoCal Topock EPNG 1/25/01 Reliant Energy Services, Inc. 8 

37 SoCal Topock EPNG 1/22/01 Reliant Energy Services, Inc. 8 

38 SoCal Topock EPNG 1/17/01 Reliant Energy Services, Inc. 8 

39 SoCal Topock EPNG 1/3/01 Reliant Energy Services, Inc. 8 

40 SoCal Topock EPNG 1/2/01 Reliant Energy Services, Inc. 8 
 Appendix II-A 

Docket No. PA02-2-000 II-A-21 Price Manipulation in Western Markets 

Table II-A13. EOL Western Gas Spot Trades, November 2000 – June 2001, 

Most Consecutive “Sell” Transactions By One Firm10 (continued on next page) 

Rank Location 

Transaction 

Date Counterparty 

Consecutive 

Transactions

1 EPNG SoCal Ehrenberg 6/15/01 Reliant Energy Services, Inc. 14 

2 SoCal Topock EPNG 2/5/01 El Paso Merchant Energy, L.P. 11 

3 SoCal Topock EPNG 1/31/01 Reliant Energy Services, Inc. 11 

4 SoCal Topock EPNG 11/3/00 Aquila Energy Marketing Corporation 11 

5 EPNG SoCal Ehrenberg 4/26/01 Reliant Energy Services, Inc. 10 

6 EPNG SoCal Ehrenberg 4/11/01 Reliant Energy Services, Inc. 10 

7 EPNG SoCal Ehrenberg 4/5/01 Reliant Energy Services, Inc. 10 

8 EPNG SoCal Ehrenberg 3/23/01 El Paso Merchant Energy, L.P. 10 

9 EPNG SoCal Ehrenberg 3/8/01 El Paso Merchant Energy, L.P. 10 

10 SoCal Topock EPNG 6/11/01 Reliant Energy Services, Inc. 10 

11 EPNG SoCal Ehrenberg 3/26/01 Reliant Energy Services, Inc. 9 

12 SoCal Topock EPNG 6/13/01 Reliant Energy Services, Inc. 9 

13 SoCal Topock EPNG 3/23/01 Reliant Energy Services, Inc. 9 

14 SoCal Topock EPNG 3/21/01 El Paso Merchant Energy, L.P. 9 

15 SoCal Topock EPNG 1/31/01 Reliant Energy Services, Inc. 9 

16 SoCal Topock EPNG 1/29/01 Aquila Energy Marketing Corporation 9 

17 SoCal Topock EPNG 12/19/00 Reliant Energy Services, Inc. 9 

18 SoCal Topock EPNG 12/5/00 Reliant Energy Services, Inc. 9 

19 SoCal Topock EPNG 12/1/00 Reliant Energy Services, Inc. 9 

20 EPNG SoCal Ehrenberg 5/23/01 BP Energy Company 8 

21 EPNG SoCal Ehrenberg 3/27/01 El Paso Merchant Energy, L.P. 8 

22 EPNG SoCal Ehrenberg 3/22/01 Reliant Energy Services, Inc. 8 

23 PG&E Topock 4/2/01 El Paso Merchant Energy, L.P. 8 

24 SoCal Topock EPNG 12/15/00 Southern California Gas Company 8 

25 SoCal Topock EPNG 12/11/00 Reliant Energy Services, Inc. 8 

26 SoCal Topock EPNG 12/11/00 Reliant Energy Services, Inc. 8 

27 SoCal Topock EPNG 11/20/00 Reliant Energy Services, Inc. 8 

28 SoCal Topock EPNG 11/1/00 Dynegy Marketing and Trade 8 

29 CIG Mainline 12/11/00 BP Energy Company 7 

30 EPNG SoCal Ehrenberg 4/16/01 Reliant Energy Services, Inc. 7 

31 EPNG SoCal Ehrenberg 3/29/01 Southern California Gas Company 7 

32 EPNG SoCal Ehrenberg 3/16/01 El Paso Merchant Energy, L.P. 7 

33 EPNG SoCal Ehrenberg 3/13/01 El Paso Merchant Energy, L.P. 7 

34 PG&E Ctygte Pool 1/22/01 El Paso Merchant Energy, L.P. 7 

35 PGT Malin 5/1/01 Enserco Energy, Inc. 7 

 

10These are the longest sequences of transactions for spot gas at a single location that are sell transactions by a single 

firm. 
 Appendix II-A 

Docket No. PA02-2-000 II-A-22 Price Manipulation in Western Markets 

Rank Location 

Transaction 

Date Counterparty 

Consecutive 

Transactions

36 SoCal Topock EPNG 2/13/01 Reliant Energy Services, Inc. 7 

37 SoCal Topock EPNG 2/7/01 El Paso Merchant Energy, L.P. 7 

38 SoCal Topock EPNG 2/2/01 Reliant Energy Services, Inc. 7 

39 SoCal Topock EPNG 2/2/01 Reliant Energy Services, Inc. 7 

40 SoCal Topock EPNG 1/31/01 Reliant Energy Services, Inc. 7 
 Appendix II-A 

Docket No. PA02-2-000 II-A-23 Price Manipulation in Western Markets 

Table II-A14. Reliant’s Profit From EOL-Reliant Netting Agreement, Highest Daily Profit From the 

Netting Agreement ($100,000 or More) 

 Reliant Selling to EOL Reliant Buying From EOL 

Transaction 

Date 

Churn 

Day Transactions 

Volume 

(MMBtu) Price Transactions

Volume 

(MMBtu) Price 

Reliant’s 

Net Buy 

From EOL

Profit From 

the Netting 

Agreement 

12/11/00 Yes 56 554,000 $60.77 80 800,000 $57.84 246,000 $1,622,025 

12/08/00 Yes 15 450,000 $57.73 33 990,000 $54.21 540,000 $1,584,545 

03/01/01 Yes 15 155,000 $26.03 16 160,000 $22.43 5,000 $558,156 

01/31/01 Yes 73 730,000 $14.21 101 1,010,000 $13.62 280,000 $431,267 

02/13/01 Yes 17 170,000 $36.78 54 540,000 $34.30 370,000 $421,343 

02/02/01 Yes 44 1,320,000 $16.24 80 2,385,000 $15.96 1,065,000 $369,726 

12/05/00 Yes 29 311,000 $27.34 60 600,000 $26.22 289,000 $350,617 

12/01/00 Yes 25 750,000 $19.21 51 1,530,000 $18.75 780,000 $345,000 

03/06/01 No 7 70,000 $30.07 6 60,000 $24.42 (10,000) $339,286 

11/17/00 No 1 150,000 $10.50 21 630,000 $8.30 480,000 $329,929 

12/06/00 Yes 23 313,000 $38,68 49 490,000 $37.78 177,000 $282,265 

11/30/00 Yes 19 182,000 $19.82 32 320,000 $18.28 138,000 $280,313 

03/02/01 Yes 12 360,000 $30.22 30 855,000 $29.46 495,000 $273,158 

12/04/00 Yes 21 203,000 $22.54 31 310,000 $21.39 107,000 $233,919 

12/07/00 Yes 23 220,000 $43.85 48 480,000 $43.00 260,000 $186,000 

11/20/00 No 8 80,000 $13.75 7 70,000 $11.19 (10,000) $179,250 

02/23/01 No 3 90,000 $14.33 18 540,000 $12.38 450,000 $176,250 

02/09/01 No 9 232,500 $15.95 13 390,000 $15.45 157,500 $115,529 

12/19/00 Yes 20 200,000 $20.53 47 470,000 $19.98 270,000 $109,255 

19 Days 14 

Churn 

Days 

420 6,540,500 777 12,630,000 6,089,500 $8187,833 

Total Profit on the Churn Days $7,047,590 86.07% 

Total Profit on the other Days $1,140,243 13.93%
 Appendix II-A 

Docket No. PA02-2-000 II-A-24 Price Manipulation in Western Markets 

Table II-A15. EOL-Reliant Netting Agreement’s Impact on Physical Spot Trading Outcomes, 

Highest Daily Profit From the Netting Agreement ($100,000 or More) 

Average Buy Price 

Transaction 

Date 

Churn 

Day 

Profit From 

the Netting 

Agreement 

Without the Netting 

Agreement 

Applying Profit From the 

Netting Agreement, 

Assuming 60% Flow 

GasDaily SoCal 

Large Packages 

Midpoint Price 

Index 

12/11/00 Yes $1,622,025 $51.24 $46.85 $59.42 

12/08/00 Yes $1,584,545 $51.28 $49.32 $54.66 

03/01/01 Yes $558,156 N/A11 N/A11 $23.95 

01/31/01 Yes $431,267 $12.08 $11.05 $13.75 

02/13/01 Yes $421,343 $33.16 $32.40 $34.53 

02/02/01 Yes $369,726 $15.61 $15.38 $15.39 

12/05/00 Yes $350,617 $25.00 $24.19 $26.60 

12/01/00 Yes $345,000 $18.31 $18.01 $18.50 

03/06/01 No $339,286 N/A12 N/A12 $25.27 

11/17/00 No $329,929 $7.61 $7.15 $9.60 

12/06/00 Yes $282,265 $36.18 $35.12 $36.25 

11/30/00 Yes $280,313 $16.25 $14.90 $18.90 

03/02/01 Yes $273,158 $28.91 $28.54 $27.79 

12/04/00 Yes $233,919 $19.20 $17.74 $21.61 

12/07/00 Yes $186,000 $42.28 $41.81 $42.02 

11/20/00 No $179,250 N/A12 N/A12 $13.42 

02/23/01 No $176,250 $11.98 $11.72 $12.68 

02/09/01 No $115,529 $14.72 $14.23 $14.83 

12/19/00 Yes $109,255 $19.57 $19.30 $19.56 

 

11On March 1, 2001, Reliant bought 160,000 MMBtu on EOL and sold back 155,000 MMBtu. The net purchase, 

5,000 MMBtu, is very small relative to the gross volume (only 1.59 percent). The profit generated by the difference 

between the buy price and the sell price for the 155,000 MMBtu is $558,156. 

12On March 6, 2001 and November 20, 2000, Reliant was a net seller on EOL. 
 Appendix II-A 

Docket No. PA02-2-000 II-A-25 Price Manipulation in Western Markets 

Table II-A16. Reliant’s Profit From EOL-Reliant Netting Agreement for 24 Churn Days 

 Reliant Selling to EOL Reliant Buying From EOL 

Transaction 

Date Transactions

Volume 

(MMBtu) Price Transactions

Volume 

(MMBtu) Price 

Reliant’s Net 

Buy From 

EOL 

Profit From 

the Netting 

Agreement

11/01/00 10 100,000 $5.07 11 100,000 $5.11 0 ($4,700) 

11/13/00 19 190,000 $7.41 21 200,000 $7.40 10,000 $3,605 

11/30/00 19 182,000 $19.82 32 320,000 $18.28 138,000 $280,313 

12/01/00 25 750,000 $19.21 51 1,530,000 $18.75 780,000 $345,000 

12/04/00 21 203,000 $22.54 31 310,000 $21.39 107,000 $233,919 

12/05/00 29 311,000 $27.34 60 600,000 $26.22 289,000 $350,617 

12/06/00 23 313,000 $38.68 49 490,000 $37.78 177,000 $282,265 

12/07/00 23 220,000 $43.85 48 480,000 $43.00 260,000 $186,000 

12/08/00 15 450,000 $57.73 33 990,000 $54.21 540,000 $1,584,545

12/11/00 56 554,000 $60.77 80 800,000 $57.84 246,000 $1,622,025

12/13/00 7 108,000 $20.69 67 665,000 $20.72 557,000 ($3,549) 

12/19/00 20 200,000 $20.53 47 470,000 $19.98 270,000 $109,255 

01/31/01 73 730,000 $14.21 101 1,010,000 $13.62 280,000 $431,267 

02/02/01 44 1,320,000 $16.24 80 2,385,000 $15.96 1,065,000 $369,726 

02/13/01 17 170,000 $36.78 54 540,000 $34.30 370,000 $421,343 

02/28/01 12 120,000 $12.76 21 210,000 $12.93 90,000 ($20,429) 

03/01/01 15 155,000 $26.03 16 160,000 $22.43 5,000 $558,156 

03/02/01 12 360,000 $30.22 30 855,000 $29.46 495,000 $273,158 

03/20/01 11 110,000 $11.17 16 160,000 $11.01 50,000 $17,863 

03/22/01 13 130,000 $11.09 10 100,000 $10.80 (30,000) $29,077 

03/23/01 31 960,000 $11.12 35 1,050,000 $11.12 90,000 $4,929 

04/03/01 12 120,000 $15.09 10 100,000 $14.56 (20,000) $53,167 

06/11/01 21 224,000 $7.23 40 400,000 $6.84 176,000 $89,460 

06/13/01 11 110,000 $8.98 41 379,479 $8.51 269,479 $50,950 

 Total Profit $7,267,962 
 Appendix II-A 

Docket No. PA02-2-000 II-A-26 Price Manipulation in Western Markets 

Table II-A17. EOL-Reliant Netting Agreement’s Impact on Physical Spot Trading 

Outcomes for 24 Churn Days 

Average Buy Price 

Transaction 

Date 

Profit From 

the Netting 

Agreement 

Without the Netting 

Agreement 

Applying Profit From the 

Netting Agreement, Assuming 

60% Flow 

GasDaily SoCal 

Large Packages 

Midpoint Price 

Index 

11/01/00 ($4,700) N/A13 N/A13 $5.20 

11/13/00 $3,605 $7.04 $6.79 $7.37 

11/30/00 $280,313 $16.25 $14.90 $18.90 

12/01/00 $345,000 $18.31 $18.01 $18.50 

12/04/00 $233,919 $19.20 $17.74 $21.61 

12/05/00 $350,617 $25.00 $24.19 $26.60 

12/06/00 $282,265 $36.18 $35.12 $36.25 

12/07/00 $186,000 $42.28 $41.81 $42.02 

12/08/00 $1,584,545 $51.28 $49.32 $54.66 

12/11/00 $1,622,025 $51.24 $46.85 $59.42 

12/13/00 ($3,549) $20.72 $20.73 $20.26 

12/19/00 $109,255 $19.57 $19.30 $19.56 

01/31/01 $431,267 $12.08 $11.05 $13.75 

02/02/01 $369,726 $15.61 $15.38 $15.39 

02/13/01 $421,343 $33.16 $32.40 $34.53 

02/28/01 ($20,429) $13.16 $13.31 $12.96 

03/01/01 $558,156 N/A14 N/A14 $23.95 

03/02/01 $273,158 $28.91 $28.54 $27.79 

03/20/01 $17,863 $10.65 $10.42 $11.04 

03/22/01 $29,077 N/A15 N/A15 $11.00 

03/23/01 $4,929 $11.06 $11.03 $11.13 

04/03/01 $53,167 N/A15 N/A15 $14.71 

06/11/01 $89,460 $6.33 $5.99 $6.74 

06/13/01 $50,950 $8.33 $8.20 $8.47 

Total Profit $7,267,962 

 

13On November 1, 2000, Reliant bought 100,000 MMBtu on EOL and sold back the whole amount. Since the net 

purchase is zero, the average price cannot be calculated. 

14On March 1, 2001, Reliant bought 160,000 MMBtu on EOL and sold back 155,000 MMBtu. The net purchase, 

5,000 MMBtu, is very small relative to the gross volume (only 1.59 percent). The profit generated by the difference 

between the buy price and the sell price for the 155,000 MMBtu is $558,156. 

15On March 22, 2001 and April 3, 2001, Reliant was a net seller on EOL. 
 Appendix II-A 

Docket No. PA02-2-000 II-A-27 Price Manipulation in Western Markets 

Table II-A18. Reliant’s Profit From EOL-Reliant Netting Agreement for December 2000 Flow 

 Reliant Selling to EOL Reliant Buying From EOL 

Transaction 

Date 

Churn 

Day Transactions 

Volume 

(MMBtu) Price Transactions

Volume 

(MMBtu) Price 

Reliant’s 

Net Buy 

From EOL 

Profit From 

the Netting 

Agreement 

11/30/00 Yes 19 182,000 $19.82 32 320,000 $18.28 138,000 $280,313 

12/1/00 Yes 25 750,000 $19.21 51 1,530,000 $18.75 780,000 $345,000 

12/4/00 Yes 21 203,000 $22.54 31 310,000 $21.39 107,000 $233,919 

12/5/00 Yes 29 311,000 $27.34 60 600,000 $26.22 289,000 $350,617 

12/6/00 Yes 23 313,000 $38.68 49 490,000 $37.78 177,000 $282,265 

12/7/00 Yes 23 220,000 $43.85 48 480,000 $43.00 260,000 $186,000 

12/8/00 Yes 15 450,000 $57.73 33 990,000 $54.21 540,000 $1,584,545 

12/11/00 Yes 56 554,000 $60.77 80 800,000 $57.84 246,000 $1,622,025 

12/12/00 No 8 80,000 $29.38 49 490,000 $30.04 410,000 ($53,265) 

12/13/00 Yes 7 108,000 $20.69 67 665,000 $20.72 557,000 ($3,549) 

12/14/00 No 2 18,000 $21.06 34 340,000 $19.97 322,000 $19,569 

12/15/00 No 5 234,000 $17.79 53 1,590,000 $17.83 1,356,000 ($9,764) 

12/18/00 No 1 10,000 $20.50 47 470,000 $21.10 460,000 ($5,957) 

12/19/00 Yes 20 200,000 $20.53 47 470,000 $19.98 270,000 $109,255 

12/20/00 No 1 10,000 $21.00 39 390,000 $21.72 380,000 ($7,179) 

12/21/00 No 6 60,000 $20.33 28 275,000 $18.78 215,000 $93,091 

12/22/00 No 2 75,000 $17.67 17 850,000 $18.76 775,000 ($82,353) 

12/27/00 No 0 0 N/A 22 220,000 $17.17 220,000 $0 

12/28/00 No 0 0 N/A 10 300,000 $15.17 300,000 $0 

12/29/00 No 2 40,000 $15.50 20 400,000 $14.95 360,000 $22,000 

20 Days 10 

Churn 

Days 

265 3,818,000 817 11,980,000 8,162,000 $4,966,5325 

Total Profit on the Churn Days $4,990,390 

Total Profit on the other Days -$ 23,859
 Appendix II-A 

Docket No. PA02-2-000 II-A-28 Price Manipulation in Western Markets 

Table II-A19. EOL-Reliant Netting Agreement’s Impact on Physical Spot Trading Outcomes for 

December 2000 Flow 

Average Buy Price 

Transaction 

Date 

Churn 

Day 

Profit From 

the Netting 

Agreement Without the Netting 

Agreement 

Applying Profit From the 

Netting Agreement, 

Assuming 60% Flow 

GasDaily SoCal 

Large Packages 

Midpoint Price 

Index 

11/30/00 Yes $280,313 $16.25 $14.90 $18.90 

12/1/00 Yes $345,000 $18.31 $18.01 $18.50 

12/4/00 Yes $233,919 $19.20 $17.74 $21.61 

12/5/00 Yes $350,617 $25.00 $24.19 $26.60 

12/6/00 Yes $282,265 $36.18 $35.12 $36.25 

12/7/00 Yes $186,000 $42.28 $41.81 $42.02 

12/8/00 Yes $1,584,545 $51.28 $49.32 $54.66 

12/11/00 Yes $1,622,025 $51.24 $46.85 $59.42 

12/12/00 No -$53,265 $30.17 $30.26 $32.75 

12/13/00 Yes -$3,549 $20.72 $20.73 $20.26 

12/14/00 No $19,569 $19.91 $19.87 $19.03 

12/15/00 No -$9,764 $17.84 $17.84 $17.06 

12/18/00 No -$5,957 $21.11 $21.12 $20.39 

12/19/00 Yes $109,255 $19.57 $19.30 $19.56 

12/20/00 No -$7,179 $21.74 $21.75 $20.36 

12/21/00 No $93,091 $18.35 $18.06 $18.98 

12/22/00 No -$82,353 $18.87 $18.94 $18.78 

12/27/00 No $0 $17.17 $17.17 $16.64 

12/28/00 No $0 $15.17 $15.17 $14.41 

12/29/00 No $22,000 $14.89 $14.85 $14.33 

Volume Weighted Price $23.71 $23.30 $24.09 
 Appendix II-A 

Docket No. PA02-2-000 II-A-29 Price Manipulation in Western Markets 

Table II-A20. Reliant’s Balance-of-Month Swap Trading Activities and Profits, 

November 27, 2000 – December 29, 2000 

 Profit Statistics 

Trader 

Transaction 

Date 

Transaction 

Time 

Buy/ 

Sell 

Swap 

Volume 

(MMBtu/d) Price 

Contract 

Begin 

Date 

Contract 

End Date Counterparty 

Profit 

Generated 

per Trade 

Total Profit 

Generated 

11/28/00 3:49 PM S -30,000 14.68 12/1/00 12/31/00 ENRON NORTH AMERICA CORP. -$9,114,750 -$9,114,750

7:46 AM B 10,000 15.20 12/1/00 12/31/00 MIRANT AMERICAS ENERGY MARKETING, LP $3,063,050 

7:52 AM B 30,000 15.10 12/1/00 12/31/00 ENRON NORTH AMERICA CORP. $9,282,150 

2:25 PM B 5,000 17.07 12/1/00 12/31/00 ENRON NORTH AMERICA CORP. $1,241,675 

2:34 PM B 5,000 16.85 12/1/00 12/31/00 ENRON NORTH AMERICA CORP. $1,275,775 

2:38 PM B 10,000 16.94 12/1/00 12/31/00 MIRANT AMERICAS ENERGY MARKETING, LP $2,523,650 

3:52 PM B 10,000 17.50 12/1/00 12/31/00 SEMPRA ENERGY TRADING CORP. $2,350,050 

3:54 PM B 10,000 17.20 12/1/00 12/31/00 ENRON NORTH AMERICA CORP. $2,443,050 

11/30/00 

3:55 PM B 5,000 16.96 12/1/00 12/31/00 ENRON NORTH AMERICA CORP. $1,258,725 $23,438,125

12:42 PM B 15,000 16.05 12/2/00 12/31/00 ENRON NORTH AMERICA CORP. $4,158,900 

12:44 PM B 5,000 16.27 12/2/00 12/31/00 ENRON NORTH AMERICA CORP. $1,353,300 

12:45 PM B 5,000 16.15 12/2/00 12/31/00 ENRON NORTH AMERICA CORP. $1,370,925 

12:53 PM S -5,000 16.56 12/2/00 12/31/00 ENRON NORTH AMERICA CORP. -$1,309,800 

12:55 PM S -5,000 16.12 12/2/00 12/31/00 ENRON NORTH AMERICA CORP. -$1,375,800 

12/1/00 

1:56 PM S -2,000 16.70 12/2/00 12/31/00 SOUTHERN CALIFORNIA GAS COMPANY -$515,220 $3,682,305

3:44 PM B 5,000 18.83 12/5/00 12/31/00 ENRON NORTH AMERICA CORP. $973,575 

4:25 PM S -5,000 22.39 12/6/00 12/31/00 ENRON NORTH AMERICA CORP. -$496,900 12/4/00 

4:26 PM S -5,000 22.48 12/6/00 12/31/00 ENRON NORTH AMERICA CORP. -$485,850 -$9,175

12/6/00 2:06 PM S -5,000 35.32 12/7/00 12/31/00 ENRON NORTH AMERICA CORP. $1,140,375 $1,140,375

1:58 PM B 2,000 37.00 12/9/00 12/31/00 DYNEGY MARKETING AND TRADE -$548,680 

2:00 PM B 10,000 37.25 12/9/00 12/31/00 SEMPRA ENERGY TRADING CORP. -$2,800,900 12/7/00 

2:24 PM S -10,000 38.00 12/8/00 12/31/00 DYNEGY MARKETING AND TRADE $2,933,200 -$416,380

12/12/00 12:38 PM B 1,500 22.60 12/14/00 12/31/00 AQUILA, INC. D/B/A AQUILA NETWORKS -$129,405 -$129,405

Financial 

Trader A 

12/13/00 8:53 AM B 5,000 24.00 12/14/00 12/31/00 ENRON NORTH AMERICA CORP. -$557,350 -$557,350

 Total = $18,033,745
 Appendix II-A 

Docket No. PA02-2-000 II-A-30 Price Manipulation in Western Markets 

Table II-A21. Reliant’s Balance-of-Month Swap Trading Activities and Profits, 

February 6, 2001 – February 24, 2001 

 Profit Statistics 

Trader 

Transaction 

Date 

Transaction 

Time 

Buy/ 

Sell 

Swap 

Volume 

(MMBtu/d) Price 

Contract 

Begin 

Date 

Contract 

End Date Counterparty 

Profit 

Generated 

per Trade

Total 

Profit 

Generated

2/6/01 10:59 AM S -5,000 15.00 2/7/01 2/28/01 SOUTHERN CALIFORNIA GAS COMPANY -$530,525 -$530,525

4:00 PM B 10,000 17.50 2/14/01 2/28/01 WILLIAMS ENERGY MARKETING & TRADING COMPANY $702,550 

4:03 PM B 5,000 17.75 2/14/01 2/28/01 DUKE ENERGY TRADING & MARKETING. L.L.C. $332,525 

4:04 PM B 10,000 18.00 2/14/01 2/28/01 MIRANT AMERICAS ENERGY MARKETING, LP $627,550 

4:06 PM B 5,000 18.00 2/14/01 2/28/01 DUKE ENERGY TRADING & MARKETING. L.L.C. $313,775 

4:13 PM B 5,000 18.79 2/14/01 2/28/01 ENRON NORTH AMERICA CORP. $254,525 

4:14 PM B 5,000 19.74 2/14/01 2/28/01 ENRON NORTH AMERICA CORP. $183,275 

4:16 PM B 5,000 19.30 2/14/01 2/28/01 WILLIAMS ENERGY MARKETING & TRADING COMPANY $216,275 

4:24 PM B 5,000 16.90 2/13/01 2/28/01 WILLIAMS ENERGY MARKETING & TRADING COMPANY $410,650 

4:26 PM B 5,000 17.85 2/13/01 2/28/01 ENRON NORTH AMERICA CORP. $334,650 

4:28 PM B 5,000 17.50 2/13/01 2/28/01 ENRON NORTH AMERICA CORP. $362,650 

4:32 PM B 5,000 19.10 2/14/01 2/28/01 J. ARON & COMPANY $231,275 

4:33 PM B 5,000 19.25 2/14/01 2/28/01 ENRON NORTH AMERICA CORP. $220,025 

Financial 

Trader A 2/12/01 

4:34 PM B 5,000 19.50 2/14/01 2/28/01 CINERGY MARKETING & TRADING, LLC $201,275 $4,391,000

 Total = $3,860,475
 Appendix II-B 

Docket No. PA02-2-000 II-B-1 Price Manipulation in Western Markets 

Appendix II-B: Econometric Analysis of Impact of Reliant 

Trading on Gas Prices 

Intraday EOL Price Analysis 

The dependent variable in the analysis is the percentage price change over a trade day (i.e., the 

intraday change in spot price, measured as the log ratio of the price of the last EOL trade over the 

price of the first EOL trade). We present two regressions, one with each measure of Reliant’s 

churning activity. The period of interest is November 1, 2000 through June 2001. 

For the discrete specification of churning, we estimate the following regression: 

LCO = β0+ β1 BNS100K + β2 DEC2000 + β3 MONDAY + β4 LSUMASD + β5 LNBNDD + ε, 

Where: 

♦ LCO is the intraday change in the logarithm of the SoCal spot price. 

♦ BNS100K is a binary variable indicating whether there are buys and sells of at least 100,000 

MMBtu/d on a specific day. 

♦ DEC2000 and MONDAY are binary variables indicating that the transaction occurs in 

December 2000 or for Saturday to Monday flow, respectively. 

♦ LSUMASD and LNBNDD are the interday changes in the logarithms of gas prices at Sumas 

and San Juan Non-Bondad, respectively.1

♦ ε captures the remaining unexplained component of LCO. 

For the continuous specification of churning, we estimate the same regression as above, but for 

the second churn measure: 

LCO = β0+ β1 CHURN + β2 DEC2000 + β3 MONDAY + β4 LSUMASD + β5 LNBNDD + ε,

Where: 

♦ CHURN is the minimum of sales and purchases (in thousands of MMBtu/d). 

♦ All other variables are as previously defined. 

 

1

We use the Gas Daily Midpoint Price Index. 
 Appendix II-B 

Docket No. PA02-2-000 II-B-2 Price Manipulation in Western Markets 

The results for these two models are provided in Table II-B1 and can be interpreted as follows: 

♦ For both regression specifications, churning is found to be positively correlated with intraday 

gas price changes and is statistically significant. Stated differently, when Reliant churned, 

prices rose. 

♦ Changes in gas prices at Sumas and San Juan Non-Bondad, and whether a trade occurs on 

Friday for weekend flow, are also positively correlated with intraday price changes. 

♦ The coefficient on the December 2000 variable is negative, indicating that intraday price 

changes were smaller (i.e., more negative) during this period. 
 Appendix II-B 

Docket No. PA02-2-000 II-B-3 Price Manipulation in Western Markets 

Table II-B1. Intraday Regression Results 

Churn 

Measure 

Regression 

Variable 

Variable 

Definition 

Parameter Estimate 

(Absolute value 

of t statistics) 

BnS100K Binary variable indicating whether 

there are purchases and sales of at 

least 100,000 MMBtu/d on a specific 

day 

0.0731 

(2.74) 

 

Lsumasd_mid Logarithm of the interday change in 

gas price at Sumas 

0.4714 

(5.82) 

 

Lnbndd_mid Logarithm of the interday change in 

gas price at San Juan Non-Bondad 

0.1941 

(1.77) 

 

Monday Binary variable indicating that the 

transaction occurs for Sat-Mon flow 

0.0557 

(2.43) 

 

Dec2000 Binary variable indicating that the 

transaction occurs in December 2000

-0.0678 

(2.40) 

Purchases and 

sales of at least 

100,000 

MMBtu/d 

 

Churn Minimum of total purchases and total 

sales 

0.0002 

(2.34) 

 

Lsumasd_mid Logarithm of the interday change in 

gas price at Sumas 

0.4919 

(6.05) 

 

Lnbndd_mid Logarithm of the interday change in 

gas price at San Juan Non-Bondad 

0.1751 

(1.55) 

 

Monday Binary variable indicating that the 

transaction occurs for Sat-Mon flow 

0.0528 

(2.27) 

 

Dec2000 Binary variable indicating that the 

transaction occurs in December 2000

-0.0618 

(2.19) 

Minimum of total 

sales and total 

purchases 

 

Interday EOL Price Analyses and Counterfactual Gas Prices 

The calculation of counterfactual gas prices is based on regression analysis similar to that 

described in the previous section, with three main differences: 

First, we include overnight price changes in our analysis. We analyze the interday price change 

(i.e., the difference between the average EOL price on a trading day and the price on the next 

trading day). 
 Appendix II-B 

Docket No. PA02-2-000 II-B-4 Price Manipulation in Western Markets 

Second, we model the churn’s dynamic effect on prices on days subsequent to the churning days 

by including lags of the churn variables.2

 In other words, we investigate whether today’s churn 

affects price changes for several days in the future.3 We estimated our model using different 

numbers of lags. We found that the effect of churn could not be estimated precisely beyond three 

lags, so we report results based on the three-lags specifications. Even in some of these 

specifications, the effects of some lags of churn are not statistically significant. The 

counterfactual prices that we computed based on regressions including greater numbers of lags 

were qualitatively similar. 

Third, because we are concerned with price dynamics, we also model general mean-reversion in 

prices that are independent of the effect of churn. Energy prices tend to mean-revert, at least in 

the medium to long term. High prices induce further exploration and production, leading to 

increased supply. To the extent that demand is price-sensitive, high prices may also reduce 

demand. By inducing additional supply and reducing demand, high current prices tend to lead to 

lower prices in the future. Conversely, low prices today tend to lead to higher prices in the future. 

We model the daily price change on the churn variable, lags of the churn variable, and the 

difference between the lagged EOL price and an estimate of the equilibrium price. For the 

interday models with the discrete specification of churning, we estimate the following 

regression: 

LCC = β0+ β1 LAGCH0 + β2 LAGCH1 + β3 LAGCH2 + β4 LAGCH3 + 

β5 (LGLGP-EQLOGP )+ ε,

Where: 

♦ LCC is the change in the logarithm of the EOL price from the previous day. 

♦ LAGCH0, LAGCH1, LAGCH2, and LAGCH3 are binary variables indicating whether there 

are purchases and sales of at least 100,000 MMBtu/d on the day associated with the 

observation, the previous day, two days earlier, and three days earlier. 

♦ LGLGP is the lagged log EOL gas price level. 

♦ EQLOGP is the estimated log equilibrium price. 

♦ ε captures the remaining unexplained component of LCO. 

There are two model specifications for each of the two churn definitions (discrete and 

continuous) for which regressions are performed and counterfactual prices are estimated. These 

model specifications correspond to alternative methods of specifying the equilibrium price. In 

the first approach, we include levels of the lagged log price and other independent variables, 

primarily log prices at various upstream locations, in the regression. Levels of the independent 

 

2

We also include lags of other independent variables in our regressions. 

3

There are at least two possible reasons why the effects of churn might persist beyond the day on which it occurs. 

First, churning on one day may push up prices on subsequent days if it changes market psychology and generates 

momentum. Second, because churning does not change fundamental supply and demand conditions, to the extent 

that churning results in inflated prices one might expect prices to revert to a “normal” level relatively quickly. 
 Appendix II-B 

Docket No. PA02-2-000 II-B-5 Price Manipulation in Western Markets 

variables determine the “equilibrium” level of the log EOL Topock gas price. To the extent that 

the lagged log price is above this equilibrium level, prices tend to fall, i.e., price changes are 

more negative. To the extent that the lagged log price is below this equilibrium level, prices tend 

to rise, i.e., price changes are more positive. Hence, this type of econometric model is sometimes 

known as an error-correction model (ECM).4

 Our ECM is specified as follows: 

{ }

5

1

3

0

1

log

log

log log

log log log log

EOLT NOV DEC DOWj

t j

j

CHURN Sumas Sumas

i ti i ti

SJNB SJNB DSHOCK i i ti i ti

EOLT Sumas Sumas SJNB SJNB QASYS

t tt

p NOV DEC DOW

CHURN p

p DSHOCK

p p p QASYS

αβ β β

β β

β β

λγ γ γ

=

− −

= − −

−

∆ =+ + +

    + ∆

+       +∆ +

+− + + +    

∑

∑

t ε

 

Where: 

♦ log EOLTopock

t ∆ p is the first difference of the log of the EOL Topock price. 

♦ CHURNt i − is the i’th lag of churn. 

♦ log Sumas

t i p ∆ − and log SJNBt i p ∆ − are the i’th lags of the first differences of the logs of the Sumas 

and San Juan Non-Bondad prices. 

♦ log DSHOCKt i − is the i’th lag of the difference between the log realized ISO system load and 

the day-ahead forecast. 

♦ NOV and DEC are dummy variables for the months of November and December. 

♦ DOWj is a dummy variable for day-of-week j. In the estimation, the constant and all five 

day-of-week dummies are collinear and cannot be estimated uniquely, so we drop one of the 

day-of-week dummies. 

♦ 1 log EOLTopock

t p − is the lagged level of the log of the EOL Topock price. 

♦ log Sumas

t p and log SJNBt p are the logs of the contemporaneous Sumas and San-Juan NonBondad prices. 

♦ logQASYS is the log of realized ISO system demand. 

♦ t ε is the error. 

In this specification, log Sumas

t p , log SJNBt p , and logQASYS determine an equilibrium log price and 

λ measures the speed of mean-reversion toward the equilibrium price. 

 

4

See William Greene, Econometric Analysis, 4th ed., Chapter 17, for a brief overview of error-correction and related 

models. 
 Appendix II-B 

Docket No. PA02-2-000 II-B-6 Price Manipulation in Western Markets 

The second approach is a simplification of the first approach. Rather than modeling an 

equilibrium price that can change in response to changes in certain variables, we assume that the 

equilibrium price is fixed, so the regression equation becomes: 

{ }

5

1

3

0

1

log

log

log log

log

EOLT NOV DEC DOWj

t j

j

CHURN Sumas Sumas

i ti i ti

SJNB SJNB DSHOCK i i ti i ti

EOLT

t t

p NOV DEC DOW

CHURN p

p DSHOCK

p

αβ β β

β β

β β

λ φε

=

− −

= − −

−

∆ =+ + +

    + ∆       +∆ +

+ −+

∑

∑

where φ is the log of the estimated long-run equilibrium price. Note that the equilibrium price 

cannot be estimated if an additive constant is included in the model, i.e., α and λφ cannot be 

identified separately. 

Which of these models is “better” is ultimately an empirical question. Estimation of the first 

specification suggests that some of the parameters that determine the equilibrium price, i.e., the 

γ ’s, are statistically significantly different from zero. In other words, the levels of current 

upstream prices and California load help predict price movements and hence should be included 

in the model. The second specification is more parsimonious but less completely models price 

movements. 

For the continuous specification of churning, we estimate the same regression as above but with 

the second churn measure, i.e., the minimum of sales and purchases (in thousands of MMBtu/d). 

Thus, the variables LAGCH0–LAGCH3 are continuous variables defined as the minimum of 

sales and purchases for the observation day (LAGCH0) and three prior days (LAGCH1–

LAGCH3). 

The regression results are summarized in Table II-B2. We report results for four different 

specifications based on combinations of the churn variable, i.e., a binary churn variable or the 

actual volume of churn, and the two methods of modeling the equilibrium price. The results of 

all specifications are similar and show that: 

♦ Churn tends to elevate prices close to when it occurs, but the effect dissipates after several 

days. 

♦ Mean-reversion seems to be present but is not necessarily statistically significant. In every 

specification, the coefficient on the lagged log price is negative, i.e., when prices are high 

they tend to fall, and when prices are low they tend to rise. 

The mean-reversion parameter is statistically significant only in the specifications in which we 

allow the equilibrium price to vary as a function of data. 
 Appendix II-B 

Docket No. PA02-2-000 II-B-7 Price Manipulation in Western Markets 

Table II-B2. Interday Regression Results 

 Model 1 Model 2 

Binary Churn 

Coefficient Coef. Se Coef. Se 

Churn Lag 

 0 0.0975 0.0243 0.1016 0.2468 

 1 0.0664 0.0248 0.0634 0.0251 

 2 (0.0560) 0.0243 (0.0628) 0.0247 

 3 (0.0125) 0.0240 (0.0189) 0.0243 

 

Lagged log EOL price (0.0621) 0.0170 (0.0112) 0.0099 

Continuous Churn 

 Coef. Se Coef. Se 

Churn Lag 

 0 0.0003 0.0001 0.0003 0.0001 

 1 0.0002 0.0001 0.0002 0.0001 

 2 (0.0002) 0.0001 (0.0002) 0.0001 

 3 (0.0001) 0.0001 (0.0001) 0.0001 

 

Lagged log EOL price (0.0575) 0.0170 (0.0109) 0.0102 

 

All Models The dependent variable is the change in the log price from the previous day. 

Model 1 Time-varying equilibrium price is assumed to be a function of independent variables.

Model 2 Constant equilibrium price is assumed. 

Table II-B3 shows how counterfactual prices are calculated from the model for an example 

day—April 3, 2001, one of the Reliant churn days. This example is illustrative and ignores the 

effects of mean-reversion. The actual log price change for April 3 (the logarithm of the price 

change from April 2, 2001 to April 3, 2001) is 0.172. Based on a set of regression results (for 

Model 1 with discrete churn variable), we estimate that churn raises log prices by 0.098 on the 

day on which it occurs; therefore, we estimate that the price change in the absence of churn 

would have been 0.075, the value shown in the fourth column. The sum of this counterfactual 

price change and the previous period’s price, 2.520, results in an estimated counterfactual log 

price of 2.595. This log price corresponds to a price in levels of 13.40, the value shown in the 

seventh column. The counterfactual log price then forms the basis for the subsequent day’s 

counterfactual price calculation until the fourth day from the churn event, at which point we 

assume that the actual and counterfactual prices are equal.5

 

5

This illustrative calculation ignores mean-reversion. When mean-reversion is modeled, not only does the 

counterfactual price for one day form the starting point for the calculation of the counterfactual price on the 

subsequent day, but it also affects the extent of mean-reversion on the subsequent day. 
 Appendix II-B 

Docket No. PA02-2-000 II-B-8 Price Manipulation in Western Markets 

Table II-B3. Sample Counterfactual Price Calculation 

Date 

Churn 

dummy [1] [2] [3] [4] [5] [6] [7] [8] 

2-Apr-01 0 2.520 0.010 0.000 0.010 2.520 12.43 12.43 0.00 

3-Apr-01 1 2.693 0.172 0.098 0.075 2.595 14.77 13.40 1.37 

4-Apr-01 0 2.743 0.051 0.066 -0.016 2.579 15.54 13.19 2.35 

5-Apr-01 0 2.752 0.009 -0.056 0.065 2.645 15.68 14.08 1.60 

6-Apr-01 0 2.664 -0.089 -0.013 -0.076 2.568 14.35 13.05 1.31 

9-Apr-01 0 2.613 -0.051 0.000 -0.051 2.613 13.64 13.64 0.00 

Where: 

♦ [1] log mean EOL price 

♦ [2] log mean EOL price - log mean EOL price(-1)

♦ [3] Effect of churn (regression coefficients on churn binary variable) 

♦ [4] Counterfactual log price changes ([2] - [3]) 

♦ [5] Counterfactual log price (in churn “event” window = [5](-1) + [4], else = [1]) 

♦ [6] Mean EOL price 

♦ [7] Counterfactual price (exp([5])) 

♦ [8] [6] - [7] 
 Appendix V-A 

Docket No. PA02-2-000 Price Manipulation in Western Markets V-A-1

Appendix V-A: Details of Data Validation 

Introduction 

Staff’s long-term transaction data consist of sellers’ responses to Staff’s data request, 

including backup data in the form of the underlying contracts and contract confirmation 

notices. We audited contracts and contract confirmations and use this information to 

validate reported transaction data. In this section, we discuss this audit process and 

describe how the dataset used for the regression analysis was created. 

Auditing Sales Contracts and Confirmations 

The first step was to audit contracts and/or contract confirmations to determine if they 

could be used to validate reported transaction data. To be useful for validation the 

contract or confirmation had to include name of seller, name of purchaser, sales price, 

commencement date, termination date, execution date, type of service (flat, on-peak, or 

off-peak), and delivery point. We also narrowed the number of contracts and 

confirmations we audited by the following criteria: 

♦ Only fixed-price contracts were audited, i.e., contracts with time-varying prices or 

prices tied to index or fuel prices were not included. 

♦ Only contracts for delivery at PV, NP15, SP15, COB, or Mid-C were audited. 

♦ Only contracts where the type of service was “on-peak” were audited. 

There were 1,630 written contracts or confirmations that met the criteria for auditing. The 

data entry process was straightforward because the contracts and confirmations were 

generally unambiguous. To prevent the introduction of error in the audit process, all data 

entries were double-checked. 

The number of audited contracts/confirmations varied widely across sellers. Table V-A1 

summarizes the number of audited contracts/confirmations by seller and trading hub. 
 Appendix V-A 

Docket No. PA02-2-000 Price Manipulation in Western Markets V-A-2

Table V-A1. Number of Audited Contracts/Confirmations by Seller and Trading Hub 

Seller COB Mid-C NP15 PV SP15 Total 

AEP 1 1 20 2 24 

Avista 4 5 11 11 31 

Cargill-Alliant 1 1 

City of Burbank 2 2 

Coral 75 7 64 146 

Duke 38 79 228 211 233 789 

Dynegy 1 1 2 

El Paso Merchant 8 21 57 115 114 315 

Merrill Lynch 11 11 

Morgan Stanley 3 3 15 6 27 

PSC of New Mexico 5 5 

Reliant 2 5 2 73 72 154 

Sempra 9 13 16 28 28 94 

Strategic Energy 3 3 

TransAlta 2 2 

Williams 2 1 12 9 24 

Total 67 130 378 512 543 1,630 

Of the 1,630 audited contracts/confirmations, 73 transactions were dropped because they 

were signed before January 1, 2000. We added 26 long-term power purchases by the 

California Department of Water Resources to the remaining 1,557 audited 

contracts/confirmations. These contracts have received extensive scrutiny and so their 

terms are well understood. The California State Auditor’s characterization of these 

contracts was used.1

Matching Audited Contracts/Confirmations and Reported Transactions 

The audited contracts/confirmations were compared with the sales transactions reported 

by various sellers. The comparison was made using several specifications, including 

buyer and seller names, contract price and sales amount (MWh), trading hub, type of 

service, and execution, commencement, and termination dates. 

In most cases the match was perfect. In cases where the match was not perfect, a 

decision was made as to whether a match was “close enough.” Generally, if one field 

varied slightly between the two data sources but all other fields matched, a match was 

declared. Specifically, contracts/confirmations were matched with their corresponding 

reported sale transaction if one of the following conditions was present: 

 

1

See California State Auditor, Bureau of State Audits, California Energy Markets: Pressures Have Eased 

But Cost Risks Remain, December 2001. 
 Appendix V-A 

Docket No. PA02-2-000 Price Manipulation in Western Markets V-A-3

♦ Execution dates varied by no more than 1 day and all other fields matched (12 

matches). 

♦ Prices differed by no more than a few percent and could reasonably be attributed to 

different interpretations of illegible documents and all other fields matched (28 

matches). 

♦ Either the commencement date or termination date varied by 1 year, but all other 

fields matched (9 matches). 

♦ Either the commencement or termination day of month varied, but all other fields 

matched, including commencement or termination month and year (69 matches). 

♦ Delivery locations did not match (e.g., PV vs. Mid-C), but all other fields matched (3 

matches). 

♦ Buyer names did not match, but the different buyers were affiliated (27 matches). 

♦ Sales amount varied by no more than 25 MWh, but all other fields matched (117 

matches). 

All audited contracts/confirmations were matched with reported sales transactions. 

However, not all sellers provided adequate backup documentation to sufficiently validate 

their reported sales transactions. Table V-A2 provides the number of reported sales 

transactions that were adequately documented and not adequately documented by sellers. 
 Appendix V-A 

Docket No. PA02-2-000 Price Manipulation in Western Markets V-A-4

Table V-A2. Adequacy of Reported Sales Transaction Documentation 

Number of Reported Sales Transactions 

Seller 

Without Adequate 

Documentation 

With Adequate 

Documentation 

Mirant 569 - 

Allegheny 170 - 

Duke 83 769 

El Paso Merchant 61 315 

MIECO 35 - 

Reliant 35 119 

Idaho Power 24 - 

Calpine 22 - 

Coral 19 146 

Morgan Stanley 16 21 

Other 17 13 

AEP 5 24 

PGE 5 - 

Avista 4 31 

Dynegy 3 1 

Merrill Lynch 1 11 

Sempra - 92 

Williams - 15 

All 1,069 1,557 

Comparison of Regression Results Based on Validated-Only Data and All Data 

Since 40 percent of reported sales transactions lack adequate backup documentation, it is 

important to determine if the inclusion of these transaction data has a significant effect on 

regression parameter estimates. To address this issue, we ran a basic “twelve bin” 

regression (described in Appendix V-C) on the two sets of data. The first set included 

1,583 validated transactions (1,557 transactions with adequate backup documentation and 

26 transactions from publicly available California power purchase contracts). The second 

set included 1,583 validated transactions and 1,069 unvalidated transactions. Tables VA3 and V-A4 summarize parameters estimates for each regression run for the “during” 

and “after” periods. 
 Appendix V-A 

Docket No. PA02-2-000 Price Manipulation in Western Markets V-A-5

Table V-A3. Validated vs. All Comparison: “During” Period 

Validated Transactions 

Gas Futures Estimates Spot Power Estimates R2

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) 

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) Hubs OLS IV Obs 

Time-toDelivery 

Class 

Coeff. Std. 

Err. t-stat Coeff. Std. 

Err. t-stat Coeff. Std. 

Err. t-stat Coeff. Std. 

Err. t-stat 

1-2 Years -0.34 0.51 -0.67 0.50 0.76 0.65 0.49 0.18 2.71 0.24 0.25 0.94 36% 34% 42 

3-4 Years 0.54 0.20 2.81 0.36 0.33 1.16 0.14 0.06 2.56 0.18 0.09 2.22 89% 88% 32 Mid-C/ 

COB 

5-8 Years -0.14 0.17 -0.82 0.07 0.84 0.09 -0.05 0.05 -1.04 -0.09 0.15 -0.59 97% 95% 8 

1-2 Years 1.29 0.29 4.82 1.43 0.31 5.09 0.01 0.13 0.07 -0.04 0.14 -0.34 87% 87% 19 

NP15 3-4 Years 2.02 0.32 6.42 2.15 0.39 5.66 0.16 0.05 3.34 0.15 0.05 3.19 85% 84% 52 

5-8 Years -0.24 0.22 -1.08 -0.08 0.23 -0.34 0.04 0.04 0.97 0.05 0.04 1.25 59% 57% 20 

1-2 Years 0.49 0.21 2.41 0.42 0.21 2.05 0.32 0.06 5.11 0.33 0.06 5.38 64% 64% 141 

PV 3-4 Years 0.92 0.26 3.71 0.98 0.26 3.91 0.01 0.05 0.17 0.00 0.05 -0.03 56% 56% 85 

5-8 Years -0.04 0.13 -0.29 -0.04 0.13 -0.28 0.10 0.03 3.26 0.10 0.03 3.26 65% 65% 43 

1-2 Years 0.37 0.15 2.47 0.60 0.17 3.59 0.19 0.08 2.54 0.11 0.08 1.32 62% 63% 81 

SP15 3-4 Years 0.26 0.13 2.16 0.24 0.14 1.80 0.04 0.04 1.05 0.05 0.04 1.12 36% 36% 91 

5-8 Years 0.16 0.20 0.82 0.15 0.20 0.75 0.05 0.04 1.29 0.05 0.04 1.32 48% 48% 46 

All Transactions 

Gas Futures Estimates Spot Power Estimates R2

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) 

Ordinary Least 

Squares (OLS) 

With 

Instrumental 

Variables (IV) 

OLS IV Obs Hubs 

Time-toDelivery 

Class 

Coeff. Std. 

Err. t-stat Coeff. Std. 

Err. t-stat Coeff. Std. 

Err. t-stat Coeff. Std. 

Err. t-stat 

1-2 Years 0.03 0.27 0.10 0.62 0.42 1.45 0.38 0.09 4.16 0.21 0.13 1.66 43% 43% 101 

3-4 Years 0.52 0.16 3.15 0.26 0.22 1.21 0.13 0.04 3.12 0.19 0.05 3.58 79% 78% 62 Mid-C/ 

COB 

5-8 Years 0.40 0.09 4.43 0.63 0.16 3.84 0.00 0.03 -0.13 -0.01 0.03 -0.41 86% 83% 36 

1-2 Years 1.09 0.31 3.52 0.82 0.34 2.42 0.22 0.13 1.64 0.29 0.14 2.10 65% 62% 40 

NP15 3-4 Years 1.69 0.26 6.52 1.76 0.31 5.65 0.14 0.04 3.16 0.14 0.05 3.01 83% 83% 72 

5-8 Years -0.03 0.26 -0.12 -0.10 0.28 -0.38 0.06 0.05 1.33 0.06 0.05 1.20 63% 63% 24 

1-2 Years 0.09 0.19 0.49 0.02 0.19 0.09 0.38 0.06 6.58 0.40 0.06 6.90 49% 49% 221 

PV 3-4 Years 0.42 0.14 3.00 0.46 0.14 3.26 0.09 0.04 2.37 0.08 0.04 2.14 50% 51% 122 

5-8 Years 0.10 0.09 1.10 0.10 0.09 1.11 0.07 0.02 3.36 0.07 0.02 3.35 66% 66% 74 

1-2 Years 0.27 0.15 1.76 0.51 0.17 2.99 0.23 0.08 2.99 0.14 0.08 1.69 60% 60% 89 

SP15 3-4 Years 0.28 0.10 2.63 0.29 0.11 2.52 0.07 0.03 2.33 0.07 0.03 2.28 39% 39% 142 

5-8 Years -0.23 0.07 -3.49 -0.24 0.07 -3.60 0.04 0.03 1.29 0.04 0.03 1.35 46% 47% 83 
 Appendix V-A 

Docket No. PA02-2-000 Price Manipulation in Western Markets V-A-6

Table V-A4. Validated vs. All Comparison: “After” Period 

All Transactions 

Gas Futures Estimates Spot Power Estimates R2

 

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) 

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) Hubs OLS IV Obs Time-to-Delivery 

Class 

Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat 

1-2 Years 0.73 0.12 6.10 0.61 0.13 4.64 0.03 0.05 0.67 0.05 0.05 1.05 78% 76% 91 

3-4 Years 0.76 0.19 3.97 0.87 0.27 3.26 0.38 0.08 4.83 0.37 0.08 4.46 80% 80% 45 MIDC/ 

COB 

5-8 Years 0.22 0.16 1.39 0.04 0.21 0.19 0.14 0.07 1.94 0.17 0.08 2.16 89% 89% 27 

1-2 Years 0.71 0.05 13.10 0.68 0.06 12.25 0.08 0.02 3.17 0.08 0.02 3.43 86% 86% 204 

NP 15 3-4 Years 0.72 0.11 6.87 0.65 0.11 5.71 0.02 0.02 0.90 0.03 0.02 1.17 68% 67% 145 

5-8 Years 0.38 0.11 3.31 0.28 0.12 2.41 0.02 0.03 0.70 0.03 0.03 0.96 53% 51% 80 

1-2 Years 0.28 0.18 1.63 0.28 0.18 1.60 0.10 0.06 1.74 0.10 0.06 1.74 20% 20% 197 

PV 3-4 Years 0.67 0.16 4.07 0.65 0.16 3.93 0.02 0.05 0.53 0.03 0.05 0.57 53% 53% 106 

5-8 Years -0.04 0.22 -0.17 -0.07 0.22 -0.33 0.13 0.06 2.30 0.13 0.06 2.27 34% 34% 56 

1-2 Years 0.70 0.05 13.86 0.72 0.06 12.99 0.07 0.02 3.26 0.06 0.02 3.04 68% 67% 395 

SP15 3-4 Years 0.70 0.09 7.69 0.69 0.09 7.28 0.09 0.02 3.82 0.09 0.02 3.88 76% 76% 177 

5-8 Years 0.78 0.16 4.76 0.79 0.16 4.79 0.09 0.04 2.29 0.09 0.04 2.28 69% 69% 63 

Tables V-A3 and V-A4 show that for most statistically significant estimates, the 

estimated parameters based only on validated transactions are close to parameter 

estimates based on all reported transactions, thus implying that the inclusion of 

unvalidated transaction data in the regression analysis has a minimal effect on our 

parameter estimates. 

Validated Transactions 

Gas Futures Estimates Spot Power Estimates R2

 

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) 

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) Hubs OLS IV Obs 

Time-toDelivery 

Class Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat 

1-2 Years 0.70 0.13 5.47 0.54 0.14 3.77 0.01 0.05 0.16 0.04 0.05 0.69 75% 72% 50 

3-4 Years 0.27 0.28 0.95 0.34 0.44 0.78 0.37 0.12 3.03 0.35 0.13 2.72 81% 81% 32 Mid-C/ 

COB 

5-8 Years 0.17 0.16 1.09 0.06 0.20 0.29 0.16 0.07 2.08 0.17 0.08 2.23 89% 89% 24 

1-2 Years 0.69 0.07 10.58 0.64 0.07 9.56 0.09 0.03 3.24 0.10 0.03 3.54 89% 88% 123 

NP15 3-4 Years 0.76 0.12 6.51 0.74 0.13 5.69 0.03 0.03 1.11 0.03 0.03 1.16 81% 81% 92 

5-8 Years 0.32 0.10 3.16 0.23 0.10 2.21 0.02 0.03 0.63 0.03 0.03 0.86 71% 70% 60 

1-2 Years 0.02 0.32 0.07 0.00 0.32 0.01 0.26 0.13 2.09 0.26 0.13 2.10 13% 13% 93 

PV 3-4 Years 1.01 0.17 6.21 1.00 0.17 6.13 0.00 0.04 -0.05 0.00 0.04 -0.03 73% 73% 65 

5-8 Years 0.00 0.25 0.00 -0.05 0.25 -0.18 0.12 0.06 1.88 0.11 0.06 1.84 28% 28% 46 

1-2 Years 0.63 0.08 7.81 0.62 0.09 7.00 0.14 0.04 3.91 0.15 0.04 3.85 65% 65% 196 

SP 15 3-4 Years 0.71 0.12 6.01 0.71 0.12 5.88 0.08 0.03 3.17 0.08 0.03 3.13 81% 81% 103 

5-8 Years 0.64 0.18 3.50 0.64 0.18 3.50 0.20 0.05 3.77 0.20 0.05 3.77 76% 76% 39 
 Appendix V-B 

Docket No. PA02-2-000 Price Manipulation in Western Markets V-B-1

Appendix V-B: Comparison of Forward Gas Curves 

Comparison of Forward Gas Curves 

Table V-B1. TFS Historical Forward Gas Prices ($/MMBtu) 

 Malin Southern California Border 

 Delivery Dates Delivery Dates 

Month 7/1/2001 7/1/2002 7/1/2003 7/1/2004 7/1/2001 7/1/2002 7/1/2003 7/1/2004 

Jan 01 7.15 5.58 4.70 n.a. 7.56 5.78 5.10 n.a. 

Feb 01 7.67 6.07 5.10 n.a. 8.83 6.50 5.47 n.a. 

Mar 01 8.34 6.20 4.86 n.a. 10.17 6.72 5.24 n.a. 

Apr 01 9.94 7.34 5.02 n.a. 13.72 8.40 5.32 n.a. 

May 01 7.32 5.84 4.66 n.a. 11.22 6.44 4.78 n.a. 

Jun 01 4.63 4.33 4.04 n.a. 6.91 4.56 4.06 n.a. 

Table V-B2. Williams’ Historical Forward Gas Prices ($/MMBtu) 

 Malin Southern California Border 

 Delivery Dates Delivery Dates 

Month 7/1/2001 7/1/2002 7/1/2003 7/1/2004 7/1/2001 7/1/2002 7/1/2003 7/1/2004 

Jan 01 8.18 6.36 4.32 4.19 8.18 6.36 5.46 5.04 

Feb 01 8.61 7.06 4.57 4.53 8.61 7.06 6.03 5.65 

Mar 01 9.54 6.45 4.87 4.76 9.99 6.67 5.82 5.59 

Apr 01 10.97 6.78 5.19 5.06 13.83 7.75 5.19 5.06 

May 01 7.73 5.52 4.66 4.79 11.80 6.01 4.66 4.79 

Jun 01 3.75 4.41 4.15 4.29 6.88 4.65 4.07 4.22 

Table V-B3. Enron’s Historical Forward Gas Prices ($/MMBtu) 

 Malin Southern California Border 

 Delivery Dates Delivery Dates 

Month 7/1/2001 7/1/2002 7/1/2003 7/1/2004 7/1/2001 7/1/2002 7/1/2003 7/1/2004 

Jan 01 7.73 5.89 4.42 4.06 8.18 6.29 5.18 4.68 

Feb 01 7.74 6.62 5.11 4.40 8.59 7.05 5.51 5.06 

Mar 01 8.44 6.20 4.84 4.48 10.06 6.70 5.24 5.06 

Apr 01 10.16 6.39 4.70 4.26 13.86 7.80 5.16 4.78 

May 01 7.80 5.38 4.11 4.08 11.75 6.07 4.61 4.56 

Jun 01 4.40 4.19 3.47 3.51 6.90 4.66 3.97 3.99 
 Appendix V-B 

Docket No. PA02-2-000 Price Manipulation in Western Markets V-B-2

Table V-B4. Morgan Stanley’s Historical Forward Gas Prices ($/MMBtu) 

 PG&E Citygate Southern California Border 

 Delivery Dates Delivery Dates 

Month 7/1/2001 7/1/2002 7/1/2003 7/1/2004 7/1/2001 7/1/2002 7/1/2003 7/1/2004 

Jan 01 8.06 6.30 5.51 4.90 7.99 6.24 5.45 4.84 

Feb 01 8.63 7.00 5.75 5.20 8.56 6.94 5.69 5.14 

Mar 01 9.05 6.41 5.39 5.16 10.08 6.55 5.34 5.09 

Apr 01 11.70 6.58 5.08 4.79 13.85 7.55 5.02 4.71 

May 01 9.79 5.57 4.67 4.71 11.79 5.85 4.47 4.50 

Jun 01 5.78 4.71 4.24 4.25 7.27 4.58 3.98 4.00 

TFS vs. Other Forward Gas Curves 

Table V-B5. TFS vs. Williams 

 Malin Southern California Border 

 Delivery Dates Delivery Dates 

Month 7/1/2001 7/1/2002 7/1/2003 7/1/2001 7/1/2002 7/1/2003 

Jan 01 14% 14% -8% 8% 10% 7% 

Feb 01 12% 16% -11% -3% 9% 10% 

Mar 01 14% 4% 0% -2% -1% 11% 

Apr 01 10% -8% 3% 1% -8% -3% 

May 01 6% -5% 0% 5% -7% -2% 

Jun 01 -19% 2% 3% 0% 2% 0% 

Table V-B6. TFS vs. Enron 

 Malin Southern California Border 

 Delivery Dates Delivery Dates 

Month 7/1/2001 7/1/2002 7/1/2003 7/1/2001 7/1/2002 7/1/2003 

Jan 01 8% 6% -6% 8% 9% 1% 

Feb 01 1% 9% 0% -3% 8% 1% 

Mar 01 1% 0% 0% -1% 0% 0% 

Apr 01 2% -13% -6% 1% -7% -3% 

May 01 7% -8% -12% 5% -6% -4% 

Jun 01 -5% -3% -14% 0% 2% -2% 
 Appendix V-B 

Docket No. PA02-2-000 Price Manipulation in Western Markets V-B-3

Table V-B7. TFS vs. Morgan Stanley 

 Southern California Border 

 Delivery Dates 

Month 7/1/2001 7/1/2002 7/1/2003 

Jan 01 6% 8% 7% 

Feb 01 -3% 7% 4% 

Mar 01 -1% -3% 2% 

Apr 01 1% -10% -6% 

May 01 5% -9% -6% 

Jun 01 5% 0% -2% 
 Appendix V-C 

Docket No. PA02-2-000 Price Manipulation in Western Markets V-C-1

Appendix V-C: Disaggregated Regressions 

The following tables summarize spot power and forward gas parameter estimates for 

various regression formulations. Each regression includes only on-peak transactions that 

were executed between January 1, 2000 and June 30, 2001 (“during period”) or between 

July 1, 2001 and March 31, 2002 (“after period”) for power deliveries at NP15, SP15, 

COB, PV, or Mid-C. All regressions use TFS’ historic natural gas basis and historic 

NYMEX forwards at Henry Hub. To address the potential simultaneity of the explanatory 

variables, we perform both the ordinary least squares (OLS) estimation and the 

instrumental variable (IV) estimation. 

Twelve Bin Regressions 

In this formulation we aggregate time-to-delivery class periods 1-2 years, 3-4 years, and 

5-8 years and the Mid-C/COB hubs. We then run a separate regression for each 

combination of aggregated hubs and time-to-delivery classes (i.e., 12 regressions). The 

results of these regressions are summarized in Tables V-C1 and V-C2. 

Table V-C1. Twelve Bin Regression for “During” Period 

Gas Futures Estimates Spot Power Estimates R2

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) 

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) Hubs OLS IV 

Time-toDelivery 

Class 

Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat 

Obs

1-2 Years 0.03 0.27 0.10 0.62 0.42 1.45 0.38 0.09 4.16 0.21 0.13 1.66 43% 43% 101

3-4 Years 0.52 0.16 3.15 0.26 0.22 1.21 0.13 0.04 3.12 0.19 0.05 3.58 79% 78% 62 Mid-C/ 

COB 

5-8 Years 0.40 0.09 4.43 0.63 0.16 3.84 0.00 0.03 -0.13 -0.01 0.03 -0.41 86% 83% 36 

1-2 Years 1.09 0.31 3.52 0.82 0.34 2.42 0.22 0.13 1.64 0.29 0.14 2.10 65% 62% 40 

NP15 3-4 Years 1.69 0.26 6.52 1.76 0.31 5.65 0.14 0.04 3.16 0.14 0.05 3.01 83% 83% 72 

5-8 Years -0.03 0.26 -0.12 -0.10 0.28 -0.38 0.06 0.05 1.33 0.06 0.05 1.20 63% 63% 24 

1-2 Years 0.09 0.19 0.49 0.02 0.19 0.09 0.38 0.06 6.58 0.40 0.06 6.90 49% 49% 221

PV 3-4 Years 0.42 0.14 3.00 0.46 0.14 3.26 0.09 0.04 2.37 0.08 0.04 2.14 50% 51% 122

5-8 Years 0.10 0.09 1.10 0.10 0.09 1.11 0.07 0.02 3.36 0.07 0.02 3.35 66% 66% 74 

1-2 Years 0.27 0.15 1.76 0.51 0.17 2.99 0.23 0.08 2.99 0.14 0.08 1.69 60% 60% 89 

SP15 3-4 Years 0.28 0.10 2.63 0.29 0.11 2.52 0.07 0.03 2.33 0.07 0.03 2.28 39% 39% 142

5-8 Years -0.23 0.07 -3.49 -0.24 0.07 -3.60 0.04 0.03 1.29 0.04 0.03 1.35 46% 47% 83 
 Appendix V-C 

Docket No. PA02-2-000 Price Manipulation in Western Markets V-C-2

Table V-C2. Twelve Bin Regression for “After” Period 

“Pool by Hub” Regressions 

In this formulation, we aggregate time-to-delivery class periods 1-2 years, 3-4 years, and 

5-8 years and aggregate all hubs. We run a separate regression for each aggregated timeto-delivery class. The results of these regressions are summarized in Tables V-C3 and VC4. 

Table V-C3. Pool by Hub Regression for “During” Period 

Gas Futures Estimates Spot Power Estimates R2

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) 

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) OLS IV 

Time-toDelivery 

Class 

Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat 

Obs

1-2 Years 0.29 0.08 3.57 0.46 0.12 3.96 0.33 0.03 9.80 0.27 0.04 6.34 50% 50% 451 

3-4 Years 0.31 0.06 5.17 0.34 0.07 4.95 0.12 0.02 6.54 0.11 0.02 5.73 52% 52% 398 

5-8 Years 0.04 0.04 0.82 (0.05) 0.05 (1.10) 0.05 0.01 3.36 0.06 0.01 4.18 51% 50% 217 

Table V-C4. Pool by Hub Regression for “After” Period 

Gas Futures Estimates Spot Power Estimates R2

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) 

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) Hubs OLS IV 

Time-toDelivery 

Class 

Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat 

Obs

1-2 Years 0.73 0.12 6.10 0.61 0.13 4.64 0.03 0.05 0.67 0.05 0.05 1.05 78% 76% 91 

3-4 Years 0.76 0.19 3.97 0.87 0.27 3.26 0.38 0.08 4.83 0.37 0.08 4.46 80% 80% 45 Mid-C/COB 

5-8 Years 0.22 0.16 1.39 0.04 0.21 0.19 0.14 0.07 1.94 0.17 0.08 2.16 89% 89% 27 

1-2 Years 0.71 0.05 13.10 0.68 0.06 12.25 0.08 0.02 3.17 0.08 0.02 3.43 86% 86% 204

3-4 Years 0.72 0.11 6.87 0.65 0.11 5.71 0.02 0.02 0.90 0.03 0.02 1.17 68% 67% 145 NP15 

5-8 Years 0.38 0.11 3.31 0.28 0.12 2.41 0.02 0.03 0.70 0.03 0.03 0.96 53% 51% 80 

1-2 Years 0.28 0.18 1.63 0.28 0.18 1.60 0.10 0.06 1.74 0.10 0.06 1.74 20% 20% 197

3-4 Years 0.67 0.16 4.07 0.65 0.16 3.93 0.02 0.05 0.53 0.03 0.05 0.57 53% 53% 106 PV 

5-8 Years -0.04 0.22 -0.17 -0.07 0.22 -0.33 0.13 0.06 2.30 0.13 0.06 2.27 34% 34% 56 

1-2 Years 0.70 0.05 13.86 0.72 0.06 12.99 0.07 0.02 3.26 0.06 0.02 3.04 68% 67% 395

3-4 Years 0.70 0.09 7.69 0.69 0.09 7.28 0.09 0.02 3.82 0.09 0.02 3.88 76% 76% 177 SP15 

5-8 Years 0.78 0.16 4.76 0.79 0.16 4.79 0.09 0.04 2.29 0.09 0.04 2.28 69% 69% 63 

Gas Futures Estimates Spot Power Estimates R2

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) 

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) OLS IV 

Time-toDelivery 

Class 

Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat 

Obs 

1-2 Years 0.66 0.04 16.74 0.60 0.05 12.08 0.12 0.02 7.15 0.13 0.02 7.41 58% 55% 887 

3-4 Years 0.72 0.05 15.03 0.60 0.07 8.34 0.12 0.02 7.12 0.14 0.02 7.35 70% 67% 473 

5-8 Years 0.46 0.06 7.23 0.18 0.10 1.77 0.15 0.02 6.83 0.17 0.02 7.22 58% 51% 226 
 Appendix V-C 

Docket No. PA02-2-000 Price Manipulation in Western Markets V-C-3

Pool by Hub Regressions With Additive and Spot Power Interacted Hub Dummies 

For each time-to-delivery class, we estimate regressions that include transactions for all 

hubs. We specify separate intercepts and spot power coefficients for each hub, but 

constrain the forward gas coefficient to be equal across hubs. Our regression equation is 

as follows: 

log( ) log( ) it it i it { i i it log( )}

i

FP c FG HubDummy e =+ + ∑ d b SP +

where i d and bi are the hub-specific intercepts and spot power coefficients, respectively. 

The results of these regressions are summarized in Tables V-C5 and V-C6. 

Table V-C5. Pool by Hub Regressions With Additive and Spot Power 

 Interacted Hub Dummies for “During” Period 

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) 

Hub-specific 

Interacted Dummy 

on Spot Power 

Time-toDelivery 

Class Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat 

1-2 Years 0.31 0.05 6.76 0.28 0.05 5.49 

Mid-C/COB 3-4 Years 0.17 0.03 5.31 0.16 0.03 5.11 

5-8 Years (0.02) 0.03 (0.56) (0.01) 0.03 (0.48) 

1-2 Years 0.42 0.10 4.17 0.39 0.10 3.75 

NP15 3-4 Years 0.21 0.04 5.83 0.21 0.04 5.78 

5-8 Years 0.07 0.04 1.73 0.07 0.04 1.75 

1-2 Years 0.35 0.04 8.56 0.32 0.05 7.07 

PV 3-4 Years 0.11 0.02 4.51 0.11 0.02 4.31 

5-8 Years 0.09 0.02 5.46 0.10 0.02 5.76 

1-2 Years 0.26 0.07 3.64 0.22 0.08 2.75 

SP15 3-4 Years 0.07 0.03 2.65 0.07 0.03 2.58 

5-8 Years 0.00 0.02 0.00 0.01 0.02 0.30 

Gas Futures Estimates R2

 

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) Obs 

Time-toDelivery 

Class 

Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat 

OLS IV 

1-2 Years 0.27 0.10 2.63 0.38 0.12 3.08 52% 52% 451 

3-4 Years 0.37 0.07 5.20 0.38 0.08 4.95 57% 56% 398 

5-8 Years (0.04) 0.04 (1.01) (0.08) 0.05 (1.79) 60% 60% 217 
 Appendix V-C 

Docket No. PA02-2-000 Price Manipulation in Western Markets V-C-4

Table V-C6. Pool by Hub Regressions With Additive and Spot Power 

Interacted Hub Dummies for “After” Period 

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) 

Hub-specific 

Interacted Dummy 

on Spot Power 

Time-toDelivery 

Class Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat 

1-2 Years 0.22 0.03 6.79 0.22 0.03 6.77 

Mid-C/COB 3-4 Years 0.21 0.03 6.98 0.21 0.03 7.02 

5-8 Years 0.22 0.03 8.60 0.23 0.03 8.75 

1-2 Years 0.11 0.03 3.52 0.11 0.03 3.50 

NP15 3-4 Years 0.01 0.02 0.49 0.01 0.02 0.62 

5-8 Years 0.04 0.03 1.28 0.05 0.03 1.61 

1-2 Years 0.08 0.02 3.54 0.08 0.02 3.54 

PV 3-4 Years 0.08 0.02 3.90 0.08 0.02 3.95 

5-8 Years 0.10 0.02 4.13 0.10 0.02 4.20 

1-2 Years 0.08 0.02 3.38 0.08 0.02 3.36 

SP15 3-4 Years 0.10 0.02 5.25 0.10 0.02 5.33 

5-8 Years 0.15 0.03 5.35 0.15 0.03 5.44 

Gas Futures Estimates R2

 

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) Obs 

Time-toDelivery 

Class 

Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat

OLS IV 

1-2 Years 0.58 0.05 12.42 0.57 0.05 11.74 62% 62% 887 

3-4 Years 0.67 0.06 11.01 0.64 0.07 9.86 76% 76% 473 

5-8 Years 0.34 0.07 4.51 0.25 0.08 3.08 70% 70% 226 

Pool by Hub Regressions With Spot Power Interacted Hub Dummies 

These regressions are identical to those in the previous section except that we exclude 

hub-specific intercepts. Therefore, the regression equation for each time-to-delivery class 

is as follows: 

log( ) log( ) log( ) * it it i i it it

i

FP a c FG b HubDummy SP e =+ + + ∑
 Appendix V-C 

Docket No. PA02-2-000 Price Manipulation in Western Markets V-C-5

The results of these regressions are summarized in Tables V-C7 and V-C8. 

Table V-C7. Pool by Hub Regressions With Spot Power 

 Interacted Hub Dummies for “During” Period 

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) 

Hub-specific 

Interacted Dummy 

on Spot Power 

Time-toDelivery Class Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat 

1-2 Years 0.32 0.04 8.44 0.28 0.04 6.37 

3-4 Years 0.14 0.02 7.33 0.14 0.02 7.17 Mid-C/ 

COB 

5-8 Years 0.05 0.01 3.43 0.05 0.01 3.86 

1-2 Years 0.35 0.04 9.00 0.31 0.05 6.78 

NP15 3-4 Years 0.12 0.02 5.87 0.12 0.02 5.72 

5-8 Years 0.06 0.02 3.82 0.07 0.02 4.30 

1-2 Years 0.34 0.04 9.47 0.30 0.04 7.30 

PV 3-4 Years 0.12 0.02 6.50 0.12 0.02 6.38 

5-8 Years 0.05 0.01 3.47 0.05 0.01 3.89 

1-2 Years 0.34 0.04 8.26 0.30 0.05 6.05 

SP15 3-4 Years 0.11 0.02 5.79 0.11 0.02 5.64 

5-8 Years 0.06 0.01 4.48 0.07 0.01 4.95 

Gas Futures Estimates R2 

OLS IV Obs 

Time-toDelivery 

Class Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat 

OLS IV 

1-2 Years 0.25 0.10 2.47 0.38 0.13 3.06 52% 52% 451 

3-4 Years 0.37 0.07 5.40 0.36 0.07 4.91 55% 55% 398 

5-8 Years (0.04) 0.05 (0.80) (0.08) 0.05 (1.77) 56% 56% 217 
 Appendix V-C 

Docket No. PA02-2-000 Price Manipulation in Western Markets V-C-6

Table V-C8. Pool by Hub Regressions With Spot Power Interacted 

Hub Dummies for “After” Period 

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) 

Hub-specific 

Interacted Dummy on 

Spot Power 

Time-toDelivery Class 

Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat 

1-2 Years 0.08 0.02 4.43 0.08 0.02 4.44 

Mid-C/COB 3-4 Years 0.07 0.02 4.02 0.07 0.02 4.03 

5-8 Years 0.13 0.02 5.93 0.13 0.02 6.04 

1-2 Years 0.10 0.02 5.44 0.10 0.02 5.45 

NP15 3-4 Years 0.09 0.02 5.48 0.10 0.02 5.46 

5-8 Years 0.15 0.02 7.15 0.16 0.02 7.29 

1-2 Years 0.10 0.02 5.91 0.10 0.02 5.92 

PV 3-4 Years 0.10 0.02 5.90 0.10 0.02 5.89 

5-8 Years 0.15 0.02 6.99 0.15 0.02 7.10 

1-2 Years 0.10 0.02 5.63 0.10 0.02 5.63 

SP15 3-4 Years 0.09 0.02 5.50 0.10 0.02 5.48 

5-8 Years 0.15 0.02 6.92 0.16 0.02 7.07 

Gas Futures Estimates R2 

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) Obs 

Time-toDelivery 

Class 

Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat 

OLS IV 

1-2 Years 0.59 0.05 12.81 0.59 0.05 12.01 61% 60% 887 

3-4 Years 0.65 0.06 10.26 0.64 0.07 9.21 74% 73% 473 

5-8 Years 0.30 0.08 3.69 0.23 0.09 2.58 63% 63% 226 
 Appendix V-C 

Docket No. PA02-2-000 Price Manipulation in Western Markets V-C-7

“Pool by Class” Regressions 

Here we aggregate the Mid-C and COB hubs and pool across all time-to-delivery classes. 

We run a separate regression for four aggregated hubs. The results of these regressions 

are summarized in Tables V-C9 and V-C10. 

Table V-C9. Pool by Class Regression for “During” Period 

Gas Futures Estimates Spot Power Estimates R2 

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) 

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) 

Hubs OLS IV Obs

Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat 

Mid-C/COB 0.62 0.15 4.19 0.89 0.21 4.29 0.13 0.04 3.04 0.07 0.05 1.29 38% 38% 199

NP15 1.35 0.16 8.41 1.23 0.17 7.14 0.12 0.05 2.54 0.13 0.05 2.67 73% 72% 136

PV 0.79 0.11 6.99 0.78 0.11 6.87 0.05 0.03 1.79 0.06 0.03 1.85 34% 34% 417

SP15 0.72 0.06 11.73 0.47 0.07 6.35 (0.04) 0.03 (1.27) 0.00 0.03 (0.07) 41% 27% 314

Table V-C10. Pool by Class Regression for “After” Period 

“Pool by Class and Hub” Regressions 

We run a single regression by pooling across all time-to-delivery classes and hubs. The 

results of these regressions are summarized in Table V-C11. 

Table V-C11. Pool by Class and Hub Regression Results 

Gas Futures Estimates Spot Power Estimates R2

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) 

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) Period OLS IV 

Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat 

Obs

"During" 0.61 0.05 13.17 0.63 0.06 11.19 0.07 0.02 4.48 0.07 0.02 3.83 36% 34% 1066

"After" 0.57 0.02 23.11 0.46 0.03 15.02 0.14 0.01 12.32 0.15 0.01 13.17 60% 57% 1586

Gas Futures Estimates Spot Power Estimates R2 

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) 

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) OLS IV Obs Hubs 

Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat 

Mid-C/COB 0.54 0.08 7.09 0.44 0.09 5.04 0.13 0.03 3.92 0.14 0.03 4.13 77% 76% 163

NP15 0.68 0.04 18.58 0.64 0.04 17.15 0.04 0.01 2.54 0.04 0.01 2.91 77% 76% 429

PV 0.27 0.09 2.89 0.25 0.09 2.67 0.09 0.03 2.74 0.09 0.03 2.75 27% 27% 359

SP15 0.46 0.03 13.64 0.47 0.04 13.24 0.12 0.01 8.54 0.12 0.01 8.41 66% 66% 635
 Appendix V-C 

Docket No. PA02-2-000 Price Manipulation in Western Markets V-C-8

 “No Aggregation” Regression 

We run a separate regression for each disaggregated time-to-delivery class and hub. As 

illustrated in Tables V-C12 and V-C13, the results of these regressions are somewhat 

irregular due to an insignificant number of transactions in many time-to-delivery class 

and hub bins. 

Table V-C12. No Aggregation Regression for “During” Period 

Gas Futures Estimates Spot Power Estimates R2

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) 

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) Hubs OLS IV 

Time-toDelivery 

Class 

Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat 

Obs

1 year (7.01) 0.45 (15.62) (6.63) 0.53 (12.57) (0.65) 0.14 (4.74) (0.75) 0.16 (4.76) 100% 100% 9 

2 years 2.23 0.28 7.86 2.17 0.30 7.19 (0.24) 0.10 (2.33) (0.22) 0.11 (2.04) 93% 92% 28 

3 years 0.85 0.17 4.87 0.60 0.21 2.81 0.06 0.05 1.27 0.13 0.06 2.16 98% 98% 24 

4 years 3.88 0.14 28.62 3.88 0.14 28.62 (0.39) 0.04 (9.63) (0.39) 0.04 (9.63) 100% 100% 4 

5 years 0.00 . . 0.00 . . 0.68 . . 0.68 . . 100% 100% 2 

COB 

7 years 0.00 . . 0.00 . . 0.63 . . 0.63 . . 100% 100% 3 

1 year (18.86) 18.44 (1.02) 109.08 314.38 0.35 1.51 5.86 0.26 (39.15) 99.92 (0.39) 100% 94% 8 

2 years 0.29 0.14 2.05 1.58 0.55 2.90 0.47 0.04 11.44 0.18 0.13 1.39 91% 80% 56 

3 years 0.46 0.39 1.17 0.61 0.40 1.52 0.15 0.06 2.24 0.13 0.07 2.03 68% 68% 22 

4 years 2.09 0.09 23.72 1.99 0.11 17.51 0.04 0.08 0.55 0.06 0.09 0.63 100% 100% 12 

5 years 0.62 0.19 3.25 0.62 0.19 3.25 0.00 0.04 (0.03) 0.00 0.04 (0.03) 87% 87% 26 

Mid-C 

6 years 0.00 . . 0.00 . . 0.68 0.00 737.17 0.68 0.00 737.17 . . 5 

1 year 2.33 . . 2.33 . . (0.04) . . (0.04) . . 100% 100% 4 

2 years 1.24 0.38 3.27 0.82 0.42 1.97 0.17 0.16 1.07 0.29 0.17 1.73 64% 60% 36 

3 years 2.21 0.33 6.77 2.29 0.39 5.91 0.12 0.05 2.61 0.12 0.05 2.46 82% 81% 56 

4 Years 0.91 0.62 1.48 1.20 0.99 1.21 0.24 0.17 1.45 0.25 0.17 1.47 92% 92% 16 

5 Years (0.65) 0.13 (5.07) (0.61) 0.13 (4.71) 0.07 0.03 2.43 0.08 0.03 2.58 93% 93% 15 

6 Years 2.52 . . 2.52 . . 0.00 . . 0.00 . . 100% 100% 3 

NP15 

7 Years 0.52 0.00 . 0.52 0.00 . (0.04) 0.00 . (0.04) 0.00 . 100% 100% 6 

1 Year (0.02) 0.90 (0.03) (0.02) 0.90 (0.03) 0.12 0.18 0.67 0.12 0.18 0.67 39% 39% 48 

2 Years 1.15 0.14 8.34 1.10 0.14 7.96 0.19 0.04 4.71 0.20 0.04 4.99 84% 84% 173 

3 Years 0.46 0.22 2.09 0.58 0.22 2.59 0.09 0.06 1.53 0.06 0.06 1.11 57% 58% 77 

4 Years 0.19 0.15 1.25 0.19 0.15 1.28 0.11 0.04 2.44 0.10 0.04 2.41 50% 50% 45 

5 Years 0.22 0.16 1.38 0.22 0.16 1.39 0.05 0.04 1.30 0.05 0.04 1.29 62% 62% 51 

6 Years 0.03 0.06 0.54 0.03 0.06 0.53 0.10 0.02 6.13 0.10 0.02 6.13 93% 93% 16 

PV 

7 Years 0.79 0.56 1.40 0.79 0.56 1.40 (0.22) 0.22 (0.99) (0.22) 0.22 (0.99) 87% 87% 7 

1 Year (0.69) 0.38 (1.82) (0.63) 0.75 (0.83) 0.34 0.19 1.82 0.33 0.21 1.62 78% 78% 31 

2 Years 0.72 0.12 6.21 0.84 0.13 6.55 0.17 0.05 3.30 0.13 0.06 2.28 87% 87% 58 

3 Years 0.22 0.14 1.59 0.27 0.14 1.93 0.07 0.04 1.58 0.06 0.04 1.40 32% 33% 96 

4 Years 0.88 0.20 4.48 0.89 0.21 4.21 0.14 0.04 3.84 0.14 0.04 3.83 73% 73% 46 

5 Years (0.26) 0.06 (4.38) (0.27) 0.06 (4.48) 0.04 0.03 1.51 0.05 0.03 1.58 64% 65% 61 

6 Years (0.10) 0.83 (0.11) (0.44) 0.85 (0.52) 0.16 0.11 1.47 0.18 0.11 1.59 35% 36% 15 

SP15 

7 Years 0.76 0.57 1.34 0.76 0.57 1.34 (0.05) 0.07 (0.84) (0.05) 0.07 (0.84) 99% 99% 7 
 Appendix V-C 

Docket No. PA02-2-000 Price Manipulation in Western Markets V-C-9

Table V-C13. No Aggregation Regression for “After” Period 

 

Gas Futures Estimates Spot Power Estimates R2

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) 

Ordinary Least 

Squares (OLS) 

With Instrumental 

Variables (IV) Hubs OLS IV 

Time-toDelivery 

Class 

Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat Coeff. Std. Err. t-stat 

Obs

1 Year (0.48) 0.67 (0.71) (0.48) 0.67 (0.71) 1.19 0.22 5.51 1.19 0.22 5.51 99% 99% 4 

2 Years 1.84 0.23 7.98 1.84 0.23 7.98 (0.50) 0.07 (7.05) (0.50) 0.07 (7.05) 100% 100% 6 

3 Years 0.45 0.04 10.09 0.45 0.04 10.09 0.79 0.02 49.53 0.79 0.02 49.53 100% 100% 5 

6 Years 0.00 . . 0.00 . . 1.19 0.00 4,222.98 1.19 0.00 4,222.98 . . 3 

COB 

7 Years 0.00 . . 0.00 . . 0.88 . . 0.88 . . . . 1 

1 Year (0.38) 0.52 (0.73) (0.39) 0.52 (0.74) (0.21) 0.10 (2.08) (0.21) 0.10 (2.08) 95% 95% 8 

2 Years 0.93 0.23 4.00 0.67 0.24 2.76 0.03 0.07 0.48 0.07 0.07 1.06 79% 78% 73 

3 Years 0.33 0.41 0.80 0.43 0.42 1.03 0.35 0.26 1.36 0.36 0.26 1.38 90% 90% 18 

4 Years 1.15 0.37 3.14 1.13 0.38 2.98 0.11 0.19 0.57 0.11 0.19 0.60 68% 68% 22 

5 Years (0.11) 0.40 (0.27) (0.11) 0.40 (0.27) 0.48 0.25 1.93 0.48 0.25 1.93 92% 92% 15 

6 Years 0.00 . . 0.00 . . 1.16 . . 1.16 . . . . 1 

Mid-C 

7 Years 3.56 1.33 2.68 3.56 1.33 2.69 0.87 0.32 2.73 0.87 0.32 2.73 97% 97% 7 

1 Year 0.36 0.17 2.08 0.36 0.18 2.04 (0.01) 0.08 (0.07) (0.01) 0.08 (0.07) 86% 86% 18 

2 Years 0.88 0.07 12.32 0.81 0.07 11.14 0.05 0.03 2.07 0.06 0.03 2.55 88% 88% 186 

3 Years 0.81 0.11 7.47 0.84 0.12 6.92 0.02 0.02 0.93 0.02 0.02 0.78 83% 83% 83 

4 Years 0.79 0.22 3.53 0.60 0.24 2.52 0.00 0.06 0.00 0.02 0.06 0.37 52% 49% 62 

5 Years 0.39 0.16 2.48 0.28 0.16 1.76 0.00 0.04 0.06 0.02 0.04 0.40 73% 73% 42 

6 Years 0.18 0.08 2.26 0.19 0.08 2.24 (0.07) 0.01 (4.59) (0.07) 0.01 (4.59) 95% 95% 13 

NP15 

7 Years (0.21) 0.36 (0.59) (0.29) 0.36 (0.80) 0.01 0.17 0.09 0.01 0.17 0.07 29% 30% 25 

1 Year 0.39 6.38 0.06 (1.35) 6.58 (0.20) (0.56) 1.36 (0.41) (0.32) 1.38 (0.23) 4% 4% 15 

2 Years 0.78 0.09 8.32 0.77 0.09 8.28 0.06 0.03 2.20 0.06 0.03 2.21 66% 66% 182 

3 Years 1.07 0.31 3.46 1.00 0.31 3.20 (0.01) 0.06 (0.10) 0.00 0.06 (0.01) 54% 54% 55 

4 Years 0.52 0.23 2.24 0.52 0.23 2.21 0.04 0.08 0.56 0.04 0.08 0.57 57% 57% 51 

5 Years 0.21 0.39 0.56 0.22 0.39 0.56 0.14 0.08 1.66 0.14 0.08 1.66 36% 36% 26 

6 Years 0.68 0.48 1.41 0.67 0.48 1.41 0.00 0.18 0.01 0.00 0.18 0.01 98% 98% 11 

PV 

7 Years (0.17) 0.44 (0.39) (0.32) 0.45 (0.72) 0.02 0.12 0.19 0.04 0.12 0.33 55% 55% 19 

1 Year 0.76 0.52 1.46 0.29 0.66 0.44 0.18 0.20 0.92 0.32 0.23 1.38 48% 45% 27 

2 Years 0.70 0.04 16.20 0.79 0.05 16.66 0.04 0.02 2.82 0.03 0.02 1.63 81% 81% 368 

3 Years 0.74 0.12 6.13 0.72 0.12 5.81 0.08 0.03 2.63 0.08 0.03 2.68 76% 76% 135 

4 Years 0.50 0.19 2.68 0.51 0.19 2.75 0.12 0.04 3.12 0.12 0.04 3.08 77% 77% 42 

5 Years 0.71 0.27 2.61 0.71 0.27 2.61 0.07 0.06 1.15 0.07 0.06 1.15 68% 68% 45 

6 Years 1.30 1.17 1.11 1.30 1.17 1.11 0.16 0.08 1.96 0.16 0.08 1.96 64% 64% 11 

SP15 

7 Years (0.58) 0.12 (4.96) (0.58) 0.12 (4.96) 0.38 0.03 10.91 0.38 0.03 10.91 99% 99% 7 
 Appendix V-D 

Docket No. PA02-2-000 Price Manipulation in Western Markets V-D-1

Appendix V-D: Serial Correlation 

Our statistical model attempts to capture the main determinants of forward power prices. 

Inference based on standard OLS or IV coefficient estimates and standard errors assumes 

that there is no systematic variation in the portion of the dependent variable, in this case 

the price of forward power, that is not explained by the statistical model (i.e., the error). 

Serial correlation occurs when the errors in the estimates are not independent. In the 

presence of serial correlation, standard errors from conventional OLS and IV estimation 

tend to be understated and, therefore, claims of statistical significance of model 

coefficients tend to be overstated.1

 

To test the sensitivity of our regression results to the potential presence of serial 

correlation, we re-estimated one model specification using techniques that produce 

standard errors that explicitly account for the presence of serial correlation. Because our 

data are organized as an unbalanced panel (i.e., we have contracts signed at irregularly 

spaced points in time for different delivery periods and locations), correcting for serial 

correlation could be computationally intensive. We have chosen a method that requires 

minimal amounts of computation but requires some aggregation of the underlying data. 

We perform a panel version of Prais-Winsten estimation2

 and treat each combination of 

hub and time-to-delivery as a subpanel.3

 Within each subpanel, multiple contracts signed 

on the same day are averaged. The Prais-Winsten estimation is performed on these 

aggregated data. We constrain the extent of serial correlation to be equal across 

subpanels. The results are shown in Table V-D1 below. The table also shows OLS results 

on the aggregated data for comparison with our OLS results on the disaggregated data.4

 

1

See William Greene, Econometric Analysis, 4th ed., Chapter 13, for a description of how the presence of 

serial correlation affects statistical inference. 

2

See William Greene, Econometric Analysis, 4th ed., p. 546. 3

Our estimation is performed using Stata’s “xtpsce” command. See the Stata, version 7 manuals for the 

details of this command.

4

The OLS parameter estimates for the disaggregated data match the estimates in Table V-3, but the 

standard errors are slightly different. The parameter estimates in Table V-D1 are the result of a single 

stacked regression rather than four separate hub-specific regressions. In this particular stacked regression, 

we constrain our estimate of the error variance to be equal across hubs. This constraint affects estimated 

standard errors but not parameter estimates. 
 Appendix V-D 

Docket No. PA02-2-000 Price Manipulation in Western Markets V-D-2

Table V-D1. Prais-Winsten Estimates of the Spot Power Coefficient 

Coefficient on log spot power 

Disaggregated Data Aggregated Data 

OLS (stacked) OLS (stacked) Prais-Winsten 

Hubs 

Time-toDelivery 

Class 

Coef. Std. Err. Coef. Std. Err. Coef. Std. Err. 

1 Year 0.375 0.053 0.364 0.061 0.422 0.056 

Mid-C/ COB 2 Years 0.135 0.076 0.163 0.088 0.162 0.080 

3 Years -0.004 0.131 -0.016 0.134 -0.018 0.123 

1 Year 0.219 0.129 0.227 0.160 0.201 0.141 

NP15 2 Years 0.141 0.091 0.112 0.124 0.104 0.113 

3 Years 0.063 0.132 0.057 0.160 0.059 0.142 

1 Year 0.383 0.045 0.314 0.058 0.246 0.053 

PV 2 Years 0.088 0.045 0.079 0.057 0.100 0.051 

3 Years 0.070 0.059 0.066 0.079 0.064 0.074 

1 Year 0.232 0.066 0.207 0.074 0.225 0.070 

SP15 2 Years 0.072 0.044 0.017 0.058 0.004 0.055 

3 Years 0.037 0.065 0.043 0.076 0.044 0.069 

N 1066 598 598 

rho 0.433 

Neither aggregation nor controlling for serial correlation produces qualitatively different 

results. That is, the coefficients do not differ between the OLS disaggregated case and the 

OLS aggregated case, nor between the OLS aggregated case and the Prais-Winsten case. 

The standard errors in the OLS aggregated case and the Prais-Winsten case are also 

similar. This last result shows that serial correlation does not affect the precision of our 

estimates. In part, this is because the estimated degree of serial correlation, labeled “rho” 

in Table V-D1, is modest. In addition, there are significant gaps in the data. Successive 

transactions with the same delivery location and time to delivery may be several days 

apart. Even if serial correlation is present, if trades are spaced far enough apart in time, it 

may not matter.5

 

5

Serial correlation is a more serious issue for similar analyses based on daily index prices. See Harvey and 

Hogan, op. cit., note 2. 
Appendix IX-A

Docket No. PA02-2-000 Price Manipulation in Western Markets IX-A-1

Appendix IX-A: A Detailed Description of 

Trader 1’s Trading Positions and Profits for 

the June 14, 2001 Market Test 

This appendix describes trading of NYMEX look-alike swaps on EOL 

on June 14, 2001 by one trader. As described in detail in Chapter III, 

one of the most common OTC derivative products is known as the 

OTC swap or the NYMEX look-alike swap. This swap derives its 

value from the price of the NYMEX natural gas futures contract. 

Henry Hub physical transactions strongly correlate with the NYMEX 

futures and the related OTC NYMEX look-alike swaps because the 

NYMEX futures directly settle based on the Henry Hub physical 

delivery price. 

Following the run-up in prices in the next-day physical market from 

10:12 a.m. through 10:35 a.m., trader 1 of the Central desk entered 

short transactions in July delivery OTC swaps through four sales of 

15,000 MMBtu swaps at 4.095, 4.09, 4.085, and 4.09, respectively 

(where the four average $4.09).1

 The total volume amounted to 60,000 

MMBtu in July delivery OTC swaps. That is, the trader promised to 

sell 60,000 MMBtu of gas every day for the next month (July) at an 

average price of $4.09/MMBtu. If the NYMEX price for the July gas 

on a given day in June is more that $4.09, then the trader has incurred 

losses for that day because he is selling gas (whether he actually has 

the gas or needs to buy it) at a price below the market value. 

Conversely, if the price is below $4.09, then his position is profitable 

because he is selling gas for more than the market value. 

 

1

Data reflect that the Enron trader was net short OTC swaps prior to the beginning of 

the day. However, because the market first rose and then fell back to the approximate 

opening price, Staff only allocated the financial trades that occurred during the 

physical manipulation as vehicles potentially purchased to profit by the 

manipulation. 

Recall that this manipulation involved first selling slowly into the market and then 

repurchasing quickly. The strategy did not involve additional downward pressure in 

the physical market at the end of the manipulation as was displayed in the July 19 

manipulation. In that manipulation, Staff allocated the opening short position as a 

vehicle to profit from the manipulation due to Enron’s apparent intent to push the 

market down further. The data reflected this intent where they showed Enron was a 

net seller of Henry Hub next-day physical gas for the day. This was also supported 

by depositional testimony. 
Appendix IX-A

Docket No. PA02-2-000 Price Manipulation in Western Markets IX-A-2

These swaps have a term of 31 days and the quoted volume is a daily 

volume; therefore, 60,000 multiplied by 31 days yields an intraday 

short position of 1,860,000 MMBtu. Trader 1 then increased the short 

position by the additional sale of another 15,000 MMBtu/d (for a total 

of 465,000 MMBtu) at the price of $4.045/MMBtu at 11:24 a.m., 

resulting in a total increase of his intraday short position to 75,000 

MMBtu/d (for a total of 2,325,000 MMBtu) and an average sell price 

of $4.081. In essence, the trader has promised to sell 75,000 MMBtu 

of gas for every day of July at an average price of $4.081. 

Between 2:19 and 2:20 p.m., after the market test ceased, trader 1 

reduced his net short position by buying 25,000 MMBtu/d at $4.05. 

Here, the trader has promised to purchase 25,000 MMBtu of gas for 

each day in July at a price of $4.05. If the NYMEX price for July gas 

on a given day in June is above $4.05, the trader earns a profit because 

he is buying gas below market value. If the price is below $4.05, he is 

incurring a loss because he is buying gas above the market price. This 

purchase is used to meet and close out 25,000 MMBtu of his promise 

to sell. Since the trader bought at $.031 less than his obligation to sell, 

he generates a profit of $24,025.2

 

Trader 1 then further reduced his short position by 30,000 MMBtu/d. 

He bought the 30,000 MMBtu/d at an average price of $4.0883, 

generating a loss of $6,820 on this portion of his position or a net gain 

of only $17,205. He is effectively buying the gas at $4.0883 for every 

day of July to fulfill his promise to sell the gas at $4.081, generating a 

loss of $.0073/MMBtu for each of the 31 days in July. 

Trader 1 retained the remaining 20,000 MMBtu/d of his short position 

until the end of trading, when the market closed at $4.02. This 

generated additional profits of $37,820. He now has a promise to sell 

20,000 MMBtu of gas for each day of July at a price of $4.081 and can 

meet that obligation by purchasing gas at a market value of $4.02, 

generating a profit of $37,820. 

Trader 1’s total profit arising from the market test amounted to 

$55,025. 

 

2

Trader 1 sold at an average price of $4.081 and bought at an average price of $4.05, 

yielding a profit of 3.1 cents/MMBtu ($.031 multiplied by 25,000 MMBtu/d and then 

multiplied by 31 days in the contract yields a profit of $24,025).