InvalidOrder: Not enough base currency. Available: 0.02037. hold: 0. requested: 0.02038.

[rohsat]

Description

I was backtesting my custom logic (exchange=Binance) but I keep getting the below error frequently. I have seen this error in the example code also. It works fine for some of resolution/duration. It seems to be a floating point/rounding/truncate issue.

Could you please take a look?

Error

Traceback (most recent call last):
  File "/Users/rs/Desktop/ML/GitHub/blankly/blankly/exchanges/interfaces/paper_trade/backtest_controller.py", line 771, in run
    self.price_events[0]['function'](self.interface.get_price(self.price_events[0]['asset_id']),
  File "/Users/rs/Desktop/ML/GitHub/blankly/examples/rolling_window_breakout.py", line 84, in price_event
    interface.market_order(symbol, 'sell', state.interface.account[state.base_asset].available)
  File "/Users/rs/Desktop/ML/GitHub/blankly/blankly/exchanges/interfaces/paper_trade/paper_trade_interface.py", line 391, in market_order
    self.local_account.test_trade(symbol, side, qty, price, market_limits['market_order']["quote_increment"],
  File "/Users/rs/Desktop/ML/GitHub/blankly/blankly/exchanges/interfaces/paper_trade/local_account/trade_local.py", line 192, in test_trade
    raise InvalidOrder("Not enough base currency. Available: " +
blankly.utils.exceptions.InvalidOrder: Not enough base currency. Available: 0.02037. hold: 0. requested: 0.02038.

Code

import blankly
from blankly import Strategy, StrategyState, Interface
from blankly import Binance
from blankly.indicators import sma
#import math

my_stop_loss = 0
my_target = 0

my_winning_trades =0
my_losing_trades = 0

my_stop_loss_percent = 1
my_target_percent = 1.5


def init(symbol, state: StrategyState):
    interface: Interface = state.interface
    resolution = state.resolution
    variables = state.variables
    # initialize the historical data
    variables['history'] = interface.history(symbol, 25, resolution, end_date=state.time, return_as='deque')['close']
    variables['owns_position'] = False


def price_event(price, symbol, state: StrategyState):
    interface: Interface = state.interface
    variables = state.variables
    window_max_price = max(variables['history'])
    window_min_price = min(variables['history'])

    action = 'Hold'
    global my_stop_loss
    global my_target
    global my_winning_trades
    global my_losing_trades

    if window_max_price > price > window_min_price:
        action = 'Hold'

    elif price > window_max_price:
        action = 'Buy'

    elif price < window_min_price:
        action = 'Sell'

    # trailing stoploss and target

    if my_stop_loss < price*(100-my_stop_loss_percent)/100:
        my_stop_loss = price*(100-my_stop_loss_percent)/100
        my_target = my_target+ 0.5 * price*(my_target_percent) / 100


    #print(f'{action} --- price:{price},    max:{window_max_price},    min:{window_min_price}')
    variables['history'].append(price)

    # comparing prev diff with current  diff will show a cross
    if action == 'Buy' and not variables['owns_position']:
        interface.market_order(symbol, 'buy', blankly.trunc(interface.cash / price, 5))
        variables['owns_position'] = True
        my_stop_loss = price * (100-my_stop_loss_percent)/100
        my_target = price * (100+my_target_percent)/100
        print(f'My Buy:{price}')
    # Stop Loss Handling
    # elif price < my_stop_loss and variables['owns_position']:
    #     interface.market_order(symbol, 'sell', state.interface.account[state.base_asset].available)
    #     variables['owns_position'] = False
    #     my_stop_loss = 0


    #elif action == 'Sell' and variables['owns_position']:
    elif (price > my_target or price < my_stop_loss) and variables['owns_position']:
        if(price < my_stop_loss):
            print(f'SL Hit:{price}  Target{my_target}   SL {my_stop_loss}')
            my_losing_trades +=1
        elif (price > my_target):
            my_winning_trades +=1
            print(f'Target Hit:{price}  Target{my_target}   SL {my_stop_loss}')
        # use strategy.base_asset if on CoinbasePro or Binance
        # interface.market_order(symbol, 'sell', int(interface.account[symbol].available))
        interface.market_order(symbol, 'sell', state.interface.account[state.base_asset].available)

        variables['owns_position'] = False
        my_stop_loss = 0
        my_target = 0

    # sma200 = sma(variables['history'], period=200)
    # # match up dimensions
    # sma50 = sma(variables['history'], period=50)[-len(sma200):]
    # diff = sma200 - sma50
    # slope_sma50 = (sma50[-1] - sma50[-5]) / 5  # get the slope of the last 5 SMA50 Data Points
    # prev_diff = diff[-2]
    # curr_diff = diff[-1]
    # is_cross_up = slope_sma50 > 0 and curr_diff >= 0 and prev_diff < 0
    # is_cross_down = slope_sma50 < 0 and curr_diff <= 0 and prev_diff > 0
    #
    # # comparing prev diff with current  diff will show a cross
    # if is_cross_up and not variables['owns_position']:
    #     interface.market_order(symbol, 'buy', blankly.trunc(interface.cash/price,5))
    #     variables['owns_position'] = True
    # elif is_cross_down and variables['owns_position']:
    #     # use strategy.base_asset if on CoinbasePro or Binance
    #     # interface.market_order(symbol, 'sell', int(interface.account[symbol].available))
    #     interface.market_order(symbol, 'sell', state.interface.account[state.base_asset].available)

    #     variables['owns_position'] = False

if __name__ == "__main__":
    ex = Binance()
    s = Strategy(ex)
    s.add_price_event(price_event, 'BTC-USDT', resolution='30m', init=init)
    # s.add_price_event(price_event, 'GME', resolution='1h', init=init)
    results = s.backtest(initial_values={'USDT': 1000}, to='3mo')
    print(results)
    print(f'Win Count:{my_winning_trades}, Loss Count:{my_losing_trades}')
    # Or just run it directly on the exchange
    # s.start()

settings.json

{
  "settings": {
    "use_sandbox_websockets": false,
    "websocket_buffer_size": 10000,
    "test_connectivity_on_auth": true,

    "coinbase_pro": {
      "cash": "USD"
    },
    "binance": {
      "cash": "USDT",
      "binance_tld": "com"
    },
    "alpaca": {
      "websocket_stream": "iex",
      "cash": "USD",
      "enable_shorting": true,
      "use_yfinance": false
    },
    "oanda": {
      "cash": "USD"
    },
    "keyless": {
      "cash": "USD"
    },
    "kucoin": {
      "cash": "USDT"
    },
    "ftx": {
      "cash": "USD"
    }
  }
}

backtest.json

{
  "price_data": {
    "assets": []
  },
  "settings": {
    "use_price": "close",
    "smooth_prices": false,
    "GUI_output": true,
    "show_tickers_with_zero_delta": false,
    "save_initial_account_value": true,
    "show_progress_during_backtest": true,
    "cache_location": "./price_caches",
    "continuous_caching": true,
    "resample_account_value_for_metrics": "1d",
    "quote_account_value_in": "USDT",
    "ignore_user_exceptions": true,
    "risk_free_return_rate": 0.0,
    "benchmark_symbol" : null
  }
}

Platform Info

• Python version: 3.10
• Platform: MacOS (M1)

Additional context
Add any other context about the problem here.

[EmersonDove]

Nice catch, this is a known bug but I've never been able to track down where the rounding error happens. I would recommend for now using blankly.trunc to round one more decimal on your account value.

[EmersonDove]

Hey I just ran your code and I can't seem to replicate your error. I'm using python 3.7 but I also couldn't replicate it in a Docker image running python 3.10 (intel Mac).

[AlphonsG]

Back-testing bitcoin from 2022-5-1 to 2023-12-1 with an initial amount of 100000 USDT on KuCoin produced this error. Increasing the initial amount to 10000000000 eliminated it. @EmersonDove