import pandas as pd
import numpy as np

from ipy_table import make_table,apply_theme,set_cell_style,set_column_style,set_row_style
from IPython.display import clear_output, display

from ipywidgets import interact, interactive, fixed, interact_manual
import ipywidgets as widgets

%precision 4

'%.4f'

TaiOpt=pd.read_csv("TaiOpt.csv")#,skiprows = [1])

TaiOpt=TaiOpt.iloc[0:15,:]

#TaiOptPut=pd.DataFrame()
#TaiOptCall=pd.DataFrame()
TaiTotal=pd.DataFrame()

def updown(x):
    if float(x)>0:
       x='△'+(x) 
    elif float(x)<0:
        x='▽'+str(abs(float(x)) )
    return x

TaiTotal['買權 履約價']=TaiOpt.iloc[1:14,7]
TaiTotal['時間']=TaiOpt.iloc[1:14,6].astype(str).str[:5]
TaiTotal['成交價']=TaiOpt.iloc[1:14,2]
TaiTotal['買價']=TaiOpt.iloc[1:14,2]
TaiTotal['賣價']=TaiOpt.iloc[1:14,1]
TaiTotal['漲跌']=TaiOpt.iloc[1:14,3].apply(lambda x:updown(x))
TaiTotal['總量']=TaiOpt.iloc[1:14,5]
TaiTotal['賣權 履約價']=TaiOpt.iloc[1:14,7]
TaiTotal['時間_']=TaiOpt.iloc[1:14,14].astype(str).str[:5]
TaiTotal['成交價_']=TaiOpt.iloc[1:14,10]
TaiTotal['買價_']=TaiOpt.iloc[1:14,8]
TaiTotal['賣價_']=TaiOpt.iloc[1:14,9]
TaiTotal['漲跌_']=TaiOpt.iloc[1:14,11].apply(lambda x:updown(x))
TaiTotal['總量_']=TaiOpt.iloc[1:14,13]

display(TaiTotal)

	買權履約價	時間	成交價	買價	賣價	漲跌	總量	賣權履約價	時間_	成交價_	買價_	賣價_	漲跌_	總量_
1	9900	10:45	725	725	755	△25	16	9900	13:44	16.5	16.5	17.5	△2	2094
2	10000	13:04	595	595	670	▽15.0	7	10000	13:43	22.5	21.5	22	△3.5	2138
3	10100	12:17	515	515	520	0	15	10100	13:42	30	28.5	30	△5	2052
4	10200	13:38	421	421	428	▽8.0	10	10200	13:44	40.5	40.5	41	△4.5	5065
5	10300	13:39	339	339	343	▽3.0	894	10300	13:44	56	55	56	△5	5273
6	10400	13:43	262	262	265	0	1022	10400	13:44	78	77	78	△7	3636
7	10500	13:44	193	193	194	▽2.0	2351	10500	13:44	108	107	108	△7	5123
8	10600	13:44	133	133	135	▽2.0	3092	10600	13:44	149	147	150	△9	3486
9	10700	13:44	88	88	89	0	4187	10700	13:44	203	201	205	△8	2529
10	10800	13:44	55	55	55	△2	8020	10800	13:44	267	266	271	△4	979
11	10900	13:44	33	33	33	△2	7049	10900	13:34	343	345	349	△2	481
12	11000	13:44	19.5	19.5	20	△1	5793	11000	13:11	450	432	436	△23	64
13	11100	13:43	12.5	12.5	13	△2.5	13481	11100	13:01	535	520	535	△10	2

r=0.01844

def arb(df_,S1,S2):
    df=df_.copy()
    df['cp']=df['買價'].astype(float)-df['賣價'].astype('float')
    df['b']=S1-df['買權 履約價'].astype(float)*(1+r)**(-1/12)
    df['arbitrage']=(df['b']-df['cp']).map('{:,.2f}'.format)
    #df['arbitrage']=df['買權 履約價'].apply(lambda K:arbitrage(C,P,S,float(K),r))
    df['cp1']=df['買價_'].astype(float)-df['賣價_'].astype('float')
    df['b1']=S2-df['賣權 履約價'].astype(float)*(1+r)**(-1/12)
    df['arbitrage1']=(df['b1']-df['cp1']).map('{:,.2f}'.format)
    
    print('買權 履約價','  Arbitrage','  賣權 履約價','  Arbitrage')
    for i in range(len(df)):
        print('{:11} {:>9} {:>11} {:>9}'.format(df.iloc[i,0],df.iloc[i,-4],df.iloc[i,0],df.iloc[i,-1]))
    #print(df[['買權 履約價','arbitrage']])

@interact
def show_arbitrage(Pull=(9900, 12000, 100),Call=(9900, 12000, 100)):
    return arb(TaiTotal,Pull,Call)

Future Arbitrage¶

def arb_future(df_,S1,S2):
    df=df_.copy()
    df['cp']=df['買價'].astype(float)-df['賣價'].astype('float')
    df['b']=S1-df['買權 履約價'].astype(float)*(1+r)**(1/12)
    df['arbitrage']=(df['b']-df['cp']).map('{:,.2f}'.format)
    #df['arbitrage']=df['買權 履約價'].apply(lambda K:arbitrage(C,P,S,float(K),r))
    df['cp1']=df['買價_'].astype(float)-df['賣價_'].astype('float')
    df['b1']=S2-df['賣權 履約價'].astype(float)*(1+r)**(1/12)
    df['arbitrage1']=(df['b1']-df['cp1']).map('{:,.2f}'.format)
    
    print('買權 履約價','  Arbitrage','  賣權 履約價','  Arbitrage')
    for i in range(len(df)):
        print('{:11} {:>9} {:>11} {:>9}'.format(df.iloc[i,0],df.iloc[i,-4],df.iloc[i,0],df.iloc[i,-1]))
    #print(df[['買權 履約價','arbitrage']])

@interact
def show_arbitrage_future(Pull=(9900, 12000, 100),Call=(9900, 12000, 100)):
    return arb_future(TaiTotal,Pull,Call)