sirolf2009

ANN 2 signals

14858 vizualizações
1773
This is a different approach from my original ANN strategy.
This version does 2 ANN predictions and only when they are both in the same direction, a trade will be opened.
When either of them switches, the trade is closed.
Script de código aberto

No verdadeiro espírito TradingView, o autor deste script o publicou com código aberto, para que os traders possam compreendê-lo e verificá-lo. Um brinde ao autor! Você pode usá-lo gratuitamente, mas a reutilização deste código em uma publicação é regida pelas Regras da Casa. Você pode favoritá-lo para utilizá-lo em um gráfico.

Quer usar esse script no gráfico?
//@version=2
strategy("ANN 2 signals", overlay=false, precision=4, calc_on_every_tick=true)

threshold = input(title="Threshold", type=float, defval=0.006, step=0.001)
largeTimeframe = input(title="Large timeframe", type=resolution, defval='D')
smallTimeframe = input(title="Small timeframe", type=resolution, defval='60')

PineActivationFunctionLinear(v) => v
PineActivationFunctionTanh(v) => 
    (exp(v) - exp(-v))/(exp(v) + exp(-v))

ANN(input) =>
    l0_0 = PineActivationFunctionLinear(input)
    l0_1 = PineActivationFunctionLinear(input)
    l0_2 = PineActivationFunctionLinear(input)
    l0_3 = PineActivationFunctionLinear(input)
    l0_4 = PineActivationFunctionLinear(input)
    l0_5 = PineActivationFunctionLinear(input)
    l0_6 = PineActivationFunctionLinear(input)
    l0_7 = PineActivationFunctionLinear(input)
    l0_8 = PineActivationFunctionLinear(input)
    l0_9 = PineActivationFunctionLinear(input)
    l0_10 = PineActivationFunctionLinear(input)
    l0_11 = PineActivationFunctionLinear(input)
    l0_12 = PineActivationFunctionLinear(input)
    l0_13 = PineActivationFunctionLinear(input)
    l0_14 = PineActivationFunctionLinear(input)
 
    l1_0 = PineActivationFunctionTanh(l0_0*5.040340774 + l0_1*-1.3025994088 + l0_2*19.4225543981 + l0_3*1.1796960423 + l0_4*2.4299395823 + l0_5*3.159003445 + l0_6*4.6844527551 + l0_7*-6.1079267196 + l0_8*-2.4952869198 + l0_9*-4.0966081154 + l0_10*-2.2432843111 + l0_11*-0.6105764807 + l0_12*-0.0775684605 + l0_13*-0.7984753138 + l0_14*3.4495907342)
    l1_1 = PineActivationFunctionTanh(l0_0*5.9559031982 + l0_1*-3.1781960056 + l0_2*-1.6337491061 + l0_3*-4.3623166512 + l0_4*0.9061990402 + l0_5*-0.731285093 + l0_6*-6.2500232251 + l0_7*0.1356087758 + l0_8*-0.8570572885 + l0_9*-4.0161353298 + l0_10*1.5095552083 + l0_11*1.324789197 + l0_12*-0.1011973878 + l0_13*-2.3642090162 + l0_14*-0.7160862442)
    l1_2 = PineActivationFunctionTanh(l0_0*4.4350881378 + l0_1*-2.8956461034 + l0_2*1.4199762607 + l0_3*-0.6436844261 + l0_4*1.1124274281 + l0_5*-4.0976954985 + l0_6*2.9317456342 + l0_7*0.0798318393 + l0_8*-5.5718144311 + l0_9*-0.6623352208 +l0_10*3.2405203222 + l0_11*-10.6253384513 + l0_12*4.7132919253 + l0_13*-5.7378151597 + l0_14*0.3164836695)
    l1_3 = PineActivationFunctionTanh(l0_0*-6.1194605467 + l0_1*7.7935605604 + l0_2*-0.7587522153 + l0_3*9.8382495905 + l0_4*0.3274314734 + l0_5*1.8424796541 + l0_6*-1.2256355427 + l0_7*-1.5968600758 + l0_8*1.9937700922 + l0_9*5.0417809111 + l0_10*-1.9369944654 + l0_11*6.1013201778 + l0_12*1.5832910747 + l0_13*-2.148403244 + l0_14*1.5449437366)
    l1_4 = PineActivationFunctionTanh(l0_0*3.5700040028 + l0_1*-4.4755892733 + l0_2*0.1526702072 + l0_3*-0.3553664401 + l0_4*-2.3777962662 + l0_5*-1.8098849587 + l0_6*-3.5198449134 + l0_7*-0.4369370497 + l0_8*2.3350169623 + l0_9*1.9328960346 + l0_10*1.1824141812 + l0_11*3.0565148049 + l0_12*-9.3253401534 + l0_13*1.6778555498 + l0_14*-3.045794332)
    l1_5 = PineActivationFunctionTanh(l0_0*3.6784907623 + l0_1*1.1623683715 + l0_2*7.1366362145 + l0_3*-5.6756546585 + l0_4*12.7019884334 + l0_5*-1.2347823331 + l0_6*2.3656619827 + l0_7*-8.7191778213 + l0_8*-13.8089238753 + l0_9*5.4335943836 + l0_10*-8.1441181338 + l0_11*-10.5688113287 + l0_12*6.3964140758 + l0_13*-8.9714236223 + l0_14*-34.0255456929)
    l1_6 = PineActivationFunctionTanh(l0_0*-0.4344517548 + l0_1*-3.8262167437 + l0_2*-0.2051098003 + l0_3*0.6844201221 + l0_4*1.1615893422 + l0_5*-0.404465314 + l0_6*-0.1465747632 + l0_7*-0.006282458 + l0_8*0.1585655487 + l0_9*1.1994484991 + l0_10*-0.9879081404 + l0_11*-0.3564970612 + l0_12*1.5814717823 + l0_13*-0.9614804676 + l0_14*0.9204822346)
    l1_7 = PineActivationFunctionTanh(l0_0*-4.2700957175 + l0_1*9.4328591157 + l0_2*-4.3045548 + l0_3*5.0616868842 + l0_4*3.3388781058 + l0_5*-2.1885073225 + l0_6*-6.506301518 + l0_7*3.8429000108 + l0_8*-1.6872237349 + l0_9*2.4107095799 + l0_10*-3.0873985314 + l0_11*-2.8358325447 + l0_12*2.4044366491 + l0_13*0.636779082 + l0_14*-13.2173215035)
    l1_8 = PineActivationFunctionTanh(l0_0*-8.3224697492 + l0_1*-9.4825530183 + l0_2*3.5294389835 + l0_3*0.1538618049 + l0_4*-13.5388631898 + l0_5*-0.1187936017 + l0_6*-8.4582741139 + l0_7*5.1566299292 + l0_8*10.345519938 + l0_9*2.9211759333 + l0_10*-5.0471804233 + l0_11*4.9255989983 + l0_12*-9.9626142544 + l0_13*23.0043143258 + l0_14*20.9391809343)
    l1_9 = PineActivationFunctionTanh(l0_0*-0.9120518654 + l0_1*0.4991807488 + l0_2*-1.877244586 + l0_3*3.1416466525 + l0_4*1.063709676 + l0_5*0.5210126835 + l0_6*-4.9755780108 + l0_7*2.0336532347 + l0_8*-1.1793121093 + l0_9*-0.730664855 + l0_10*-2.3515987428 + l0_11*-0.1916546514 + l0_12*-2.2530340504 + l0_13*-0.2331829119 + l0_14*0.7216218149)
    l1_10 = PineActivationFunctionTanh(l0_0*-5.2139618683 + l0_1*1.0663790028 + l0_2*1.8340834959 + l0_3*1.6248173447 + l0_4*-0.7663740145 + l0_5*0.1062788171 + l0_6*2.5288021501 + l0_7*-3.4066549066 + l0_8*-4.9497988755 + l0_9*-2.3060668143 + l0_10*-1.3962486274 + l0_11*0.6185583427 + l0_12*0.2625299576 + l0_13*2.0270246444 + l0_14*0.6372015811)
    l1_11 = PineActivationFunctionTanh(l0_0*0.2020072665 + l0_1*0.3885852709 + l0_2*-0.1830248843 + l0_3*-1.2408598444 + l0_4*-0.6365798088 + l0_5*1.8736534268 + l0_6*0.656206442 + l0_7*-0.2987482678 + l0_8*-0.2017485963 + l0_9*-1.0604095303 + l0_10*0.239793356 + l0_11*-0.3614172938 + l0_12*0.2614678044 + l0_13*1.0083551762 + l0_14*-0.5473833797)
    l1_12 = PineActivationFunctionTanh(l0_0*-0.4367517149 + l0_1*-10.0601304934 + l0_2*1.9240604838 + l0_3*-1.3192184047 + l0_4*-0.4564760159 + l0_5*-0.2965270368 + l0_6*-1.1407423613 + l0_7*2.0949647291 + l0_8*-5.8212599297 + l0_9*-1.3393321939 + l0_10*7.6624548265 + l0_11*1.1309391851 + l0_12*-0.141798054 + l0_13*5.1416736187 + l0_14*-1.8142503125)
    l1_13 = PineActivationFunctionTanh(l0_0*1.103948336 + l0_1*-1.4592033032 + l0_2*0.6146278432 + l0_3*0.5040966421 + l0_4*-2.4276090772 + l0_5*-0.0432902426 + l0_6*-0.0044259999 + l0_7*-0.5961347308 + l0_8*0.3821026107 + l0_9*0.6169102373 +l0_10*-0.1469847611 + l0_11*-0.0717167683 + l0_12*-0.0352403695 + l0_13*1.2481310788 + l0_14*0.1339628411)
    l1_14 = PineActivationFunctionTanh(l0_0*-9.8049980534 + l0_1*13.5481068519 + l0_2*-17.1362809025 + l0_3*0.7142100864 + l0_4*4.4759163422 + l0_5*4.5716161777 + l0_6*1.4290884628 + l0_7*8.3952862712 + l0_8*-7.1613700432 + l0_9*-3.3249489518+ l0_10*-0.7789587912 + l0_11*-1.7987628873 + l0_12*13.364752545 + l0_13*5.3947219678 + l0_14*12.5267547127)
    l1_15 = PineActivationFunctionTanh(l0_0*0.9869461803 + l0_1*1.9473351905 + l0_2*2.032925759 + l0_3*7.4092080633 + l0_4*-1.9257741399 + l0_5*1.8153585328 + l0_6*1.1427866392 + l0_7*-0.3723167449 + l0_8*5.0009927384 + l0_9*-0.2275103411 + l0_10*2.8823012914 + l0_11*-3.0633141934 + l0_12*-2.785334815 + l0_13*2.727981E-4 + l0_14*-0.1253009512)
    l1_16 = PineActivationFunctionTanh(l0_0*4.9418118585 + l0_1*-2.7538199876 + l0_2*-16.9887588104 + l0_3*8.8734475297 + l0_4*-16.3022734814 + l0_5*-4.562496601 + l0_6*-1.2944373699 + l0_7*-9.6022946986 + l0_8*-1.018393866 + l0_9*-11.4094515429 + l0_10*24.8483091382 + l0_11*-3.0031522277 + l0_12*0.1513114555 + l0_13*-6.7170487021 + l0_14*-14.7759227576)
    l1_17 = PineActivationFunctionTanh(l0_0*5.5931454656 + l0_1*2.22272078 + l0_2*2.603416897 + l0_3*1.2661196599 + l0_4*-2.842826446 + l0_5*-7.9386099121 + l0_6*2.8278849111 + l0_7*-1.2289445238 + l0_8*4.571484248 + l0_9*0.9447425595 + l0_10*4.2890688351 + l0_11*-3.3228258483 + l0_12*4.8866215526 + l0_13*1.0693412194 + l0_14*-1.963203112)
    l1_18 = PineActivationFunctionTanh(l0_0*0.2705520264 + l0_1*0.4002328199 + l0_2*0.1592515845 + l0_3*0.371893552 + l0_4*-1.6639467871 + l0_5*2.2887318884 + l0_6*-0.148633664 + l0_7*-0.6517792263 + l0_8*-0.0993032992 + l0_9*-0.964940376 + l0_10*0.1286342935 + l0_11*0.4869943595 + l0_12*1.4498648166 + l0_13*-0.3257333384 + l0_14*-1.3496419812)
    l1_19 = PineActivationFunctionTanh(l0_0*-1.3223200798 + l0_1*-2.2505204324 + l0_2*0.8142804525 + l0_3*-0.848348177 + l0_4*0.7208860589 + l0_5*1.2033423756 + l0_6*-0.1403005786 + l0_7*0.2995941644 + l0_8*-1.1440473062 + l0_9*1.067752916 + l0_10*-1.2990534679 + l0_11*1.2588583869 + l0_12*0.7670409455 + l0_13*2.7895972983 + l0_14*-0.5376152512)
    l1_20 = PineActivationFunctionTanh(l0_0*0.7382351572 + l0_1*-0.8778865631 + l0_2*1.0950766363 + l0_3*0.7312146997 + l0_4*2.844781386 + l0_5*2.4526730903 + l0_6*-1.9175165077 + l0_7*-0.7443755288 + l0_8*-3.1591419438 + l0_9*0.8441602697 + l0_10*1.1979484448 + l0_11*2.138098544 + l0_12*0.9274159536 + l0_13*-2.1573448803 + l0_14*-3.7698356464)
    l1_21 = PineActivationFunctionTanh(l0_0*5.187120117 + l0_1*-7.7525670576 + l0_2*1.9008346975 + l0_3*-1.2031603996 + l0_4*5.917669142 + l0_5*-3.1878682719 + l0_6*1.0311747828 + l0_7*-2.7529484612 + l0_8*-1.1165884578 + l0_9*2.5524942323 + l0_10*-0.38623241 + l0_11*3.7961317445 + l0_12*-6.128820883 + l0_13*-2.1470707709 + l0_14*2.0173792965)
    l1_22 = PineActivationFunctionTanh(l0_0*-6.0241676562 + l0_1*0.7474455584 + l0_2*1.7435724844 + l0_3*0.8619835076 + l0_4*-0.1138406797 + l0_5*6.5979359352 + l0_6*1.6554154348 + l0_7*-3.7969458806 + l0_8*1.1139097376 + l0_9*-1.9588417 + l0_10*3.5123392221 + l0_11*9.4443103128 + l0_12*-7.4779291395 + l0_13*3.6975940671 + l0_14*8.5134262747)
    l1_23 = PineActivationFunctionTanh(l0_0*-7.5486576471 + l0_1*-0.0281420865 + l0_2*-3.8586839454 + l0_3*-0.5648792233 + l0_4*-7.3927282026 + l0_5*-0.3857538046 + l0_6*-2.9779885698 + l0_7*4.0482279965 + l0_8*-1.1522499578 + l0_9*-4.1562500212 + l0_10*0.7813134307 + l0_11*-1.7582667612 + l0_12*1.7071109988 + l0_13*6.9270873208 + l0_14*-4.5871357362)
    l1_24 = PineActivationFunctionTanh(l0_0*-5.3603442228 + l0_1*-9.5350611629 + l0_2*1.6749984422 + l0_3*-0.6511065892 + l0_4*-0.8424823239 + l0_5*1.9946675213 + l0_6*-1.1264361638 + l0_7*0.3228676616 + l0_8*5.3562230396 + l0_9*-1.6678168952+ l0_10*1.2612580068 + l0_11*-3.5362671399 + l0_12*-9.3895191366 + l0_13*2.0169228673 + l0_14*-3.3813191557)
    l1_25 = PineActivationFunctionTanh(l0_0*1.1362866429 + l0_1*-1.8960071702 + l0_2*5.7047307243 + l0_3*-1.6049785053 + l0_4*-4.8353898931 + l0_5*-1.4865381145 + l0_6*-0.2846893475 + l0_7*2.2322095997 + l0_8*2.0930488668 + l0_9*1.7141411002 + l0_10*-3.4106032176 + l0_11*3.0593289612 + l0_12*-5.0894813904 + l0_13*-0.5316299133 + l0_14*0.4705265416)
    l1_26 = PineActivationFunctionTanh(l0_0*-0.9401400975 + l0_1*-0.9136086957 + l0_2*-3.3808688582 + l0_3*4.7200776773 + l0_4*3.686296919 + l0_5*14.2133723935 + l0_6*1.5652940954 + l0_7*-0.2921139433 + l0_8*1.0244504511 + l0_9*-7.6918299134 + l0_10*-0.594936135 + l0_11*-1.4559914156 + l0_12*2.8056435224 + l0_13*2.6103905733 + l0_14*2.3412348872)
    l1_27 = PineActivationFunctionTanh(l0_0*1.1573980186 + l0_1*2.9593661909 + l0_2*0.4512594325 + l0_3*-0.9357210858 + l0_4*-1.2445804495 + l0_5*4.2716471631 + l0_6*1.5167912375 + l0_7*1.5026853293 + l0_8*1.3574772038 + l0_9*-1.9754386842 + l0_10*6.727671436 + l0_11*8.0145772889 + l0_12*7.3108970663 + l0_13*-2.5005627841 + l0_14*8.9604502277)
    l1_28 = PineActivationFunctionTanh(l0_0*6.3576350212 + l0_1*-2.9731672725 + l0_2*-2.7763558082 + l0_3*-3.7902984555 + l0_4*-1.0065574585 + l0_5*-0.7011836061 + l0_6*-1.0298068578 + l0_7*1.201007784 + l0_8*-0.7835862254 + l0_9*-3.9863597435 + l0_10*6.7851825502 + l0_11*1.1120256721 + l0_12*-2.263287351 + l0_13*1.8314374104 + l0_14*-2.279102097)
    l1_29 = PineActivationFunctionTanh(l0_0*-7.8741911036 + l0_1*-5.3370618518 + l0_2*11.9153868964 + l0_3*-4.1237170553 + l0_4*2.9491152758 + l0_5*1.0317132502 + l0_6*2.2992199883 + l0_7*-2.0250502364 + l0_8*-11.0785995839 + l0_9*-6.3615588554 + l0_10*-1.1687644976 + l0_11*6.3323478015 + l0_12*6.0195076962 + l0_13*-2.8972208702 + l0_14*3.6107747183)
 
    l2_0 = PineActivationFunctionTanh(l1_0*-0.590546797 + l1_1*0.6608304658 + l1_2*-0.3358268839 + l1_3*-0.748530283 + l1_4*-0.333460383 + l1_5*-0.3409307681 + l1_6*0.1916558198 + l1_7*-0.1200399453 + l1_8*-0.5166151854 + l1_9*-0.8537164676 +l1_10*-0.0214448647 + l1_11*-0.553290271 + l1_12*-1.2333302892 + l1_13*-0.8321813811 + l1_14*-0.4527761741 + l1_15*0.9012545631 + l1_16*0.415853215 + l1_17*0.1270548319 + l1_18*0.2000460279 + l1_19*-0.1741942671 + l1_20*0.419830522 + l1_21*-0.059839291 + l1_22*-0.3383001769 + l1_23*0.1617814073 + l1_24*0.3071848006 + l1_25*-0.3191182045 + l1_26*-0.4981831822 + l1_27*-1.467478375 + l1_28*-0.1676432563 + l1_29*1.2574849126)
    l2_1 = PineActivationFunctionTanh(l1_0*-0.5514235841 + l1_1*0.4759190049 + l1_2*0.2103576983 + l1_3*-0.4754377924 + l1_4*-0.2362941295 + l1_5*0.1155082119 + l1_6*0.7424215794 + l1_7*-0.3674198672 + l1_8*0.8401574461 + l1_9*0.6096563193 + l1_10*0.7437935674 + l1_11*-0.4898638101 + l1_12*-0.4168668092 + l1_13*-0.0365111095 + l1_14*-0.342675224 + l1_15*0.1870268765 + l1_16*-0.5843050987 + l1_17*-0.4596547471 + l1_18*0.452188522 + l1_19*-0.6737126684 + l1_20*0.6876072741 + l1_21*-0.8067776704 + l1_22*0.7592979467 + l1_23*-0.0768239468 + l1_24*0.370536097 + l1_25*-0.4363884671 + l1_26*-0.419285676 + l1_27*0.4380251141 + l1_28*0.0822528948 + l1_29*-0.2333910809)
    l2_2 = PineActivationFunctionTanh(l1_0*-0.3306539521 + l1_1*-0.9382247194 + l1_2*0.0746711276 + l1_3*-0.3383838985 + l1_4*-0.0683232217 + l1_5*-0.2112358049 + l1_6*-0.9079234054 + l1_7*0.4898595603 + l1_8*-0.2039825863 + l1_9*1.0870698641+ l1_10*-1.1752901237 + l1_11*1.1406403923 + l1_12*-0.6779626786 + l1_13*0.4281048906 + l1_14*-0.6327670055 + l1_15*-0.1477678844 + l1_16*0.2693637584 + l1_17*0.7250738509 + l1_18*0.7905904504 + l1_19*-1.6417250883 + l1_20*-0.2108095534 +l1_21*-0.2698557472 + l1_22*-0.2433656685 + l1_23*-0.6289943273 + l1_24*0.436428207 + l1_25*-0.8243825184 + l1_26*-0.8583496686 + l1_27*0.0983131026 + l1_28*-0.4107462518 + l1_29*0.5641683087)
    l2_3 = PineActivationFunctionTanh(l1_0*1.7036869992 + l1_1*-0.6683507666 + l1_2*0.2589197112 + l1_3*0.032841148 + l1_4*-0.4454796342 + l1_5*-0.6196149423 + l1_6*-0.1073622976 + l1_7*-0.1926393101 + l1_8*1.5280232458 + l1_9*-0.6136527036 +l1_10*-1.2722934357 + l1_11*0.2888655811 + l1_12*-1.4338638512 + l1_13*-1.1903556863 + l1_14*-1.7659663905 + l1_15*0.3703086867 + l1_16*1.0409140889 + l1_17*0.0167382209 + l1_18*0.6045646461 + l1_19*4.2388788116 + l1_20*1.4399738234 + l1_21*0.3308571935 + l1_22*1.4501137667 + l1_23*0.0426123724 + l1_24*-0.708479795 + l1_25*-1.2100800732 + l1_26*-0.5536278651 + l1_27*1.3547250573 + l1_28*1.2906250286 + l1_29*0.0596007114)
    l2_4 = PineActivationFunctionTanh(l1_0*-0.462165126 + l1_1*-1.0996742176 + l1_2*1.0928262999 + l1_3*1.806407067 + l1_4*0.9289147669 + l1_5*0.8069022793 + l1_6*0.2374237802 + l1_7*-2.7143979019 + l1_8*-2.7779203877 + l1_9*0.214383903 + l1_10*-1.3111536623 + l1_11*-2.3148813568 + l1_12*-2.4755355804 + l1_13*-0.6819733236 + l1_14*0.4425615226 + l1_15*-0.1298218043 + l1_16*-1.1744832824 + l1_17*-0.395194848 + l1_18*-0.2803397703 + l1_19*-0.4505071197 + l1_20*-0.8934956598 + l1_21*3.3232916348 + l1_22*-1.7359534851 + l1_23*3.8540421743 + l1_24*1.4424032523 + l1_25*0.2639823693 + l1_26*0.3597053634 + l1_27*-1.0470693728 + l1_28*1.4133480357 + l1_29*0.6248098695)
    l2_5 = PineActivationFunctionTanh(l1_0*0.2215807411 + l1_1*-0.5628295071 + l1_2*-0.8795982905 + l1_3*0.9101585104 + l1_4*-1.0176831976 + l1_5*-0.0728884401 + l1_6*0.6676331658 + l1_7*-0.7342174108 + l1_8*9.4428E-4 + l1_9*0.6439774272 + l1_10*-0.0345236026 + l1_11*0.5830977027 + l1_12*-0.4058921837 + l1_13*-0.3991888077 + l1_14*-1.0090426973 + l1_15*-0.9324780698 + l1_16*-0.0888749165 + l1_17*0.2466351736 + l1_18*0.4993304601 + l1_19*-1.115408696 + l1_20*0.9914246705 + l1_21*0.9687743445 + l1_22*0.1117130875 + l1_23*0.7825109733 + l1_24*0.2217023612 + l1_25*0.3081256411 + l1_26*-0.1778007966 + l1_27*-0.3333287743 + l1_28*1.0156352461 + l1_29*-0.1456257813)
    l2_6 = PineActivationFunctionTanh(l1_0*-0.5461783383 + l1_1*0.3246015999 + l1_2*0.1450605434 + l1_3*-1.3179944349 + l1_4*-1.5481775261 + l1_5*-0.679685633 + l1_6*-0.9462335139 + l1_7*-0.6462399371 + l1_8*0.0991658683 + l1_9*0.1612892194 +l1_10*-1.037660602 + l1_11*-0.1044778824 + l1_12*0.8309203243 + l1_13*0.7714766458 + l1_14*0.2566767663 + l1_15*0.8649416329 + l1_16*-0.5847461285 + l1_17*-0.6393969272 + l1_18*0.8014049359 + l1_19*0.2279568228 + l1_20*1.0565217821 + l1_21*0.134738029 + l1_22*0.3420395576 + l1_23*-0.2417397219 + l1_24*0.3083072038 + l1_25*0.6761739059 + l1_26*-0.4653817053 + l1_27*-1.0634057566 + l1_28*-0.5658892281 + l1_29*-0.6947283681)
    l2_7 = PineActivationFunctionTanh(l1_0*-0.5450410944 + l1_1*0.3912849372 + l1_2*-0.4118641117 + l1_3*0.7124695074 + l1_4*-0.7510266122 + l1_5*1.4065673913 + l1_6*0.9870731545 + l1_7*-0.2609363107 + l1_8*-0.3583639958 + l1_9*0.5436375706 +l1_10*0.4572450099 + l1_11*-0.4651538878 + l1_12*-0.2180218212 + l1_13*0.5241262959 + l1_14*-0.8529323253 + l1_15*-0.4200378937 + l1_16*0.4997885721 + l1_17*-1.1121528189 + l1_18*0.5992411048 + l1_19*-1.0263270781 + l1_20*-1.725160642 + l1_21*-0.2653995722 + l1_22*0.6996703032 + l1_23*0.348549086 + l1_24*0.6522482482 + l1_25*-0.7931928436 + l1_26*-0.5107994359 + l1_27*0.0509642698 + l1_28*0.8711187423 + l1_29*0.8999449627)
    l2_8 = PineActivationFunctionTanh(l1_0*-0.7111081522 + l1_1*0.4296245062 + l1_2*-2.0720732038 + l1_3*-0.4071818684 + l1_4*1.0632721681 + l1_5*0.8463224325 + l1_6*-0.6083948423 + l1_7*1.1827669608 + l1_8*-0.9572307844 + l1_9*-0.9080517673 + l1_10*-0.0479029057 + l1_11*-1.1452853213 + l1_12*0.2884352688 + l1_13*0.1767851586 + l1_14*-1.089314461 + l1_15*1.2991763966 + l1_16*1.6236630806 + l1_17*-0.7720263697 + l1_18*-0.5011541755 + l1_19*-2.3919413568 + l1_20*0.0084018338 + l1_21*0.9975216139 + l1_22*0.4193541029 + l1_23*1.4623834571 + l1_24*-0.6253069691 + l1_25*0.6119677341 + l1_26*0.5423948388 + l1_27*1.0022450377 + l1_28*-1.2392984069 + l1_29*1.5021529822)
 
    l3_0 = PineActivationFunctionTanh(l2_0*0.3385061186 + l2_1*0.6218531956 + l2_2*-0.7790340983 + l2_3*0.1413078332 + l2_4*0.1857010624 + l2_5*-0.1769456351 + l2_6*-0.3242337911 + l2_7*-0.503944883 + l2_8*0.1540568869)
 
entryYesterday = security(tickerid, largeTimeframe, ohlc4[2])
entryToday = security(tickerid, largeTimeframe, ohlc4[1])
entry = (entryToday-entryYesterday)/entryYesterday
exitYesterday = security(tickerid, smallTimeframe, ohlc4[2])
exitToday = security(tickerid, smallTimeframe, ohlc4[1])
exit = (exitToday-exitYesterday)/exitYesterday

exitPrediction = ANN(exit)
entryPrediction = ANN(entry)
goLong = entryPrediction < -threshold and exitPrediction < -threshold
goShort = entryPrediction > threshold and exitPrediction > threshold
 
strategy.close("LONG", exitPrediction >= threshold or entryPrediction >= threshold)
strategy.close("SHORT", exitPrediction <= -threshold or entryPrediction <= threshold)

strategy.entry("LONG", strategy.long, when = goLong)
strategy.entry("SHORT", strategy.short, when = goShort) 

plot(entryPrediction, color=blue)
plot(exitPrediction, color=yellow)

bgcolor(goLong ? green : goShort ? red : gray, transp=20)

Comentários

Sir in which chart time period is suitable for intraday and carry forward , and how can we decide target and SL.?? Many times i saw long and short are too close than how can we will trade?? reply please... :(
+16 Resposta
This strategy is awesome! I can't understand why more people have not been checking it out..........It seems to avoid the repaint issue that your earlier ANN strategy.
+8 Resposta
how to set a alarm for this
any coding to it or what
+1 Resposta
Hi,
Could you prevent the use of the functions that makes repainting?
I'm sure you understood the stated in that tradingview note:
https://www.tradingview.com/wiki/Pine_Script:_Release_Notes#Repainting_issue

thanks
+1 Resposta
malotiin malotiin
@malotiin, Hi @yazeed, do your script consider the mentioned above?
Resposta
how to fix maximum number of orders (3000) reached ?! @sirolf2009 would you please help
Resposta
This strategy does not work on the realtime
it has repaint ,
I would advise you to test my osilator (powerful bay signal) .

Resposta
I think you got off to a good idea here, but I think a better idea would be to have trades REVERSED (instead of closed, since that's how ANN was originally intended), until bigtimeframe and smalltimeframe BOTH indicate the same thing, because the problem I see with the original ANN strategy is usually where reversals take place, where things could flip both ways, those are the failing trades in the original ANN strategy. Let me know if you'd like to have a discussion.
Resposta
yazeed yazeed
@yazeed, Also, please check my version of ANN strategy, updated to Pine 3 with 0 repaint, I don't use close, lookahead, or calc_on_every_tick, all of which cause repaint in strategies. I just gave you access to check it out.
Resposta
awesome scripts. are they still working? pleaase advise
Resposta