Ejemplo n.º 1
0
#!/usr/bin/env python
# Import required modules for this CRT
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from pandas.plotting import register_matplotlib_converters
register_matplotlib_converters()
from printdescribe import print2, describe2, changepath

# import excel sheets
path = r"D:\Wqu_FinEngr\Portfolio Theory and Asset Pricing\GroupWork"

with changepath(path):
    data = pd.read_excel("GWP_PTAP_Data_2010.10.08.xlsx",
                         skiprows=1,
                         nrows=13,
                         sheet_name='10 SPDRs and S&P 500',
                         index_col=0)

describe2(data)
print2(data)

df_return = data.pct_change().dropna()
print2(df_return)

# df_activeReturn = df_return.sub(df_return.iloc[:,-1], axis=0).drop(['SP_500'], axis=1)
df_activeReturn = df_return.sub(df_return['S&P 500'], axis=0).drop(['S&P 500'],
                                                                   axis=1)
print2(df_activeReturn)

tracking_error = df_activeReturn.std()
Ejemplo n.º 2
0
import tensorflow.compat.v1 as tf

tf.disable_v2_behavior()

from printdescribe import print2, changepath
from datetime import datetime

print2(" ")

path22 = r"D:\PythonDataScience"
sys.path.insert(0, path22)
import input_data

path2 = r"D:\Wqu_FinEngr\Machine Learning in Finance\CourseMaterials\Module5\WQU_MLiF_Module5_Notebooks\ML M5 Notebooks (updated)"

with changepath(path2):
    print2(os.getcwd())
    mnist = input_data.read_data_sets('MNIST_data', one_hot=True)

m, n = mnist.train.images.shape
number_to_show = 100


def show_digits(i=0):
    """
    Show some of the digits
    """
    im = np.reshape(mnist.train.images[i], (28, 28))
    plt.imshow(im, cmap='viridis')
    plt.title('The digits')
Ejemplo n.º 3
0
# starttime = '1997-12-31'
# endtime = '2018-10-22'

# etfs_data =  pdr.get_data_yahoo(etf_symbols, starttime, endtime)
# etfs_data.dropna(axis=1, inplace=True)
# print2(etfs_data.head(), etfs_data.shape)

# data = yf.download(etf_symbols)
# data.dropna(axis=1, inplace=True)
# print2(data.head())

# tt = robin_stocks.stocks.get_stock_historicals(etf_symbols)
# print(tt)

with changepath(pathway):
    data = pd.read_csv('StyleIndexes.csv')

data.set_index(pd.to_datetime(data.Date), inplace=True)
data.drop(columns=['Date'], inplace=True)
data.plot()
plt.show()

data = data.pct_change().dropna()
# data = data.iloc[::-1].iloc[-1000:, :]
# data = data.iloc[:1000,:].iloc[::-1,:]
# print2(data.head(), data.shape)
data2 = data.add(1).cumprod()
print2(data2.head(), data.shape)
data3 = data2.loc["2016-12-31":"2000-01-01", :]
print2(data3.head())