async def _init(self):
info = await self.cc.public_get_symbols()
for e in info['result']:
if e['name'] == self.symbol:
break
else:
raise Exception('symbol missing')
self.coin = e['base_currency']
self.quot = e['quote_currency']
self.price_step = float(e['price_filter']['tick_size'])
self.qty_step = float(e['lot_size_filter']['qty_step'])
self.min_qty = float(e['lot_size_filter']['min_trading_qty'])
self.prdn = lambda n: round_dn(n, self.price_step)
self.prup = lambda n: round_up(n, self.price_step)
self.ardn = lambda n: round_dn(n, self.qty_step)
self.arup = lambda n: round_up(n, self.qty_step)
await self.update_position()
await self.init_order_book()
async def _init(self):
exchange_info = await self.cc.fapiPublic_get_exchangeinfo()
for e in exchange_info['symbols']:
if e['symbol'] == self.symbol:
self.coin = e['baseAsset']
self.quot = e['quoteAsset']
self.margin_coin = e['marginAsset']
price_precision = e['pricePrecision']
qty_precision = e['quantityPrecision']
for q in e['filters']:
if q['filterType'] == 'LOT_SIZE':
self.min_qty = float(q['minQty'])
elif q['filterType'] == 'MARKET_LOT_SIZE':
self.qty_step = float(q['stepSize'])
elif q['filterType'] == 'PRICE_FILTER':
self.price_step = float(q['tickSize'])
self.ardn = lambda n: round_dn(n, self.qty_step)
self.arup = lambda n: round_up(n, self.qty_step)
self.prdn = lambda n: round_dn(n, self.price_step)
self.prup = lambda n: round_up(n, self.price_step)
break
await self.update_position()
await self.init_order_book()
def backtest(trades_list: [dict], settings: dict):
# trades format is [{price: float, buyer_maker: bool}]
# no static mode
grid_spacing = settings['grid_spacing']
grid_coefficient = settings['grid_coefficient']
price_step = settings['price_step']
qty_step = settings['qty_step']
inverse = settings['inverse']
liq_diff_threshold = settings['liq_diff_threshold']
stop_loss_pos_reduction = settings['stop_loss_pos_reduction']
min_qty = settings['min_qty']
ddown_factor = settings['ddown_factor']
leverage = settings['leverage']
max_leverage = settings['max_leverage']
maker_fee = settings['maker_fee']
taker_fee = settings['taker_fee']
min_markup = settings['min_markup']
max_markup = settings['max_markup']
n_close_orders = settings['n_close_orders']
do_long = settings['do_long']
do_shrt = settings['do_shrt']
min_notional = settings[
'min_notional'] if 'min_notional' in settings else 0.0
cross_mode = settings['cross_mode'] if 'cross_mode' in settings else True
if inverse:
calc_cost = lambda qty_, price_: qty_ / price_
if settings['cross_mode']:
calc_liq_price = lambda balance_, pos_size_, pos_price_: \
bybit_calc_cross_shrt_liq_price(balance_,
pos_size_,
pos_price_,
leverage=max_leverage) \
if pos_size_ < 0.0 else \
bybit_calc_cross_long_liq_price(balance_,
pos_size_,
pos_price_,
leverage=max_leverage)
else:
calc_liq_price = lambda balance_, pos_size_, pos_price_: \
bybit_calc_isolated_shrt_liq_price(balance_,
pos_size_,
pos_price_,
leverage=leverage) \
if pos_size_ < 0.0 else \
bybit_calc_isolated_long_liq_price(balance_,
pos_size_,
pos_price_,
leverage=leverage)
if settings['default_qty'] <= 0.0:
calc_default_qty_ = lambda balance_, last_price: \
calc_default_qty(min_qty, qty_step, balance_ * last_price, settings['default_qty'])
else:
calc_default_qty_ = lambda balance_, last_price: settings[
'default_qty']
calc_max_pos_size = lambda balance_, price_: balance_ * price_ * leverage
else:
calc_cost = lambda qty_, price_: qty_ * price_
if settings['cross_mode']:
calc_liq_price = lambda balance_, pos_size_, pos_price_: \
binance_calc_cross_shrt_liq_price(balance_,
pos_size_,
pos_price_,
leverage=leverage) \
if pos_size_ < 0.0 else \
binance_calc_cross_long_liq_price(balance_,
pos_size_,
pos_price_,
leverage=leverage)
else:
calc_liq_price = lambda balance_, pos_size_, pos_price_: \
binance_calc_isolated_shrt_liq_price(balance_,
pos_size_,
pos_price_,
leverage=leverage) \
if pos_size_ < 0.0 else \
binance_calc_isolated_long_liq_price(balance_,
pos_size_,
pos_price_,
leverage=leverage)
if settings['default_qty'] <= 0.0:
calc_default_qty_ = lambda balance_, last_price: \
calc_default_qty(max(min_qty, round_up(min_notional / last_price, qty_step)),
qty_step, balance_ / last_price, settings['default_qty'])
else:
calc_default_qty_ = lambda balance_, last_price: \
max(settings['default_qty'], round_up(min_notional / last_price, qty_step))
calc_max_pos_size = lambda balance_, price_: balance_ / price_ * leverage
calc_long_reentry_price_ = lambda balance_, pos_margin_, pos_price_, highest_bid_: \
min(highest_bid_, calc_long_reentry_price(price_step, grid_spacing, grid_coefficient,
balance_, pos_margin_, pos_price_))
calc_shrt_reentry_price_ = lambda balance_, pos_margin_, pos_price_, lowest_ask_: \
max(lowest_ask_, calc_shrt_reentry_price(price_step, grid_spacing, grid_coefficient,
balance_, pos_margin_, pos_price_))
balance = settings['starting_balance']
trades = []
ob = [
min(trades_list[0]['price'], trades_list[1]['price']),
max(trades_list[0]['price'], trades_list[1]['price'])
]
pos_size = 0.0
pos_price = 0.0
bid_price = ob[0]
ask_price = ob[1]
liq_price = 0.0
pnl_sum = 0.0
loss_sum = 0.0
profit_sum = 0.0
ema_alpha = 2 / (settings['ema_span'] + 1)
ema_alpha_ = 1 - ema_alpha
ema = trades_list[0]['price']
k = 0
break_on = {
e[0]: eval(e[1])
for e in settings['break_on'] if e[0].startswith('ON:')
}
for t in trades_list:
append_trade = False
if t['buyer_maker']:
# buy
if pos_size == 0.0:
# no pos
if do_long:
bid_price = min(ob[0], round_dn(ema, price_step))
bid_qty = calc_default_qty_(balance, ob[0])
else:
bid_price = 0.0
bid_qty = 0.0
elif pos_size > 0.0:
if calc_diff(
liq_price, ob[1]
) < liq_diff_threshold and t['price'] <= liq_price:
# long liq
print(f'break on long liquidation, liq price: {liq_price}')
return []
# long reentry
bid_qty = calc_entry_qty(qty_step, ddown_factor,
calc_default_qty_(balance, ob[0]),
calc_max_pos_size(balance, ob[0]),
pos_size)
if bid_qty >= max(min_qty, min_notional / t['price']):
pos_margin = calc_cost(pos_size, pos_price) / leverage
bid_price = calc_long_reentry_price_(
balance, pos_margin, pos_price, ob[0])
else:
bid_price = 0.0
else:
# short pos
if calc_diff(liq_price, ob[0]) < liq_diff_threshold:
# short soft stop
bid_price = ob[0]
bid_qty = round_up(-pos_size * stop_loss_pos_reduction,
qty_step)
else:
if t['price'] <= pos_price:
# short close
min_close_qty = \
max(min_qty,
round_dn(calc_default_qty_(balance, ob[0]) * 0.5, qty_step))
qtys, prices = calc_shrt_closes(
price_step, qty_step, min_qty, min_markup,
max_markup, min_close_qty, pos_size, pos_price,
ob[0], n_close_orders)
if len(qtys) > 0:
bid_qty = qtys[0]
bid_price = prices[0]
else:
bid_price = 0.0
else:
bid_price = 0.0
ob[0] = t['price']
if t['price'] < bid_price and bid_qty >= min_qty:
# filled trade
qty = bid_qty
price = bid_price
cost = calc_cost(bid_qty, bid_price)
pnl = -cost * maker_fee
if pos_size >= 0.0:
# create or increase long pos
trade_side = 'long'
trade_type = 'entry'
new_pos_size = pos_size + bid_qty
pos_price = pos_price * (pos_size / new_pos_size) + \
bid_price * (bid_qty / new_pos_size)
pos_size = new_pos_size
roi = 0.0
else:
# close short pos
trade_side = 'shrt'
gain = pos_price / bid_price - 1
pnl += cost * gain
if gain > 0.0:
trade_type = 'close'
profit_sum += pnl
else:
trade_type = 'stop_loss'
loss_sum += pnl
pos_size = pos_size + bid_qty
roi = gain * leverage
balance += pnl
pnl_sum += pnl
liq_price = calc_liq_price(balance, pos_size, pos_price)
append_trade = True
else:
# sell
if pos_size == 0.0:
# no pos
if do_shrt:
ask_price = max(ob[1], round_up(ema, price_step))
ask_qty = -calc_default_qty_(balance, ob[1])
else:
ask_price = 9e9
ask_qty = 0.0
elif pos_size > 0.0:
# long pos
if calc_diff(liq_price, ob[1]) < liq_diff_threshold:
# long soft stop
ask_price = ob[1]
ask_qty = -round_up(pos_size * stop_loss_pos_reduction,
qty_step)
else:
if t['price'] >= pos_price:
# long close
min_close_qty = \
max(min_qty,
round_dn(calc_default_qty_(balance, ob[1]) * 0.5, qty_step))
qtys, prices = calc_long_closes(
price_step, qty_step, min_qty, min_markup,
max_markup, min_close_qty, pos_size, pos_price,
ob[1], n_close_orders)
if len(qtys) > 0:
ask_qty = qtys[0]
ask_price = prices[0]
else:
ask_price = 9e9
else:
ask_price = 9e9
else:
if calc_diff(
liq_price, ob[1]
) < liq_diff_threshold and t['price'] >= liq_price:
# shrt liq
print(f'break on shrt liquidation, liq price: {liq_price}')
return []
# shrt reentry
ask_qty = -calc_entry_qty(
qty_step, ddown_factor, calc_default_qty_(balance, ob[1]),
calc_max_pos_size(balance, ob[1]), pos_size)
if -ask_qty >= max(min_qty, min_notional / t['price']):
pos_margin = calc_cost(-pos_size, pos_price) / leverage
ask_price = calc_shrt_reentry_price_(
balance, pos_margin, pos_price, ob[0])
else:
ask_price = 9e9
ob[1] = t['price']
if t['price'] > ask_price and abs(ask_qty) >= min_qty:
# filled trade
qty = ask_qty
price = ask_price
cost = calc_cost(-ask_qty, ask_price)
pnl = -cost * maker_fee
if pos_size <= 0.0:
# create or increase shrt pos
trade_side = 'shrt'
trade_type = 'entry'
new_pos_size = pos_size + ask_qty
pos_price = pos_price * (pos_size / new_pos_size) + \
ask_price * (ask_qty / new_pos_size)
pos_size = new_pos_size
roi = 0.0
else:
# close long pos
trade_side = 'long'
gain = ask_price / pos_price - 1
pnl += cost * gain
if gain > 0.0:
trade_type = 'close'
profit_sum += pnl
else:
trade_type = 'stop_loss'
loss_sum += pnl
pos_size = pos_size + ask_qty
roi = gain * leverage
balance += pnl
pnl_sum += pnl
liq_price = calc_liq_price(balance, pos_size, pos_price)
append_trade = True
if append_trade:
progress = k / len(trades_list)
total_gain = (pnl_sum + settings['starting_balance']
) / settings['starting_balance']
n_days_ = (t['timestamp'] -
trades_list[0]['timestamp']) / (1000 * 60 * 60 * 24)
adg = total_gain**(1 / n_days_)
trades.append({
'trade_id':
k,
'side':
trade_side,
'type':
trade_type,
'price':
price,
'qty':
qty,
'pnl':
pnl,
'roi':
roi,
'pos_size':
pos_size,
'pos_price':
pos_price,
'balance':
balance,
'max_pos_size':
calc_max_pos_size(balance, t['price']),
'pnl_sum':
pnl_sum,
'loss_sum':
loss_sum,
'profit_sum':
profit_sum,
'progress':
progress,
'liq_price':
liq_price,
'gain':
total_gain,
'n_days':
n_days_,
'average_daily_gain':
adg,
'liq_diff':
min(1.0, calc_diff(liq_price, t['price'])),
'timestamp':
t['timestamp']
})
balance = max(balance, settings['starting_balance'])
line = f"\r{progress:.3f} net pnl {pnl_sum:.8f} "
line += f"profit sum {profit_sum:.5f} "
line += f"loss sum {loss_sum:.5f} "
line += f"balance {balance:.5f} qty {calc_default_qty_(balance, ob[0]):.4f} "
line += f"adg {trades[-1]['average_daily_gain']:.3f} "
line += f"max pos pct {abs(pos_size) / calc_max_pos_size(balance, t['price']):.3f} "
line += f"liq diff {min(1.0, calc_diff(trades[-1]['liq_price'], ob[0])):.3f} "
line += f"pos size {pos_size:.4f} "
print(line, end=' ')
for key, condition in break_on.items():
if condition(trades[-1], t):
print('break on', key)
return []
ema = ema * ema_alpha_ + t['price'] * ema_alpha
k += 1
return trades
def backtest(trades_list: [dict], settings: dict):
# trades format is [{price: float, buyer_maker: bool}]
# no static mode
grid_spacing = settings['grid_spacing']
grid_coefficient = settings['grid_coefficient']
price_step = settings['price_step']
qty_step = settings['qty_step']
inverse = settings['inverse']
liq_diff_threshold = settings['liq_diff_threshold']
stop_loss_pos_reduction = settings['stop_loss_pos_reduction']
min_qty = settings['min_qty']
ddown_factor = settings['ddown_factor']
leverage = settings['leverage']
starting_balance = settings['balance']
maker_fee = settings['maker_fee']
taker_fee = settings['taker_fee']
min_markup = settings['min_markup']
max_markup = settings['max_markup']
n_close_orders = settings['n_close_orders']
break_on_loss = settings['break_on_loss']
min_notional = settings[
'min_notional'] if 'min_notional' in settings else 0.0
if inverse:
calc_cost = lambda qty_, price_: qty_ / price_
calc_liq_price = lambda balance_, pos_size_, pos_price_: \
bybit_calc_cross_shrt_liq_price(balance_, pos_size_, pos_price_, leverage=leverage) \
if pos_size_ < 0.0 else \
bybit_calc_cross_long_liq_price(balance_, pos_size_, pos_price_, leverage=leverage)
if settings['default_qty'] <= 0.0:
calc_default_qty_ = lambda balance_, last_price: \
calc_default_qty(min_qty, qty_step, balance_ * last_price, settings['default_qty'])
else:
calc_default_qty_ = lambda balance_, last_price: settings[
'default_qty']
calc_max_pos_size = lambda balance_, price_: balance_ * price_ * leverage
else:
calc_cost = lambda qty_, price_: qty_ * price_
calc_liq_price = lambda balance_, pos_size_, pos_price_: \
binance_calc_cross_shrt_liq_price(balance_, pos_size_, pos_price_, leverage=leverage) \
if pos_size_ < 0.0 else \
binance_calc_cross_long_liq_price(balance_, pos_size_, pos_price_, leverage=leverage)
if settings['default_qty'] <= 0.0:
calc_default_qty_ = lambda balance_, last_price: \
calc_default_qty(max(min_qty, round_up(min_notional / last_price, qty_step)),
qty_step, balance_ / last_price, settings['default_qty'])
else:
calc_default_qty_ = lambda balance_, last_price: \
max(settings['default_qty'], round_up(min_notional / last_price, qty_step))
calc_max_pos_size = lambda balance_, price_: balance_ / price_ * leverage
calc_long_reentry_price_ = lambda balance_, pos_margin_, pos_price_, highest_bid_: \
min(highest_bid_, calc_long_reentry_price(price_step, grid_spacing, grid_coefficient,
balance_, pos_margin_, pos_price_))
calc_shrt_reentry_price_ = lambda balance_, pos_margin_, pos_price_, lowest_ask_: \
max(lowest_ask_, calc_shrt_reentry_price(price_step, grid_spacing, grid_coefficient,
balance_, pos_margin_, pos_price_))
balance = starting_balance
trades = []
ob = [
min(trades_list[0]['price'], trades_list[1]['price']),
max(trades_list[0]['price'], trades_list[1]['price'])
]
pos_size = 0.0
pos_price = 0.0
bid_price = ob[0]
ask_price = ob[1]
liq_price = 0.0
pnl_sum = 0.0
loss_sum = 0.0
ema_alpha = 2 / (settings['ema_span'] + 1)
ema_alpha_ = 1 - ema_alpha
ema = trades_list[0]['price']
k = 0
prev_len_trades = 0
for t in trades_list:
if t['buyer_maker']:
# buy
if pos_size == 0.0:
# no pos
bid_price = min(ob[0], round_dn(ema, price_step))
bid_qty = calc_default_qty_(balance, ob[0])
elif pos_size > 0.0:
# long pos
liq_price = calc_liq_price(balance, pos_size, pos_price)
if calc_diff(liq_price, ob[0]) < liq_diff_threshold:
# long soft stop, no reentry
bid_price = 0.0
else:
# long reentry
bid_qty = calc_entry_qty(qty_step, ddown_factor,
calc_default_qty_(balance, ob[0]),
calc_max_pos_size(balance, ob[0]),
pos_size)
if bid_qty >= min_qty:
pos_margin = calc_cost(pos_size, pos_price) / leverage
bid_price = calc_long_reentry_price_(
balance, pos_margin, pos_price, ob[0])
else:
bid_price = 0.0
else:
# short pos
liq_price = calc_liq_price(balance, pos_size, pos_price)
if calc_diff(liq_price, ob[0]) < liq_diff_threshold:
# short soft stop
bid_price = ob[0]
bid_qty = round_up(-pos_size * stop_loss_pos_reduction,
qty_step)
else:
if t['price'] <= pos_price:
# short close
qtys, prices = calc_shrt_closes(
price_step, qty_step, min_qty, min_markup,
max_markup, pos_size, pos_price, ob[0],
n_close_orders)
bid_qty = qtys[0]
bid_price = prices[0]
else:
bid_price = 0.0
ob[0] = t['price']
if t['price'] < bid_price:
# filled trade
cost = calc_cost(bid_qty, bid_price)
pnl = -cost * maker_fee
if pos_size >= 0.0:
# create or increase long pos
trade_side = 'long'
trade_type = 'entry'
new_pos_size = pos_size + bid_qty
pos_price = pos_price * (pos_size / new_pos_size) + \
bid_price * (bid_qty / new_pos_size)
pos_size = new_pos_size
roi = 0.0
else:
# close short pos
trade_side = 'shrt'
gain = pos_price / bid_price - 1
pnl += cost * gain
trade_type = 'close' if gain > 0.0 else 'stop_loss'
pos_size = pos_size + bid_qty
roi = gain * leverage
balance += pnl
pnl_sum += pnl
trades.append({
'trade_id':
k,
'side':
trade_side,
'type':
trade_type,
'price':
bid_price,
'qty':
bid_qty,
'pnl':
pnl,
'roi':
roi,
'pos_size':
pos_size,
'pos_price':
pos_price,
'liq_price':
calc_liq_price(balance, pos_size, pos_price)
})
else:
# sell
if pos_size == 0.0:
# no pos
ask_price = max(ob[1], round_up(ema, price_step))
ask_qty = -calc_default_qty_(balance, ob[1])
elif pos_size > 0.0:
# long pos
liq_price = calc_liq_price(balance, pos_size, pos_price)
if calc_diff(liq_price, ob[1]) < liq_diff_threshold:
# long soft stop
ask_price = ob[1]
ask_qty = -round_up(pos_size * stop_loss_pos_reduction,
qty_step)
else:
if t['price'] >= pos_price:
# long close
qtys, prices = calc_long_closes(
price_step, qty_step, min_qty, min_markup,
max_markup, pos_size, pos_price, ob[1],
n_close_orders)
ask_qty = qtys[0]
ask_price = prices[0]
else:
ask_price = 9e9
else:
# short pos
liq_price = calc_liq_price(balance, pos_size, pos_price)
if calc_diff(liq_price, ob[1]) < liq_diff_threshold:
# shrt soft stop, no reentry
ask_price = 9e9
else:
# shrt reentry
ask_qty = -calc_entry_qty(
qty_step, ddown_factor,
calc_default_qty_(balance, ob[1]),
calc_max_pos_size(balance, ob[1]), pos_size)
if -ask_qty >= min_qty:
pos_margin = calc_cost(-pos_size, pos_price) / leverage
ask_price = calc_shrt_reentry_price_(
balance, pos_margin, pos_price, ob[0])
else:
ask_price = 9e9
ob[1] = t['price']
if t['price'] > ask_price:
# filled trade
cost = calc_cost(-ask_qty, ask_price)
pnl = -cost * maker_fee
if pos_size <= 0.0:
# create or increase shrt pos
trade_side = 'shrt'
trade_type = 'entry'
new_pos_size = pos_size + ask_qty
pos_price = pos_price * (pos_size / new_pos_size) + \
ask_price * (ask_qty / new_pos_size)
pos_size = new_pos_size
roi = 0.0
else:
# close long pos
trade_side = 'long'
gain = ask_price / pos_price - 1
pnl += cost * gain
trade_type = 'close' if gain > 0.0 else 'stop_loss'
pos_size = pos_size + ask_qty
roi = gain * leverage
balance += pnl
pnl_sum += pnl
trades.append({
'trade_id':
k,
'side':
trade_side,
'type':
trade_type,
'price':
ask_price,
'qty':
ask_qty,
'pnl':
pnl,
'roi':
roi,
'pos_size':
pos_size,
'pos_price':
pos_price,
'liq_price':
calc_liq_price(balance, pos_size, pos_price)
})
ema = ema * ema_alpha_ + t['price'] * ema_alpha
k += 1
if k % 10000 == 0 or len(trades) != prev_len_trades:
if trades and trades[-1]['type'] == 'stop_loss':
loss_sum += pnl
if break_on_loss:
print('break on loss')
return trades
balance = max(balance, settings['balance'])
prev_len_trades = len(trades)
progress = k / len(trades_list)
if pnl_sum < 0.0 and progress >= settings['break_on_negative_pnl']:
print('break on negative pnl')
return trades
line = f"\r{progress:.3f} pnl sum {pnl_sum:.8f} "
line += f"loss sum {loss_sum:.6f} balance {balance:.6f} "
line += f"qty {calc_default_qty_(balance, ob[0]):.4f} "
line += f"liq diff {min(1.0, calc_diff(trades[-1]['liq_price'], ob[0])):.3f} "
line += f"pos size {pos_size:.6f} "
print(line, end=' ')
return trades
def backtest(df: pd.DataFrame, settings: dict):
grid_step = settings['grid_step']
price_step = settings['price_step']
qty_step = settings['qty_step']
inverse = settings['inverse']
break_on_loss = settings['break_on_loss']
if inverse:
calc_cost = lambda qty_, price_: qty_ / price_
else:
calc_cost = lambda qty_, price_: qty_ * price_
maker_fee = settings['maker_fee']
min_qty = settings['min_qty']
min_markup = sorted(settings['markups'])[0]
max_markup = sorted(settings['markups'])[-1]
n_close_orders = settings['n_close_orders']
default_qty = settings['default_qty']
leverage = settings['leverage']
margin_limit = settings['margin_limit']
trades = []
ob = [df.iloc[:2].price.min(), df.iloc[:2].price.max()]
pos_size = 0.0
pos_price = 0.0
bid_price = round_dn(ob[0], grid_step)
ask_price = round_up(ob[1], grid_step)
pnl_sum = 0.0
for row in df.itertuples():
if row.buyer_maker:
if pos_size == 0.0: # no pos
bid_qty = default_qty
bid_price = round_dn(ob[0], grid_step)
elif pos_size > 0.0: # long pos
if calc_cost(pos_size, pos_price) / leverage > margin_limit:
# limit reached; enter no more
bid_qty = 0.0
bid_price = 0.0
else: # long reentry
bid_qty = default_qty
bid_price = round_dn(min(ob[0], pos_price), grid_step)
else: # shrt pos
if row.price <= pos_price: # shrt close
qtys, prices = calc_shrt_closes(price_step, qty_step,
default_qty, min_markup,
max_markup, pos_size,
pos_price, ob[0],
n_close_orders)
bid_qty = qtys[0]
bid_price = prices[0]
elif -calc_cost(pos_size, pos_price) / leverage > margin_limit:
if break_on_loss:
return []
# controlled shrt loss
bid_qty = default_qty
bid_price = round_dn(ob[0], grid_step)
else: # no shrt close
bid_qty = 0.0
bid_price = 0.0
ob[0] = row.price
if row.price < bid_price:
if pos_size >= 0.0:
# create or add to long pos
cost = calc_cost(bid_qty, bid_price)
margin_cost = cost / leverage
pnl = -cost * maker_fee
new_pos_size = pos_size + bid_qty
pos_price = pos_price * (pos_size / new_pos_size) + \
bid_price * (bid_qty / new_pos_size)
pos_size = new_pos_size
trades.append({
'trade_id': row.Index,
'side': 'long',
'type': 'entry',
'price': bid_price,
'qty': bid_qty,
'pnl': pnl,
'pos_size': pos_size,
'pos_price': pos_price,
'roe': np.nan,
'margin_cost': margin_cost
})
pnl_sum += pnl
print(
f'\r{row.Index / len(df):.2f} pnl sum {pnl_sum:.4f} pos_size {pos_size:.3f} ',
end=' ')
else:
# close shrt pos
cost = calc_cost(bid_qty, bid_price)
margin_cost = cost / leverage
gain = (pos_price / bid_price - 1)
pnl = cost * gain - cost * maker_fee
pos_size += bid_qty
roe = gain * leverage
trades.append({
'trade_id': row.Index,
'side': 'shrt',
'type': 'close',
'price': bid_price,
'qty': bid_qty,
'pnl': pnl,
'pos_size': pos_size,
'pos_price': pos_price,
'roe': roe,
'margin_cost': margin_cost
})
pnl_sum += pnl
print(
f'\r{row.Index / len(df):.2f} pnl sum {pnl_sum:.4f} pos_size {pos_size:.3f} ',
end=' ')
else:
if pos_size == 0.0: # no pos
ask_qty = -default_qty
ask_price = round_up(ob[1], grid_step)
elif pos_size < 0.0: # shrt pos
if -calc_cost(pos_size, pos_price) / leverage > margin_limit:
# limit reached; enter no more
ask_qty = 0.0
ask_price = 9.9e9
else: # shrt reentry
ask_qty = -default_qty
ask_price = round_up(max(ob[1], pos_price), grid_step)
else: # long pos
if row.price >= pos_price: # close long pos
qtys, prices = calc_long_closes(price_step, qty_step,
default_qty, min_markup,
max_markup, pos_size,
pos_price, ob[1],
n_close_orders)
ask_qty = qtys[0]
ask_price = prices[0]
elif calc_cost(pos_size, pos_price) / leverage > margin_limit:
if break_on_loss:
return []
# controlled long loss
ask_qty = -default_qty
ask_price = round_up(ob[1], grid_step)
else: # no close
ask_qty = 0.0
ask_price = 9.9e9
ob[1] = row.price
if row.price > ask_price:
if pos_size <= 0.0:
# add to or create short pos
cost = -calc_cost(ask_qty, ask_price)
margin_cost = cost / leverage
pnl = -cost * maker_fee
new_pos_size = pos_size + ask_qty
pos_price = pos_price * (pos_size / new_pos_size) + \
ask_price * (ask_qty / new_pos_size)
pos_size = new_pos_size
trades.append({
'trade_id': row.Index,
'side': 'shrt',
'type': 'entry',
'price': ask_price,
'qty': ask_qty,
'pnl': pnl,
'pos_size': pos_size,
'pos_price': pos_price,
'roe': np.nan,
'margin_cost': margin_cost
})
pnl_sum += pnl
print(
f'\r{row.Index / len(df):.2f} pnl sum {pnl_sum:.4f} pos_size {pos_size:.3f} ',
end=' ')
else:
# close long pos
cost = -calc_cost(ask_qty, ask_price)
margin_cost = cost / leverage
gain = (ask_price / pos_price - 1)
pnl = cost * gain - cost * maker_fee
pos_size += ask_qty
roe = gain * leverage
trades.append({
'trade_id': row.Index,
'side': 'long',
'type': 'close',
'price': ask_price,
'qty': ask_qty,
'pnl': pnl,
'pos_size': pos_size,
'pos_price': pos_price,
'roe': roe,
'margin_cost': margin_cost
})
pnl_sum += pnl
print(
f'\r{row.Index / len(df):.2f} pnl sum {pnl_sum:.4f} pos_size {pos_size:.3f} ',
end=' ')
return trades
