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Brokerages

Key Concepts

Introduction

Brokerages provide you with a connection to the market so you can fill trades. Brokerage models simulate the live behavior of a real brokerage. To avoid sending invalid orders for execution in live trading, the brokerage model validates your orders before LEAN sends them to the real brokerage. Brokerage models combine together all of the models relevant for a brokerage. If you set the appropriate brokerage model, the supported order types, default markets, and some of the security-level models are appropriately set in your algorithm.

Set Models

To set a brokerage model, in the initialize method, call the set_brokerage_model method with a BrokerageName and an AccountType. If you set a brokerage model, it overrides any security level models you manually set in your algorithm.

Select Language:
def initialize(self) -> None:
	# Set the brokerage model to backtest with the most realistic scenario to handle the order validity, margin rate and transaction fee
	self.set_brokerage_model(BrokerageName.OANDA_BROKERAGE) # Defaults to margin account
	self.set_brokerage_model(BrokerageName.BITFINEX, AccountType.MARGIN) # Overrides the default account type, which is AccountType.Cash

In live trading, LEAN doesn't ignore your set_brokerage_model method calls. LEAN uses some of the brokerage model rules to catch invalid orders before they reach your real brokerage.

To view all the pre-built brokerage models, see Supported Models.

Default Behavior

The default brokerage model is the DefaultBrokerageModel, but LEAN has many other brokerage models you can use in your algorithms. For more information about the DefaultBrokerageModel, see QuantConnect Paper Trading.

Modeled Properties

Brokerage models model that following properties:

  • Transaction fees
  • Supported asset classes
  • Account types
  • Support for extended market hours
  • Leverage for assets
  • Trade settlement rules
  • Order properties and updates

Model Structure

Brokerage models should extend the DefaultBrokerageModel class. Extensions of the DefaultBrokerageModel class should implement the following methods:

Select Language:
class CustomBrokerageModelExampleAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        # In the Initialize method, set the custom brokerage model
        self.set_brokerage_model(MyBrokerageModel())

# Define the custom brokerage model outside of the algorithm
class MyBrokerageModel(DefaultBrokerageModel):
    default_markets = {SecurityType.EQUITY: Market.USA}
    required_free_buying_power_percent = 0

    def __init__(self, accountType: account_type = account_type.margin):
        self.account_type = accountType
    
    def can_submit_order(self, security: Security, order: Order,
         message: BrokerageMessageEvent) -> bool:
        return super().can_submit_order(security, order, message)

    def can_update_order(self, security: Security, order: Order,
         request: UpdateOrderRequest, message: BrokerageMessageEvent) -> bool:
        return super().can_update_order(security, order, request, message)

    def can_execute_order(self, security: Security, order: Order) -> bool:
        return super().can_execute_order(security, order)

    def apply_split(self, tickets: List[OrderTicket], split: Split) -> None:
        super().apply_split(tickets, split)

    def get_leverage(self, security: Security) -> float:
        return super().get_leverage(security)

    def get_benchmark(self, securities: SecurityManager) -> IBenchmark:
        return super().get_benchmark(securities)

    def get_fill_model(self, security: Security) -> IFillModel:
        return super().get_fill_model(security)

    def get_fee_model(self, security: Security) -> IFeeModel:
        return super().get_fee_model(security)

    def get_slippage_model(self, security: Security) -> ISlippageModel:
        return super().get_slippage_model(security)

    def get_settlement_model(self, security: Security) -> ISettlementModel:
        return super().get_settlement_model(security)

    def get_buying_power_model(self, security: Security) -> IBuyingPowerModel:
        return super().get_buying_power_model(security)

    def get_margin_interest_rate_model(self, security: Security) -> IMarginInterestRateModel:
        return super().get_margin_interest_rate_model(security)

    def get_shortable_provider(self, security: Security) -> IShortableProvider:
        return super().get_shortable_provider(security)

For a full example algorithm, see this backtest.

Custom brokerage models give you enormous control over your algorithm behavior and allow you to model virtually any brokerage in the world.

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