def bbtInit(self):
self.api = cl.bbCCXTInit(n=self.n)
riskDf = cl.bbtGetRiskDf(self.api, self.spotDict)
for ccy in self.validCcys:
if ccy in riskDf.index:
self.futures.loc[ccy, 'FutDelta']=cl.bbtGetFutPos(self.api,ccy)
self.liqDict[ccy] = riskDf.loc[ccy,'liq']
else:
self.liqDict[ccy] = 0
self.calcFuturesDeltaUSD()
#####
if self.n>=2: # trim list for auxiliary BBTs
self.validCcys=list(self.futures.index[self.futures['FutDelta'] != 0])
#####
self.oneDayIncome = 0
self.prevIncome = 0
if CR_CONFIGS_DICT['IS_CALC_PAYMENTS']:
pmts=pd.DataFrame()
for ccy in self.validCcys:
data = cl.bbtGetTradeExecutionList(self.api,ccy)
if not data is None:
pmts = pmts.append(pd.DataFrame(data).set_index('symbol', drop=False))
if len(pmts)>0:
cl.dfSetFloat(pmts, ['fee_rate', 'exec_fee'])
pmts.loc[['Sell' in z for z in pmts['order_id']],'fee_rate']*=-1 # Correction for fee_rate signs
pmts['incomeUSD'] = -pmts['exec_fee'] * self.spotDict['USDT']
pmts['date'] = [datetime.datetime.fromtimestamp(int(ts) / 1000) for ts in pmts['trade_time_ms']]
pmts = pmts.set_index('date').sort_index()
#####
self.oneDayIncome = pmts['incomeUSD'].sum()
self.prevIncome = pmts.loc[pmts.index[-1]]['incomeUSD'].sum()
self.setAnnRets()
#####
usdtDict=self.api.v2_private_get_wallet_balance({'coin': 'USDT'})['result']['USDT']
equity = float(usdtDict['equity'])
self.nav = equity * self.spotDict['USDT']
self.spots.loc['USDT', 'SpotDelta'] = equity
self.calcSpotDeltaUSD()
#####
for ccy in self.validCcys:
oneDayFunding = 0
prevFunding = 0
estFunding=0
estFunding2=0
if CR_CONFIGS_DICT['IS_CALC_PAYMENTS']:
if len(pmts)>0:
df=pmts.loc[pmts['symbol']==ccy+'USDT','fee_rate']
if len(df) > 0:
oneDayFunding = df.mean() * 3 * 365
prevFunding = df[df.index[-1]].mean() * 3 * 365
#####
if CR_CONFIGS_DICT['IS_CALC_ESTS']:
estFunding, estFunding2 = self.bbtGetEstFundings_fast(ccy)
self.makeFundingStr(ccy, oneDayFunding, prevFunding, estFunding, estFunding2)
#####
self.makeIncomesStr()
self.makeLiqStr(riskDf=riskDf,availableBalance=float(usdtDict['available_balance']))
self.isDone = True
if max_size > position_value:
select_id = int(risk['id'])
select_lev = float(risk['max_leverage'])
if int(pos['risk_id']) != select_id:
api.v2_private_post_position_risk_limit({
'symbol':
sym,
'risk_id':
select_id
})
if lev < select_lev:
api.v2_private_post_position_leverage_save({
'symbol':
sym,
'leverage':
select_lev,
'leverage_only':
True
})
print(
f'{sym} {position_value:,.0f} -> Risk limit ({max_size:,.0f}) Leverage ({select_lev})'
)
break
######
# Main
######
cl.printHeader('BBAutoRiskLimit - ' + cl.getCurrentTime())
bb = cl.bbCCXTInit()
BB_AutoRiskLimit(bb, sym_list)
for i in range(-100, 100):
additional = i * 5000
df['unrealised_pnl_sim'] = df['unrealised_pnl'] + df['delta_value'] * (tgtLiqH - 1)
df['ab_delta'] = df['unrealised_pnl_sim'].clip(None, 0) - df['unrealised_pnl'].clip(None, 0)
ab = availableBalance + additional + df['ab_delta'].sum()
df['cushion'] = ab + df['im_value'] - df['mm_value'] + df['unrealised_pnl_sim'].clip(0, None)
if df['cushion'].min() > 0:
return additional # -ve = money can leave account
return 0
######
# Init
######
apiDict=cl.getApiDict()
spotDict=dict()
spotDict['USDT']=cl.ftxGetMid(apiDict['ftx'],'USDT/USD')
#####
riskDfs = []
for i in range(SHARED_EXCH_DICT['bbt']):
riskDfs.append(cl.bbtGetRiskDfs(i + 1, spotDict))
cl.parallelRun(riskDfs)
######
# Main
######
for i in range(SHARED_EXCH_DICT['bbt']):
cl.printHeader('BBT' + str(i + 1))
usdtDict=cl.bbCCXTInit(i+1).v2_private_get_wallet_balance({'coin': 'USDT'})['result']['USDT']
print('Adjustment = ',str(bbtGetAdj(riskDfs[0].riskDf, float(usdtDict['available_balance']), tgtLiqH)))
if lev[side] < select_lev:
api.private_linear_post_position_set_leverage({
'symbol':
sym,
side.lower() + '_leverage':
select_lev,
opp_side.lower() + '_leverage':
lev[opp_side]
})
isMod = True
if isMod:
print(
f'{sym} {position_value:,.0f} -> Risk limit ({max_size:,.0f}) Leverage ({select_lev})'
)
break
######
# Init
######
cl.printHeader('BBTAutoRiskLimit - ' + cl.getCurrentTime())
apiDict = cl.getApiDict()
spotDict = dict()
spotDict['USDT'] = cl.ftxGetMid(apiDict['ftx'], 'USDT/USD')
# Traditional
for i in range(SHARED_EXCH_DICT['bbt']):
cl.printHeader('BBT' + str(i + 1))
bb = cl.bbCCXTInit(i + 1)
df = cl.bbtGetRiskDf(bb, spotDict)
autoRiskLimit(bb, df.index)
def bbtCrossOrder(bbNB, bbNS, ccy, trade_qty, distance=0):
@retry(wait_fixed=1000, stop_max_attempt_number=SHARED_ETC_DICT['RETRY_MAX_ATTEMPTS'])
def getSymbols(bb):
return pd.DataFrame(bb.v2PublicGetSymbols()['result']).set_index('name')
######
@retry(wait_fixed=1000, stop_max_attempt_number=SHARED_ETC_DICT['RETRY_MAX_ATTEMPTS'])
def getData(bb, ticker):
return bb.v2PublicGetTickers({'symbol': ticker})['result'][0]
######
# Do not use @retry
def getIsReduceOnly(bb, ticker, side, qty):
df = pd.DataFrame(bb.private_linear_get_position_list({'symbol': ticker})['result']).set_index('side')
oppSide = 'Sell' if side == 'BUY' else 'Buy'
return qty <= float(df.loc[oppSide, 'size'])
#####
# Do not use @retry
def placeOrder(bb, ticker, side, qty, limitPrice):
return bb.private_linear_post_order_create({'side': side.capitalize(), 'symbol': ticker, 'order_type': 'Limit', 'qty': qty, 'price': limitPrice, 'time_in_force': 'GoodTillCancel',
'reduce_only': bool(getIsReduceOnly(bb, ticker, side, qty)), 'close_on_trigger': False})['result']['order_id']
#####
# Do not use @retry
def cancelOrder(bb, ticker, orderId):
try:
bb.private_linear_post_order_cancel({'symbol': ticker, 'order_id': orderId})
except:
pass
#####
@retry(wait_fixed=1000, stop_max_attempt_number=SHARED_ETC_DICT['RETRY_MAX_ATTEMPTS'])
def getOrder(bb, ticker, orderId):
return bb.private_linear_get_order_search({'symbol': ticker, 'order_id': orderId})['result']
#####
# Do not use @retry
def calcFill(orderStatus):
filledSize = float(orderStatus['cum_exec_qty'])
filledValue = float(orderStatus['cum_exec_value'])
if filledSize == 0:
return 0
else:
return filledValue / filledSize
#####
if bbNB==bbNS:
print('Cannot cross against oneself!')
sys.exit(1)
bbB=cl.bbCCXTInit(bbNB)
bbS=cl.bbCCXTInit(bbNS)
ticker = ccy+'USDT'
symbols = getSymbols(bbB)
maxTradingQty=float(symbols.loc[ticker, 'lot_size_filter']['max_trading_qty'])
qty = round(min(trade_qty,maxTradingQty), 3)
data = getData(bbB, ticker)
bid = float(data['bid_price'])
ask = float(data['ask_price'])
isUpTick = 'Plus' in data['last_tick_direction']
limitPrice = ask if isUpTick else bid
suffix1 = ' (qty=' + str(qty) + ') ....'
suffix2 = '; price=' + str(limitPrice) + '] '
if not isUpTick:
print(cl.timeTag('Sending buy order in BBT' + str(bbNB) + suffix1))
print(cl.timeTag('Sending sell order in BBT' + str(bbNS) + suffix1))
buyOrderId = placeOrder(bbB, ticker, 'BUY', qty, limitPrice)
sellOrderId = placeOrder(bbS, ticker, 'SELL', qty, limitPrice)
print(cl.timeTag('[DEBUG: buyOrderId=' + buyOrderId + suffix2))
print(cl.timeTag('[DEBUG: sellOrderId=' + sellOrderId + suffix2))
else:
print(cl.timeTag('Sending sell order in BBT' + str(bbNS) + suffix1))
print(cl.timeTag('Sending buy order in BBT' + str(bbNB) + suffix1))
sellOrderId = placeOrder(bbS, ticker, 'SELL', qty, limitPrice)
buyOrderId = placeOrder(bbB, ticker, 'BUY', qty, limitPrice)
print(cl.timeTag('[DEBUG: sellOrderId=' + sellOrderId + suffix2))
print(cl.timeTag('[DEBUG: buyOrderId=' + buyOrderId + suffix2))
time.sleep(3)
cancelOrder(bbB, ticker, buyOrderId)
cancelOrder(bbS, ticker, sellOrderId)
buyOrderStatus = getOrder(bbB, ticker, buyOrderId)
sellOrderStatus = getOrder(bbS, ticker, sellOrderId)
leavesQtyB=qty-float(buyOrderStatus['cum_exec_qty'])
leavesQtyS=qty-float(sellOrderStatus['cum_exec_qty'])
# Fix rounding issues
threshold=500
if (leavesQtyB*limitPrice)<threshold: leavesQtyB=0
if (leavesQtyS*limitPrice)<threshold: leavesQtyS=0
fillB1 = calcFill(buyOrderStatus)
fillS1 = calcFill(sellOrderStatus)
if leavesQtyB==0 and leavesQtyS==0:
print(cl.timeTag('[DEBUG: clean cross!]'))
return 0 # zero slippage
elif leavesQtyB>0 and leavesQtyS==0:
fillB2=cl.bbtRelOrder('BUY',bbB,ccy,leavesQtyB,maxChases=888,distance=distance)
fillBAvg=(fillB1*(qty-leavesQtyB) + fillB2*leavesQtyB)/qty
fillSAvg=fillS1
elif leavesQtyB==0 and leavesQtyS>0:
fillS2 = cl.bbtRelOrder('SELL', bbS, ccy, leavesQtyS, maxChases=888, distance=distance)
fillSAvg = (fillS1 * (qty - leavesQtyS) + fillS2 * leavesQtyS) / qty
fillBAvg=fillB1
else: # partial fills for both
print('bbtCrossOrder abnormal termination!')
sys.exit(1)
return fillBAvg / fillSAvg - 1 # slippage
self.label = self.ccy + ': ' + str(round(self.fDict['ftxEstFunding1'] * 100)) + '//' + \
str(round(self.fDict['bbtEstFunding1'] * 100)) + '/' + str(round(self.fDict['bbtEstFunding2'] * 100)) + \
'; sb=' + str(round(sbBps)) + \
'; yield=' + cl.fmtPct(self.yld, None)
self.label += '; turn=$' + str(round(self.tickersDf.loc[self.ccy, 'turnover_24h'] / 1e6)) + 'M'
if len(self.df) > 0:
self.label += '; fut=$' + str(round(self.futDeltaUSD / 1000)) + 'K'
if self.futDeltaUSD>0: color = 'red'
self.label = termcolor.colored(self.label, color)
######
# Init
######
cl.printHeader('BBTr - '+cl.getCurrentTime())
apiDict=cl.getApiDict()
apiDict['bb']=cl.bbCCXTInit(2)
spotDict=dict()
spotDict['USDT']=cl.ftxGetMid(apiDict['ftx'],'USDT/USD')
#####
riskDfs = []
for i in range(SHARED_EXCH_DICT['bbt']):
riskDfs.append(cl.bbtGetRiskDfs(i + 1, spotDict))
cl.parallelRun(riskDfs)
#####
ccys=[]
for i in range(SHARED_EXCH_DICT['bbt']):
ccys.extend(list(riskDfs[i].riskDf.index))
#####
tickersDf = pd.DataFrame(apiDict['bb'].v2PublicGetTickers()['result']).set_index('symbol')
tickersDf = tickersDf[['USDT' in symbol for symbol in tickersDf.index]]
myList=[ticker[:len(ticker)-4] for ticker in tickersDf.index]
def bbInit(self):
def getPayments(ccy):
n = 0
df = pd.DataFrame()
while True:
n += 1
tl = self.api.v2_private_get_execution_list({'symbol': ccy + 'USD', 'start_time': cl.getYest() * 1000, 'limit': 1000, 'page': n})['result']['trade_list']
if tl is None:
break
else:
df = df.append(pd.DataFrame(tl))
if len(df)==0:
return None
else:
return df.set_index('symbol', drop=False)
#####
self.api = cl.bbCCXTInit()
self.wallet=pd.DataFrame(self.api.v2_private_get_wallet_balance()['result']).transpose()
cl.dfSetFloat(self.wallet,'equity')
for ccy in self.validCcys:
self.spots.loc[ccy,'SpotDelta']=self.wallet.loc[ccy,'equity']
self.calcSpotDeltaUSD()
#####
futs = self.api.v2_private_get_position_list()['result']
futs = pd.DataFrame([pos['data'] for pos in futs]).set_index('symbol')
cl.dfSetFloat(futs, ['size','liq_price','position_value','unrealised_pnl'])
for ccy in self.validCcys:
ccy2=ccy+'USD'
mult = -1 if futs.loc[ccy2,'side']=='Sell' else 1
self.futures.loc[ccy, 'FutDelta'] = futs.loc[ccy2, 'size'] * mult / self.spotDict[ccy]
self.liqDict[ccy] = futs.loc[ccy2,'liq_price'] / cl.bbGetMid(self.api,ccy)
self.calcFuturesDeltaUSD()
#####
self.oneDayIncome=0
self.prevIncome=0
if CR_CONFIGS_DICT['IS_CALC_PAYMENTS']:
pmts = pd.DataFrame()
for ccy in self.validCcys:
pmts = pmts.append(getPayments(ccy))
if len(pmts)>0:
pmts = pmts[pmts['exec_type'] == 'Funding'].copy()
cl.dfSetFloat(pmts, ['fee_rate', 'exec_fee'])
pmts.loc[['Sell' in z for z in pmts['order_id']],'fee_rate']*=-1 # Correction for fee_rate signs
for ccy in self.validCcys:
ccy2=ccy+'USD'
if ccy2 in pmts.index: pmts.loc[ccy2, 'incomeUSD'] = -pmts.loc[ccy2, 'exec_fee'] * self.spotDict[ccy]
pmts['date'] = [datetime.datetime.fromtimestamp(int(ts) / 1000) for ts in pmts['trade_time_ms']]
pmts = pmts.set_index('date')
#####
if len(pmts)>0:
self.oneDayIncome = pmts['incomeUSD'].sum()
self.prevIncome = pmts.loc[pmts.index[-1]]['incomeUSD'].sum()
self.setAnnRets()
#####
self.nav=self.spots['SpotDeltaUSD'].sum()
#####
for ccy in self.validCcys:
oneDayFunding = 0
prevFunding = 0
estFunding = 0
estFunding2 = 0
if CR_CONFIGS_DICT['IS_CALC_PAYMENTS']:
if len(pmts) > 0:
df = pmts.loc[pmts['symbol'] == ccy + 'USD', 'fee_rate']
if len(df) > 0:
oneDayFunding = df.mean() * 3 * 365
prevFunding = df[df.index[-1]].mean() * 3 * 365
#####
if CR_CONFIGS_DICT['IS_CALC_ESTS']:
estFunding,estFunding2 = cl.bbGetEstFundings(self.api, ccy)
self.makeFundingStr(ccy, oneDayFunding, prevFunding, estFunding, estFunding2)
#####
self.makeIncomesStr()
self.isDone = True
