The ZoneTraderPro AutoTrader New User Manual
Contents
1. 56 3 56 3 5 40 0 0 of 56 3 Jan 23 Jul 23 Aug 13 Sep 23 Oct 16 E amp OpenCndl_15 gt 0 OL 332798 3327 9 2 63 0 0 569 62 4 Jan 08 Jan 13 Feb 03 Feb 05 Feb 13 Mar 16 Gap amp OpenCndl_15 lt 0 0 56 3 56 3 5 40 0 0 of 56 3 Jan 23 Jul 23 Aug 13 Sep 235 Oct 16 Gap lt 0 amp OpenCndl_15 gt 0 0 491 6 491 6 3 J33 0 0 49 53 1 Feb 11 Feb 24 Jun 11 Gap gt 0 amp OpenCndl_15 lt 0 0 49499 4949 9 33 66 7 0 0 739 62 5 Jan 09 Jan 15 Jan 20 Jan 22 Jan 26 Feb 06 F Gap amp OpenCndl_15 lt 0 and OpenCndl_30 gt 0 0 0 0 0 0 0 0 0 0 Gap amp OpenCndl_30 gt 0 O 80124 5012 4 31 67 7 0 0 614 64 5 Jan 08 Jan 13 Feb 03 Feb 05 Feb 12 Feb 13 0 56 3 56 3 5 40 0 0 of 56 3 Jan 23 Jul 23 Aug 13 Sep 23 Oct 16 Gap amp OpenCndl_30 lt 0 The statistics in the following picture are from a combined chart of red green and yellow days The highlighted green cells are the green days yellow days and red days respectively A m S E 1 Stat Typ LngProf oshrtProf TotProf oo Open gt PrevDayvAH 9346 6 3284 6 12631 2 i Open gt PrevDayVAH and BD 5034 Bo 5027 2 Open PrevDay iAH and SD 1012 5 970 6 1583 1 i Qpen gt PrevDayWAH and SSC 9 3300 1 2320 6 5620 9 Qpoen gt PrevDaywAH and Gap 8545 6 3537 0 120867 6 Qpen gt PrevDayWAH amp Gapel 4825 2 1391 6 6214 8 Open in PrevDayalue 5068 1 101171 1 152739 2 o Open in PrevDayW alue and E ral 3506 4 4539 4 a Open in PrevOayValue and 3222 2 25 70 5000 2 ae Open in PrevDayValue and 1114 9 afit 7 4099 6 oF 082. 0 0 0 0 0 0 0 2 gt 2 lt 4 280 3 562 6 202 3 9 55 6 83 59 114 55 3 Feb 26 Mar 02 Mar 09 Apr 26 May 16 May 26 Jul 3 gt 4 lt 6 2947 6 3802 6749 6 13 64 6 236 66 9 220 67 3 Jan O Feb 04 Feb 16 Mar 11 Mar 2 Apr 02 Apr 4 gt 6 lt 6 1738 6 490 1248 6 7 42 9 129 46 6 150 60 Mar 23 Apr O May 2 7 Jul 08 Aug 26 Sep 11 Sep 5 gt 6 lt 10 207 4 518 8 311 4 3 66 7 61 SS 68 67 6 Apr O9 May 0 May 13 6 gt 10 501 920 3 1421 3 4 75 110 60 9 108 64 6 Jan 21 Jan 30 Mar 12 Jun 16 7 gt 2 lt 0 0 0 0 0 0 0 0 0 0 B gt 4 lt 2 32 1 44 1 12 4 50 31 61 3 24 58 3 Feb 23 Feb 25 Jun 19 Jun 23 9 gt 6 lt 4 1253 3345 4 4596 4 15 80 205 63 4 244 67 2 Feb 17 Feb 2 Mar 03 Mar 17 Mar 19 Apr 22 Apr 0 gt 6 lt 6 700 7 elia 30 6 5 40 123 54 5 116 62 7 Jan 06 May 20 Jun 26 Jul 24 Aug 03 1 gt 10 lt 6 633 4 813 4 1701 8 5 80 99 61 6 99 63 6 Jun 02 Jun 25 Jun 30 Jul 30 Aug 06 2 lt 10 2679 5 887 5 3567 f 71 4 245 66 5 250 61 2 Jan 12 Feb 02 Apr O1 May 06 Jun 05 Aug 26 Sep a Here we are looking specifically at short trades on a yellow day and the condition of the gap and opening candle and can see that based on the history we would like a gap in opening 30 minute candle to be positive and not negative Stat Typ 7 LngProf ShrtProf _ TotProf DTrdCnt DWin LTrdCnt LWin STrdCnt SWin Trd Dates i Gap OpenCndl_15 OpenCndl_30 gt 0 0 3414 3414 29 64 0 0 540 63 Jan 08 Jan 13 Feb 03 Feb 05 Feb 15 Mar 16 Gap OpenCndl_15 OpenCndl_30 lt 0 0
3. 177 3 490 7 0 270 2 30 9 402 9 0 232 5 270 5 422 5 n 24m 7 1no 7 a7 7 Now go back and review Sheet1 Use NinjaTrader to pull up those specific charts You can also find out if a news event during the trading day caused these losses Review the overnight data on these days This is not the picture that you want to see from an 0830 news event BES 4 Min 3 6 2015 esseer v amrik Z to Ke he E ZigZag_ZTPCES 4 Min 1 25 8 5 True False ZoneTraderPro AMACD 5 20 0 001 0 001 FRR cen L015 NinjaTrader LLC i y 19 00 EUR Div k I Tyo Vr Thy i uth ES Mar 06 Gap 7 75 OvernightRng 17 50 15mRng 5 50 15mOpenCndl 3 00 ValuePostn 8 50 21 00 2200 23 00 36 01 00 02 00 0200 D lex ree 2088 00 2085 00 2084 00 2082 00 2080 00 2078 00 2076 00 2074 00 2072 00 2070 00 2068 00 2065 00 2064 00 2062 00 2054 00 E 07 00 08 00 09 00 10 00 11 00 12 00 13 00 14 00 Disclaimer Hypothetical performance results have many inherent limitations some of which are described below No representation is being made that any account will or is likely to achieve profits or losses similar to those shown In fact there are frequently sharp differences between hypothetical performance results and the actual results subsequently achieved by any particular trading program One of the limitations of hypothetical performance results is that they are generally prepared with the benefit of hindsi
4. OpensPrevDayVAL 2264 1334 6 929 4 i Open lt PrevDayVAL and BO 2550 1739 1 610 4 OpensPreDay YAL and S0 159 3 851 1 1010 4 a Qpen lt PrevDayVAL and SSC F33 1255 6 1526 9 qo We Now that you have a basic understanding of what your trading plan is going to be it is time to begin testing and sending those results to ZoneTraderPro to data mine the results There are 3 testing parameters that will make or break this system Those parameters are 1 Your stop loss strategy 2 The quantity of contracts traded and their positions 3 The beginning and ending of the trading day and the times you will not trade It would be logical to look at the trading times 1 After you ve looked at and tested the trading times the next logical parameter would be the quantity and contracts traded and from what position Why is this important The historical data shows that on a green day it is twice as profitable to trade long then it is short On a yellow day it is twice as profitable to trade short than it is to trade long The question you have to answer for yourself is whether or not you use leverage when it is not statistically favored Looking at those statistics would you place your leverage trading the same number of contracts long and short on a Green day You ask yourself the same question in reverse for a yellow day trading short One area to study is trading long on a yellow day and short on a Green day If you re going to make that trade
5. what position do you use Here we have the analysis trading long on a yellow day You get more trades and have a higher winning percentage at position 2 however it is more profitable to trade from position 1 in terms of just dollars because it has better risk reward J Entry Postn Cum Prot Trade Cnt wiin Yo Trade Long Prot Long Cnt Long Win Yo Lyng b Trade Postnt 0 0 0 0 2 Pastnz eg 5 1275 ad 6 95 3119 3 p23 57 8 5 01 3 Fostna DESEN 1442 65 3 5 5 2739 9 p99 54 5 3 91 1 Postn4 0 0 0 0 3 Total 168637 2 And finally once those questions have been answered you need to conduct testing on your stop loss strategy You will likely have a different number for trading long then you have for trading short on a Green day There are 2 reasons 1 you may have a different number of contracts The 2 reason is because you are more likely to take a loss from a short trade Now that you have actual tests based on parameters you are likely to use go to Sheet2 and look at the intraday loss figures The hardest decision you can make is choosing a value here because you will see days that had a loss early in the day but had less loss by the end of the day I M Wy Intr Final S Intra Day Proft Max 5 Intra Day Prof Max 5 Intra Day Loss 0 1512 1 103 4 1512 1 0 D27 30 9 889 6 0 645 2 337 6 750 9 0 F23 105 7 FAES 0 174 7 gz 574 8 0 157 8 565 9 071 5 0 465 8 30 9 09749 0 214 5 104 7 535 0 50 7 af 2 4 515 3 0 406 6
6. 015 0 9 25 163940 575 0 25 1 25 SD 0 4627 22 16 439 9 14 5 5 2015 0 75 6 25 121610 9 75 7 25 9 5 BD 0 2002 22 13 591 214 9 14 528 2015 15 75 255 371066 6 75 4 575 SD D 221 3 32 18 56 2 637 5 33 5 29 2016 45 10 75 171164 55 4 25 3 25 SSD 0 2303 18 12 0667 1715 23 15 652 5 18 2015 1 75 11 5 192479 4 25 2 75 1 SSD 0 3499 11 5 45 5 101 3 18 11 614 5 11 2015 2 525 132243 55 0 1 25 BD 0 7192 13 3 2331 213 7 7 5 The sheet above and below is from a test based on a yellow day which is going to do better with its short trades This sheet contains some important information concerning the overnight gap the overnight range the overnight volume the opening 15 minute range and candle bar and the 30 minute candle bar This information is important because it can help you determine volatility from a historical point of view to compare to real time The column Value Position is how we determine the type of day it is If it is Green day this column will have a positive value If it is a Yellow day this column will have a O value Ifitisa Red day this column will have a negative value Next you can see the long profit the number of trades the number of winning trades and the winning percentage based upon long and short trades Further to the right are 6 columns which tell you what the final profit was your highest profit during the day and your maximum loss during the day broken down between long and short trades These numbers are based on 2
7. 525 6 ala 27 66 BO ri 24 04 1154 9 59 29 61 30 10 25 446 BU Yds 417 3 20 14 9 20 7 J2 0 9 11 10 30 1216 6 Bo 17 92 019 7 42 19 52 399 1 26 15 35 14 10 35 bad 67 Ga 1261 7 ae 34 1 2f aU 20 9 ig 10 40 313 ri 4 4 103 1 a4 3 03 209 9 J6 5 83 3 10 45 soy fal 5 54 212 5 43 6 45 174 2 ae 44 15 10 50 1299 5 ro 18 56 29 4 16 1 54 1325 9 54 24 51 a6 10 55 121 1 54 2 24 148 7 16 5 26 27 6 J6 Of if 11 00 1093 8 Be 19 19 517 9 51 16 71 575 9 26 22 15 j5 11 05 133 6 r 1 58 fag 2 ae 20 25 515 6 a4 18 11 Ete 11 10 25 5 ale 0 46 003 2 23 34 92 D20 r az 2a il 11 15 3437 ot 6 03 1105 4 41 35 566 1445 1 26 Sofa 7 11 20 453 5 ai 5 06 417 4 39 10 7 BE 1 z 5 15 2 11 25 1753 9 54 32 40 bes 0 AUF 7 1130 4 24 47 12 oa 11 30 1560 7 Bz 35 76 1611 6 26 61 98 249 1 26 5 55 a 11 56 13272 45 29 30 503 2 ri 21 6 730 0 16 41 04 de H Sheeti Sheet Sheets pam In the example above we can see that long trades are profitable starting at 945 However short trades do not become profitable until 950 in the morning Again you should be comparing all 5 of the worksheets and making notes Another tool that ZoneTraderPro provides is an Excel worksheet that you can transfer these numbers to and create graphs to visually help you decide when to and when not to trade These graphs placed the 3 month 6 month and 9 months data on the chart This will help you carve out times when it is not profitable to trade based on historical patterns It is important th
8. Ga Qvernighth Overnight 15mAng 15mCndlB S0mCndlIB TTE Day WaluePost Long Prof L Cnt L Cnt LVM So Short Prof 5 Cnt SW Cnt SW So 404 60 32 533 036 9 59 1730 2015 20 75 25 25 26 000 11 25 5 5 6 SD m 2 18 2015 4 65 128033 4 5 1 75 1 SSD 0 2308 13 9 153 5 10 23 2015 3 5 676 103329 3 75 2 5 2 SSD 0 1944 9 7 11 4 4 227 2015 2 25 55 111193 4 75 2 5 2 25 BD 0 169 2 13 7 538 B16 10 311 2015 6 25 9 75 226438 45 2 0 25 SSD 0 2309 24 Ho 419 5 20 312 2015 8 125 218941 10 5 9 5 9 4 BD o 3967 12 10 320 6 16 3 17 2015 5 9 25 178148 5 75 0 25 1 5 BD 0 4999 11 3 491 1 21 23 2015 1 25 A275 145105 6 75 4 75 3 25 SD 0 34 10 6 60 169 4 9 327 2015 4 16 75 186038 5 25 1 5 4 5 SSD 0 8610 4 19 12 63 2 591 1 21 4 13 2016 3 675 127203 5 75 55 5 75 SD o 4081 16 120075 5o 5 4 24 2015 4 1025 204462 5 75 4 25 1 5 SD 0 fo 3 1 33 3 662 6 11 5 3 2015 2 10 765 221807 9 5 6 75 3 75 SSD 0 2066 24 12 50 446 8 23 5 19 2016 1 75 8 5 172990 55 15 2 BD 0 2238 5 6B 75 o 385 10 6 5 2015 4 6 75 183398 55 2 25 3 25 SSD 0 78 6 21 13 519 251 9 9 6 19 2015 1 75 7 25 198090 4 1 25 1 5 SSD 0 447 8 2 25 63 7 7 6 25 2015 65 13 25 216924 9 25 5 3 5 BD O 160 1 14 B 429 456 8 13 6 30 2015 13 19 5 422652 8 25 65 11 25 BD 0 EF a 22 595 752 6 36 71 4 2016 5 475 165721 3 75 2 75 475 SD Oo 242 1 G aA eer o 3251 11 7 21 2015 3 75 97646 3 25 275 BD 0 1374 11 5 455 455 3 5 7 29 2015 0 5 9 25 191870 5 1 75 1 5 BD 0 1523 3 e 559 2 12 5 4 2
9. Target offset from Blue Use Intermediate one TRUE TRUE TRUE TRUE TRUE TRUE TRUE Use Red Bar Volume Setting Bar Setting Auta Exit Cancel Orders Use Tick Divergence TRUE TRUE TRUE TRUE TRUE Auto Exit on Red Dot Auto Exit with Limit Move Stop on Red Oot TRUE TRUE TRUE Move stop offset on Dot 4 4 4 Override original target to intermediate TRUE TRUE TRUE TRUE TRUE Non divergent tick target g z g g g Cancel orders non divergent Processed yes yes yes yes yes yes LONG 2015 Open gt PrevDayVAH Green Day 10113 11756 1333 12683 11775 12058 Open in PrevDayValue Yellow Day 2342 54564985 4820 eg 5332 Open PrevDayVAL Red Day O40 A30 2424 2735 1273 474 2209 SHORT 2015 Open gt PreyDay 4H Green Day 4097 3915 s403 4950 5619 5426 Open in PrevDayalue Yellow Day 6991 H529 odar g536 6456 Open lt PrevDayVAL Red Day 2036 1668 1462 1082 1339 S20 2355 LONG 2014 ZoneTraderPro will give you the data mined excel worksheets used to create this data It isa good idea to treat each trading condition as a separate evaluation For example 1 study the tests for Green Day going long Next study Green days going short When you have identified 5 or 6 tests that you are going to study open the worksheet folders and you will find that tests have been broken down based on the type of day and the year So if we were beginning to look at test 30 we would want to open the 2015 chart that says Test 30 Combined Green Ej NinjaTrader Tra
10. The ZoneTraderPro Auto Trader New User Manual The purpose of this manual is to give the new user of the ZoneTraderPro AutoTrader a guide to some of the considerations needed to develop a trading plan using the AutoTrader The 1 thing you need is a notebook You will be going through a lot of data and when you see a data point that is interesting to me to write that down so you will remember it in the future ZonelraderPro has spent months testing parameters using the NinjaTrader Market Replay This data is available to all ZoneTraderPro customers to help them establish a trading plan It is by no means a complete test of the interaction between every parameter Feel free to suggest combinations of parameters based upon interactions you see on the charts and worksheets ZonelTraderPro created an Excel worksheet called the Parameters Summary The parameters summary lists all of the available parameters and displays the test results for 2014 and 2015 The parameter studies are broken down further based on the type of trading day on l Ma Test Number z 22 25 26 af 20 3 Target g z g g g g 10 Stop z 4 J 5 5 J 5 Breakeven Trigger 5 5 5 E 5 E Breakeven Offset 2 2 2 2 2 2 Breakeven on 1st Target Level Use Breakeven TRUE TRUE TRUE TRUE TRUE TRUE Move in Minor Touch hove Ticks from Minor Adverse Ticks to Activate Move Profit Target Adverse Tick from Primary Target Offset Move Profit ta Minar TRUE Adverse Ticks from Primary 3
11. at you create this time list only based on the type of trade and the type of day that you are analyzing Do not use the cumulative values to analyze short and long trades Do not use the 30 minute time frames as it is too general Write down the times for each test that you think you would use when trading the system Again compare the systems to find consistency with the information 1500 j 1000 1000 1500 10 15 74 8 724 7 874 5 10 25 62 7 10 30 345 3 10 35 701 725 8 1206 4 10 40 229 5 1145 2 1401 9 10 45 378 3 160 10 50 572 6 360 240 6 10 55 11 00 831 7 489 5 206 11 05 264 7 17 3 11 10 11 15 11 20 11 5 53 2 229 2 371 5 31 6 Also on Sheett1 to the far right of the individual trades is a cumulative running total broken down between long and short trades This is going to become important later when we look to figure out where to place a stop loss for the day It is also very important to note that this information is not necessarily the most important right now The reason is because you are looking at all of the trades from 945 to 1600 As you can see from the picture above you probably would not trade the time period from 1035 to 1105 What is suggested is that you analyze looking at the stop loss is a test run based on your actual trading strategy that includes the timeouts T U E Ww X Y LongCum ShortCum Ga Overnighth 145mRn 16 5 T39 6 Date
12. contracts being traded We can see a majority of these days had little to no loss trading short on a Yellow day 2 J 4 J 5 J J 0 3 a 4 5 G i g g These columns are extremely important once again to determine your maximum stop loss settings for a particular trading system Again it is important to view these values based upon your actual trading strategy and not a data run to accumulate data from all trading times What is suggested is that you create 3 or 4 trading plans for each type of trade and conduct a test using market replay You then save the trade list from NinjaTrader and send that trade list to ZoneTraderPro to analyze your trading system This way you can properly analyze your system without having to trade with live money Sheet3 provides additional statistical information to help you determine the potential volatility based upon historical statistics This is information meant to be used in real time on an actual trading day Stat T LngProf ShrtProf TotProf DTrdCnt DWin LTrdCnt LWin STrdCnt SWin Trd Dates i gt 4 lt 6 344 4 1049 1 1393 5 4 75 134 60 4 151 62 9 Jan 12 Feb 02 May 06 Sep 21 i gt 6 lt 6 735 3 1125 2 1860 5 5 80 133 63 2 147 65 3 Mar 11 Mar 12 May 01 Jun 25 Sep 29 gt B lt 10 0 0 0 0 0 0 0 0 0 gt 10 1013 2 Siz 15252 3 66 7 77 67 5 70 62 9 Jan O Jun 30 Aug 26 gt 2 lt 0 697 8 1317 3 2015 1 10 60 133 63 2 153 62 1 Feb 25 Feb 26 Mar 23 Jun 19 Jul 15 Jul 29 Aug 0 0 gt 4 l
13. de List 15 2015 9 29 20157est30Combined xls 10 17 2015 3 16 AM Microsoft Excel 97 2 607 KB Ejj NinjaTrader Trade List 15 2015 9 29 20157Test30Combined_green xls 10 17 2015 3 20 AM Microsoft Excel 9 925 KB Ei NinjaTrader Trade List 1_5_2015 9_29_2015Test30Combined_red xls 10 17 2015 3 24 AM Microsoft Excel 97 932 KB NinjaTrader Trade List 15 2015 9 29 2015Test30Combined_yellow xls 10 17 2015 3 29 AM Microsoft Excel 9 1 076 KB E NinjaTrader Trade List 7_7_2014 9_29_2015Test30 Combined xls 10 17 2015 12 49 PM Microsoft Excel 97 4 376 KB Ejj NinjaTrader Trade List 77 2014 9 29 20157Test30Combined_green xls 10 17 2015 12 58PM Microsoft Excel 97 1 379 KB Ej NinjaTrader Trade List 7_7_2014 9_29_2015Test30Combined_red xls 10 17 2015 1 08 PM Microsoft Excel 97 1 506 KB E NinjaTrader Trade List 77 2014 9 29 20157Test30Combined_yellow xls 10 17 2015 1 16 PM Microsoft Excel 9 1 611 KB NinjaTrader Trade List _ _ 2014 12_19 20147est30Combined xls 10 17 2015 6 10 PM Microsoft Excel 9 1 643 KB NinjaTrader Trade List _ _2014 12_19_20147est30Combined_green xls 10 17 2015 6 15 PM Microsoft Excel 97 524 KB Ej NinjaTrader Trade List 7_7_z2014 12_19_2014Test30Combined_red xls 10 17 2015 6 20 PM Microsoft Excel 9 643 KB NinjaTrader Trade List _ _2014 12_19_20147est30Combined_yellow xls 10 17 2015 6 25 PM Microsoft Excel 97 605 KB Starting on Sheet1 after the trades you will find the 1 t
14. e profit This information is again broken down between long and short The ZoneTraderPro AutoTrader provides the ability to timeout and stop trading 3 times during the day You also have the ability to start and stop the strategy at a specific time a7 Trade Fntrl amp S Trade Cnt Trade Long Long Cnt Lng Trad Short short Cnt shit Trade jo 9 45 4121 5 240 17 17 3065 105 29 22 1053 5 135 7 0 jg 10 00 6412 9 419 15 31 46355 159 24 5 1577 220 fata 10 10 30 3105 9 399 Dis 2013 180 11 18 1092 9 219 4 99 1 11 00 1646 4 34 4 65 536 9 151 3 33 2203 3 163 14 01 12 11 30 65446 201 25 29 3567 2 142 2512 287 Fe 139 21 42 13 200 2859 2 262 10 91 1935 5 Tas 14 55 9235 9 129 r16 14 12 30 1527 4 236 6 47 1655 7 123 13 46 126 3 113 1 14 15 13 00 553 3 be 2 11 1226 1 121 10 13 1779 4 14 12 52 1h 13 50 3262 9 24d 13 45 2500 125 20 702 9 119 6 56 if 14 00 1179 9 209 406 J324 140 25 74 2144 1 149 14 39 i5 14 30 BOY 1 251 2 45 175 8 og a 4335 5 163 2 56 1g 15 00 1600 6 316 5 07 123 5 165 0 75 1724 1 151 11 42 i 15 30 90 9 afd 1 85 BBB 5S 130 4 51 244 184 0 13 11 Jz 9 45 E g1 0 03 fgg 2 ae 21 6 96 1 54 14 74 3 9 50 2305 3 53 X77 7355 30 24521 1569 8 53 2962 3 Reis 1513 1 ala af Af 1653 3 30 40 35 279 0 20 53 99 15 10 00 of70 0 45 20 44 770 6 z 37 08 100 2 22 4 55 a6 10 05 oo 107 o d Oo T 172r 0 5 55 0 01 af 10 10 1006 3 bg 14 6 1326 4 29 45 74 320 1 39 5 21 00 10 15 1357 5 r5 18 1 fad 42 TF Fa 612 5 Ja 18 57 19 10 20 1
15. ffiliated or associated with DISCLAIMER The risk of loss in trading futures contracts can be substantial You should carefully consider whether such trading is suitable for you No representation is being made that any account will or is likely to achieve profits or losses Past performance is not necessarily indicative of future results
16. ght In addition hypothetical trading does not involve financial risk and no hypothetical trading record can completely account for the impact of financial risk in actual trading For example the ability to withstand losses or to adhere to a particular trading program in spite of trading losses are material points which can also adversely affect actual trading results There are numerous other factors related to the markets in general or to the implementation of any specific trading program which cannot be fully accounted for in the preparation of hypothetical performance results and all of which can adversely affect actual trading results Unlike an actual performance record simulated results do not represent actual trading Also since the trades have not actually been executed the results may have under or over compensated for the impact if any of certain market factors such as lack of liquidity Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight Information herein has been obtained and prepared from sources believed to be reliable however no guarantee to its accuracy is made Comments contained in these materials are not intended to be a solicitation to buy or sell any of the commodities mentioned Past performance is not indicative of future performance results Opinions expressed herein are the options of the author only and not the opinion of any firm the author may be a
17. n Shrt Trade 3931 Postn1 7167 2 892 54 8 03 4639 1 426 56 1 10 89 2528 1 466 52 1 5 43 3932 Postn2 8216 2 1032 60 9 7 96 5601 1 496 63 1 11 29 2615 1 536 59 4 88 3933 Postn3 8347 5 1225 66 4 6 81 6164 6 606 68 5 10 17 21829 619 64 3 3 53 3934 Postn4 6242 3 778 47 3 8 02 4490 9 374 50 3 12 01 1751 4 404 44 6 4 34 3935 Total 29973 2 3936 3937 Trade Entr L amp 5 Trade Cnt Trade Long Long Cnt Lng Trad Short Short Cnt Shrt Trade Month Month Prot Cum Month Prof 1938 9 45 4121 5 240 1717 3068 105 29 22 1053 5 135 7 8 16 Jan 32288 3228 8 1939 10 00 64129 49 15 31 48369 199 24 3 1577 220 7 17 15 Feb 46419 7811 5 3940 10 30 3105 9 399 7 78 2013 180 11 18 10929 219 4 99 15 Mar 2557 10459 4 1941 11 00 1646 4 354 465 636 9 191 3 33 2283 3 163 14 01 15 Apr 3696 2 14246 5 1942 11 30 65406 281 23 29 3567 2 142 2512m 139 21 42 15 May 2557 9 16757 8 3943 12 00 2859 2 262 10 91 1935 3 133 1455 9239 129 7 16 15 Jun 873 3 175845 1944 12 30 1527 4 236 6 47 1655 7 123 13 46 128 3 113 1 14 15 Jul 44549 22117 8 1945 13 00 553 3 262 2 11 1226 1 121 10 13 1779 4 141 12 62 15 Aug 2262 8 24321 5 3946 13 30 3282 9 244 13 45 2500 125 20 7829 119 6 58 15 Sep 5700 5 299879 1947 ann 11799 259 ANA 3324 140 2374 944d 4 149 14 39 4 4 gt Sheet1 Sheet2 Sheet3 2 us Ready The next piece of information on Sheet1 is a 30 minute and a 5 minute break down of the trading times showing the number of trades the dollars per trades and th
18. t 2 1604 6 24705 4075 1 19 69 4 256 61 3 255 63 5 Feb 17 Feb 18 Feb 23 Feb 27 Mar 02 Mar 27 Apr 1 gt 6 lt 4 54 4 Wet 227 1 8 50 109 59 6 122 60 7 Jan 21 Mar 03 Mar 17 Apr 23 May 26 May 29 Ser 2 gt 8 lt 6 2721 4 219 2 2940 6 5 80 104 an 112 56 Feb 04 Jun 02 Jun 05 Jul 30 Aug 17 3 gt 10 lt 6 104 4 354 7 250 3 1 100 16 56 2 17 76 5 19 Mar 4 lt 10 1436 3 1063 7 372 6 3 66 7 132 50 58 T32 62 9 Jan 30 Jul 08 Aug 26 5 6 OvernightRng 7 gt 0 lt 2 0 0 0 0 0 0 0 0 0 B gt 2 lt 4 0 0 0 0 0 0 0 0 0 9 gt 4 lt 6 704 8 1047 262 2 5 40 47 447 45 73 3 Feb 25 Feb 27 May 11 May 20 Jul 14 0 gt 6 lt 8 991 1 409 5 1400 6 9 55 6 104 529 80 56 2 Feb 23 Feb 26 Mar O3 May 26 Jun 08 Jun 19 Jun 1 gt 8 lt 10 2317 3524 2 5641 2 19 taf 245 64 5 207 64 6 Feb 16 Mar 02 Mar O9 Mar 11 Mar 17 Apr O Apr 2 gt 10 lt 12 2635 6 2432 2 5067 6 12 75 291 64 6 292 64 Jan 06 Feb 04 Apr 09 Apr 24 Apr 28 May 06 May 3 gt 12 lt 14 846 6 1722 9 2569 5 8 75 126 62 7 144 66 7 Jan 21 Feb O2 Mar 12 Mar 23 Apr O2 Apr 23 Jun 1 4 gt 14 lt 16 655 2 75 8 731 4 100 2 66 7 88 60 2 Jan 12 Feb 17 Mar 19 Aug 17 5 gt 16 lt 16 1056 1 1185 6 2241 7 2 100 46 717 41 76 Mar 27 Jun 05 6 gt 18 lt 20 1157 487 3 2203 4 100 102 69 6 103 61 2 Jan O Apr 22 Jun 02 Jun 30 Z gt 20 lt 22 09 6 57 7 147 3 2 0 19 52 6 26 60 7 May O Sep 11 B gt 22 1505 5 974 2 531 3 7 42 9 270 54 6 207 60 3 Jan 30 Apr 01 Jul O8 Aug 26 Aug 26 Sep 21 Sep g 0 15mRng 1 gt 0 lt 2 0 0
19. wo pieces of data The position data tells you information about the most profitable and least profitable trading positions The information includes the cumulative profit for each position the number of trades the winning percentage and the dollars per trade This information is then further broken down between long and short trades The question you need to ask yourself is from what positions you will be trading from The easy answer is not where you get the most dollars per trade If you look at the chart below the most dollars per trade come from the 1 position Postn4 for trading long However that is the least profitable in that it only produced 4490 in profit The most profitable from a dollar perspective was from the 2 position Postn3 which produced 6164 in profit Position 1 is always 0 Position 2 is always 1 Position 3 is always 2 Position 4 is always 1 The next piece of data is the monthly profit and the cumulative monthly profit for each system When choosing a system it is suggested that you look at these columns side by side Sometimes a particular system such as the one shown here does not experience deep drawdowns or big winning months It just consistently turns a profit By comparing 4 or 5 test results together in this manner you can see which system is the most consistent to match your trading style 3930 Entry Post Cum Prof Trade Cnt Vin Trade Long Prof Long Cnt Long Win Lng Trade Short Prof Short Cnt Short Wi
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