안녕하세요 예스스탁입니다. 삼성전자나 코스피 지수에 적용해 보면 트레이딩뷰와 동일하게 그려지고 있습니다. 아마 데이터에 따른 차이가 있는 것 같은데 정확히 해당식 수식상 어느 부분이 다른지 모르겠습니다. 즐거운 하루되세요 > 해암 님이 쓴 글입니다. > 제목 : 문의드립니다. > 필요한 수식을 검색하던 중 이전에 어떤 분이 요청한 수식에 대한 답변(92732번)을 아래와 같이 주셔서 적용해봤는데(같은 기간값적용) 첨부된 그림과 같이 트레이딩뷰와 다른 부분이 나옵니다. 번거로우시겠지만 다시한번 검토해주시면 감사하겠습니다. 매번 도움을 받아서 감사드립니다.!!! ============================= 지표라인만 작성해 드립니다. 나머지 부가적인 표시들은 업무상 시간이 많이 소모되어 추가해 드리기 어렵습니다. input : vidya_length(10); input : vidya_momentum(20); input : band_distance(2); input : up_trend_color(Green); input : down_trend_color(Red); input : shadow(true); var : pivot_left_bars(3),pivot_right_bars(0),source(0); var : pivot_line(Nan); var : volume_value(Nan); var : smoothed_value(Nan); var : is_trend_up(False); var : up_trend_volume(False); var : down_trend_volume(Nan); Array : liquidity_lines_low[500](0),liquidity_lines_high[500](0); pivot_left_bars = 3; pivot_right_bars = 3; source = close; var : al(0),atr_value(0); al = 1/200; atr_value = IFf(IsNan(atr_value[1]) == true,ma(TrueRange, 200) , al * TrueRange + (1 - al) * IFf(IsNaN(atr_value[1])==true,0,atr_value[1])); var : momentum(0),sum_pos_momentum(0),sum_neg_momentum(0),abs_cmo(0),alpha(0),vidya_v(0),vidya_value(0); momentum = source-source[1]; sum_pos_momentum = AccumN(IFf(momentum >= 0, momentum , 0), vidya_momentum); sum_neg_momentum = AccumN(IFf(momentum >= 0, 0, -momentum), vidya_momentum); abs_cmo = abs(100 * (sum_pos_momentum - sum_neg_momentum) / (sum_pos_momentum + sum_neg_momentum)); alpha = 2 / (vidya_length + 1); vidya_v = alpha * abs_cmo / 100 * source + (1 - alpha * abs_cmo / 100) * iff(IsNan(vidya_v[1])==true,0,vidya_v[1]); vidya_value = ma(vidya_v, 15); var : upper_band(0),lower_band(0); upper_band = vidya_value + atr_value * band_distance; lower_band = vidya_value - atr_value * band_distance; // Detect trend direction using crossovers of source with bands if CrossUp(source, upper_band) Then is_trend_up = true ; if CrossDown(source, lower_band) Then is_trend_up = false ; // Set trend-based smoothing variable if is_trend_up == true Then smoothed_value = lower_band; if is_trend_up == False Then smoothed_value = upper_band; if is_trend_up != is_trend_up[1] Then smoothed_value = Nan; // Calculate pivot highs and lows for price action var : pivot_high(0),pivot_low(0); pivot_high = SwingHigh(1,high,pivot_left_bars, pivot_right_bars,pivot_left_bars+pivot_right_bars+1); pivot_low = SwingLow(1, close, pivot_left_bars, pivot_right_bars,pivot_left_bars+pivot_right_bars+1); if smoothed_value > 0 Then plot1(smoothed_value,"smoothed_value",iff(is_trend_up , up_trend_color ,down_trend_color)); Else NoPlot(1); var : tx(0); if is_trend_up == is_trend_up[1] and is_trend_up[1] != is_trend_up[2] Then { if is_trend_up == true Then { tx = Text_New(sDate,sTime,smoothed_value,"▲"); Text_SetStyle(tx,2,0); Text_SetColor(tx,up_trend_color); Text_SetSize(tx,20); } if is_trend_up == False Then { tx = Text_New(sDate,sTime,smoothed_value,"▼"); Text_SetStyle(tx,2,1); Text_SetColor(tx,down_trend_color); Text_SetSize(tx,20); } } ================ 트레이딩뷰 수식 //@version=6 indicator('Volumatic Variable Index Dynamic Average [BigBeluga]', 'Volumatic VIDYA [BigBeluga]', overlay = true, max_lines_count = 500, max_labels_count = 500) // ＩＮＰＵＴＳ ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――{ // Input parameters for length, momentum, and source data int vidya_length = input.int(10, 'VIDYA Length') // Length of the VIDYA calculation int vidya_momentum = input.int(20, 'VIDYA Momentum') // Momentum length for VIDYA float band_distance = input.float(2, 'Distance factor for upper/lower bands', step = 0.1) // Distance factor for upper/lower bands // Define pivot parameters int pivot_left_bars = 3 // Left side pivot bars int pivot_right_bars = pivot_left_bars // Right side pivot bars float source = input.source(close, 'Source') // Source for VIDYA calculation // Define colors for up and down trends color up_trend_color = input(#17dfad, '+', group = 'Color', inline = 'c') // Color for uptrend color down_trend_color = input(#dd326b, '-', group = 'Color', inline = 'c') // Color for downtrend bool shadow = input.bool(true, 'Shadow', group = 'Color', inline = 'c') // Initialize variables for line, volume, and trend state var line pivot_line = na // Variable for storing line references var float volume_value = na // Variable for storing volume data float smoothed_value = na // Smoothing variable for VIDYA trend levels var bool is_trend_up = false // Boolean variable for tracking trend direction // Initialize arrays for storing line and volume information var array<line> liquidity_lines_low = array.new<line>(500) // Array for storing lines for lows var array<line> liquidity_lines_high = array.new<line>(500) // Array for storing lines for highs var float up_trend_volume = na // Volume accumulated during uptrend var float down_trend_volume = na // Volume accumulated during downtrend // } // ＦＵＮＣＴＩＯＮＳ―――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――{ // Define VIDYA (Variable Index Dynamic Average) function vidya_calc(src, vidya_length, vidya_momentum) => float momentum = ta.change(src) float sum_pos_momentum = math.sum(momentum >= 0 ? momentum : 0.0, vidya_momentum) float sum_neg_momentum = math.sum(momentum >= 0 ? 0.0 : -momentum, vidya_momentum) float abs_cmo = math.abs(100 * (sum_pos_momentum - sum_neg_momentum) / (sum_pos_momentum + sum_neg_momentum)) float alpha = 2 / (vidya_length + 1) var float vidya_value = 0.0 vidya_value := alpha * abs_cmo / 100 * src + (1 - alpha * abs_cmo / 100) * nz(vidya_value[1]) ta.sma(vidya_value, 15) // Method to extend lines and add labels for liquidity levels method extend_liquidity_lines(array<line> line_array, float price_level, bool is_cross, volume_val) => if line_array.size() > 0 and last_bar_index - bar_index < 5000 for i = 0 to line_array.size() - 1 by 1 if i < line_array.size() line liquidity_line = line_array.get(i) float current_line_level = line.get_y2(liquidity_line) bool price_cross = is_cross ? price_level < current_line_level and price_level[1] >= current_line_level : price_level > current_line_level and price_level[1] <= current_line_level bool is_short_line = bar_index - line.get_x1(liquidity_line) < 50 if price_cross and is_short_line line.set_x2(liquidity_line, bar_index) line_array.remove(i) // Add volume label to the liquidity zone label.new(bar_index - 1, price_level[1], str.tostring(volume_val, format.volume), color = color.rgb(0, 0, 0, 99), style = is_cross ? label.style_label_lower_left : label.style_label_upper_left, textcolor = chart.fg_color, size = size.small) // Add a circle label to represent liquidity zone label.new(bar_index - 1, price_level[1], text = '&#9673;', color = #00000003, textcolor = is_cross ? down_trend_color : up_trend_color, style = label.style_label_center, size = size.normal) // } // ＣＡＬＣＵＬＡＴＩＯＮＳ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――{ // Calculate the Average True Range (ATR) float atr_value = ta.atr(200) // ATR calculation with length of 200 // Calculate the VIDYA (Variable Index Dynamic Average) vidya_value = vidya_calc(source, vidya_length, vidya_momentum) // Calculate upper and lower bands based on VIDYA and ATR float upper_band = vidya_value + atr_value * band_distance float lower_band = vidya_value - atr_value * band_distance // Detect trend direction using crossovers of source with bands if ta.crossover(source, upper_band) is_trend_up := true is_trend_up if ta.crossunder(source, lower_band) is_trend_up := false is_trend_up // Set trend-based smoothing variable if is_trend_up smoothed_value := lower_band smoothed_value if not is_trend_up smoothed_value := upper_band smoothed_value if ta.change(is_trend_up) smoothed_value := na smoothed_value // Calculate pivot highs and lows for price action bool pivot_high = not na(ta.pivothigh(pivot_left_bars, pivot_right_bars)) bool pivot_low = not na(ta.pivotlow(close, pivot_left_bars, pivot_right_bars)) // Create and store lines for pivot lows (support zones) if low[pivot_right_bars] > smoothed_value and pivot_low pivot_line := line.new(bar_index[pivot_right_bars], low[pivot_right_bars], bar_index[pivot_right_bars] + 5, low[pivot_right_bars], color = color.new(up_trend_color, 50)) liquidity_lines_low.push(pivot_line) volume_value := math.sum(volume, pivot_right_bars + pivot_left_bars) / (pivot_right_bars + pivot_left_bars) volume_value // Create and store lines for pivot highs (resistance zones) if high[pivot_right_bars] < smoothed_value and pivot_high pivot_line := line.new(bar_index[pivot_right_bars], high[pivot_right_bars], bar_index[pivot_right_bars] + 5, high[pivot_right_bars], color = color.new(down_trend_color, 50)) liquidity_lines_high.push(pivot_line) volume_value := math.sum(-volume, pivot_right_bars + pivot_left_bars) / (pivot_right_bars + pivot_left_bars) volume_value // Extend lines to track price movements liquidity_lines_high.extend_liquidity_lines(smoothed_value, true, volume_value) liquidity_lines_low.extend_liquidity_lines(smoothed_value, false, volume_value) // Detect changes in the trend direction bool trend_cross_up = not is_trend_up[1] and is_trend_up bool trend_cross_down = not is_trend_up and is_trend_up[1] // Reset volume counters when trend changes if ta.change(trend_cross_up) or ta.change(trend_cross_down) up_trend_volume := 0 down_trend_volume := 0 down_trend_volume // Accumulate volume during trends if not(ta.change(trend_cross_up) or ta.change(trend_cross_down)) up_trend_volume := up_trend_volume + (close > open ? volume : 0) down_trend_volume := down_trend_volume + (close < open ? volume : 0) down_trend_volume // Calculate average volume float avg_volume_delta = (up_trend_volume + down_trend_volume) / 2 // Determine the color of the trend color trend_color = is_trend_up ? up_trend_color : not is_trend_up ? down_trend_color : chart.fg_color // Calculate delta volume percentage string delta_volume = str.tostring((up_trend_volume - down_trend_volume) / avg_volume_delta * 100, format.percent) == 'NaN%' ? '0%' : str.tostring((up_trend_volume - down_trend_volume) / avg_volume_delta * 100, format.percent) // } // ＰＬＯＴ ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――{ // Display labels for volume and trend statistics on the last bar if barstate.islast label.delete(label.new(bar_index, smoothed_value, 'Buy: ' + str.tostring(up_trend_volume, format.volume) + '￦n Sell: ' + str.tostring(down_trend_volume, format.volume) + '￦nDelta Volume: ' + delta_volume, color = color.new(trend_color, 90), style = is_trend_up ? label.style_label_upper_left : label.style_label_lower_left, textcolor = chart.fg_color)[1]) label.delete(label.new(bar_index, smoothed_value, text = '&#10026;', color = #00000003, textcolor = trend_color, style = label.style_label_center, size = size.large)[1]) // Plot the VIDYA trend line p1 = plot(smoothed_value, color = trend_color, linewidth = 2, style = plot.style_linebr) p2 = plot(hl2, display = display.none) // Fill between the plot and the VIDYA line fill(p1, p2, smoothed_value, hl2, color.new(trend_color, shadow ? 80 : 100), na) // Plot trend change markers (up and down arrows) plotshape(series = trend_cross_up[1] ? smoothed_value[0] : na, title = 'Trend Up', style = shape.labelup, location = location.absolute, color = color.new(up_trend_color, 50), text = '▲', textcolor = chart.fg_color) plotshape(series = trend_cross_down[1] ? smoothed_value[0] : na, title = 'Trend Down', style = shape.labeldown, location = location.absolute, color = color.new(down_trend_color, 50), text = '▼', textcolor = chart.fg_color) // }