Remember: The returns an asset made in the past don't mean that future returns will be the same.
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  • The Interpreter

    Hi Friend, The Interpreter here. Here are all the backtests I have performed within "Public Service Enterprise Gp (PEG)"

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    Please select the "Detailed View" button to see how it performs!

Find The Lastest Buy Signals for PEG Below.



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Algorithms Results since Jan/2010


  to  
Sort Factor Algorithm % Result # Trades % Result/Trade Days/Trade Hit % Detailed View
999961 Patrick (#1) 37.9 7 5.4 50 100.0 %
999960 Robert (#2) 38.8 6 6.5 58 100.0 %
999968 Morgan (#3) 35.2 9 3.9 40 88.9 %
999962 Eric (#4) 37.0 7 5.3 60 100.0 %
999966 Danielle (#5) 33.0 8 4.1 53 100.0 %
999966 Jacob (#6) 32.9 6 5.5 56 100.0 %
999970 Daniel (#7) 32.0 11 2.9 34 90.9 %
999973 Mary (#8) 29.3 10 2.9 36 90.0 %
999970 Samantha (#9) 28.7 8 3.6 50 100.0 %
999974 Nathan (#10) 28.9 7 4.1 61 85.7 %
999976 Sarah (#11) 32.1 7 4.6 56 71.4 %
999974 Matthew (#12) 28.4 8 3.5 54 87.5 %
999976 Benjamin (#13) 26.5 21 1.3 18 85.7 %
999976 Chelsea (#14) 26.1 15 1.7 25 86.7 %
999972 Richard (#15) 26.9 7 3.9 59 100.0 %
999977 Alyssa (#16) 25.3 22 1.1 17 86.4 %
999974 Hannah (#17) 25.1 6 4.2 58 100.0 %
999980 Kimberly (#18) 22.9 12 1.9 31 83.3 %
999978 Amanda (#19) 23.5 14 1.6 30 92.9 %
999984 Megan (#20) 21.6 27 0.8 15 70.4 %
999979 Brandon (#21) 21.9 12 1.8 35 91.7 %
999981 Joshua (#22) 21.3 13 1.6 28 84.6 %
999983 Kyle (#23) 21.4 9 2.3 47 77.8 %
999982 Christian (#24) 20.3 8 2.5 52 87.5 %
999984 Juan (#25) 17.6 11 1.6 39 81.8 %
999984 Emily (#26) 17.9 7 2.6 52 85.7 %
999987 Haley (#27) 17.1 7 2.4 53 71.4 %
999988 Melissa (#28) 15.3 18 0.8 22 72.2 %
999988 Elizabeth (#29) 14.9 7 2.1 54 71.4 %
999991 Olivia (#30) 14.5 7 2.0 56 57.1 %
999990 Erin (#31) 15.0 8 1.9 48 62.5 %
999988 Lauren (#32) 16.5 27 0.6 14 70.4 %
999988 Joseph (#33) 14.3 16 0.9 25 81.3 %
999989 Courtney (#34) 14.1 10 1.4 38 70.0 %
999986 Ashley (#35) 14.8 20 0.8 20 85.0 %
999990 Charles (#36) 11.8 11 1.1 35 72.7 %
999991 Brittany (#37) 10.3 18 0.6 22 77.8 %
999992 David (#38) 9.9 13 0.8 30 69.2 %
999991 Anthony (#39) 10.5 24 0.4 17 79.2 %
999991 Allison (#40) 10.0 18 0.6 22 77.8 %
999992 Austin (#41) 9.2 14 0.6 28 78.6 %
999993 Maria (#42) 7.7 15 0.5 26 80.0 %
999993 Alexis (#43) 7.6 21 0.4 19 81.0 %
999994 Cameron (#44) 7.1 14 0.5 28 71.4 %
999995 Nicholas (#45) 6.6 15 0.5 26 60.0 %
999995 Kevin (#46) 5.2 12 0.4 33 75.0 %
999995 Brianna (#47) 5.2 24 0.2 16 70.8 %
999995 Christopher (#48) 4.5 14 0.4 28 78.6 %
999996 Mark (#49) 3.9 9 0.4 44 77.8 %
999996 Jose (#50) 4.3 19 0.2 22 84.2 %
999997 Madison (#51) 2.9 18 0.2 22 55.6 %
999998 Cody (#52) 2.4 11 0.2 35 63.6 %
999997 Michael (#53) 3.0 10 0.3 41 70.0 %
999998 Christina (#54) 2.2 18 0.1 22 72.2 %
999997 Jonathan (#55) 3.0 36 0.1 11 69.4 %
999998 Kelsey (#56) 1.1 15 0.1 26 80.0 %
999998 Dylan (#57) 0.6 9 0.1 42 66.7 %
999997 Alexander (#58) 2.8 38 0.1 11 73.7 %
999998 Laura (#59) 1.4 39 0.0 11 59.0 %
999999 Rebecca (#60) 0.2 9 0.0 46 66.7 %
999999 Katherine (#61) 0.5 31 0.0 13 67.7 %
1000000 Jordan (#62) -1.3 28 -0.0 15 71.4 %
1000000 Kayla (#63) -2.2 20 -0.1 20 60.0 %
1000000 Alexandra (#64) -2.2 30 -0.1 14 66.7 %
1000001 Anna (#65) -2.9 30 -0.1 14 66.7 %
1000000 Brian (#66) -1.1 29 -0.0 14 65.5 %
1000002 Andrew (#67) -3.7 35 -0.1 12 65.7 %
1000001 Justin (#68) -3.3 61 -0.1 7 62.3 %
1000003 Kaitlyn (#69) -5.9 39 -0.2 11 59.0 %
1000003 Jessica (#70) -6.3 59 -0.1 8 66.1 %
1000004 John (#71) -7.1 44 -0.2 10 65.9 %
1000003 Adam (#72) -6.4 41 -0.2 10 70.7 %
1000005 Nicole (#73) -9.6 9 -1.1 46 55.6 %
1000006 Aaron (#74) -9.6 67 -0.2 7 65.7 %
1000006 Abigail (#75) -10.0 51 -0.2 9 70.6 %
1000004 Jesse (#76) -8.4 104 -0.1 5 58.7 %
1000008 Amber (#77) -12.5 42 -0.3 10 66.7 %
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