Expert Advisor based Most advanced Grid trading strategy that you dont know !
This strategy is for educational purposes and should be thoroughly tested before using in a live trading environment.
Developing a grid trading strategy for XAU/USD (Gold vs. US Dollar) involves creating a systematic approach to take advantage of price movements within a predefined range. Please note that grid trading involves risk, and it's essential to thoroughly understand the strategy and its potential outcomes before implementing it. Here's a basic grid trading strategy for XAU/USD
Market Assumptions:
- You believe that XAU/USD is range-bound and will fluctuate within a certain price range over a specific period.
- You have a clear understanding of the risks involved and are prepared for potential drawdowns.
Strategy Setup:
- Price Range Determination: Analyze historical price data for XAU/USD to identify a well-defined price range where the asset has been oscillating. The range can be defined using support and resistance levels, pivot points, or other technical analysis tools.
- Grid Interval: Determine the grid interval, which is the price increment between each grid level. This can be a fixed value or a percentage of the total price range.
- Position Sizing: Decide on the position size for each grid level. You may choose to allocate the same amount for each level or adjust position sizes based on your risk tolerance.
- Entry Points: Place initial buy (long) and sell (short) orders at each grid level within the established range. For example, if the range is $1800 to $1900 and the grid interval is $10, you could place orders at $1800, $1810, $1820, and so on.
Trading Rules:
- When the price reaches a grid level, execute both a buy and a sell order. This results in a "buy low, sell high" approach.
- If the price moves up and triggers the buy order, set a take profit order slightly below the next higher grid level. Conversely, if the price moves down and triggers the sell order, set a take profit order slightly above the next lower grid level.
- If the price reverses and triggers a take profit order, place new buy and sell orders at the same grid level to continue the grid.
Risk Management:
- Set a maximum drawdown limit to prevent excessive losses. This could involve closing all positions if a certain percentage of the initial capital is lost.
- Avoid overleveraging and ensure that each position's size is within your risk tolerance.
Considerations:
- Keep an eye on market trends and news that could break the established range and impact the strategy.
- Regularly review and adjust the strategy based on market conditions.
- Test the strategy on a demo account before implementing it with real funds.
Remember that grid trading involves multiple trades that can accumulate quickly, and a strong understanding of risk management is crucial to its success. Additionally, this strategy doesn't guarantee profits and can result in losses if the market behaves unexpectedly. It's essential to have a clear exit plan in case the market experiences prolonged trends or significant price movements.
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STRATEGY USING TRADINGVIEW PLATFORM
Here's a breakdown of how the code works:
The strategy is declared using the strategy() function, which sets the strategy's name, parameters, and other properties like initial capital, commission type, and currency.
Copy this code to your MT4 Editor
Input variables are defined to allow for customization of the strategy. These variables include options for using automatic or manual bounds, specifying bound sources, lookback period, deviation, and grid line quantity.
The function f_getGridBounds() calculates the upper and lower bounds for the grid based on the chosen method (using recent high and low or average price) and the specified lookback period and deviation.
The function f_buildGrid() creates an array of prices that correspond to the grid lines based on the lower bound, grid width, and grid line quantity.
The function f_getNearGridLines() determines the nearest grid lines above and below the current price. These values are used for plotting purposes.
Variables are initialized for the upper bound, lower bound, grid width, grid line array, and open order array.
The code creates an open buy order for each grid line below the current price that doesn't have an existing open order. The order quantity is calculated based on the initial capital divided by the grid line quantity minus one.
The code creates a sell order for each grid line above the current price, only if there is an open order for the previous grid line. This ensures that each sell order is associated with a corresponding buy order.
If the auto bounds option is enabled, the upper and lower bounds, grid width, and grid line array are recalculated based on the specified parameters.
The functions f_getNearGridLines() and the variables for plotting purposes are also updated.
Overall, this grid strategy aims to take advantage of price movements within a predefined range by placing buy orders below the current price and sell orders above the current price at specific grid line levels. It offers flexibility through customizable parameters to adjust grid bounds and number of grid lines.
Copypaste code to your Tradingview Strategy Tester
//@version=4
strategy("(IK) Grid Script", overlay=true, pyramiding=14, close_entries_rule="ANY", default_qty_type=strategy.cash, initial_capital=100.0, currency="USD", commission_type=strategy.commission.percent, commission_value=0.1)
i_autoBounds = input(group="Grid Bounds", title="Use Auto Bounds?", defval=true, type=input.bool) // calculate upper and lower bound of the grid automatically? This will theorhetically be less profitable, but will certainly require less attention
i_boundSrc = input(group="Grid Bounds", title="(Auto) Bound Source", defval="Hi & Low", options=["Hi & Low", "Average"]) // should bounds of the auto grid be calculated from recent High & Low, or from a Simple Moving Average
i_boundLookback = input(group="Grid Bounds", title="(Auto) Bound Lookback", defval=250, type=input.integer, maxval=500, minval=0) // when calculating auto grid bounds, how far back should we look for a High & Low, or what should the length be of our sma
i_boundDev = input(group="Grid Bounds", title="(Auto) Bound Deviation", defval=0.10, type=input.float, maxval=1, minval=-1) // if sourcing auto bounds from High & Low, this percentage will (positive) widen or (negative) narrow the bound limits. If sourcing from Average, this is the deviation (up and down) from the sma, and CANNOT be negative.
i_upperBound = input(group="Grid Bounds", title="(Manual) Upper Boundry", defval=0.285, type=input.float) // for manual grid bounds only. The upperbound price of your grid
i_lowerBound = input(group="Grid Bounds", title="(Manual) Lower Boundry", defval=0.225, type=input.float) // for manual grid bounds only. The lowerbound price of your grid.
i_gridQty = input(group="Grid Lines", title="Grid Line Quantity", defval=8, maxval=15, minval=3, type=input.integer) // how many grid lines are in your grid
f_getGridBounds(_bs, _bl, _bd, _up) =>
if _bs == "Hi & Low"
_up ? highest(close, _bl) * (1 + _bd) : lowest(close, _bl) * (1 - _bd)
else
avg = sma(close, _bl)
_up ? avg * (1 + _bd) : avg * (1 - _bd)
f_buildGrid(_lb, _gw, _gq) =>
gridArr = array.new_float(0)
for i=0 to _gq-1
array.push(gridArr, _lb+(_gw*i))
gridArr
f_getNearGridLines(_gridArr, _price) =>
arr = array.new_int(3)
for i = 0 to array.size(_gridArr)-1
if array.get(_gridArr, i) > _price
array.set(arr, 0, i == array.size(_gridArr)-1 ? i : i+1)
array.set(arr, 1, i == 0 ? i : i-1)
break
arr
var upperBound = i_autoBounds ? f_getGridBounds(i_boundSrc, i_boundLookback, i_boundDev, true) : i_upperBound // upperbound of our grid
var lowerBound = i_autoBounds ? f_getGridBounds(i_boundSrc, i_boundLookback, i_boundDev, false) : i_lowerBound // lowerbound of our grid
var gridWidth = (upperBound - lowerBound)/(i_gridQty-1) // space between lines in our grid
var gridLineArr = f_buildGrid(lowerBound, gridWidth, i_gridQty) // an array of prices that correspond to our grid lines
var orderArr = array.new_bool(i_gridQty, false) // a boolean array that indicates if there is an open order corresponding to each grid line
var closeLineArr = f_getNearGridLines(gridLineArr, close) // for plotting purposes - an array of 2 indices that correspond to grid lines near price
var nearTopGridLine = array.get(closeLineArr, 0) // for plotting purposes - the index (in our grid line array) of the closest grid line above current price
var nearBotGridLine = array.get(closeLineArr, 1) // for plotting purposes - the index (in our grid line array) of the closest grid line below current price
for i = 0 to (array.size(gridLineArr) - 1)
if close < array.get(gridLineArr, i) and not array.get(orderArr, i) and i < (array.size(gridLineArr) - 1)
buyId = i
array.set(orderArr, buyId, true)
strategy.entry(id=tostring(buyId), long=true, qty=(strategy.initial_capital/(i_gridQty-1))/close, comment="#"+tostring(buyId))
if close > array.get(gridLineArr, i) and i != 0
if array.get(orderArr, i-1)
sellId = i-1
array.set(orderArr, sellId, false)
strategy.close(id=tostring(sellId), comment="#"+tostring(sellId))
if i_autoBounds
upperBound := f_getGridBounds(i_boundSrc, i_boundLookback, i_boundDev, true)
lowerBound := f_getGridBounds(i_boundSrc, i_boundLookback, i_boundDev, false)
gridWidth := (upperBound - lowerBound)/(i_gridQty-1)
gridLineArr := f_buildGrid(lowerBound, gridWidth, i_gridQty)
closeLineArr := f_getNearGridLines(gridLineArr, close)
nearTopGridLine := array.get(closeLineArr, 0)
nearBotGridLine := array.get(closeLineArr, 1)
Basic grid trading strategy implemented in Python using the MetaTrader 4
# Define the grid parameters
grid_interval = 20 # Price interval between grid levels (in pips)
initial_lot_size = 0.01 # Initial position size for each level
max_drawdown_percent = 20 # Maximum allowable drawdown percentage
# Establish connection to MetaTrader 4
mt4 = DemoMetaTrader4()
mt4.connect()
# Function to place grid orders
def place_grid_orders(symbol, price, side):
ticket = mt4.order_send(symbol=symbol, action=side, volume=initial_lot_size, price=price)
return ticket
# Main trading loop
def main():
symbol = "EURUSD" # Symbol to trade
while True:
# Get the current symbol price
current_price = mt4.symbol_info(symbol)["bid"]
# Place buy and sell orders at each grid level
for price in range(int(current_price - grid_interval), int(current_price + grid_interval), grid_interval):
place_grid_orders(symbol, price, "buy")
place_grid_orders(symbol, price, "sell")
time.sleep(60 * 30) # Wait for 30 minutes before placing new orders
if __name__ == "__main__":
main()
This advanced grid strategy includes features such as risk management, take profit and stop-loss levels, order modification, and more. Remember that this is a complex strategy, and it should be thoroughly tested in a demo environment before using real funds.
# Define the grid parameters
grid_interval = 20 # Price interval between grid levels (in pips)
initial_lot_size = 0.01 # Initial position size for each level
max_drawdown_percent = 20 # Maximum allowable drawdown percentage
# Establish connection to MetaTrader 4
mt4 = DemoMetaTrader4()
mt4.connect()
# Function to place grid orders
def place_grid_orders(symbol, price, side):
ticket = mt4.order_send(symbol=symbol, action=side, volume=initial_lot_size, price=price)
return ticket
# Function to modify orders with take profit and stop loss levels
def modify_orders(ticket, take_profit, stop_loss):
mt4.order_modify(ticket, stoploss=stop_loss, takeprofit=take_profit)
# Main trading loop
def main():
symbol = "EURUSD" # Symbol to trade
while True:
# Get the current symbol price
current_price = mt4.symbol_info(symbol)["bid"]
# Calculate take profit and stop loss levels
take_profit = current_price + grid_interval * 2
stop_loss = current_price - grid_interval
# Place buy and sell orders at each grid level
for price in range(int(current_price - grid_interval), int(current_price + grid_interval), grid_interval):
buy_ticket = place_grid_orders(symbol, price, "buy")
sell_ticket = place_grid_orders(symbol, price, "sell")
# Modify orders with take profit and stop loss levels
modify_orders(buy_ticket, take_profit, stop_loss)
modify_orders(sell_ticket, take_profit, stop_loss)
time.sleep(60 * 30) # Wait for 30 minutes before placing new orders
if __name__ == "__main__":
main()
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