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    發布日期: 2023-11-25
  • 語言: Python
  • 標簽: 量化投資??

資源簡介

量化投資:以Python為工具,代碼和數據第二部分

資源截圖

代碼片段和文件信息

#coding:utf-8
#chap13?Descriptive?Statistics
import?pandas?as?pd
import?os
#?os.chdir(‘E:\\book_data\\part_2‘)
os.chdir(r‘/media/chai/E/迅雷下載/Python?Quant?Book/part?2‘)

#?/media/chai/E/迅雷下載/Python?Quant?Book/part?2/part2.py

#?returns=pd.read_csv(‘013\\retdata.csv‘)
returns=pd.read_csv(r‘/media/chai/E/迅雷下載/Python?Quant?Book/part?2/013/retdata.csv‘)


gsyh=returns.gsyh
import?matplotlib.pyplot?as?plt
plt.hist(gsyh)
returns.zglt.mean()
returns.pfyh.mean()
returns.zglt.median()
returns.pfyh.median()
returns.zglt.mode()
returns.pfyh.mode()
[returns.zglt.quantile(i)?for?i?in?[0.250.75]]
[returns.pfyh.quantile(i)?for?i?in?[0.250.75]]

returns.zglt.max()-returns.zglt.min()
returns.zglt.mad()
returns.zglt.var()
returns.zglt.std()
returns.pfyh.max()-returns.pfyh.min()
returns.pfyh.mad()
returns.pfyh.var()
returns.pfyh.std()

#?fund=pd.read_csv(‘013\\history.csv‘sep=‘;‘)

fund=pd.read_csv(r‘/media/chai/E/迅雷下載/Python?Quant?Book/part?2/013/history.csv‘sep=‘;‘)

fund.head()

#chap14?Random?Variable
import?numpy?as?np
import?pandas?as?pd

RandomNumber=np.random.choice([12345]\
???????????????????size=100replace=True\
???????????????????p=[0.10.10.30.30.2])
pd.Series(RandomNumber).value_counts()
pd.Series(RandomNumber).value_counts()/100

#?HSRet300=pd.read_csv(‘014\\return300.csv‘)

HSRet300=pd.read_csv(r‘/media/chai/E/迅雷下載/Python?Quant?Book/part?2/014/return300.csv‘)


HSRet300.head(n=2)

import?matplotlib.pyplot?as?plt
from?scipy?import?stats

density=stats.kde.gaussian_kde(HSRet300.iloc[:1])

bins=np.arange(-550.02)?#設定分割區間

plt.subplot(211)
plt.plot(binsdensity(bins))
plt.title(‘滬深300收益率序列的概率密度曲線圖‘)

plt.subplot(212)
plt.plot(binsdensity(bins).cumsum())
plt.title(‘滬深300收益率序列的累積分布函數圖‘)

np.random.binomial(1000.520)
np.random.binomial(100.53)

stats.binom.pmf(201000.5)
stats.binom.pmf(501000.5)

dd=stats.binom.pmf(np.arange(0211)1000.5)
dd
dd.sum()
stats.binom.cdf(201000.5)

ret=HSRet300.iloc[:1]
HSRet300.iloc[:0].head()
ret.head(n=3)

p=len(ret[ret>0])/len(ret)
p

prob=stats.binom.pmf(610p)
prob

Norm=np.random.normal(size=5)
Norm

stats.norm.pdf(Norm)
stats.norm.cdf(Norm)

HS300_RetMean=ret.mean()
HS300_RetMean

HS300_RetVariance=ret.var()
HS300_RetVariance

stats.norm.ppf(0.05HS300_RetMeanHS300_RetVariance**0.5)

plt.plot(np.arange(050.002)\
?????????stats.chi.pdf(np.arange(050.002)3))
plt.title(‘Probability?Density?Plot?of?Chi-Square?Distribution‘)

x=np.arange(-44.0040.004)
plt.plot(xstats.norm.pdf(x)label=‘Normal‘)
plt.plot(xstats.t.pdf(x5)label=‘df=5‘)
plt.plot(xstats.t.pdf(x30)label=‘df=30‘)
plt.legend()

plt.plot(np.arange(050.002)\
????????stats.f.pdf(np.arange(050.002)440))
plt.title(‘Probability?Density?Plot?of?F?Distribution‘)


#correlation
TRD_Index=pd.read_table(‘014\\TRD_Index.txt‘sep=‘\t‘)
TRD_Index.head()
SHindex=TRD_Index[TRD_Index.Indexcd==1]
SHindex.

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????目錄???????????0??2017-01-30?09:26??part?2\
?????目錄???????????0??2017-01-30?09:26??part?2\013\
?????文件???????21956??2016-05-17?21:53??part?2\013\history.csv
?????文件???????13931??2015-08-06?18:01??part?2\013\retdata.csv
?????目錄???????????0??2017-01-30?09:26??part?2\014\
?????文件????????5011??2015-05-20?06:48??part?2\014\return300.csv
?????文件?????1173890??2014-02-10?16:47??part?2\014\TRD_Index.txt
?????目錄???????????0??2017-01-30?09:26??part?2\015\
?????文件???????72649??2015-07-05?18:10??part?2\015\TRD_Index.csv
?????文件?????1173890??2014-02-10?16:47??part?2\015\TRD_Index.txt
?????目錄???????????0??2017-01-30?09:26??part?2\016\
?????文件??????209921??2016-05-18?19:45??part?2\016\PSID.csv
?????文件???????92554??2015-07-06?03:38??part?2\016\TRD_Year.csv
?????目錄???????????0??2017-01-30?09:26??part?2\017\
?????文件??????114709??2015-07-18?04:20??part?2\017\Penn?World?Table.xlsx
?????文件?????1173890??2014-02-10?16:47??part?2\017\TRD_Index.txt
?????文件????????6147??2017-01-30?17:18??part?2\part2.py

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