Short term Down Trend Strategy Based on EMA and Adaptive Fibonacci Retracement

This strategy uses EMA to determine trend direction and adaptive Fibonacci retracement to automatically identify reversal points, aiming to sell high and buy low by catching down trends. It involves frequent trading…

Pine ScriptTrend following Mean reversion EMA Fibonacci

Author: ChaoZhang
Complexity: Starter · 75 lines
Parameters: 3
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Logic

Use 9-day EMA and 21-day EMA golden cross and death cross to determine trend direction. 21-day EMA crossing below 55-day EMA signals a down trend start.
Implement adaptive Fibonacci retracement with 100 periods to automatically determine key retracement levels based on recent price swings.
Price breaking 0.236 Fibonacci retracement indicates a reversal and closes existing position.
When 9-day EMA crosses below 21-day EMA, and price is lower than adaptive Fibonacci high, go short.
Long profit target is a crossover above 200-day EMA. Short stop loss is breaking 0.236 Fibonacci retracement.

Advantages

EMA gives clear trend signals, easy to implement
Adaptive Fibonacci avoids manual parameter tuning
Frequent trading catches short-term moves for high frequency strategies
Key retracement levels for timely stop loss
Configurable parameters for optimization across cycles

Risks

EMA lagging requires confirmation from other indicators
Adaptive Fibonacci risks overfitting with unstable levels
High frequency trading increases costs from commissions and slippage
Ineffective filtering of range-bound trends leads to false signals
Needs improvement in drawdown management and risk-reward control

Enhancement

Add volume indicators to avoid false signals from price-volume divergence
Optimize EMA periods to better fit current market conditions
Implement dynamic stop loss for better risk control
Incorporate trend strength index to avoid whipsaws
Consider trading costs impact and set minimum profit target

Conclusion

This strategy identifies trend direction with EMA and determines reversal levels dynamically using adaptive Fibonacci retracement, which automatically adapts to different market conditions. But it relies more on indicator cues without trend segmentation and Elliott Wave logic, leaving room for optimization. Overall, as a high frequency short-term trading strategy, it can capture fast price changes but involves risks of frequent stop loss and overtrading that traders need to manage.

Parameters

Name	Default	What it controls
v_input_int_1	100	(?Automatic Fibonacci Retracement)Fibonacci Length
v_input_int_2	true	Show Last
v_input_int_3	5	Offset Length

Source Pine Script

/*backtest
start: 2023-08-21 00:00:00
end: 2023-09-20 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © CheatCode1

//@version=5
strategy("CC-Trend strategy 2", overlay=true, initial_capital = 10000, commission_type = strategy.commission.percent, commission_value = 0.01, default_qty_type =  strategy.percent_of_equity, default_qty_value = 100 )
ema9 = ta.ema(close, 9)
ema21 = ta.ema(close, 21)
ema55 = ta.ema(close, 55)
ema200 = ta.ema(close, 200)


plot(ema200, '22', color.blue, 2)

FibL = input.int(100, 'Fibonacci Length', 1, 500, group = 'Automatic Fibonacci Retracement')
len1 = input.int(1, 'Show Last', 0, 1000, group = 'Automatic Fibonacci Retracement')
len2 = input.int(5, 'Offset Length', 0, 1000, group = 'Automatic Fibonacci Retracement')

highF = ta.highest(ema55 >= ema9 ? ema55:ema9, FibL)
lowF = ta.lowest(ema55 >= ema9 ? ema9:ema55, FibL)
AvgFib = highF - lowF

//Fibonacci Executions
LL2 = highF + .618 * AvgFib
LL1 = highF + .272 * AvgFib
L1 = highF
L236 = highF - 0.236 * AvgFib
L382 = highF - 0.382 * AvgFib
Mid =  highF - 0.50 * AvgFib
S382 = lowF + 0.382 * AvgFib
S236 = lowF + 0.236 * AvgFib
S1 = lowF
SS1 = lowF - .272 * AvgFib
SS2 = lowF - .618 * AvgFib
//Fibonacci Plot's


high2FP = plot(LL2, 'Highe2', color.red,offset = len2, show_last = len1, trackprice = true)
high1FP = plot(LL1, 'Highe1', color.red,offset = len2, show_last = len1, trackprice = true)
highFP = plot(highF, 'High', color.red,offset = len2, show_last = len1, trackprice = true)
L236P = plot(L236, "0.764", #ED381C, offset = len2, show_last = len1, trackprice = true )
L382P = plot(L382, "0.618", color.white,offset = len2, show_last = len1, trackprice = true )
MidP = plot(Mid, "0.5", color.orange,offset = len2, show_last = len1, trackprice = true )
S382P = plot(S382, "0.382", color.yellow ,offset = len2, show_last = len1, trackprice = true)
S236P = plot(S236, "0.236", color.lime ,offset = len2, show_last = len1, trackprice = true)
lowFP = plot(lowF, 'Low', color.green,offset = len2, show_last = len1, trackprice = true)
low1FP = plot(SS1, 'Lowe1', color.green,offset = len2, show_last = len1, trackprice = true)
low2FP = plot(SS2, 'Lowe2', color.green,offset = len2, show_last = len1, trackprice = true)

plot(ema9, '22', color.yellow, 2)

plot(ema55, '55', color.aqua, 2)

plot(ema200, '200', color.maroon, 2)



shortCondition = close[1] < highF and ema21 < ema55
if (shortCondition)
    strategy.entry("Short", strategy.short)

shorttp = ta.crossover(close, ema200) and strategy.openprofit >= 0
if (shorttp)
    strategy.close('Short', 'Short TP', qty_percent = 100)

shortclose2 = close[1] > L236 and not (shortCondition) 
if(shortclose2)
    strategy.close('Short', 'Short RM', qty_percent = 100)

Published by ChaoZhang on the FMZ strategy square · last modified 2023-09-21. 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/Short-term-Down-Trend-Strategy-Based-on-EMA-and-Adaptive-Fibonacci-Retracement.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.