CONVERSION INDICADOR TRADINGVIEW:Regression Indicator

• 09/03/2024 at 1:38 PM #237045
  Fr7

  Solicito, si es posible, convertir el indicador adjunto:

  Descripción general del indicador:
  El indicador de regresión está diseñado para ayudar a los operadores a identificar tendencias y posibles reversiones en los movimientos de precios. Al calcular una línea de regresión y un indicador de regresión normalizado, proporciona señales visuales claras para la dirección del mercado, lo que ayuda a tomar decisiones comerciales informadas. El indicador se actualiza dinámicamente con los últimos datos del mercado, lo que garantiza señales oportunas y relevantes.

  https://es.tradingview.com/script/rFrilcDi-Regression-Indicator-BigBeluga/
  A ver si Iván el moderador tiene un hueco libre y lo puede traducir.
  Muchas gracias.

  

  Fr7

  Participant

  Topics: 51

  Replies: 160

  Been thanked: 21 times
  09/03/2024 at 1:39 PM #237046
  Fr7

  // This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
  // © BigBeluga

  //@version=5
  indicator(“Regression Indicator [BigBeluga]”, overlay = false, max_bars_back = 500)

  // =====================================================================================================================}
  // ＩＮＰＵＴＳ
  // ====================================================================================================================={

  int length = input.int(400, “Regression Length”)
  int length1 = input.int(100, “Regression Normalization”)
  int length2 = input.int(50, “Signal Line”)

  color m_color = #049ef7

  // =====================================================================================================================}
  // ＣＡＬＣＵＬＡＴＩＯＮＳ
  // ====================================================================================================================={

  // @function regression_indicator is a Normalized Ratio of Regression Lines with close
  regression_indicator(src, length) =>
  sum_x = 0.0
  sum_y = 0.0
  sum_xy = 0.0
  sum_x_sq = 0.0
  distance = 0.0
  // Calculate Sum
  for i = 0 to length – 1 by 1
  sum_x += i + 1
  sum_y += src[i]
  sum_xy += (i + 1) * src[i]
  sum_x_sq += math.pow(i + 1, 2)

  // Calculate linear regression coefficients
  slope = (length * sum_xy – sum_x * sum_y)
  / (length * sum_x_sq – math.pow(sum_x, 2))
  intercept = (sum_y – slope * sum_x) / length

  // Calculate Regression Indicator
  y1 = intercept + slope
  distance := (close – y1)
  distance_n = ta.sma((distance – ta.sma(distance, length1))
  / ta.stdev(distance, length1), 10)

  [distance_n, y1]

  [y, y1] = regression_indicator(close, length)

  // Signal Lines
  mean = ta.sma(y, length2)
  mean1 = ta.ema(y, 5)
  // Conditions
  cond1 = ta.crossunder(mean1, mean) and y > 0
  cond2 = ta.crossover(mean1, mean) and y < 0
  cond3 = ta.crossover(y, 0)
  cond4 = ta.crossunder(y, 0)

  // =====================================================================================================================}
  // ＰＬＯＴ
  // ====================================================================================================================={
  // Candles Colors
  color = y > 0 ? color.from_gradient(y, 0, 1, na, m_color) : color.from_gradient(y, -1, 0, chart.fg_color, na)

  barcolor(color)
  plotcandle(open, high, low, close, “Color Candles”,
  color = color,
  wickcolor = color,
  bordercolor = color,
  force_overlay = true
  )

  // Plot Regression Line
  plot(series = y1,
  title = “Regression Line”,
  color = color,
  linewidth = 2,
  force_overlay = true
  )
  // Plot Regression Indicator
  p1 = plot(series = y,
  title = “Regression Indicator”,
  color = color,
  linewidth = 1
  )

  p0 = plot(series = 0,
  title = “Zero Line”,
  color = color,
  linewidth = 1
  )

  // Fill Color Regression Indicator
  fill(p1, p0, 2.5, 0, m_color, na, title = “Upper Fill”)
  fill(p1, p0, 0, -2.5, na, chart.fg_color, title = “Lower Fill”)

  // Signal Line
  plot(mean, color = color.rgb(3, 100, 165, 52), linewidth = 2)

  // Arrow Trend Direction
  var txt = “”
  switch
  cond3 => txt := “➚”
  cond4 => txt := “➘”

  if barstate.islast
  label.delete(
  label.new(
  x = bar_index+3,
  y = y1,
  text = txt,
  style = label.style_label_center,
  color = color(na),
  textcolor = color,
  size = size.huge,
  force_overlay = true
  )[1]
  )

  // Reversion Signals
  if cond1
  label.new(
  x = bar_index,
  y = high,
  text = “◓”,
  style = label.style_label_down,
  color = color(na),
  textcolor = chart.fg_color,
  size = size.large,
  force_overlay = true
  )

  if cond2
  label.new(
  x = bar_index,
  y = low,
  text = “◒”,
  style = label.style_label_up,
  color = color(na),
  textcolor = m_color,
  size = size.large,
  force_overlay = true
  )

  // Trend Signals
  plotchar(cond3 ? 0 : na, “TrendUp”, “⦿”,
  location = location.absolute,
  size = size.small,
  color = #0364a5
  )
  plotchar(cond3 ? close : na, “TrendUp”, “⦿”,
  location = location.absolute,
  size = size.small,
  color = #0364a5,
  force_overlay = true
  )

  plotchar(cond4 ? 0 : na, “TrendDn”, “⦿”,
  location = location.absolute,
  size = size.small,
  color = chart.fg_color
  )
  plotchar(cond4 ? close : na, “TrendDn”, “⦿”,
  location = location.absolute,
  size = size.small,
  color = chart.fg_color,
  force_overlay = true
  )

  // =====================================================================================================================}

   

  

  Fr7

  Participant

  Topics: 51

  Replies: 160

  Been thanked: 21 times
  09/05/2024 at 9:30 AM #237117
  Iván

  Buenas! Aquí tienes la traducción

  //-------------------------------------------------------// //PRC_Regression Oscilator //version = 0 //05.09.2024 //Iván González @ www.prorealcode.com //Sharing ProRealTime knowledge //-------------------------------------------------------// //-----Inputs--------------------------------------------// //-------------------------------------------------------// length=400 //regression Length length1=100 //regression normalization length2=50 //signal lane //-------------------------------------------------------// //-----Regression Calculation----------------------------// //-------------------------------------------------------// src=close sumx=0 sumy=0 sumxy=0 sumxsq=0 distance=0 //Calculate sum for i=0 to length-1 do sumx=sumx+i+1 sumy=sumy+src[i] sumxy=sumxy+(i+1)*src[i] sumxsq=sumxsq+pow(i+1,2) next //Calculate linear regression coefficients slope=(length*sumxy-sumx*sumy)/(length*sumxsq-pow(sumx,2)) intercept=(sumy-slope*sumx)/length //Calculate Regression indicator y1=intercept+slope distance=(close-y1) distanceN=average[10]((distance-average[length1](distance))/std[length1](distance)) //-------------------------------------------------------// //-----Signal Lines--------------------------------------// //-------------------------------------------------------// y=distanceN mean=average[length2](y) mean1=average[5](y) //-------------------------------------------------------// //-----Conditions----------------------------------------// //-------------------------------------------------------// cond1=mean1 crosses under mean and y>0 cond2=mean1 crosses over mean and y<0 cond3=y crosses over 0 cond4=y crosses under 0 //-------------------------------------------------------// //-----Plot----------------------------------------------// //-------------------------------------------------------// if y>0 then r=0 g=255 b=255 else r=255 g=0 b=255 endif //Reversion Signals if cond1 then drawtext("▼",barindex,mean)coloured("fuchsia") elsif cond2 then drawtext("▲",barindex,mean)coloured(0,255,255) endif //Trend Signals if cond3 then drawpoint(barindex,0,3)coloured("lightgreen") elsif cond4 then drawpoint(barindex,0,3)coloured("red") endif //-------------------------------------------------------// return y as "Regression Line" coloured(r,g,b)style(line,3), 0 as "Zero" style(dottedline), mean as "mean"coloured(3,100,165)style(line,2)

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  //-------------------------------------------------------// //PRC_Regression Oscilator //version = 0 //05.09.2024 //Iván González @ www.prorealcode.com //Sharing ProRealTime knowledge //-------------------------------------------------------// //-----Inputs--------------------------------------------// //-------------------------------------------------------// length=400 //regression Length length1=100 //regression normalization length2=50 //signal lane //-------------------------------------------------------// //-----Regression Calculation----------------------------// //-------------------------------------------------------// src=close sumx=0 sumy=0 sumxy=0 sumxsq=0 distance=0 //Calculate sum for i=0 to length-1 do sumx=sumx+i+1 sumy=sumy+src[i] sumxy=sumxy+(i+1)*src[i] sumxsq=sumxsq+pow(i+1,2) next //Calculate linear regression coefficients slope=(length*sumxy-sumx*sumy)/(length*sumxsq-pow(sumx,2)) intercept=(sumy-slope*sumx)/length //Calculate Regression indicator y1=intercept+slope distance=(close-y1) distanceN=average[10]((distance-average[length1](distance))/std[length1](distance)) //-------------------------------------------------------// //-----Signal Lines--------------------------------------// //-------------------------------------------------------// y=distanceN mean=average[length2](y) mean1=average[5](y) //-------------------------------------------------------// //-----Conditions----------------------------------------// //-------------------------------------------------------// cond1=mean1 crosses under mean and y>0 cond2=mean1 crosses over mean and y<0 cond3=y crosses over 0 cond4=y crosses under 0 //-------------------------------------------------------// //-----Plot----------------------------------------------// //-------------------------------------------------------// if y>0 then r=0 g=255 b=255 else r=255 g=0 b=255 endif //Reversion Signals if cond1 then drawtext("▼",barindex,mean)coloured("fuchsia") elsif cond2 then drawtext("▲",barindex,mean)coloured(0,255,255) endif //Trend Signals if cond3 then drawpoint(barindex,0,3)coloured("lightgreen") elsif cond4 then drawpoint(barindex,0,3)coloured("red") endif //-------------------------------------------------------// return y as "Regression Line" coloured(r,g,b)style(line,3), 0 as "Zero" style(dottedline), mean as "mean"coloured(3,100,165)style(line,2)

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  Fr7

  

  Iván

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  09/05/2024 at 9:38 AM #237118
  Iván

  Y este sería el mismo indicador pero en precio

  //-------------------------------------------------------// //PRC_Regression Oscilator on Price //version = 0 //05.09.2024 //Iván González @ www.prorealcode.com //Sharing ProRealTime knowledge //-------------------------------------------------------// //-----Inputs--------------------------------------------// //-------------------------------------------------------// length=400 //regression Length length1=100 //regression normalization length2=50 //signal lane colorcandle=1 trendsignal=1 revsignal=1 //-------------------------------------------------------// //-----Regression Calculation----------------------------// //-------------------------------------------------------// src=close sumx=0 sumy=0 sumxy=0 sumxsq=0 distance=0 //Calculate sum for i=0 to length-1 do sumx=sumx+i+1 sumy=sumy+src[i] sumxy=sumxy+(i+1)*src[i] sumxsq=sumxsq+pow(i+1,2) next //Calculate linear regression coefficients slope=(length*sumxy-sumx*sumy)/(length*sumxsq-pow(sumx,2)) intercept=(sumy-slope*sumx)/length //Calculate Regression indicator y1=intercept+slope distance=(close-y1) distanceN=average[10]((distance-average[length1](distance))/std[length1](distance)) //-------------------------------------------------------// //-----Signal Lines--------------------------------------// //-------------------------------------------------------// y=distanceN mean=average[length2](y) mean1=average[5](y) //-------------------------------------------------------// //-----Conditions----------------------------------------// //-------------------------------------------------------// cond1=mean1 crosses under mean and y>0 cond2=mean1 crosses over mean and y<0 cond3=y crosses over 0 cond4=y crosses under 0 //-------------------------------------------------------// //-----Plot----------------------------------------------// //-------------------------------------------------------// if y>0 then r=0 g=255 b=255 else r=255 g=0 b=255 endif //Reversion Signals if revsignal and cond1 then drawtext("▼",barindex,high+0.25*tr)coloured("fuchsia") elsif revsignal and cond2 then drawtext("▲",barindex,low-0.25*tr)coloured(0,255,255) endif //Trend Signals if trendsignal and cond3 then drawpoint(barindex,close,3)coloured("lightgreen") elsif trendsignal and cond4 then drawpoint(barindex,close,3)coloured("red") endif //Draw candles if colorcandle then drawcandle(open,high,low,close)coloured(r,g,b,150) endif //-------------------------------------------------------// return y1 as "Regression Line" coloured(r,g,b)style(line,3)

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  //-------------------------------------------------------// //PRC_Regression Oscilator on Price //version = 0 //05.09.2024 //Iván González @ www.prorealcode.com //Sharing ProRealTime knowledge //-------------------------------------------------------// //-----Inputs--------------------------------------------// //-------------------------------------------------------// length=400 //regression Length length1=100 //regression normalization length2=50 //signal lane colorcandle=1 trendsignal=1 revsignal=1 //-------------------------------------------------------// //-----Regression Calculation----------------------------// //-------------------------------------------------------// src=close sumx=0 sumy=0 sumxy=0 sumxsq=0 distance=0 //Calculate sum for i=0 to length-1 do sumx=sumx+i+1 sumy=sumy+src[i] sumxy=sumxy+(i+1)*src[i] sumxsq=sumxsq+pow(i+1,2) next //Calculate linear regression coefficients slope=(length*sumxy-sumx*sumy)/(length*sumxsq-pow(sumx,2)) intercept=(sumy-slope*sumx)/length //Calculate Regression indicator y1=intercept+slope distance=(close-y1) distanceN=average[10]((distance-average[length1](distance))/std[length1](distance)) //-------------------------------------------------------// //-----Signal Lines--------------------------------------// //-------------------------------------------------------// y=distanceN mean=average[length2](y) mean1=average[5](y) //-------------------------------------------------------// //-----Conditions----------------------------------------// //-------------------------------------------------------// cond1=mean1 crosses under mean and y>0 cond2=mean1 crosses over mean and y<0 cond3=y crosses over 0 cond4=y crosses under 0 //-------------------------------------------------------// //-----Plot----------------------------------------------// //-------------------------------------------------------// if y>0 then r=0 g=255 b=255 else r=255 g=0 b=255 endif //Reversion Signals if revsignal and cond1 then drawtext("▼",barindex,high+0.25*tr)coloured("fuchsia") elsif revsignal and cond2 then drawtext("▲",barindex,low-0.25*tr)coloured(0,255,255) endif //Trend Signals if trendsignal and cond3 then drawpoint(barindex,close,3)coloured("lightgreen") elsif trendsignal and cond4 then drawpoint(barindex,close,3)coloured("red") endif //Draw candles if colorcandle then drawcandle(open,high,low,close)coloured(r,g,b,150) endif //-------------------------------------------------------// return y1 as "Regression Line" coloured(r,g,b)style(line,3)

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  Fr7

  

  Iván

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