def upd_portfolio(self):
signal = self.upd_signal()
trade_number = 1
trade = None
if signal == 'buy':
#Create Trade
trade = td.Trade(name = "Trade"+str(trade_number),
type = "Eq",
notional = 1)
#Add to portfolio
self.portfolio.add_trade(trade)
#update cash for trade
md_slice = md.market_data_slice(self.market_data, self.time)
self.portfolio.trades[0].notional -= trade.value(md_slice)
elif signal == 'sell':
trade = td.Trade(name = "Trade"+str(trade_number),
type = "Eq",
notional = -1)
#Add to portfolio
self.portfolio.add_trade(trade)
#update cash for trade
md_slice = md.market_data_slice(self.market_data, self.time)
self.portfolio.trades[0].notional -= trade.value(md_slice)
def upd_portfolio(self):
#Update portfolio by making delta neutral
delta = self.upd_signal()
#upd portfolio
name = "Hedge" + str(self.time)
thisHedge = td.TradeEquity(name = name,
notional = - delta,
price_series_label = 'underlying')
self.portfolio.add_trade(thisHedge)
#update cash for trade
md_slice = md.market_data_slice(self.market_data, self.time)
self.portfolio.trades[0].notional -= thisHedge.value(md_slice)
def DeltaHedgeVanillaCallEg():
import numpy as np
import pandas as pd
import Portfolio as pf
import GenerateData as gd
import matplotlib.pyplot as plt
steps = 3000
stepsize = 1.0/steps
r = 0.05
dividend = 0.0
vol = 0.2
S0 = 50.0
t0 = 0.0
expiry = 1.0
K = 50.0
#setup market data#
#Generate Series
rseries = steps*[r]
dividendseries = steps*[dividend]
volseries = steps*[vol]
underlyingSeries = gd.GenerateLogNormalTS(S0, mu=0.03, covariance=vol, stepsize=stepsize,steps=steps-1).get_data()
data2 = [rseries,dividendseries,volseries, underlyingSeries]
data2 = np.array(data2)
data2.shape
data2 = data2.transpose()
data2[1,:]
columns = ['rate','dividend','vol','underlying']
data = pd.DataFrame(data2, columns = columns)
data.index = list(np.arange(0,steps,dtype='float64')/steps)
md1 = md.market_data(data)
#need to add to self to use in test functions
md_slice = md.market_data_slice(md1,time_index=0)
md_slice.data
tradeUnderlying = td.TradeEquity('underlying',
notional= 0,
price_series_label = 'underlying')
tradeCall = td.TradeVanillaEuroCall(name = "Call",
notional = 0,
strike = K,
expiry = expiry)
price = tradeCall.price(md_slice)
print "price = ", price
delta = tradeCall.delta(md_slice)
print "delta = ", delta
#Setup portfolio
#First initialise trade type but empty portfolio
port1 = pf.Portfolio("port1")
port1.add_trade(tradeUnderlying)
port1.add_trade(tradeCall)
#Second initialise starting value
initPort = {'Call':1}
port1.adjustNotional(initPort)
delta = tradeCall.delta(md_slice)
print "delta", delta
trade = {'underlying':-delta}
port1.adjustNotional(trade)
port1Slice = pf.PortfolioSlice(portfolio = port1,
market_data= md1,
time_index = 0)
initHedgPort = {'Call':1, "underlying":-delta}
port1Slice.adjustCash(initHedgPort)
#addsome cash
MoreCash = {'Cash':1}
port1.adjustNotional(MoreCash)
prt1Val = port1Slice.value()
print "Portfolio Value" , prt1Val
prt1Del = port1Slice.delta()
print "Portfolio Del" , prt1Del
ts_deltaHedge = tsc.Delta_Hedging(market_data = md1,
portfolio = port1,
initial_time_index = 0,
stepsize = stepsize)
ts_deltaHedge.run_strategy()
outfile = open('VanillaCallDelta_strat.pkl','wb')
pickle.dump(ts_deltaHedge,outfile)
outfile.close()
print ts_deltaHedge.result.head(20)
print ts_deltaHedge.result.tail(20)
print ts_deltaHedge.portfolio.get_notional()
