コード例 #1
0
ファイル: test2.py プロジェクト: jonkomperda/pyFi
from pyFi.methods import binomial as bi
from pyFi.methods import mc
from pyFi.methods import fd
from pyFi.chain import chain as ch

# This section gets our constants
exercise = 5.
print 'Exercise: $'+str(exercise)
spot = 4.
print 'Price:    $'+ str(spot)

sigma = 0.3
print 'Sigma:     '+ str(float(sigma)*100.0)+'%'

rfint = 0.04
print 'Rate:      '+str(float(rfint)*100.0)+'%'

T     = 1.
print 'Time:      '+str(T)

print '\n--------------------------'
#This section tests our solvers
solver = bi.binomial_euro(S=spot,E=exercise,r=rfint,M=60000,sigma=sigma,method='higham',T=T,opt='put')
print 'Binomial Method:    $'+str(solver.solve())

solver2 = mc.mcfast_euro(S=spot,E=exercise,r=rfint,M=100000000,sigma=sigma,T=T,opt='put')
print 'Monte Carlo Method: $'+str(solver2.solve())

solver3 = fd.BS_fd_explicit(S=spot,E=exercise,r=rfint,M=120,k=9000,L=exercise,sigma=sigma,T=T,opt='put')
print 'Finite Difference:  $'+str(float(solver3.solve()))
コード例 #2
0
ファイル: test2.py プロジェクト: jonkomperda/pyFi
print '\n--------------------------'
#This section tests our solvers
solver = bi.binomial_euro(S=spot,
                          E=exercise,
                          r=rfint,
                          M=60000,
                          sigma=sigma,
                          method='higham',
                          T=T,
                          opt='put')
print 'Binomial Method:    $' + str(solver.solve())

solver2 = mc.mcfast_euro(S=spot,
                         E=exercise,
                         r=rfint,
                         M=100000000,
                         sigma=sigma,
                         T=T,
                         opt='put')
print 'Monte Carlo Method: $' + str(solver2.solve())

solver3 = fd.BS_fd_explicit(S=spot,
                            E=exercise,
                            r=rfint,
                            M=120,
                            k=9000,
                            L=exercise,
                            sigma=sigma,
                            T=T,
                            opt='put')
print 'Finite Difference:  $' + str(float(solver3.solve()))
コード例 #3
0
ファイル: test1.py プロジェクト: jonkomperda/pyFi
# This section gets our constants
symbol = 'AAPL'
exercise = 590
print 'Exercise: $'+str(exercise)

spot = api.get_quote_google(symbol)
print symbol+ ' Price: $'+ str(spot)

sigma = volatility.hist_vol(symbol,30)
print symbol+' Sigma: '+ str(float(sigma)*100.0)+'%'

rfint = api.get_risk_free()
print 'Risk Free rate: '+str(float(rfint)*100.0)+'%'
print '\n--------------------------'

#This section tests our solvers
solver = bi.binomial_euro(S=spot,E=exercise,r=rfint,M=40000,sigma=sigma,method='higham',T=2.0/365.0,opt='put')
print 'Binomial Method:    $'+str(solver.solve())

solver2 = mc.mcfast_euro(S=spot,E=exercise,r=rfint,M=4000000,sigma=sigma,T=2.0/365.0,opt='put')
print 'Monte Carlo Method: $'+str(solver2.solve())

solver3 = fd.BS_fd_explicit(S=spot,E=exercise,r=rfint,M=1201,k=1700,L=2*exercise,sigma=sigma,T=2.0/365.0,opt='put')
print 'Finite Difference:  $'+str(float(solver3.solve()))

#This section produces an option chain
chain = ch.option_chain(spot,rfint,sigma,T=2.0/365,range=(520,5,640),method='bi')
chain.generate()
chain.export_csv('test.csv')
print '\n--------------------------\nOpen test.csv for option chain.\n'