Dual EMA Williams Indicator Trend Tracking Strategy

Author: ChaoZhang, Date: 2023-11-21 15:16:21



This strategy combines dual EMA indicators and Williams indicators to identify trend direction and track trends when they are strong. The basic idea is:

  1. Use dual EMA combos to filter out all but the strongest trends
  2. Williams indicator confirms current overbought/oversold zone
  3. Combine with RSI indicator to avoid chasing new highs and killing declines


This strategy utilizes short-term and long-term EMAs from the dual EMA indicator. When the short-term EMA crosses above the long-term EMA an entry signal is generated. When the short-term EMA crosses below the long-term EMA an exit signal is generated. It captures medium and long-term trends using the dual EMA.

In addition, the Williams Indicator is used to identify reversals. The Williams Indicator determines overbought or oversold by looking at periodic highs and lows. Sell signals are generated when overbought. Buy signals are generated when oversold.

The specific logic is:

Long entry: short-term EMA crosses above medium-term EMA and long-term EMA, Williams Indicator shows oversold zone and forms lowest point indicating reversal opportunity.

Short entry: short-term EMA crosses below medium-term EMA and long-term EMA, Williams Indicator shows overbought zone and forms highest point indicating reversal opportunity.

The RSI indicator is also introduced to further confirm trading signals and avoid chasing new highs and killing declines blindly.


The biggest advantage of this strategy is using the dual EMA to filter out invalid trends and only track the strongest medium and long-term trends. This filters out noise and reduces invalid trades.

Introducing the Williams Indicator is also very effective. Firstly, it identifies reversal opportunities to close positions in time. Secondly, it further confirms the effectiveness of trend signals.

The combination of dual EMA and Williams allows this strategy to achieve good tracking profit in medium and long-term products, while also identifying reversals and limiting losses.


The main risk lies in the difficulty of identifying trend reversal points. Although Williams Indicator and RSI Indicator ensure effectiveness of reversal trades, the difficulty is still high and the risk of chasing new highs and killing declines cannot be completely avoided.

In addition, the dual EMA itself has some lag. When the short-term and medium & long-term trends decouple, some identification difficulty can occur.


This strategy can be optimized in the following ways:

  1. Test more EMA cycle combos to find better parameters

  2. Increase adaptive exit mechanisms based on ATR, volatility index etc to judge reversals

  3. Introduce machine learning with LSTM etc to predict trends and reversals

  4. Improve reversal trading rules using Elliott Wave Theory etc

  5. Introduce adaptive position sizing based on market conditions


This strategy successfully combines dual EMA and Williams Indicator to capture medium and long-term trends and achieve higher returns during major trends. Meanwhile, introducing Williams Indicator also allows the strategy to identify reversals and cut losses in time. Next step is to further enhance stability of strategy by introducing more indicators and models for optimization.

start: 2022-11-20 00:00:00
end: 2022-11-29 05:20:00
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/
// © B_L_A_C_K_S_C_O_R_P_I_O_N
// v 1.1

strategy("vijkirti buy sell 99%", overlay=true, default_qty_type=strategy.cash, default_qty_value=1000, currency='USD')

// *************Appearance*************
theme = input(type=input.string, defval="dark", options=["light","dark"], group="Appearance")
show_fractals = input(false, "Show Fractals", group="Appearance")
show_ema = input(false, "Show EMAs", group="Appearance")

// *************colors*************
color_green = color.green
color_red = color.red
color_yellow = color.yellow
color_orange = color.orange
color_blue = color.blue
color_white = color.white

// *************WF*************
// Define "n" as the number of periods and keep a minimum value of 2 for error handling.
n = input(title="Fractal Periods", defval=2, minval=2, type=input.integer, group="Williams Fractals")

// UpFractal
bool upflagDownFrontier = true
bool upflagUpFrontier0 = true
bool upflagUpFrontier1 = true
bool upflagUpFrontier2 = true
bool upflagUpFrontier3 = true
bool upflagUpFrontier4 = true

for i = 1 to n
    upflagDownFrontier := upflagDownFrontier and (high[n-i] < high[n])
    upflagUpFrontier0 := upflagUpFrontier0 and (high[n+i] < high[n])
    upflagUpFrontier1 := upflagUpFrontier1 and (high[n+1] <= high[n] and high[n+i + 1] < high[n])
    upflagUpFrontier2 := upflagUpFrontier2 and (high[n+1] <= high[n] and high[n+2] <= high[n] and high[n+i + 2] < high[n])
    upflagUpFrontier3 := upflagUpFrontier3 and (high[n+1] <= high[n] and high[n+2] <= high[n] and high[n+3] <= high[n] and high[n+i + 3] < high[n])
    upflagUpFrontier4 := upflagUpFrontier4 and (high[n+1] <= high[n] and high[n+2] <= high[n] and high[n+3] <= high[n] and high[n+4] <= high[n] and high[n+i + 4] < high[n])
flagUpFrontier = upflagUpFrontier0 or upflagUpFrontier1 or upflagUpFrontier2 or upflagUpFrontier3 or upflagUpFrontier4

upFractal = (upflagDownFrontier and flagUpFrontier)

// downFractal
bool downflagDownFrontier = true
bool downflagUpFrontier0 = true
bool downflagUpFrontier1 = true
bool downflagUpFrontier2 = true
bool downflagUpFrontier3 = true
bool downflagUpFrontier4 = true

for i = 1 to n
    downflagDownFrontier := downflagDownFrontier and (low[n-i] > low[n])
    downflagUpFrontier0 := downflagUpFrontier0 and (low[n+i] > low[n])
    downflagUpFrontier1 := downflagUpFrontier1 and (low[n+1] >= low[n] and low[n+i + 1] > low[n])
    downflagUpFrontier2 := downflagUpFrontier2 and (low[n+1] >= low[n] and low[n+2] >= low[n] and low[n+i + 2] > low[n])
    downflagUpFrontier3 := downflagUpFrontier3 and (low[n+1] >= low[n] and low[n+2] >= low[n] and low[n+3] >= low[n] and low[n+i + 3] > low[n])
    downflagUpFrontier4 := downflagUpFrontier4 and (low[n+1] >= low[n] and low[n+2] >= low[n] and low[n+3] >= low[n] and low[n+4] >= low[n] and low[n+i + 4] > low[n])
flagDownFrontier = downflagUpFrontier0 or downflagUpFrontier1 or downflagUpFrontier2 or downflagUpFrontier3 or downflagUpFrontier4

downFractal = (downflagDownFrontier and flagDownFrontier)

plotshape(downFractal and show_fractals, style=shape.triangleup, location=location.belowbar, offset=-n, color=color_green)
plotshape(upFractal and show_fractals, style=shape.triangledown, location=location.abovebar, offset=-n, color=color_red)

// *************EMA*************
len_a = input(20, minval=1, title="EMA Length A", group="EMA")
src_a = input(close, title="EMA Source A", group="EMA")
offset_a = input(title="EMA Offset A", type=input.integer, defval=0, minval=-500, maxval=500, group="EMA")
out_a = ema(src_a, len_a)
plot(show_ema ? out_a : na, title="EMA A", color=color_green, offset=offset_a)

len_b = input(50, minval=1, title="EMA Length B", group="EMA")
src_b = input(close, title="EMA Source B", group="EMA")
offset_b = input(title="EMA Offset B", type=input.integer, defval=0, minval=-500, maxval=500, group="EMA")
out_b = ema(src_b, len_b)
ema_b_color = (theme == "dark") ? color_yellow : color_orange
plot(show_ema ? out_b : na, title="EMA B", color=ema_b_color, offset=offset_b)

len_c = input(100, minval=1, title="EMA Length C", group="EMA")
src_c = input(close, title="EMA Source C", group="EMA")
offset_c = input(title="EMA Offset C", type=input.integer, defval=0, minval=-500, maxval=500, group="EMA")
out_c = ema(src_c, len_c)
ema_c_color = (theme == "dark") ? color_white : color_blue
plot(show_ema ? out_c : na, title="EMA C", color=ema_c_color, offset=offset_c)

// *************RSI*************
rsi_len = input(14, minval=1, title="RSI Length", group="RSI")
rsi_src = input(close, "RSI Source", type = input.source, group="RSI")
up = rma(max(change(rsi_src), 0), rsi_len)
down = rma(-min(change(rsi_src), 0), rsi_len)
rsi = down == 0 ? 100 : up == 0 ? 0 : 100 - (100 / (1 + up / down))

// *************Calculation*************
long = (out_a > out_b) and (out_a > out_c) and downFractal and low[2] > out_c and rsi[2] < rsi
short = (out_a < out_b) and (out_a < out_c) and upFractal and high[2] < out_c and rsi[2] > rsi

plotshape(long, style=shape.labelup, color=color_green, location=location.belowbar, title="long label", text= "L", textcolor=color_white)
plotshape(short, style=shape.labeldown, color=color_red, location=location.abovebar, title="short label", text= "S", textcolor=color_white)

// *************End of Signals calculation*************

// Make input options that configure backtest date range
startDate = input(title="Start Date", type=input.integer,
     defval=1, minval=1, maxval=31, group="Orders")
startMonth = input(title="Start Month", type=input.integer,
     defval=1, minval=1, maxval=12, group="Orders")
startYear = input(title="Start Year", type=input.integer,
     defval=2018, minval=1800, maxval=2100, group="Orders")

endDate = input(title="End Date", type=input.integer,
     defval=1, minval=1, maxval=31, group="Orders")
endMonth = input(title="End Month", type=input.integer,
     defval=12, minval=1, maxval=12, group="Orders")
endYear = input(title="End Year", type=input.integer,
     defval=2022, minval=1800, maxval=2100, group="Orders")

// Look if the close time of the current bar
// falls inside the date range
inDateRange = (time >= timestamp(syminfo.timezone, startYear,
         startMonth, startDate, 0, 0)) and
     (time < timestamp(syminfo.timezone, endYear, endMonth, endDate, 0, 0))

// Make inputs that set the take profit % (optional)
longProfitPerc = input(title="Long Take Profit (%)",
     type=input.float, minval=0.0, step=0.1, defval=0.5, group="Orders") * 0.01

shortProfitPerc = input(title="Short Take Profit (%)",
     type=input.float, minval=0.0, step=0.1, defval=0.5, group="Orders") * 0.01

// Figure out take profit price
longExitPrice  = strategy.position_avg_price * (1 + longProfitPerc)
shortExitPrice = strategy.position_avg_price * (1 - shortProfitPerc)

// Plot take profit values for confirmation
plot(series=(strategy.position_size > 0) ? longExitPrice : na,
     color=color_green, style=plot.style_circles,
     linewidth=1, title="Long Take Profit")
plot(series=(strategy.position_size < 0) ? shortExitPrice : na,
     color=color_green, style=plot.style_circles,
     linewidth=1, title="Short Take Profit")

// Submit entry orders
if (inDateRange and long and strategy.opentrades == 0)
    strategy.entry(id="Long", long=true)

if (inDateRange and short and strategy.opentrades == 0)
    strategy.entry(id="Short", long=false)
// Set stop loss level with input options (optional)
longLossPerc = input(title="Long Stop Loss (%)",
     type=input.float, minval=0.0, step=0.1, defval=3.1, group="Orders") * 0.01

shortLossPerc = input(title="Short Stop Loss (%)",
     type=input.float, minval=0.0, step=0.1, defval=3.1, group="Orders") * 0.01

// Determine stop loss price
longStopPrice  = strategy.position_avg_price * (1 - longLossPerc)
shortStopPrice = strategy.position_avg_price * (1 + shortLossPerc)

// Plot stop loss values for confirmation
plot(series=(strategy.position_size > 0) ? longStopPrice : na,
     color=color_red, style=plot.style_cross,
     linewidth=1, title="Long Stop Loss")
plot(series=(strategy.position_size < 0) ? shortStopPrice : na,
     color=color_red, style=plot.style_cross,
     linewidth=1, title="Short Stop Loss")

// Submit exit orders based on calculated stop loss price
if (strategy.position_size > 0)
    strategy.exit(id="ExL",limit=longExitPrice, stop=longStopPrice)

if (strategy.position_size < 0)
    strategy.exit(id="ExS", limit=shortExitPrice, stop=shortStopPrice)

// Exit open market position when date range ends
if (not inDateRange)