比特量化

from abc import ABCMeta, abstractmethod import six import numpy as np import pandas as pd import matplotlib.pyplot as plt # 每个人平均寿命期望是75年，约75*365=27375天 K_INIT_LIVING_DAYS = 27375 class Person...

import matplotlib.pyplot as plt import numpy as np from mpl_toolkits.mplot3d import Axes3D np.random.seed(42) # 采样个数500 n_samples = 500 dim = 3 # 先生成一组3维正态分布数据，数据方向完全随机 samples = np.rand...

# -*- coding: utf-8 -*- # @Date: 2017-08-26 # @Original: import numpy as np stock_cnt = 200 view_days = 504 # 生成序列 stock_day_change = np.random.standard_normal((stock_cnt, view_days)) stock_...

# -*- coding: utf-8 -*- # @Date: 2017-08-26 # @Original: import numpy as np # 200支股票 stock_cnt = 200 # 504个交易日 view_days = 504 # 生成服从正态分布：均值期望＝0，标准差＝1的序列 stock_day_change = np.random.standar...

# -*- coding: utf-8 -*- # @Date: 2017-08-26 # @Original: import pdb def gen_buy_change_list(): buy_change_list = [] for buy_change in xrange(-5, -16, -1): # 只针对循环执行到buy_chan...

# -*- coding: utf-8 -*- # @Date: 2017-08-26 # @Original: # 多进程 import itertools from concurrent.futures import ProcessPoolExecutor result = [] # 回调函数，通过add_done_callback任务完成后调用 def when_done...

# -*- coding: utf-8 -*- # @Date: 2017-08-26 # @Original: ''' 在量化数据处理中，经常使用itertools来完成数据的各种排列组合以寻找最优参数 ''' import itertools items = [1, 2, 3] ab = ['a', 'b'] cd = ['c', 'd'] #1. permutatio...

# -*- coding: utf-8 -*- # @Date: 2017-08-26 # @Original: from collections import namedtuple from collections import OrderedDict from functools import reduce import itertools class StockTrade...

# -*- coding: utf-8 -*- # @Author: # @Date: 2017-08-26 # @Original: price_str = '30.14, 29.58, 26.36, 32.56, 32.82' price_str = price_str.replace(' ', '') #删除空格 price_array = price_str.spl...