def __init__(self, exch, spotDict, n=None):
self.isDone = False
self.exch = exch
self.name = exch.upper()
self.spotDict = spotDict
self.n = n
if self.n is not None: self.name += str(n)
#####
self.validCcys = cl.getValidCcys(exch)
#####
ccyList = list(SHARED_CCY_DICT.keys())
cl.appendUnique(ccyList, 'USD')
cl.appendUnique(ccyList, 'USDT')
zeroes = [0] * len(ccyList)
self.spots = pd.DataFrame({'Ccy': ccyList, 'SpotDelta': zeroes, 'SpotDeltaUSD':zeroes}).set_index('Ccy')
self.futures = pd.DataFrame({'Ccy':ccyList, 'FutDelta': zeroes, 'FutDeltaUSD':zeroes}).set_index('Ccy')
self.oneDayFlows = 0
self.flowsDict = dict()
self.oneDayIncome = 0
self.nav = 0
self.incomesStr = ''
self.fundingStrDict=dict()
self.liqDict=dict()
self.liqStr = ''
def ftxInit(self):
def cleanBorrows(ccy, df):
dummy = pd.DataFrame([[0, 0, 0, 0, 0, 0]], columns=['time', 'coin', 'size', 'rate', 'cost', 'proceeds'])
if len(df) == 0:
return dummy
df2 = df.copy()
df2 = df2[df2['coin'] == ccy]
if len(df2) == 0:
return dummy
df2 = df2.set_index('time').sort_index()
return df2
######
def makeFlows(ccy):
start_time = cl.getYest()
borrows = cleanBorrows(ccy, pd.DataFrame(self.api.private_get_spot_margin_borrow_history({'limit': 1000, 'start_time': start_time})['result']))
loans = cleanBorrows(ccy, pd.DataFrame(self.api.private_get_spot_margin_lending_history({'limit': 1000, 'start_time': start_time})['result']))
cl.dfSetFloat(borrows, ['cost','rate'])
cl.dfSetFloat(loans, 'proceeds')
prevBorrow = borrows.iloc[-1]['cost'] if borrows.index[-1] == self.payments.index[-1] else 0
prevLoan = loans.iloc[-1]['proceeds'] if loans.index[-1] == self.payments.index[-1] else 0
absBalUSD = abs(self.wallet.loc[ccy, 'total']*self.spotDict[ccy])
d=dict()
d['oneDayFlows'] = (loans['proceeds'].sum() - borrows['cost'].sum()) * self.spotDict[ccy]
d['oneDayFlowsAnnRet'] = d['oneDayFlows'] * 365 / absBalUSD
d['oneDayBorrowRate'] = borrows['rate'].mean() * 24 * 365
d['prevFlows']=(prevLoan - prevBorrow) * self.spotDict[ccy]
d['prevFlowsAnnRet']=d['prevFlows'] * 24 * 365 / absBalUSD
d['prevBorrowRate'] = borrows.iloc[-1]['rate'] * 24 * 365 if borrows.index[-1] == self.payments.index[-1] else 0
return d
######
self.api = cl.ftxCCXTInit()
self.wallet = cl.ftxGetWallet(self.api,self.validCcys)
ccys=self.validCcys.copy()
cl.appendUnique(ccys,'USDT')
for ccy in ccys:
self.spots.loc[ccy,'SpotDelta'] = self.wallet.loc[ccy,'total']
self.calcSpotDeltaUSD()
######
info = self.api.private_get_account()['result']
futs = pd.DataFrame(info['positions']).set_index('future')
cl.dfSetFloat(futs, 'size')
for ccy in self.validCcys:
ccy2 = ccy + '-PERP'
if ccy=='SHIB': ccy2='K'+ccy2 # Special fix for SHIB
if ccy2 in futs.index:
mult = -1 if futs.loc[ccy2, 'side']=='sell' else 1
if ccy == 'SHIB': mult*=1000 # Special fix for SHIB
self.futures.loc[ccy,'FutDelta']=futs.loc[ccy2,'size']*mult
self.calcFuturesDeltaUSD()
######
start_time=cl.getYest()
pmts = pd.DataFrame()
for ccy in self.validCcys:
pmts = pmts.append(pd.DataFrame(self.api.private_get_funding_payments({'future':ccy+'-PERP', 'start_time': start_time})['result']))
pmts = pmts.set_index('time').sort_index()
cl.dfSetFloat(pmts, 'payment')
self.payments = pmts
#####
self.oneDayIncome = -self.payments['payment'].sum()
self.prevIncome = -self.payments.loc[self.payments.index[-1]]['payment'].sum()
self.setAnnRets()
#####
flowsCcy=CR_FTX_FLOWS_CCYS.copy()
cl.appendUnique(flowsCcy,'USD')
cl.appendUnique(flowsCcy,'USDT')
for ccy in flowsCcy:
d=makeFlows(ccy)
self.oneDayFlows += d['oneDayFlows']
if d['oneDayFlows']==0 and d['prevFlows']==0 and not ccy in ['USD','USDT']:
self.flowsDict[ccy]=None
else:
z1 = '$' + str(round(d['oneDayFlows'])) + ' (' + str(round(d['oneDayFlowsAnnRet'] * 100)) + '% p.a.)'
z2 = '$' + str(round(d['prevFlows'])) + ' (' + str(round(d['prevFlowsAnnRet'] * 100)) + '% p.a.)'
self.flowsDict[ccy]=colored(('FTX 24h/prev ' + ccy + ' flows: ').rjust(37) + z1 + ' / ' + z2, 'blue')
if ccy in ['USD','USDT']: # Extra info for USD/USDT
zList = []
zList.append('na' if d['oneDayBorrowRate'] == 0 else str(round(d['oneDayBorrowRate'] * 100)) + '%')
zList.append('na' if d['prevBorrowRate'] == 0 else str(round(d['prevBorrowRate'] * 100)) + '%')
zList.append(str(round(cl.ftxGetEstBorrow(self.api, ccy) * 100)) + '%')
self.flowsDict[ccy+'2'] = ('FTX ' + ccy + ' 24h/prev/est: ').rjust(37) + '/'.join(zList) + ' p.a. ($' + str(round(self.wallet.loc[ccy, 'usdValue'] / 1000)) + 'K) '
#####
self.nav = self.wallet['usdValue'].sum()
#####
for ccy in self.validCcys:
oneDayFunding = 0
prevFunding = 0
estFunding = 0
if CR_CONFIGS_DICT['IS_CALC_PAYMENTS']:
df = pd.DataFrame(self.api.public_get_funding_rates({'future': ccy + '-PERP', 'start_time': start_time})['result']).set_index('time').sort_index()
cl.dfSetFloat(df, 'rate')
oneDayFunding = df['rate'].mean() * 24 * 365
prevFunding = df['rate'][-1] * 24 * 365
#####
if CR_CONFIGS_DICT['IS_CALC_ESTS']:
estFunding = cl.ftxGetEstFunding(self.api, ccy)
self.makeFundingStr(ccy, oneDayFunding, prevFunding, estFunding)
#####
self.makeIncomesStr()
#####
self.mf = float(info['marginFraction'])
self.mmReq = float(info['maintenanceMarginRequirement'])
self.freeCollateral = float(info['freeCollateral'])
totalPositionNotional = self.nav / self.mf
cushion = (self.mf - self.mmReq) * totalPositionNotional
delta = self.wallet.loc[self.validCcys, 'usdValue'].sum() + self.futures['FutDeltaUSD'].sum()
self.makeLiqStr(cushion=cushion,delta=delta)
#####
self.isDone=True
