BankNifty Supertrend Trading Strategy

This is a trading strategy based on the 5-minute K-line of BankNifty using the Supertrend indicator. The strategy mainly utilizes the Supertrend indicator to identify trends and combines trading sessions and risk…

Pine ScriptTrend following Breakout ATR Supertrend

Author: ChaoZhang
Complexity: Intermediate · 75 lines
Parameters: 11
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Principle

The strategy first defines input variables such as trading sessions and date ranges. The trading session is set to the Indian trading session from 9:15 am to 3:10 pm.

It then calculates the Supertrend indicator and its direction. The Supertrend indicator can identify the direction of the trend.

At the beginning of each trading session, the strategy waits for 3 candles to form before considering entering a trade. This is to filter false breakouts.

The long signal is when the Supertrend indicator direction changes from down to up; the short signal is when the Supertrend direction changes from up to down.

After entering, stop loss will be set. Both fixed stop loss points and trailing stop loss percentage can be adjusted through input variables.

At the end of the trading session, the strategy will close all open positions.

Advantages of the Strategy

This is a simple trading strategy that uses indicators to identify trends. It has the following advantages:

Use Supertrend indicator to judge trend direction, which can effectively identify trends
Combining trading sessions can avoid the most volatile opening and closing session
Set trailing stop loss to lock in profits
Many parameters can be adjusted freely through input variables, high adaptability

Risks of the Strategy

The strategy also has some risks:

Supertrend indicator has lagging, may miss the best entry point
Single indicator judgment is prone to be affected by false breakouts, win rate may be low
Does not consider market trend, may diverge from the overall market
Improper stop loss setting may lead to larger than expected losses

These risks can be reduced by optimizing parameters of the Supertrend indicator or adding other indicator judgments.

Optimization Directions

The strategy can also be optimized in the following aspects:

Add other indicator judgments to form a combined strategy, improve stability
Add overall market trend judgment to avoid divergence from the market
Optimize parameters of Supertrend indicator, find the best length and factor
Adjust stop loss strategy, like trailing stop loss along with the trend
Test on different products, find the best match

Conclusion

In summary, this is a Supertrend indicator trading strategy based on the BankNifty 5-minute chart. It utilizes the Supertrend indicator to determine the trend direction and combines trading sessions and risk management rules to trade. Compared to complex quantitative strategies, this strategy has simple and clear rules that are easy to understand and implement. As a sample strategy, it provides a foundation and direction for future optimization and improvement. Through continuous refinement and enhancement, it is hoped that the strategy can become a reliable and profitable quantitative trading strategy.

Parameters

Name	Default	What it controls
v_input_3	timestamp(01 Dec 2023 23:59:59)	End Date
v_input_float_1	3	Factor
v_input_1	0915-1510	(?Indian Session Time)Session
v_input_2	timestamp(01 Jan 2022 00:00:00)	(?Backtest Specific Range)Start Date
v_input_4	50	(?SuperTrend Setting)ATR Length
v_input_5	true	(?Delay at Session Start)Use Delay?
v_input_6	10	Delay N numbers of candle
v_input_7	true	(?Risk Management)Use Stoploss Points?
v_input_8	100	Stop Loss Points
v_input_9	true	Use Stoploss Trail?
v_input_float_2	0.1	Stop Loss Trail%

Source Pine Script

/*backtest
start: 2023-11-28 00:00:00
end: 2023-12-28 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
strategy("BankNifty 5min Supertrend Based Strategy, 09:15 Entry with Date Range and Risk Management")

// Session and date range input variables
session = input("0915-1510", "Session", group="Indian Session Time")
start_date = input(title="Start Date", defval=timestamp("01 Jan 2022 00:00:00"), group="Backtest Specific Range")
end_date = input(title="End Date", defval=timestamp("01 Dec 2023 23:59:59"))
atrPeriod = input(50, "ATR Length", group="SuperTrend Setting")
factor = input.float(3.0, "Factor", step=0.1)

useDelay = input(true, "Use Delay?", group="Delay at Session Start")
Delay = useDelay ? input(10, title="Delay N numbers of candle", group="Delay at Session Start") : na

useDelay_stopLoss = input(true, "Use Stoploss Points?", group="Risk Management")
stopLoss = useDelay_stopLoss ? input(100, "Stop Loss Points", group="Risk Management"): na

useDelay_stopLossPerc1 = input(true, "Use Stoploss Trail?", group="Risk Management")
stopLossPerc1 =useDelay_stopLossPerc1 ? input.float(0.1, "Stop Loss Trail%", step=0.1,maxval = 1, group="Risk Management"): na
// Check if current time is within the specified session and date range
inSession = true

[supertrend, direction] = ta.supertrend(factor, atrPeriod)

// Wait for 3 candles to form at the start of every session
var candlesFormed = 0
if inSession and not inSession[1]
    candlesFormed := 1
else if inSession and candlesFormed > 0
    candlesFormed := candlesFormed + 1
else
    candlesFormed := 0


//

// Only enter trades if 3 candles have formed at the start of the session
entryce = (ta.change(direction) < 0) or (candlesFormed >= Delay and direction < 0)
exitce = ta.change(direction) > 0
entrype = (ta.change(direction) > 0) or (candlesFormed >= Delay and direction > 0)
exitpe = ta.change(direction) < 0
var entryPrice = 0.0
if entryce and inSession
    // Enter long trade
    onePercent = strategy.position_avg_price *stopLossPerc1
    entryPrice := close
    strategy.entry("My Long Entry Id", strategy.long, comment="long" )
    // Set stop loss at x% below entry price
    strategy.exit("My Long Exit Id", "My Long Entry Id", stop=(entryPrice - stopLoss),trail_points=onePercent )
    
if entrype and inSession
    onePercent1 = strategy.position_avg_price *stopLossPerc1
    entryPrice := close
    // Enter short trade
    strategy.entry("My Short Entry Id", strategy.short, comment="short")
    // Set stop loss at x% above entry price
    strategy.exit("My Short Exit Id", "My Short Entry Id", stop=(entryPrice + stopLoss),trail_points=onePercent1)

// Close all trades at end of session
if not inSession and strategy.opentrades > 0
    strategy.close_all()

// Plot Supertrend with changing colors
plot(supertrend, title="Supertrend", color=direction == 1 ? color.red : color.green, linewidth=2)

Published by ChaoZhang on the FMZ strategy square · last modified 2023-12-29. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

Build this with AgenKit

A spec is not a trading system. Paste this into your coding agent and AgenKit runs a specialist team — architecture, test-first build, risk gates, review — with paper trading on by default.

in Claude Code, Cursor, Codex & 4 more

/agenkit build a production-grade trading bot with a backtest engine, risk controls and paper trading by default from strategies/BankNifty-Supertrend-Trading-Strategy.md

npx agenkit install engineering-kit in your project
Paste the command into your agent and approve each phase
Get tests, backtest, risk controls and a paper-trading switch

Get AgenKit How /agenkit works

Understand it first

Before you run this, read the lesson behind the idea and how to backtest it honestly. Specs like this one are the survivors of an unknown number of trials; deflate their results accordingly.