Algorithmic Trading & Indicators Beginner

Dynamic ATR Trailing Stop-Loss & Position Sizing Calculator in Python

Calculate volatility-adjusted Average True Range (ATR) trailing stop-loss levels and exact share/lot position sizes based on fixed account risk percentage.

#pandas#numpy

Problem Statement

Fixed percentage stop-losses get whipped out in high-beta stocks and leave too much risk on the table in low-volatility stocks. This script computes dynamic ATR stops and exact position size per trade.

Formula / Core Logic

Long Stop = Entry_Price - (Multiplier x ATR_14) Position Size (Qty) = (Account_Capital x Risk_Pct) / (Multiplier x ATR_14)

Installation

pip install pandas numpy

atr-stop-loss-calculation-script-python.py

import pandas as pd
import numpy as np

def atr_position_sizer(df, capital=100000, risk_pct=0.01, period=14, atr_mult=2.0):
    df = df.copy()
    tr = pd.concat([
        df['High'] - df['Low'],
        (df['High'] - df['Close'].shift(1)).abs(),
        (df['Low'] - df['Close'].shift(1)).abs()
    ], axis=1).max(axis=1)
    df['ATR'] = tr.ewm(alpha=1/period, adjust=False).mean()
    df['Long_SL'] = np.round(df['Close'] - (atr_mult * df['ATR']), 2)
    df['Short_SL'] = np.round(df['Close'] + (atr_mult * df['ATR']), 2)
    risk_amount = capital * risk_pct
    df['Suggested_Qty'] = np.floor(risk_amount / (atr_mult * df['ATR']))
    return df

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Frequently Asked Questions

Q: What ATR multiplier is ideal for swing trading?

A 2.0x to 2.5x ATR multiplier gives trades enough breathing room outside normal daily noise.