Trend Following Long Term Strategy Based on SuperTrend and Fisher Transform

Author: ChaoZhang, Date: 2023-11-03 15:42:16



This strategy combines the SuperTrend and Fisher Transform indicators to implement a relatively stable trend following long term trading strategy. It generates buy signals when the SuperTrend indicator gives a buy signal and the Fisher Transform indicator drops below -2.5 and rises. The strategy manages positions properly with stop loss and take profit.

Strategy Logic

  1. The SuperTrend indicator is used to determine the direction of the price trend. When the price crosses above the upper band, it is a bullish signal; when the price crosses below the lower band, it is a bearish signal. This strategy issues a buy signal when the SuperTrend is bullish.

  2. The Fisher Transform indicator reflects the impact of price fluctuations on consumer psychology. Fisher values between (-2.5, 2.5) represent a neutral market, below -2.5 represents a panicked market, and above 2.5 represents a euphoric market. This strategy issues a buy signal when the Fisher is below -2.5 and rising, to capture the turning point from panic to neutral.

  3. The strategy manages positions properly with stop loss and take profit. The stop loss is set at the entry price minus the ATR value multiplied by the ATR multiplier, and take profit is set at the entry price plus the ATR value multiplied by the ATR multiplier. The stop loss amplitude is greater than the take profit amplitude, reflecting the risk control idea of the trend following strategy.

  4. It also considers risk amount management. Calculate the position size based on ATR and risk amount so that the risk per unit does not exceed the set risk amount.

Advantage Analysis

  1. Combining multiple indicators avoids frequent trading caused by a single indicator. SuperTrend determines trend direction and Fisher Transform determines market psychology to form stable trading signals.

  2. Setting proper stop loss and take profit is conducive to capturing trends for long-term holding, while controlling risks.

  3. Using risk amount management and minimum tick size makes the risk of each trade controllable, avoiding large losses beyond affordability.

  4. Trading signals are stable and suitable for long-term holding. Fisher Transform is a smooth indicator, which helps filter market noise and avoid false signals.

  5. Large optimization space for indicator parameters. SuperTrend’s ATR period and multiplier, and Fisher’s smoothness can be adjusted according to different products and timeframes to find the optimal parameter combination.

Risk Analysis

  1. As a trend following strategy, it will accumulate small losses during range-bound periods. Products and timeframes with obvious trends should be selected.

  2. Fisher Transform is not effective for extreme situations. When the market stays in one state for a long time, Fisher values will continue to deviate from the neutral zone, in which case the strategy should be suspended.

  3. A stop loss too close may cause premature exit. The ATR period and ATR multiplier should be set reasonably to ensure sufficient buffer for the stop loss.

  4. Ignoring transaction costs will cause profitable trades to lose money. The transaction costs of the product should be considered and take profit adjusted accordingly.

  5. It takes long-time market participation for the strategy to realize its advantage. Ensure sufficient capital to support long-term trading and keep a stable mindset.

Optimization Directions

  1. Adjust ATR period, ATR multiplier to optimize stop loss and take profit. Optimize via backtesting or dynamically.

  2. Try different Fisher parameters like smooth period to find more stable trading signals. Can dynamically adjust based on market volatility.

  3. Add other indicators as filters to avoid wrong trades when the market is uncertain. Judge the market trend using MA, volatility etc.

  4. Test different take profit strategies like moving, partial, ATR trailing, etc. to improve profitability.

  5. Optimize capital management strategies like fixed fractional, Kelly formula etc. to increase return/risk ratio.

  6. Optimize for transaction costs, keep profitable for small positions.


This strategy integrates the advantages of SuperTrend, Fisher Transform and other indicators to form a stable trend following long term trading strategy. Through stop loss, take profit and risk management, it can achieve good risk reward ratio. The strategy needs further optimization on parameters, signal filtering, capital management etc. to improve practical performance. But the overall logic is robust and worth practical verification and continuous optimization. If managing take profit and risk mindset properly, the strategy has the potential to achieve steady long term returns.

start: 2023-10-26 00:00:00
end: 2023-11-02 00:00:00
period: 1m
basePeriod: 1m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]

strategy("Supertrend and Fisher_LONG", overlay=true)

//This block is for  Fisher Transformation Calculation.
len =, minval=1, title="Length") // Length is optional. 10 is good but is up to you.
high_ = ta.highest(hl2, len)
low_ = ta.lowest(hl2, len)
round_(val) => val > .99 ? .999 : val < -.99 ? -.999 : val
value = 0.0
value := round_(.66 * ((hl2 - low_) / (high_ - low_) - .5) + .67 * nz(value[1]))
fish1 = 0.0
fish1 := .5 * math.log((1 + value) / (1 - value)) + .5 * nz(fish1[1])
fish2 = fish1[1]

// Buy condition for Fisher transformation.
buy_signal = (fish1 < -2.5) and (fish1 > fish2)
durum = 0 //just for the situation.

if (buy_signal)
    durum := 1 // now it changes from 0 to 1.

// Supertrend indicator inputs and calculations (same as in the indicator)
Periods = input(title='ATR Period', defval=10) // period is 10, but you can change it
src = input(hl2, title='Source')
Multiplier = input.float(title='ATR Multiplier', step=0.1, defval=2) //atr multiplier is important. it is 2 for this strategy but you can find another for best performance 
RiskAmount = input.float(title='Risk Amount ($)', defval=10.0, minval=0.0, step=1.0) // ıf you use risk-reward method, risk is 10$ for each position. you can also change it
changeATR = input(title='Change ATR Calculation Method ?', defval=true)

atr2 = ta.sma(, Periods)
atr = changeATR ? ta.atr(Periods) : atr2
up = src - Multiplier * atr
up1 = nz(up[1], up)
up := close[1] > up1 ? math.max(up, up1) : up
dn = src + Multiplier * atr
dn1 = nz(dn[1], dn)
dn := close[1] < dn1 ? math.min(dn, dn1) : dn
trend = 1
trend := nz(trend[1], trend)
trend := trend == -1 and close > dn1 ? 1 : trend == 1 and close < up1 ? -1 : trend

// Calculate position size based on risk amount
riskPerContract = atr * Multiplier
contracts = RiskAmount / (riskPerContract * syminfo.mintick)

//short signal condition
buySignal = trend == 1 and trend[1] == -1 and durum == 1

plotshape(buySignal, title='Buy Signal', location=location.belowbar,, style=shape.triangleup, size=size.small)

// variables
var float entryPrice = na
var float stopLoss = na
var float takeProfit = na
var float atr1 = na
var float takeProfit2 = na
var float takeProfit3 = na

//it calculates the stop level and reward profit levels using atr.
if (buySignal)
    entryPrice := close
    atr1 := atr
    stopLoss := entryPrice - atr1 * Multiplier
    contracts := entryPrice / (entryPrice - stopLoss) * RiskAmount / entryPrice
    takeProfit := entryPrice + atr1 * Multiplier
    takeProfit2 := entryPrice + 2 * atr1 * Multiplier
    takeProfit3 := entryPrice + 3 * atr1 * Multiplier

if (buySignal)
    strategy.entry("Buy", strategy.long, qty=contracts)

if (close <= stopLoss)
    strategy.close("Buy", comment="Stop Loss Hit")
else if (close >= takeProfit)
    strategy.close("Buy", comment="Take Profit Hit")

// draw the stop, entry and profit levels
plot(stopLoss, title="Stop Loss",, linewidth=1, style=plot.style_linebr)
plot(entryPrice, title="Entry Price",, linewidth=1, style=plot.style_linebr)
plot(takeProfit, title="Take Profit",, linewidth=1, style=plot.style_linebr)
plot(takeProfit2, title="Take Profit 2",, linewidth=1, style=plot.style_linebr)
plot(takeProfit3, title="Take Profit 3", color=color.purple, linewidth=1, style=plot.style_linebr)