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How to create a trading bot in Python

This article and video offer step-by-step instructions for creating a trading robot in Python.

Note

cTrader is the only major trading platform with native Python support, allowing you to write code in Python and build bots, technical indicators and tools directly in cTrader Windows or Mac. No adapter or complex workaround required.

Create a trading robot

In the cBots tab of the Algo app, click the New button to start creating a new trading bot.

Give the cBot a name and select Python as the programming language.

Note

cTrader provides several premade algorithms in Python covering a wide range of strategies and automated trading actions. These algorithm templates already contain trading logic and customisable parameters and are ready to run once you save and build them.

Select Using template as the creation method, choose Grid Sample, then click Create.

The Grid cBot implements a grid trading strategy where multiple buy or sell orders for a symbol are placed at regular price intervals or steps, resulting in a grid of positions.

Let's build our cBot to validate its code.

Press Ctrl+B or click Build.

Press Cmd+B or click the Build icon.

Add an indicator

Let's incorporate an indicator into our trading bot to improve its accuracy.

The Relative Strength Index (RSI) is a popular indicator that signals overbought or oversold conditions in the market. This indicator can help our cBot avoid opening new positions when the market is stretched in one direction.

Integrate RSI into the robot logic. Initialise the indicator with a default period of 14 and set the overbought and oversold levels to 70 and 30 respectively. Use the closing prices of the symbol to create the RSI. 

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self.rsi_period = getattr(api, "RsiPeriod", 14)
self.rsi_overbought = getattr(api, "RsiOverbought", 70)
self.rsi_oversold = getattr(api, "RsiOversold", 30)
self.rsi = api.Indicators.RelativeStrengthIndex(api.Bars.ClosePrices, self.rsi_period)

Add the logic to check whether the RSI conditions allow a trade before opening a position. If the filter blocks the trade, log a message showing the current RSI value.

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if len(self.get_grid_positions()) == 0:
    # self.open_position()
    if self.passes_rsi_filter():
        self.open_position()
    else:
        api.Print("RSI filter blocked initial entry (RSI={:.2f})".format(self.get_rsi_value()))

Write the code that ensures that grid position is opened only if the price has moved enough and the RSI value is within a neutral range. Use the last closed bar RSI value for stability and print a message when blocked by the RSI filter.

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if distance >= api.StepPips:
    # self.open_position()
    if self.passes_rsi_filter():
        self.open_position()
    else:
        api.Print("RSI filter: no new entry (RSI={:.2f}, range {}-{})"
                    .format(self.get_rsi_value(), self.rsi_oversold, self.rsi_overbought))

def get_rsi_value(self):
    # Use the last CLOSED bar for stability
    return self.rsi.Result.Last(1)

def passes_rsi_filter(self):
    r = self.get_rsi_value()
    return (r > self.rsi_oversold) and (r < self.rsi_overbought)

Adjust the calculation logic for distance in pips between the current market price and a position's entry price.

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def get_distance_in_pips(self, position):
    # return (position.EntryPrice - api.Symbol.Ask if position.TradeType == TradeType.Buy else api.Symbol.Bid - position.EntryPrice) / api.Symbol.PipSize
    if position.TradeType == TradeType.Buy:
        diff = position.EntryPrice - api.Symbol.Ask
    else:
        diff = api.Symbol.Bid - position.EntryPrice
    return diff / api.Symbol.PipSize

You can copy the full Python code with the integrated RSI indicator below:

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import clr

clr.AddReference("cAlgo.API")

# Import cAlgo API types
from cAlgo.API import *

# Import trading wrapper functions
from robot_wrapper import *

class SupercBot():
    def on_start(self):
        self.volumeInUnits = api.Symbol.QuantityToVolumeInUnits(api.VolumeInLots)
        self.enoughMoney = True

        self.rsi_period = getattr(api, "RsiPeriod", 14)
        self.rsi_overbought = getattr(api, "RsiOverbought", 70)
        self.rsi_oversold = getattr(api, "RsiOversold", 30)
        self.rsi = api.Indicators.RelativeStrengthIndex(api.Bars.ClosePrices, self.rsi_period)

        if len(self.get_grid_positions()) == 0:
            if self.passes_rsi_filter():
                self.open_position()
            else:
                api.Print("RSI filter blocked initial entry (RSI={:.2f})".format(self.get_rsi_value()))

    def on_tick(self):
        grid_positions = self.get_grid_positions()
        net_profit_sum = sum([p.NetProfit for p in grid_positions])
        if net_profit_sum >= api.TargetProfit:
            api.Print("Target profit is reached. Closing all grid positions")
            self.close_grid_positions()
            api.Print("All grid positions are closed. Stopping cBot")
            api.Stop()

        if len(grid_positions) > 0 and self.enoughMoney == True:
            position_with_highest_pips = sorted(grid_positions, key=lambda pos: pos.Pips, reverse=True)[0]
            distance = self.get_distance_in_pips(position_with_highest_pips)          
            if distance >= api.StepPips:
                if self.passes_rsi_filter():
                    self.open_position()
                else:
                    api.Print("RSI filter: no new entry (RSI={:.2f}, range {}-{})"
                              .format(self.get_rsi_value(), self.rsi_oversold, self.rsi_overbought))

    def get_rsi_value(self):
        # Use the last CLOSED bar for stability
        return self.rsi.Result.Last(1)

    def passes_rsi_filter(self):
        r = self.get_rsi_value()
        return (r > self.rsi_oversold) and (r < self.rsi_overbought)

    def get_grid_positions(self):
        return [pos for pos in api.Positions if pos.SymbolName == api.SymbolName and pos.TradeType == api.TradeType]

    def open_position(self):
        result = api.ExecuteMarketOrder(api.TradeType, api.SymbolName, self.volumeInUnits, "Grid")
        if result.Error == ErrorCode.NoMoney:
            self.enoughMoney = False
            api.Print("Not enough money to open additional positions")

    def close_grid_positions(self):
        for position in self.get_grid_positions():
            position.Close()

        if len(self.get_grid_positions()) > 0:
            self.close_grid_positions()

    def get_distance_in_pips(self, position):
        if position.TradeType == TradeType.Buy:
            diff = position.EntryPrice - api.Symbol.Ask
        else:
            diff = api.Symbol.Bid - position.EntryPrice
        return diff / api.Symbol.PipSize

Start an instance

Let's return to our cBot and build it. Now, click the Start cBot icon for any instance, and the trading bot will begin running.

Alternatively, you can click Add instance, specify your preferred instance parameters, add the new instance and start it.

By adding and customising new instances, you can run the cBot simultaneously on different symbols, periods or parameters.

Run the bot elsewhere

With cloud synchronisation enabled, the cBot appears automatically in all cTrader applications where your cTID is active. We can start the same trading robot in Cloud in any cTrader app, including cTrader Mobile and Web.

In cTrader Algo, start the cBot.

This article has demonstrated how to create a Python trading robot and start it, empowering you to automate your strategies and run algos on any device.

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