Multi Timeframe Stochastic Oscillator Swing Trading Strategy with Dynamic Take Profit and Stop Loss

Pine ScriptMulti-timeframe Mean reversion Trend following SMA Stochastic

Author: ianzeng123
Complexity: Starter · 64 lines
Parameters: 0
Backtest bar: 1d · swing
Tested on: BTC/USDT · spot

Jump to code View in vault Original on FMZ

Overview

This strategy is a multi-timeframe swing trading system based on the Stochastic Oscillator. It identifies trading opportunities by combining stochastic signals from current and higher timeframes, using dynamic take-profit and stop-loss levels for risk management. The strategy is designed for volatile markets, aiming to capture short-term price movements for profit.

Strategy Principles

The core logic is based on several key elements:

Using Stochastic Oscillator confirmation on two timeframes (current and higher)
Looking for crossover signals in overbought/oversold zones
Buy conditions: K line crosses above D line in current timeframe with K<20; higher timeframe K<20 and K>D
Sell conditions: K line crosses below D line in current timeframe with K>80; higher timeframe K>80 and K<D
Dynamic take-profit and stop-loss system based on entry price, with adjustable multipliers

Strategy Advantages

Multi-timeframe signal confirmation improves reliability and reduces false signals
Trading in overbought/oversold zones increases probability of trend reversal
Dynamic TP/SL system automatically adjusts to market volatility, enhancing money management flexibility
Visual interface clearly displays trading signals and TP/SL levels for better understanding
Adjustable parameters allow adaptation to different market conditions

Strategy Risks

Frequent stop-losses may occur in highly volatile markets
Dual timeframe confirmation might cause missed trading opportunities
Fixed multiplier TP/SL may not suit all market conditions
Potential early profit taking in strong trends
Requires careful parameter optimization to balance reward and risk

Optimization Directions

Implement adaptive TP/SL mechanism based on market volatility
Add trend filter for adjusting trade direction in strong trends
Incorporate volume indicators as confirmation signals
Develop more sophisticated position sizing system
Consider adding market sentiment indicators for entry timing optimization

Summary

This is a comprehensive trading system combining technical analysis and risk management. Through multi-timeframe signal confirmation and dynamic TP/SL, the strategy maintains stability while offering good profit potential. However, users need to optimize parameters according to their trading style and market conditions, always maintaining strict risk control.

Source Pine Script

/*backtest
start: 2024-02-21 00:00:00
end: 2025-02-18 08:00:00
period: 1d
basePeriod: 1d
exchanges: [{"eid":"Binance","currency":"BTC_USDT"}]
*/

//@version=5
strategy("Swing Fairas Oil", overlay=true)

// Input parameters
kLength = input(14, title="Stochastic K Length")
dLength = input(3, title="Stochastic D Length")
smoothK = input(3, title="Smooth K")
tfHigher = input.timeframe("30", title="Higher Timeframe")
takeProfit = input(1.7, title="Take Profit Multiplier")
stopLoss = input(1.7, title="Stop Loss Multiplier")

// Calculate Stochastic Oscillator for current timeframe
k = ta.sma(ta.stoch(close, high, low, kLength), smoothK)
d = ta.sma(k, dLength)

// Calculate Stochastic Oscillator for higher timeframe
kHTF = request.security(syminfo.tickerid, tfHigher, ta.sma(ta.stoch(close, high, low, kLength), smoothK))
dHTF = request.security(syminfo.tickerid, tfHigher, ta.sma(kHTF, dLength))

// Buy and sell conditions (confirmation from two timeframes)
buyCondition = ta.crossover(k, d) and k < 20 and kHTF < 20 and kHTF > dHTF
sellCondition = ta.crossunder(k, d) and k > 80 and kHTF > 80 and kHTF < dHTF

// Define Take Profit and Stop Loss levels
longStopLoss = close * (1 - stopLoss / 100)
longTakeProfit = close * (1 + takeProfit / 100)
shortStopLoss = close * (1 + stopLoss / 100)
shortTakeProfit = close * (1 - takeProfit / 100)

// Execute Trades
if buyCondition
    strategy.entry("Long", strategy.long)
    strategy.exit("Long Exit", from_entry="Long", limit=longTakeProfit, stop=longStopLoss)
if sellCondition
    strategy.entry("Short", strategy.short)
    strategy.exit("Short Exit", from_entry="Short", limit=shortTakeProfit, stop=shortStopLoss)

// Plot buy/sell signals on candlestick chart
plotshape(series=buyCondition, location=location.belowbar, color=color.green, style=shape.labelup, size=size.small, title="Buy Signal")
plotshape(series=sellCondition, location=location.abovebar, color=color.red, style=shape.labeldown, size=size.small, title="Sell Signal")

// Highlight candles for buy and sell conditions
barcolor(buyCondition ? color.green : sellCondition ? color.red : na)

// Draw Take Profit and Stop Loss levels dynamically with labels
var float tpLevel = na
var float slLevel = na
if buyCondition
    tpLevel := longTakeProfit
    slLevel := longStopLoss

if sellCondition
    tpLevel := shortTakeProfit
    slLevel := shortStopLoss

Published by ianzeng123 on the FMZ strategy square · last modified 2025-02-20. 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/Multi-Timeframe-Stochastic-Oscillator-Swing-Trading-Strategy-with-Dynamic-Take-Profit-and-Stop-Loss.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.