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聚宽复现果仁网的波动率实现

sunflower821 2022-08-02 阅读 86


聚宽复现果仁网的波动率实现_hive

def get_volatility(security_list, day):
price_df = get_price(security_list, end_date=(datetime.datetime.now() + datetime.timedelta(days = -1)).strftime("%Y-%m-%d"), frequency='daily', fields=None, skip_paused=False, fq='pre', count=day, panel=False, fill_paused=False)
ret_array = []
for security in security_list:
close = price_df.loc[price_df["code"] == security]["close"]
check_day = 1
ret = np.std((np.array(close[check_day:]) - np.array(close[:-check_day]))/ np.array(close[:-check_day]) * 100) * math.sqrt(day)
ret_array.append(ret)

#print(ret_array)
a = pd.DataFrame({'volatility':ret_array})
a.index = security_list
if hasattr(a, 'sort'):
a = a.sort(['volatility'],ascending = False)
else:
a = a.sort_values(['volatility'],ascending = False)
a["volatility_score"] = range(1, len(security_list) + 1)

# a["volatility"] = ret_array
return

​​http://www.waitingfy.com/archives/5475​​


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