This indicator calculates the total transaction cost hurdle comprising commission, slippage, and spread as a percentage, price value, and fraction of ATR.
1Copy the scriptPress Copy script above, or the copy button on the code below.
2Open the Pine EditorOpen a TradingView chart and choose Pine Editor at the bottom of the screen.
3Paste over the templateCreate a new indicator, select all of the template text and paste. Press Save and give it a name.
4Add it to the chartPress Add to chart, then adjust the settings with the gear icon next to its name.
Source Code
108 lines of Pine Script v6 from scripts/cost-hurdle.pine, published under MPL-2.0. Keep the author's credit and licence lines when you reuse it.
cost-hurdle.pine
//@version=6
// Taught to Trade - Cost Hurdle
// Costs are not a fee taken off the end. They are a hurdle height you must clear
// before a trade is worth anything. This measures how tall that hurdle is here,
// and how often this instrument has actually produced a move that size.
// No buy/sell signals. Alerts are yours to configure.
indicator("Taught to Trade - Cost Hurdle", shorttitle = "TT HURDLE", overlay = true, max_bars_back = 1000)
grpC = "Your real costs"
commPct = input.float(0.04, "Commission per side (%)", minval = 0.0, step = 0.01, group = grpC)
slipPct = input.float(0.02, "Slippage per side (%)", minval = 0.0, step = 0.01, group = grpC)
spreadPct = input.float(0.0, "Spread paid once (%)", minval = 0.0, step = 0.01, group = grpC, tooltip = "Leave at zero if your commission figure already includes the spread.")
grpH = "Holding periods"
h1 = input.int(1, "Hold A (bars)", minval = 1, group = grpH)
h2 = input.int(5, "Hold B (bars)", minval = 1, group = grpH)
h3 = input.int(10, "Hold C (bars)", minval = 1, group = grpH)
h4 = input.int(20, "Hold D (bars)", minval = 1, group = grpH)
lookback = input.int(500, "Sample window (bars)", minval = 60, maxval = 1000, group = grpH)
grpT = "Table"
posIn = input.string("Top right", "Position", options = ["Top right", "Top left", "Bottom right", "Bottom left"], group = grpT)
szIn = input.string("Small", "Text size", options = ["Tiny", "Small", "Normal"], group = grpT)
hurdlePct = (commPct + slipPct) * 2.0 + spreadPct
atr = ta.atr(14)
atrPct = close > 0 ? atr / close * 100.0 : na
hurdleInAtr = nz(atrPct, 0) > 0 ? hurdlePct / atrPct : na
hurdleInPrice = close * hurdlePct / 100.0
f_move(int n) => close[n] > 0 ? math.abs(close - close[n]) / close[n] * 100.0 : na
m1 = f_move(h1)
m2 = f_move(h2)
m3 = f_move(h3)
m4 = f_move(h4)
c1 = math.sum(nz(m1, -1) > hurdlePct ? 1 : 0, lookback)
c2 = math.sum(nz(m2, -1) > hurdlePct ? 1 : 0, lookback)
c3 = math.sum(nz(m3, -1) > hurdlePct ? 1 : 0, lookback)
c4 = math.sum(nz(m4, -1) > hurdlePct ? 1 : 0, lookback)
v1 = math.sum(na(m1) ? 0 : 1, lookback)
v2 = math.sum(na(m2) ? 0 : 1, lookback)
v3 = math.sum(na(m3) ? 0 : 1, lookback)
v4 = math.sum(na(m4) ? 0 : 1, lookback)
med1 = ta.percentile_linear_interpolation(nz(m1, 0), lookback, 50)
med2 = ta.percentile_linear_interpolation(nz(m2, 0), lookback, 50)
med3 = ta.percentile_linear_interpolation(nz(m3, 0), lookback, 50)
med4 = ta.percentile_linear_interpolation(nz(m4, 0), lookback, 50)
f_safe(float num, float den) => den > 0 ? num / den : na
f_pc(float v) => na(v) ? "-" : str.tostring(v, "#") + "%"
f_pc2(float v) => na(v) ? "-" : str.tostring(v, "#.###") + "%"
s1 = f_safe(c1 * 100.0, v1)
s2 = f_safe(c2 * 100.0, v2)
s3 = f_safe(c3 * 100.0, v3)
s4 = f_safe(c4 * 100.0, v4)
tblPos = posIn == "Top left" ? position.top_left : posIn == "Bottom right" ? position.bottom_right : posIn == "Bottom left" ? position.bottom_left : position.top_right
tblSz = szIn == "Tiny" ? size.tiny : szIn == "Normal" ? size.normal : size.small
bgCol = color.new(#0E1526, 10)
txtCol = color.new(#E6EAF2, 0)
hdrCol = color.new(#2F6FED, 0)
badCol = color.new(#B3261E, 25)
okCol = color.new(#2E7D32, 25)
f_flag(float share) => na(share) ? bgCol : share < 50.0 ? badCol : okCol
var table t = table.new(tblPos, 4, 8, border_width = 1, border_color = color.new(#2F6FED, 70))
f_h(int c, string s) => table.cell(t, c, 0, s, text_color = color.white, text_size = tblSz, bgcolor = hdrCol)
f_r(int c, int r, string s, color bc) => table.cell(t, c, r, s, text_color = txtCol, text_size = tblSz, text_halign = text.align_right, bgcolor = bc)
f_l(int c, int r, string s, color bc) => table.cell(t, c, r, s, text_color = txtCol, text_size = tblSz, text_halign = text.align_left, bgcolor = bc)
if barstate.islast
f_h(0, "HOLD")
f_h(1, "Bars")
f_h(2, "Cleared")
f_h(3, "Median move")
f_l(0, 1, str.tostring(h1) + " bars", bgCol)
f_r(1, 1, str.tostring(v1), bgCol)
f_r(2, 1, f_pc(s1), f_flag(s1))
f_r(3, 1, f_pc2(med1), bgCol)
f_l(0, 2, str.tostring(h2) + " bars", bgCol)
f_r(1, 2, str.tostring(v2), bgCol)
f_r(2, 2, f_pc(s2), f_flag(s2))
f_r(3, 2, f_pc2(med2), bgCol)
f_l(0, 3, str.tostring(h3) + " bars", bgCol)
f_r(1, 3, str.tostring(v3), bgCol)
f_r(2, 3, f_pc(s3), f_flag(s3))
f_r(3, 3, f_pc2(med3), bgCol)
f_l(0, 4, str.tostring(h4) + " bars", bgCol)
f_r(1, 4, str.tostring(v4), bgCol)
f_r(2, 4, f_pc(s4), f_flag(s4))
f_r(3, 4, f_pc2(med4), bgCol)
f_l(0, 5, "Hurdle", hdrCol)
f_l(1, 5, str.tostring(hurdlePct, "#.###") + "% round trip", bgCol)
f_l(0, 6, "In price", bgCol)
f_l(1, 6, str.tostring(hurdleInPrice, format.mintick), bgCol)
f_l(0, 7, "In ATR(14)", bgCol)
f_l(1, 7, na(hurdleInAtr) ? "-" : str.tostring(hurdleInAtr, "#.##") + " x ATR", bgCol)
alertcondition(not na(hurdleInAtr) and hurdleInAtr > 1.0, title = "Round-trip cost now exceeds one ATR", message = "Cost Hurdle: a round trip on this chart now costs more than one ATR of movement.")
alertcondition(not na(hurdleInAtr) and hurdleInAtr > 0.5 and hurdleInAtr <= 1.0, title = "Round-trip cost now exceeds half an ATR", message = "Cost Hurdle: a round trip on this chart now costs more than half an ATR of movement.")
Overview
Taught to Trade - Cost Hurdle samples historical price moves across four user-defined holding periods over a configurable lookback window to determine how often moves clear the cost hurdle and computes median returns for each period. The results are displayed in an on-chart table to assess whether expected trade horizons produce enough movement to cover trading friction.
The inputs you can change from the gear icon on the chart. Defaults are the author's.
Setting
Type
Default
Variable
Commission per side (%)
float
0.04
commPct
Slippage per side (%)
float
0.02
slipPct
Spread paid once (%)
float
0.0
spreadPct
Hold A (bars)
int
1
h1
Hold B (bars)
int
5
h2
Hold C (bars)
int
10
h3
Hold D (bars)
int
20
h4
Sample window (bars)
int
500
lookback
Position
string
Top right
posIn
Text size
string
Small
szIn
Third-party code. ForexR did not write, test or endorse this script, and the summary above was generated automatically from its code and README. Indicators describe the past, and a strategy's backtest can look better than live trading, especially when a script repaints. Check it in the Strategy Tester and on a demo account before you rely on it.
This overlay indicator plots a Supertrend from an ATR length and factor, four exponential moving averages, and a selectable VWAP or TWAP taken from a chosen timeframe on the price chart. It also shows MACD and stochastic with adjustable lengths, smoothing, ver
This multi-symbol indicator evaluates a combined trading condition across up to 40 user-defined symbols. It processes MACD bullish crossovers, RSI thresholds, Bollinger Band boundaries, and DMI/ADX trend filters using security calls. When buy or sell criteria
This indicator calculates theoretical options contract values and in-the-money probabilities using historical realized volatility across multiple standard deviations. It displays these metrics in a table overlay directly on the price chart. Users can adjust th
This indicator maps market structure and supply and demand zones on the price chart. It marks validated and optional unvalidated swing highs and lows using a pivot length and extra confirmation bars. Consolidation and impulse moves are measured against ATR to
Storm Gauge calculates annualized realized volatility and compares it against a historical percentile lookback window to classify market volatility regimes into calm, normal, or storm conditions. Based on a target volatility input, it calculates dynamic positi
The 8zz Contrarian Indicator plots reverse sentiment trading signals directly on the price chart based on tracked retail post activity. It generates bullish signals during retail panic and bearish signals during market euphoria. The indicator features adjustab