def proc_iv(df, T):
r = 0.03 # 固定无风险短期利率
iv_c_list = []
iv_p_list = []
for i, row in df.iterrows():
S0 = float(row.obj) # 标的价格
K = int(row.atm) # 行权价格
C0 = float(row.close_C) # 期权价格
iv_c = bsm_call_imp_vol(S0, K, T, r, C0)
iv_c_list.append(iv_c)
C0 = float(row.close_P) # 期权价格
iv_p = bsm_put_imp_vol(S0, K, T, r, C0)
iv_p_list.append(iv_p)
# print(T, S0, K, iv_c, iv_p)
df['iv_c'] = iv_c_list
df['iv_p'] = iv_p_list
df['iv_a'] = (df['iv_c'] + df['iv_p']) / 2
df = df[[
'date', 'time', 'pz', 'symbol', 'atm', 'obj', 'close_C', 'close_P',
'iv_c', 'iv_p', 'iv_a'
]]
return df
def test_iv():
r = 0.03
S0 = 4489
K = 4600
T = 10 / 365
C0 = 64.8
sa = bsm_call_imp_vol(S0, K, T, r, C0)
# C0 = 71.4
# sa = bsm_put_imp_vol(S0, K, T, r, C0)
print(sa)
def df_iv(basic, df):
"""
输入：df，包含字段 dt, symbol, close, close_obj
"""
try:
r = 0.03
fn = get_dss() + 'fut/cfg/opt_mature.csv'
df2 = pd.read_csv(fn)
df2 = df2[pd.notnull(df2.flag)]
df2 = df2.set_index('symbol')
mature_dict = dict(df2.mature)
iv_list = []
for i, row in df.iterrows():
strike = get_contract(row.symbol).strike
opt_flag = get_contract(row.symbol).opt_flag
date_mature = mature_dict[basic]
date_mature = datetime.strptime(date_mature, '%Y-%m-%d')
td = datetime.strptime(row['dt'][:10], '%Y-%m-%d')
T = float((date_mature - td).days) / 365 # 剩余期限
T = 0.0015 if T == 0 else T # 最后一天特殊处理
try:
if opt_flag == 'C':
iv = bsm_call_imp_vol(row.close_obj, strike, T, r,
row.close)
else:
iv = bsm_put_imp_vol(row.close_obj, strike, T, r,
row.close)
except:
iv = 0
iv_list.append(round(100 * iv, 2))
df['iv'] = iv_list
df['value'] = df['iv']
df2 = df.set_index('dt')
df2 = df2.sort_index()
df2 = df2[['value']]
df2.index.name = df.index.name
return df2
except Exception as e:
s = traceback.format_exc()
to_log(s)
return None
def calc_iv(self, basic, flag, S0, K, C0):
r = 0.03
fn = get_dss() + 'fut/cfg/opt_mature.csv'
df2 = pd.read_csv(fn)
df2 = df2[df2.pz == df2.pz] # 筛选出不为空的记录
df2 = df2.set_index('symbol')
mature_dict = dict(df2.mature)
date_mature = mature_dict[basic]
date_mature = datetime.strptime(date_mature, '%Y-%m-%d')
td = datetime.now()
T = float((date_mature - td).days) / 365 # 剩余期限
skew = 0
if flag == 'C':
skew = bsm_call_imp_vol(S0, K, T, r, C0)
if flag == 'P':
skew = bsm_put_imp_vol(S0, K, T, r, C0)
return skew
def calc_greeks_common(symbol, row, S0, is_call, r, today, mature_dict, term,
K):
"""
计算新下载数据的希腊字母值，保存到yyyy-dd_greeks.csv文件
Parameters:
S0: 标的价格
K: 行权价格
T: 剩余期限，已做年化处理
r: 固定无风险短期利率
C0：期权价格
"""
C0 = float(row['LastPrice']) # 期权价格
date_mature = mature_dict[term]
date_mature = datetime.strptime(date_mature, '%Y-%m-%d')
td = datetime.strptime(today, '%Y-%m-%d')
T = float((date_mature - td).days) / 365 # 剩余期限
# print(S0, K, C0, T)
if is_call == True:
n = 1
iv = bsm_call_imp_vol(S0, K, T, r, C0)
else:
n = -1
iv = bsm_put_imp_vol(S0, K, T, r, C0)
row['obj'] = S0
row['delta'] = delta(S0, K, r, T, iv, n)
row['gamma'] = gamma(S0, K, r, T, iv)
row['theta'] = theta(S0, K, r, T, iv, n)
row['vega'] = vega(S0, K, r, T, iv)
row['iv'] = iv
df2 = pd.DataFrame([row])
df2.index.name = 'Instrument'
fn2 = get_dss() + 'opt/' + today[:7] + '_greeks.csv'
if os.path.exists(fn2):
df2.to_csv(fn2, mode='a', header=None)
else:
df2.to_csv(fn2)
def skew_now_show(basic, date):
# 获得上一个交易日，用于确定差值的基准
symbol_obj = 'IF' + basic[2:]
fn = get_dss() + 'fut/bar/day_' + symbol_obj + '.csv'
df = pd.read_csv(fn)
df = df[df.date <= date]
if date == df.iat[-1, 0]:
date_pre = df.iat[-2, 0]
else:
date_pre = df.iat[-1, 0]
# 取开盘数据的atm
fn = get_dss() + 'fut/put/rec/min5_' + symbol_obj + '.csv'
df = pd.read_csv(fn)
df = df[df.date == date]
df1 = df[df.time == '09:34:00']
if len(df1) == 0:
return '当前日期无数据'
rec = df1.iloc[0, :]
obj = rec.close
gap = 50
atm = int(round(round(obj * (100 / gap) / 1E4, 2) * 1E4 / (100 / gap),
0)) # 获得平值
fn = get_dss() + 'fut/put/rec/min5_' + basic + '-C-' + str(atm) + '.csv'
df_atm_c = pd.read_csv(fn)
df_atm_c = df_atm_c[df_atm_c.date == date]
fn = get_dss() + 'fut/put/rec/min5_' + basic + '-P-' + str(atm) + '.csv'
df_atm_p = pd.read_csv(fn)
df_atm_p = df_atm_p[df_atm_p.date == date]
fn = get_dss() + 'fut/put/rec/min5_' + basic + '-C-' + str(atm + 2 *
gap) + '.csv'
df_right_c = pd.read_csv(fn)
df_right_c = df_right_c[df_right_c.date == date]
fn = get_dss() + 'fut/put/rec/min5_' + basic + '-P-' + str(atm + 2 *
gap) + '.csv'
df_right_p = pd.read_csv(fn)
df_right_p = df_right_p[df_right_p.date == date]
fn = get_dss() + 'fut/put/rec/min5_' + basic + '-C-' + str(atm - 2 *
gap) + '.csv'
df_left_c = pd.read_csv(fn)
df_left_c = df_left_c[df_left_c.date == date]
fn = get_dss() + 'fut/put/rec/min5_' + basic + '-P-' + str(atm - 2 *
gap) + '.csv'
df_left_p = pd.read_csv(fn)
df_left_p = df_left_p[df_left_p.date == date]
df = df.reset_index()
df_atm_c = df_atm_c.reset_index()
df_atm_p = df_atm_p.reset_index()
df_right_c = df_right_c.reset_index()
df_right_p = df_right_p.reset_index()
df_left_c = df_left_c.reset_index()
df_left_p = df_left_p.reset_index()
r = 0.03
fn = get_dss() + 'fut/cfg/opt_mature.csv'
df2 = pd.read_csv(fn)
df2 = df2[df2.pz == 'IO'] # 筛选出不为空的记录
df2 = df2.set_index('symbol')
mature_dict = dict(df2.mature)
date_mature = mature_dict[basic]
date_mature = datetime.strptime(date_mature, '%Y-%m-%d')
td = datetime.strptime(date, '%Y-%m-%d')
T = float((date_mature - td).days) / 365 # 剩余期限
skew_c_list = []
skew_p_list = []
# skew_mean_c_list = []
# skew_mean_p_list = []
skew_mean_list = []
for i, row in df.iterrows():
try:
S0 = row.close
iv_atm_c = bsm_call_imp_vol(S0, atm, T, r, df_atm_c.at[i, 'close'])
iv_atm_p = bsm_put_imp_vol(S0, atm, T, r, df_atm_p.at[i, 'close'])
iv_right_c = bsm_call_imp_vol(S0, atm + 2 * gap, T, r,
df_right_c.at[i, 'close'])
iv_right_p = bsm_put_imp_vol(S0, atm + 2 * gap, T, r,
df_right_p.at[i, 'close'])
iv_left_c = bsm_call_imp_vol(S0, atm - 2 * gap, T, r,
df_left_c.at[i, 'close'])
iv_left_p = bsm_put_imp_vol(S0, atm - 2 * gap, T, r,
df_left_p.at[i, 'close'])
skew_c_list.append(
round(100 * (iv_right_c - iv_atm_c) / iv_atm_c, 2))
skew_p_list.append(
round(100 * (iv_left_p - iv_atm_p) / iv_atm_p, 2))
# skew_mean_c_list.append( round( 100*( iv_right_c + iv_right_p - iv_atm_c - iv_atm_p ) / (iv_atm_c + iv_atm_p), 2) )
# skew_mean_p_list.append( round( 100*( iv_left_c + iv_left_p - iv_atm_c - iv_atm_p ) / (iv_atm_c + iv_atm_p), 2) )
skew_mean_list.append(
round(
100 * (iv_right_c + iv_right_p - iv_left_c - iv_left_p) /
(iv_left_c + iv_left_p), 2))
except:
break
plt.figure(figsize=(13, 7))
plt.title(basic + ' ' + str(atm))
plt.xticks(rotation=90)
plt.plot(skew_c_list, label='c')
plt.plot(skew_p_list, label='p')
# plt.plot(skew_mean_c_list, label='mean_c')
# plt.plot(skew_mean_p_list, label='mean_p')
plt.plot(skew_mean_list, label='mean')
plt.legend()
fn = 'static/skew_show.jpg'
plt.savefig(fn)
plt.cla()
rr = ''
fn = 'skew_show.jpg'
now = str(int(time.time()))
rr = '<img src=\"static/' + fn + '?rand=' + now + '\" />'
return rr
def iv_min5_show(symbol_list, date):
plt.figure(figsize=(13, 7))
plt.title(date)
for symbol in symbol_list:
basic = get_contract(symbol).basic
strike = get_contract(symbol).strike
opt_flag = get_contract(symbol).opt_flag
if basic[:2] == 'IO':
symbol_obj = 'IF' + basic[2:]
else:
symbol_obj = basic
fn = get_dss() + 'fut/put/rec/min5_' + symbol_obj + '.csv'
df_obj = pd.read_csv(fn)
df_obj = df_obj.set_index(['date', 'time'])
df_obj['close_obj'] = df_obj['close']
df_obj = df_obj[['close_obj']]
# print(df_obj.tail())
fn = get_dss() + 'fut/put/rec/min5_' + symbol + '.csv'
df = pd.read_csv(fn)
df = df[df.date == date]
df = df.set_index(['date', 'time'])
# print(df.tail())
df = df.join(df_obj)
df = df.dropna()
df = df.reset_index()
df = df.set_index('time')
# print(df.tail())
r = 0.03
fn = get_dss() + 'fut/cfg/opt_mature.csv'
df2 = pd.read_csv(fn)
df2 = df2[df2.flag == df2.flag] # 筛选出不为空的记录
df2 = df2.set_index('symbol')
mature_dict = dict(df2.mature)
date_mature = mature_dict[basic]
date_mature = datetime.strptime(date_mature, '%Y-%m-%d')
td = datetime.strptime(date, '%Y-%m-%d')
T = float((date_mature - td).days) / 365 # 剩余期限
iv_list = []
for i, row in df.iterrows():
try:
if opt_flag == 'C':
iv = bsm_call_imp_vol(row.close_obj, strike, T, r,
row.close)
else:
iv = bsm_put_imp_vol(row.close_obj, strike, T, r,
row.close)
iv_list.append(round(100 * iv, 2))
except:
break
df['iv'] = iv_list
plt.plot(df.iv, label=symbol)
plt.xticks(rotation=90)
plt.legend()
fn = 'static/iv_min5_show.jpg'
plt.savefig(fn)
plt.cla()
rr = ''
fn = 'iv_min5_show.jpg'
now = str(int(time.time()))
rr = '<img src=\"static/' + fn + '?rand=' + now + '\" />'
return rr