第三章 基础数据和技术指标 |
您所在的位置：网站首页 › 数据波动率计算公式Excel › 第三章 基础数据和技术指标 |
第三章 基础数据和技术指标
|
三、波动率计算
波动率计算 历史波动率：自行采用不同算法，包括 c2c 、parkinson 、garmanklass 、rsy 、yz 隐含波动率：自行采用QuantLib/Mibian 计算实时隐含波动率 波动率VIX(恐慌指数）：自行编码模块实时计算VIX指数（分钟/日级别） # 计算历史某一天的iVIX # Based on http://www.cboe.com/micro/vix/vixwhite.pdf def calDayVIX(self,vixDate): # concat某一日行情和期权基本信息，得到所需数据 opt = self.getOPT(vixDate) flag_month_expire=opt.flag_month_expire.unique() if len(flag_month_expire)vixDate] exp_periods = {} for epd in exp_dates: exp_periods[epd] = xtool.deltaDays(vixDate,epd)*1.0/365.0 risk_free = 0.04 sigma_square = {} for date in exp_dates: # 计算某一日的vix opt_date = opt[opt.expDate==date] if len(opt_date)==0: continue rf = risk_free #rf = 0.05 opt_call = opt_date[opt_date.contractType == 'C'].set_index(['strikeMark','strikePrice']) opt_put = opt_date[opt_date.contractType == 'P'].set_index(['strikeMark','strikePrice']) opt_call_price = opt_call[[u'price']].sort_index() opt_put_price = opt_put[[u'price']].sort_index() opt_call_price.columns = [u'callPrice'] opt_put_price.columns = [u'putPrice'] opt_call_put_price = pd.concat([opt_call_price, opt_put_price], axis=1, join='inner').sort_index() opt_call_put_price['diffCallPut'] = opt_call_put_price.callPrice - opt_call_put_price.putPrice strike_mark = abs(opt_call_put_price['diffCallPut']).idxmin() price_diff = opt_call_put_price['diffCallPut'][strike_mark] ttm = exp_periods[date] # 如上，strike_mark为一tuple，（'strikeMark','strikePrice'） fw = strike_mark[1] + np.exp(ttm*rf) * price_diff # 计算delta K opt_call_put_price = opt_call_put_price.sort_index(level='strikePrice') strike_price = opt_call_put_price.reset_index(level='strikePrice').sort_values('strikePrice')['strikePrice'] delta_strike = strike_price.rolling(window=3).apply(lambda x: (x[-1] - x[0])/2.0).shift(-1).values delta_strike = np.concatenate((delta_strike[1:2], delta_strike[1:-1], delta_strike[-2:-1])) opt_call_put_price['deltaStrike'] = delta_strike # opt_otm = opt_out_of_money opt_otm = pd.concat([opt_call.loc[[x for x in opt_call.index if x[1] > fw], :],opt_put.loc[[x for x in opt_put.index if x[1] = 1.0/365.0: d_one = exp_dates[0] d_two = exp_dates[1] w = (exp_periods[d_two] - 30.0/365.0)/(exp_periods[d_two] - exp_periods[d_one]) vix30 = exp_periods[d_one]*w*sigma_square[d_one] + exp_periods[d_two]*(1 - w)*sigma_square[d_two] vix30 = 100*np.sqrt(vix30*365.0/30.0) else: d_one = exp_dates[1] vix30 = sigma_square[d_one] vix30 = 100*np.sqrt(vix30) except Exception,e: vix30=-99. ''' # d_one, d_two 将被用来计算VIX(60): d_one = exp_dates[1] d_two = exp_dates[2] w = (exp_periods[d_two] - 60.0/365.0)/(exp_periods[d_two] - exp_periods[d_one]) vix60 = exp_periods[d_one]*w*sigma_square[d_one] + exp_periods[d_two]*(1 - w)*sigma_square[d_two] vix60 = 100*np.sqrt(vix60*365.0/60.0) ''' vix30=round(vix30, 2) print('%s: %0.2f %s'%(vixDate,vix30,flag_month_expire)) return vix30
实时日内分钟级别隐含波动率及VIX
|
http://adog.net.cn
公众号：期权量化ADOG【本文地址】
今日新闻 |
推荐新闻 |