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Portfolio

Cashbook

Introduction

The CashBook is a dictionary where the keys are currency tickers and the values are Cash objects. The Cash objects track the amount of each currency in the portfolio. As you buy and sell securities, LEAN credits and debits the Cash objects to reflect your cash holdings.

Account Currency

The default account currency is USD, but you can change it. All of the properties of the Portfolio object that return a currency value denominate the currency value in your account currency. Depending on your account currency and security subscriptions, LEAN may add internal security subscriptions to calculate the value_in_account_currency. For example, if you only add BTCETH to your algorithm and set the account currency to USDT, LEAN adds BTCUSDT and ETHUSDT as internal feeds.

To get your account currency, use the account_currency property.

Select Language: 
account_currency = self.account_currency

To set your account currency, in the initialize method, call the set_account_currency method. You can only set the account currency once. LEAN ignores each additional call to set_account_currency.

Select Language: 
self.set_account_currency("EUR")

Settled vs Unsettled Cash

The portfolio has two independent cashbooks. The cash_book tracks settled cash and the unsettled_cash_book tracks unsettled cash, which you can't spend. If you trade with a margin account, trades settle immediately so LEAN credits and debits the cash_book at the time of the trade. In some cases, transactions can take time to settle. For example, Equity trades in a cash account settle in T+3. Therefore, if you sell shares of stock on Monday, the transaction settles on Thursday. In contrast, Option trades settle in T+1.

Select Language: 
settled_cash_book = self.portfolio.cash_book
unsettled_cash_book = self.portfolio.unsettled_cash_book

Track Cash Balances

To get the balance of a currency in the cash book, use the amount property.

Select Language: 
# Return the cash book balance in US Dollar amount.
usd = self.portfolio.cash_book["USD"].amount
# Return the cash book balance in Bitcoin amount.
btc = self.portfolio.cash_book["BTC"].amount

To get the value of a currency in the cash book, denominated in your account currency, use the value_in_account_currency property.

Select Language: 
# Return the cash book value of Ethereum in account currency (US Dollar, Euro, etc.) amount. 
eth_value = self.portfolio.cash_book["ETH"].value_in_account_currency

Deposits and Withdrawals

In backtests, you can add and remove cash from the cash book. To add or remove cash, call the add_amount method.

Select Language: 
# Adjust the backtesting cashbook balances to add 100 USD and subtract 1.5 BTC.
new_usd_balance = self.portfolio.cash_book["USD"].add_amount(100)
new_btc_balance = self.portfolio.cash_book["BTC"].add_amount(-1.5)

In live trading, add and withdraw cash through your brokerage account. If you adjust the cash balances in your algorithm with the add_amount method, the cash balance in your algorithm will be out of sync with the cash balance in your brokerage account.

Currency Symbols

A currency symbol is a graphic that represents the currency name. For example, $ is for dollars, € for euros, and ฿ for Bitcoin. To get the symbol of a currency in the cash book, use currency_symbol property.

Select Language: 
usd_symbol = self.portfolio.cash_book["USD"].currency_symbol

Conversion Rates

To get the conversion rate for a currency in the cashbook to your account currency, use the conversion_rate property.

Select Language: 
eur_conversion_rate = self.portfolio.cash_book["EUR"].conversion_rate

Examples

The following examples demonstrate common practices for controlling the portfolio cashbook.

Example 1: Dollar Cost Averaging

The following algorithm deposits USD 1000 on every month's start and buys SPY with the deposited cash. It results in a dollar cost averaging investment strategy on the overall market.

Select Language: 
class PortfolioCashbookAlgorithm(QCAlgorithm):
    deposit = 1000

    def initialize(self) -> None:
        self.set_start_date(2021, 1, 1)
        self.set_end_date(2022, 1, 1)
        self.set_cash(1)

        # Request SPY data to trade the overall market representative.
        self.spy = self.add_equity("SPY").symbol

        # Deposit each month start and invest in SPY by dollar cost averaging.
        self.schedule.on(
            self.date_rules.month_start(self.spy),
            self.time_rules.after_market_open(self.spy, 0),
            self.deposit_and_rebalance
        )
        
        # To warm up the price data of SPY to calculate the quantity to be brought.
        self.set_warm_up(1)
    
    def deposit_and_rebalance(self) -> None:
        # Deposit the account currency's preset level ($1000) at the month's start.
        # Simulate the monthly salary deposit for dollar cost-averaging investment in the market.
        self.portfolio.cash_book[self.account_currency].add_amount(self.deposit)

        # Calculate the number of shares that can be invested using the deposited amount.
        quantity = self.deposit // self.securities[self.spy].price
        self.market_order(self.spy, quantity)

Example 2: Crypto Cashbook

This example trades an EMA cross strategy on the ETH-BTC crypto pair in a cash account. To obtain the maximum tradable order size, we need to use the cash book and check the amount of BTC in long ETHBTC trades and in short ETHBTC trades to avoid insufficient initial margin.

Select Language: 
class PortfolioCashbookAlgorithm(QCAlgorithm):

    buffer = 0.01

    def initialize(self) -> None:
        self.set_start_date(2021, 8, 1)
        self.set_end_date(2021, 9, 1)
        # Set the account currency as USDT and set the starting cash in a cash account.
        self.set_brokerage_model(BrokerageName.COINBASE, AccountType.CASH)
        self.set_account_currency("USDT", 100)
        self.set_cash("BTC", 100)
        self.set_cash("ETH", 2000)

        # We would like to trade the EMA cross between 2 popular cryptos BTC & ETH,
        # so we are requesting ETHBTC data to find trading opportunities.
        self.ethbtc = self.add_crypto("ETHBTC", Resolution.MINUTE, Market.COINBASE).symbol

        # Add automatic-updating EMA indicator for trend trade signal emission.
        self._ema = self.ema(self.ethbtc, 50, Resolution.DAILY)
        # Warm up the indicator for its readiness usage immediately.
        self.warm_up_indicator(self.ethbtc, self._ema, Resolution.DAILY)

    def on_data(self, slice: Slice) -> None:
        bar = slice.bars.get(self.ethbtc)
        if bar and self._ema.is_ready:
            ema = self._ema.current.value
            # ETHBTC's current price is higher than EMA, suggesting an uptrend.
            if bar.close > ema and not self.portfolio[self.ethbtc].is_long:
                # Convert to the corresponding quantity of the quote currency.
                self.market_order(self.ethbtc, self.portfolio.cash_book["BTC"].amount * (1 - self.buffer) / bar.close)
            # ETHBTC's current price is below the EMA, suggesting a downtrend.
            elif bar.close < ema and not self.portfolio[self.ethbtc].is_short:
                self.market_order(self.ethbtc, -self.portfolio.cash_book["ETH"].amount)

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