안녕하세요, 예스스탁 입니다.복잡한 수식 공부 없이 여러분의 아이디어를 말하면 시스템 트레이딩 언어 예스랭귀지로 작성해주는 서비스예스나 AI(YesNa AI)가 출시되었습니다.지금 예스나 AI를 직접 경험해 보실 수 있도록 20크레딧(질문권 20회)를 무료로 증정해 드리고 있습니다.바로 여러분의 아이디어를 코드로 변환해보세요.--------------------------------------------------🚀 YesNa AI 핵심 기능- 지표식/전략식/종목검색식 생성: 자연어로 요청하면 예스랭귀지 문법에 맞는 코드를 작성합니다.- 종목검색식 변환 지원: K증권의 종목 검색식을 예스랭귀지로 변환 지원합니다.- 컴파일 검증: 작성된 코드가 실행 가능한지 컴파일러를 통해 문법 검증을 거쳐 결과물을 제공합니다.상세한 서비스 개요 및 활용 방법은 [서비스 소개 페이지]에서 확인하실 수 있습니다.▶ 서비스 소개 페이지: 바로가기서비스 사용 유의사항 및 결제 환불정책은 [이용약관]을 참고 부탁드립니다.▶ 서비스 이용약관: 바로가기💬 이용 문의사용 중 문의사항은 [프로그램 사용법 Q&A] 게시판에서 [예스나 AI] 카테고리를 설정 후 문의해 주시면 상세히 안내해 드리겠습니다.--------------------------------------------------앞으로도 AI를 활용한 다양한 트레이딩 기능들을 지속적으로 선보일 예정입니다.많은 관심과 기대 부탁드립니다.

15분봉에서, 130봉중(일주간: 일일 26봉*5일)의 최고가를, 1봉전에 돌파한 것을 0봉에 검색코자 합니다. 단, 1.1봉전의 돌파봉은 최소 3%이상 2.129봉간 -고가/저가기준으로는 최고가 ~ 최저가 차이가 10%이하 OR -종가기준은 5%이하 차이 (돌파봉(1봉전)의 상승분은 무시: 129봉전 ~ 2봉전까지 최고/최저 가격차이) 3.당일 첫번째 돌파만 검색(이후는 무시) 가능하시다면 검색수식 부탁올립니다.

안녕하세요! 아래수식을 예스로 변환부탁드립니다 감사합니다! A = ((predayhigh()+predaylow()+ predayclose())/3)+ (predayhigh()-predaylow()) (c,(A*1.07))

// This function calcualtes a se lectable average type GetAverage(_data, _len, MAOption) => value = switch MAOption 'SMA' => ta.sma(_data, _len) 'EMA' => ta.ema(_data, _len) 'HMA' => ta.hma(_data, _len) 'RMA' => ta.rma(_data, _len) => ta.wma(_data, _len) // *********************************************************************************************************** // ======================================================================================== // Normalization function - Normalizes values that are not restricted within a zero to 100 range // This technique provides a scale that is closer to a "human" estimation of value in "bands" // as in: low, below average, average, above average, high, super high // this also avoids the issue of extreme values when using the stoch() -based technique // these values are subjective, and can be changed - but slight changes here won't lead to major changes in outcome // since all is relative to the same data series. // Normalize(_Value, _Avg) => _X = _Value / _Avg _Nor = _X > 1.50 ? 1.00 : _X > 1.20 ? 0.90 : _X > 1.00 ? 0.80 : _X > 0.80 ? 0.70 : _X > 0.60 ? 0.60 : _X > 0.40 ? 0.50 : _X > 0.20 ? 0.25 : 0.1 // =================================================================================== // =========================================================================================================== // Inputs // =========================================================================================================== grp_1 = 'Rate of FLow (RoF)' grp_2 = 'Lookback Parameters' grp_3 = 'Bias / Sentiment' grp_4 = 'EVEREX Bands' length = input.int(10, minval = 1, inline = 'ROF', group = grp_1) MA_Type = input.string(defval = 'WMA', title = 'MA type', options = ['WMA', 'EMA', 'SMA', 'HMA', 'RMA'], inline = 'ROF', group = grp_1) smooth = input.int(defval = 3, title = 'Smooth', minval = 1, inline = 'ROF', group = grp_1) //src = input.source(close, title = "Source (for 2-Bar Shift)", group = grp_1) sig_length = input.int(5, 'Signal Length', minval = 1, inline = 'Signal', group = grp_1) S_Type = input.string(defval = 'WMA', title = 'Signal Type', options = ['WMA', 'EMA', 'SMA', 'HMA', 'RMA'], inline = 'Signal', group = grp_1) lookback = input.int(defval = 20, title = 'Length', minval = 1, inline = 'Lookback', group = grp_2) lkbk_Calc = input.string(defval = 'Simple', title = 'Averaging', options = ['Simple', 'Same as RRoF'], inline='Lookback', group = grp_2 ) showBias = input.bool(defval = false, title = 'Bias Plot ? -- ', inline = 'Bias', group = grp_3) B_Length = input.int(defval = 30, title = 'Length', minval = 1, inline = 'Bias', group = grp_3) B_Type = input.string(defval = 'WMA', title = 'MA type', options = ['WMA', 'EMA', 'SMA', 'HMA', 'RMA'], inline = 'Bias', group = grp_3) showEVEREX = input.bool(true, 'Show EVEREX Bands ? -- ', inline = 'EVEREX', group = grp_4) // a simple mechanism to control/change the strength band scale for improving visualization // applies only to the "bands" and the level hlines bandscale = str.tonumber(input.string("100", title = "Band Scale", options = ['100', '200', '400'], inline = 'EVEREX', group = grp_4)) DispBias = showBias ? display.pane : display.none DispBands = showEVEREX ? display.pane : display.none showhlines = showEVEREX ? display.all : display.none Disp_vals = display.status_line + display.data_window // =========================================================================================================== // Calculations // =========================================================================================================== // Volume "effort" Calculation -- will revert to no volume acceleration for instruments with no volume data v = na(volume) ? 1 : volume // this part ensures we're not hit with calc issues due to NaN's NoVol_Flag = na(volume) ? true : false // this is a flag to use later lkbk_MA_Type = lkbk_Calc == 'Simple' ? 'SMA' : MA_Type Vola = GetAverage(v, lookback, lkbk_MA_Type) Vola_n_pre = Normalize(v, Vola) * 100 //Now trap the case of no volume data - ensure final calculation not impacted Vola_n = NoVol_Flag ? 100 : Vola_n_pre //plot(Vola_n , "Volume Normalized", color = color.white, display = display.none) // =============================================================================================================== // Price "result" calculation // we'll consider "result" (strength or weakness) to be the outcome (average) of 6 elements: // Same (in-)Bar strength elements: // 1 - Bar Closing: the closing within the bar --> this will be a direct +100 / -100 value // 2 - Spread to range: the spread to range ratio (that's BoP formula) --> direct +100 / -100 value // 3 - Relative Spread: spread relative to average spread during lookback period --> normalized // 2-bar strength elements: // 4 - 2-bar closing: the closing within 2-bar range (that accomodates open gap effect) // 5 - 2-bar Closing Shift to Range: Change in close relative to the 2-bar range // 6 - 2-bar Relative Shift: the 2-bar Close (or source price) shift - relative to the average 2-bar shift during lookback period --> normalized BarSpread = close - open BarRange = high - low R2 = ta.highest(2) - ta.lowest(2) SrcShift = ta.change(close) //TR = ta.tr(true) sign_shift = math.sign(SrcShift) sign_spread = math.sign(BarSpread) // ========================================================================================================= // in-bar assessments // ========================================================================================================= // 1. Calculate closing within bar - should be max value at either ends of the bar range barclosing = 2 * (close - low) / BarRange * 100 - 100 //plot(barclosing, "Bar Closing %" , color=color.fuchsia, display = display.none) // 2. caluclate spread to range ratio s2r = BarSpread / BarRange * 100 //plot(s2r, "Spread:Range", color = color.lime, display = display.none) // 3. Calculate relative spread compared to average spread during lookback BarSpread_abs = math.abs(BarSpread) BarSpread_avg = GetAverage(BarSpread_abs, lookback, lkbk_MA_Type) BarSpread_ratio_n = Normalize(BarSpread_abs, BarSpread_avg) * 100 * sign_spread //plot(BarSpread_ratio_n, "Bar Spread Ratio", color=color.orange, display=display.none) // ========================================================================================================= // 2-bar assessments // ========================================================================================================= // 4. Calculate closing within 2 bar range - should be max value at either ends of the 2-bar range barclosing_2 = 2 * (close - ta.lowest(2)) / R2 * 100 - 100 //plot(barclosing_2, "2-Bar Closing %" , color=color.navy, display = display.none) // 5. calculate 2-bar shift to range ratio Shift2Bar_toR2 = SrcShift / R2 * 100 //plot(Shift2Bar_toR2, "2-bar Shift vs 2R", color=color.yellow, display = display.none) // 6. Calculate 2-bar Relative Shift SrcShift_abs = math.abs(SrcShift) srcshift_avg = GetAverage(SrcShift_abs, lookback, lkbk_MA_Type) srcshift_ratio_n = Normalize(SrcShift_abs, srcshift_avg) * 100 * sign_shift //plot(srcshift_ratio_n, "2-bar Shift vs Avg", color=color.white, display = display.none) // =============================================================================== // ========================================================================================= // Relative Price Strength combining all strength elements Pricea_n = (barclosing + s2r + BarSpread_ratio_n + barclosing_2 + Shift2Bar_toR2 + srcshift_ratio_n) / 6 //plot(Pricea_n, "Price Normalized", color=color.orange, display = display.none) //Let's take Bar Flow as the combined price strength * the volume:avg ratio // this works in a similar way to a volume-weighted RSI bar_flow = Pricea_n * Vola_n / 100 //plot(bar_flow, 'bar_flow', color=color.green, display = display.none) // calc avergae relative rate of flow, then smooth the resulting average // classic formula would be this //RROF = f_ma(bar_flow, length, MA_Type) // // or we can create a relative index by separating bulls from bears, like in an RSI - my preferred method // here we have an added benefit of plotting the (average) bulls vs bears separately - as an option bulls = math.max(bar_flow, 0) bears = -1 * math.min(bar_flow, 0) bulls_avg = GetAverage(bulls, length, MA_Type) bears_avg = GetAverage(bears, length, MA_Type) dx = bulls_avg / bears_avg RROF = 2 * (100 - 100 / (1 + dx)) - 100 RROF_s = ta.wma(RROF, smooth) Signal = GetAverage(RROF_s, sig_length, S_Type) // Calculate Bias / sentiment on longer length dx_b = GetAverage(bulls, B_Length, B_Type) / GetAverage(bears, B_Length, B_Type) RROF_b = 2 * (100 - 100 / (1 + dx_b)) - 100 RROF_bs = ta.wma(RROF_b, smooth) // =========================================================================================================== // Colors & plots // =========================================================================================================== c_zero = color.new(#1163f6, 25) c_band = color.new(color.yellow, 40) c_up = color.aqua c_dn = color.orange c_sup = color.new(#00aa00, 70) c_sdn = color.new(#ff180b, 70) up = RROF_s >= 0 s_up = RROF_bs >=0 // ==================================== Plots ========================================================== // // Display the ATR & VOl Ratio values only on the indicator status line & in the Data Window // plotchar(shift, title = "Shift", char = "", color = color.white, editable=false, display=display.status_line + display.data_window) // plotchar(lbk_tr, title = "Avg Shift", char = "", color = color.aqua, editable=false, display=display.status_line + display.data_window) // plotchar(vola/lbk_vola, title = "Vol Ratio", char = "", color = color.yellow, editable=false, display=display.status_line + display.data_window) hline(0, 'Zero Line', c_zero, linestyle = hline.style_solid) // plot the band scale guide lines -- these lines will show/hide along with the EVEREX "Equalizer Bands Plot" hline(0.25 * bandscale, title = '1/4 Level', color=c_band, linestyle = hline.style_dotted, display = showhlines) hline(0.50 * bandscale, title = '2/4 Level', color=c_band, linestyle = hline.style_dotted, display = showhlines) hline(0.75 * bandscale, title = '3/4 Level', color=c_band, linestyle = hline.style_dotted, display = showhlines) hline(bandscale, title = '4/4 Level', color=c_band, linestyle = hline.style_dotted, display = showhlines) // Plot Bulls & Bears - these are optional plots and hidden by default - adjust this section later plot(ta.wma(bulls_avg, smooth), "Bulls", color = #11ff20, linewidth = 2, display = display.none) plot(ta.wma(bears_avg, smooth), "Bears", color = #d5180b, linewidth = 2, display = display.none) // ============================================================================= // Plot Bias / Sentiment plot (RROF_bs, "Bias / Sentiment", style=plot.style_area, color = s_up ? c_sup : c_sdn, linewidth = 4, display = DispBias ) // ============================================================================= // Plot Price Strength & Relative Volume as stacked "equalizer bands" // adding visualization option to make the bands joint or separate at the mid-scale mark Eq_band_option = input.string("Joint", title = 'Band Option', options = ["Joint", "Separate"], group = grp_4) nPrice = math.max(math.min(Pricea_n, 100), -100) nVol = math.max(math.min(Vola_n, 100), -100) bar = bar_flow c_vol_grn = color.new(#26a69a, 75) c_vol_red = color.new(#ef5350, 75) cb_vol_grn = color.new(#26a69a, 20) cb_vol_red = color.new(#ef5350, 20) c_vol = bar > 0 ? c_vol_grn : c_vol_red cb_vol = bar > 0 ? cb_vol_grn : cb_vol_red vc_lo = 0 vc_hi = nVol * bandscale / 100 / 2 plotcandle(vc_lo, vc_hi, vc_lo, vc_hi , "Volume Band", c_vol, c_vol, bordercolor = cb_vol, display = DispBands) c_pri_grn = color.new(#3ed73e, 75) c_pri_red = color.new(#ff870a, 75) cb_pri_grn = color.new(#3ed73e, 20) cb_pri_red = color.new(#ff870a, 20) c_pri = bar > 0 ? c_pri_grn : c_pri_red cb_pri = bar > 0 ? cb_pri_grn : cb_pri_red pc_lo_base = Eq_band_option == "Joint" ? vc_hi : 0.50 * bandscale pc_lo = pc_lo_base pc_hi = pc_lo_base + math.abs(nPrice) * bandscale / 100 / 2 plotcandle(pc_lo, pc_hi, pc_lo ,pc_hi , "Price Band", c_pri, c_pri, bordercolor = cb_pri, display = DispBands) // print the normalized volume and price values - only on statys line and in the data window // these values are independant of the band scale or visualization options plotchar(nVol, "Normalized Vol", char = "", color = c_vol, editable = false, display = Disp_vals) plotchar(nPrice, "Normalized Price", char = "", color = c_pri, editable = false, display = Disp_vals) // ============================================================================= // ============================================================================= // Plot main plot, smoothed plot and signal line plot(RROF, 'RROF Raw', color.new(#2470f0, 9), display=display.none) plot(RROF_s, 'RROF Smooth', color = color.new(#b2b5be,40), linewidth = 2) plot(Signal, "Signal Line", up ? c_up : c_dn, 3) // =========================================================================================================== // basic alerts // =========================================================================================================== Alert_up = ta.crossover(RROF_s,0) Alert_dn = ta.crossunder(RROF_s,0) Alert_swing = ta.cross(RROF_s,0) // "." in alert title for the alerts to show in the right order up/down/swing alertcondition(Alert_up, ". RROF Crossing 0 Up", "RROF Up - Buying Action Detected!") alertcondition(Alert_dn, ".. RROF Crossing 0 Down", "RROF Down - Selling Action Detected!") alertcondition(Alert_swing, "... RROF Crossing 0", "RROF Swing - Possible Reversal") // =========================================================================================================== // v2.0 Adding Markers for Key Patterns // =========================================================================================================== // we can re-utilize the Normailize() function here too - but it's cleaner to have a separate ratio calc nPrice_abs = math.abs(nPrice) //EV_Ratio = 100 * Normalize(nPrice_abs, nVol) EV_Ratio = 100 * nPrice_abs / nVol // initial mapping of return ratios (to be revised) // ------------------------------------------------------- // Case (1): Price > Vol => ratio > 120 = Ease of Move (EoM) // Case (2): Price close to Vol => ratio between 80 - 120 = Reasonable Balance // Case (3): Price less than Vol but reasonable => ratio between 80 - 50 = Drift / "nothing much to see here" bar // Case (4): Price a lot less than Vol => 50 or less = Compression / Squat // we're most interested in cases 1 & 4 //plot (EV_Ratio) // for validation only is_positive = nPrice > 0 is_Compression = EV_Ratio <= 50 is_EoM = EV_Ratio >= 120 //Provide option to show/hide those EVEREX Markers - and an option for Compression bar // - some folks would prefer a cross, others may prefer a circle - can adjust based on feedback // no option for Ease of Move, guessing the triangle has the right significance var showMarkers = input.bool(true, 'Show EVEREX Markers ?') var Mshape = input.string("Circles", "Compression Marker", options = ['Circles','Crosses']) SetShape(_x) => switch _x 'Circles' => shape.circle 'Crosses' => shape.cross // Plot markers plotshape(showMarkers and is_EoM and is_positive ? 0 : na, "EoM +ve", shape.triangleup, color=color.green, location=location.absolute, size=size.auto, editable = false, display = display.pane) plotshape(showMarkers and is_EoM and not(is_positive) ? 0 : na, "EoM -ve", shape.triangledown, color=color.red, location=location.absolute, size=size.auto, editable = false, display = display.pane) plotshape(showMarkers and is_Compression and is_positive ? 0 : na, "Compression +ve", style = SetShape(Mshape), color=color.green, location=location.absolute, size = size.auto, editable = false, display = display.pane) plotshape(showMarkers and is_Compression and not(is_positive) ? 0 : na, "Compression -ve", style = SetShape(Mshape), color=color.red, location=location.absolute, size=size.auto, editable = false, display = display.pane)

안녕하세요~늘 훌륭한 답변에 진심으로 감사드리며 다음과 같이 문의드립니다. 초보입니다. if GetAccount(0)=="200-00-000000" Then { if 진입조건 then Buy("B",OnClose, Def,1); } 가령 이런식으로 산식에 계좌를 특정할 수 있는지요? 실시간 그리고 전략실행차트 상에서 만 가능한가요? 안되네요. 산식에서 계좌를 특정할 수 있는 방법이 있으면 부탁드립니다. 감사합니다~

highest(v(1),200)<v and highest(h,3) 여기서 200 수치는 period(기간)입니다.. 위수식은 키움분봉상신호검색인데 예스에서 분봉기준 종목검색 부탁드립니다...

안녕하세요. 아래 수식에서 TL_SetColor(TL1,Red); TL_SetColor(TL2,magenta); TL_SetColor(TL3,Gray); 라인 두깨를 표기할 수 있도록 부탁드립니다. 거듭 감사드립니다. 좋은 시간되세요. =========================== input : P1(2),P2(3),P3(5); var : cnt(0),d1(0); var : sum1(0),sum2(0),sum3(0),mav1(0),mav2(0),mav3(0); var : TL1(0),TL2(0),TL3(0); Array : C2[100](0); if data2(Bdate != Bdate[1]) Then { For cnt = 99 DownTo 1 { C2[cnt] = C2[cnt-1]; TL_Delete(TL1[cnt]); TL_Delete(TL2[cnt]); TL_Delete(TL3[cnt]); } C2[0] = Data2(c); sum1 = 0; sum2 = 0; sum3 = 0; For cnt = 0 to max(P1,P2,P3) { if cnt < P1 Then sum1 = sum1 + C2[cnt]; if cnt < P2 Then sum2 = sum3 + C2[cnt]; if cnt < P3 Then sum3 = sum3 + C2[cnt]; } mav1 = sum1/P1; mav2 = sum2/P2; mav3 = sum3/P3; d1 = Data2(Bdate[1]); TL1 = TL_New_Self(d1,150000,mav1,sDate,sTime,mav1); TL2 = TL_New_Self(d1,150000,mav2,sDate,sTime,mav2); TL3 = TL_New_Self(d1,150000,mav3,sDate,sTime,mav3); TL_SetColor(TL1,Red); TL_SetColor(TL2,magenta); TL_SetColor(TL3,Gray); } Else { C2[0] = Data2(c); TL_SetEnd(TL1,NextBarSdate,NextBarStime,mav1); TL_SetEnd(TL2,NextBarSdate,NextBarStime,mav2); TL_SetEnd(TL3,NextBarSdate,NextBarStime,mav3); } Plot1(Data2(OpenD(0)),"시가라인");

선물시간 8시45분 시작으로 기존 사용하던 수식에 오류가 생겼습니다. input : d2(1000); if Data2(c>lowd(0)+d2) Then Buy(); 기존에는 위 수식으로 아래 내용을 모두 해결하였는데 data1 코스피200선물 data2 외인주식순매수금액 data1 코스피200선물 data2 외인선물순매수금액 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 문제가 발생하였습니다. data1 코스피200선물 084500(3분봉) 시작 data2 외인주식순매수금액 090000(3분봉) 시작 코스피선물과 외인주식순매수금액이 시작하는 시간이 다르기 때문에 8시45분 첫봉에서 이유 없이 진입하는 경우가 자주 발생합니다. 외인주식순매수금액 봉이 9시부터 발생하므로 그 이후부터 계산하여 진입할 수 있도록 수정바랍니다. 요청사항 1. 수정할 수식입니다.(d2는 외국인주식순매수금액) input : d2(1000); if Data2(c>lowd(0)+d2) Then Buy(); 요청사항 2. 외국인순매수금액을 제외조건에 사용한 수식에서도 영향이 있을 것 같아서 추가로 수정 요청드리는 수식입니다. (d2는 외국인주식순매수금액) input : d3(1000),d2(500); if Data3(c>lowd(0)+d3) and !(data2(c<highd(0)-d2)) Then Buy();

1번: LowestSince 사용자 함수 좀 부탁 드릴께요. 2번: M2 = ma(C,1); M20 = ma(C,5); HH = LowestSince(1,CrossDown(M2,M20), M2); if( M2 != HH && M2 > M20, HH, 0) 첫 조건에 만족이 되어서 표시가 되는 종목을 찾고 싶습니다. 부탁 드릴께요..

안녕하세요 수식부탁드링니다 볼밴 상하한선 가격이 100틱이내에서 10캔들이내 횡보한후 매수 볼밴 상선돌파시 매수 볼밴 하선돌파시 매도 청산 손절 매수 볼밴중심선 돌파하락시 매도 볼밴중심선 돌파상승시 위조건으로 손절청산 한후 중심선 재돌파시 재매수 종심선 재하락시 재매도 일일 누적수익 100틱 매매스톱