//@version=5 indicator('Linear Regression Channel', overlay = true, max_lines_count = 3) // ---------------------------------------------------------------------------------------------------------------------} // 𝙐𝙎𝙀𝙍 𝙄𝙉𝙋𝙐𝙏𝙎 // ---------------------------------------------------------------------------------------------------------------------{ bool bands      = input.bool(true, "Plot Linear Regression Bands", group = "Settings Bands") int window      = input.int(150, "Length", group = "Settings Bands") float devlen_b  = input.float(3., "Deviation Linear Regression Bands",step=0.1, group = "Settings Bands") bool channel    = input.bool(false, "Plot Linear Regression Channel", group = "Settings Channel") int window1     = input.int(150, "Channel Length", group = "Settings Channel") float devlen1   = input.float(1., "Deviation Linear Regression Channel",step=0.1, group = "Settings Channel") bool channel1   = input.bool(false, "Plot Future Projection of linear regression", group = "Future Projection Channel") bool arr_dirc   = input.bool(false, "Plot Arrow Direction", group = "Future Projection Channel") int window2     = input.int(50, "Length", group = "Future Projection Channel") float devlen2   = input.float(1., "Deviation Future Projection Regression Channel",step=0.1, group = "Future Projection Channel") // Define colors for up, down, and mid lines color col_dn      = #f01313 color col_up      = color.aqua color col_mid     = color.yellow color gray        = color.gray color fg_col      = chart.fg_color // Regression Channel Arrays Line var reglines  = array.new_line(3) var reglines_ = array.new_line(3) // ---------------------------------------------------------------------------------------------------------------------} // 𝙄𝙉𝘿𝙄𝘾𝘼𝙏𝙊𝙍 𝘾𝘼𝙇𝘾𝙐𝙇𝘼𝙏𝙄𝙊𝙉𝙎 // ---------------------------------------------------------------------------------------------------------------------{ //@function linear_regression //@description Calculates linear regression coefficients for a given source and window. //@param src  (series float) The data series on which linear regression is calculated. //@param window  (int) The number of bars to use in the calculation. //@returns the intercept slope, Deviation, end of the channel. linear_regression(src, window) =>     sum_x = 0.0     sum_y = 0.0     sum_xy = 0.0     sum_x_sq = 0.0     // Calculate sums     for i = 0 to window - 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     = (window * sum_xy - sum_x * sum_y) / (window * sum_x_sq - math.pow(sum_x, 2))     intercept = (sum_y - slope * sum_x) / window     y1 = intercept  + slope * (window - 1)     dev = 0.0     for i = 0 to window - 1         dev := dev + math.pow(src[i] - (slope * (window - i) + intercept), 2)     dev := math.sqrt(dev/window)     [intercept, y1, dev, slope] [y2, y1, dev, slope] = linear_regression(close, window) [y2_, y1_, dev_, slope_] = linear_regression(close, window1) [y2__, y1__, dev__, slope__] = linear_regression(close, window2) // Linear Regression Channel Lines series float mid     = y2 + slope series float upper   = mid  + ta.rma(high - low, window) * devlen_b series float lower   = mid  - ta.rma(high - low, window) * devlen_b // Returns True for window length period isAllowed = (last_bar_index - bar_index < window1) // ---------------------------------------------------------------------------------------------------------------------} // 𝙑𝙄𝙎𝙐𝘼𝙇𝙄𝙕𝘼𝙏𝙄𝙊𝙉 // ---------------------------------------------------------------------------------------------------------------------{ // Plot upper, lower, and mid lines if channel is not enabled p_u = plot(upper, color = bands and channel ? na : bands ? gray : na, linewidth = 2) p_l = plot(lower, color = bands and channel ? na : bands ? gray : na, linewidth = 2) p_m = plot(mid,   color = bands and channel ? na : bands ? gray : na) // Fill areas between upper/mid and lower/mid lines fill(p_u, p_m, mid, upper, na, bands and channel ? na : bands ? color.new(col_up, 80) : na) fill(p_m, p_l, lower, mid,     bands and channel ? na : bands ? color.new(col_dn, 80) : na, na) if barstate.islast and channel     for i = 0 to 2         array.set(reglines, i,              line.new(x1 = bar_index - (window1 - 1),                      y1 = y1_ + dev_ * devlen1 * (i - 1),                      x2 = bar_index,                      y2 = y2_ + dev_ * devlen1 * (i - 1),                      color = color.gray,                      style = i % 2 == 1 ? line.style_dashed : line.style_solid,                      width = 2,                      extend = extend.none)                      )     linefill.new(array.get(reglines, 1), array.get(reglines, 2), color = color.new(col_up, 90))     linefill.new(array.get(reglines, 1), array.get(reglines, 0), color = color.new(col_dn, 90)) if barstate.islast and channel1     for i = 0 to 2         array.set(reglines_, i,              line.new(x1 = bar_index - (window2 - 1),                      y1 = y1__ + dev__ * devlen2 * (i - 1),                      x2 = bar_index,                      y2 = y2__ + dev__ * devlen2 * (i - 1),                      color = color.gray,                      style = i % 2 == 1 ? line.style_dotted : line.style_dashed,                      width = 1,                      extend = extend.right)                      )                   linefill.new(array.get(reglines_, 1), array.get(reglines_, 2), color = color.new(col_up, 95))     linefill.new(array.get(reglines_, 1), array.get(reglines_, 0), color = color.new(col_dn, 95)) if arr_dirc     l1 = label.new(chart.point.from_index(bar_index, hl2 > y2__ ? high : low),              text = hl2 > y2__ ? "⇗" : hl2 < y2__ ? "⇘" : "⇒",              textcolor = hl2 > y2__ ? col_up : hl2 < y2__ ? col_dn : gray,              color = color(na),              size = size.huge,              style =  label.style_label_left              )         label.delete(l1[1]) // Bar Heat Map b_c = (close - lower) / (upper - lower) b_c := b_c > 1 ? 1 : b_c < 0 ? 0 : b_c bar_color = channel ?      (isAllowed ?          (b_c <= 0.5 ? color.from_gradient(b_c, 0, 0.5, col_up, col_mid) : color.from_gradient(b_c, 0.5, 1, col_mid, col_dn))          : na)      : (b_c >= 0.5 ? color.from_gradient(b_c, 0.5, 1, col_mid, col_up) : color.from_gradient(b_c, 0, 0.5, col_dn, col_mid)) plotcandle(open, high, low, close,              title = "Bar HeatMap",                color = bar_color,                  wickcolor = bar_color,                   bordercolor = bar_color                      ) barcolor(bar_color) // Conditions for crossovers condition1 = bands and channel ? na : bands ? ta.pivotlow(3, 3) and close < lower : na condition2 = bands and channel ? na : bands ? ta.pivothigh(3, 3) and close > upper: na // Plot markers for channel break outs plotchar(condition1, "", "◆", size=size.tiny, location=location.belowbar, color = col_up) plotchar(condition2, "", "◆", size=size.tiny, location=location.abovebar, color = col_dn) // ---------------------------------------------------------------------------------------------------------------------}