指數投資方式中有四種基本的方法烫映，分別是定期定額沼本、定期不定額、不定期定額和不定期不定額锭沟，這四種方式投資效果不同抽兆，對投資者的要求也不同辫红，定期定額最簡單祝辣，但收益不算高蝙斜，不定期不定額最復雜孕荠，對投資者的要求最高，特別是對情緒的要求非常高底循，同時收益也是最好的熙涤。
這里先介紹第一種定期定額的情況祠挫，下面會通過量化的過程來反應投資的整體過程等舔。
定期定額就是按日、按周或者按月進行投資甚牲，每次投資的資金是一樣的蝶柿，比如每周買入1000塊的滬深300基金，這種方式是不管指數漲跌雏赦，到點就買芙扎；
假設每次投入的資金是1000塊戒洼，按周定投，下面是通過量化的過程跑出來的情況（源碼附在后面）敷矫，這里既然是定期定額就不考慮賣出。數據是通過中證全指（指數代碼1000002）進行計算的蠕搜。
上半部分的圖中藍線是中證全指的走勢圖轨蛤，紅點是每周定投的位置祥山，下半部分的圖中藍線是累計投入的資金缝呕，紅線是持有基金的市值斧散，整個過程投入的總資金是500000鸡捐，最終的基金總市值是680424.75栈暇，最后獲得的收益是36.08%，從下半部分圖中可以很清晰的看出源祈，當指數下跌的過程，基金市值會低于投入的資金香缺，這個過程收益為負，隨著指數的上漲脚草，基金市值上漲的幅度會高于投入的資金，然后在某些點超過投入資金的總值馏慨，這個過程收益就會轉負為正埂淮，這就是在低點積累的份額更多造成的。
整體來說定期定額的投資效果并不是很好写隶，接下來還會分享定期不定額倔撞、不定期定額和不定期不定額來進行比較。
源碼
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import math as math
name_index = 'lxr_1000002'
name_index_g = 'g_lxr'
all_data_index =pd.read_csv('./exportfile/indexDataAll/' + name_index + '.csv')
all_data_index_g =pd.read_csv('./importfile/indexSeries/indexValuation/g/' + name_index_g +'.csv')
calc_range = 2500
calc_gap = 5
data_index_p = all_data_index['close'].values[len(all_data_index['close'])- calc_range:len(all_data_index['close']):calc_gap]
data_index_g =all_data_index_g['pe'].values[len(all_data_index_g['pe']) -calc_range:len(all_data_index_g['pe']):calc_gap]
val_percentage_list = list()
sell_flag_no_regular_no_quota = [0, 0]
sell_flag_regular_quota = 0
sell_flag_regular_no_quota = 0
sell_flag_no_regular_quota = 0
def RegularQuota(val_percentage,val_data_p, buy_cnt, buy_total_share):
???global sell_flag_regular_quota
???if val_percentage <= 1:
???????sell_flag_regular_quota = 0
???????buy_each_regular_quota = 1000
???????buy_each_share = buy_each_regular_quota / val_data_p
???????buy_total_share = buy_total_share + buy_each_share
???????buy_cnt = buy_cnt + 1
???????plot_y = val_data_p
???????plot_x = i
???????plot_flag = 1
???else:
???????if sell_flag_regular_quota == 0:
???????????sell_flag_regular_quota = 1
???????????buy_each_share = -buy_total_share
???????????buy_total_share = 0
???????????plot_y = val_data_p
???????????plot_x = i
???????????plot_flag = -1
???????else:
???????????buy_each_share = 0
???????????plot_y = val_data_p
???????????plot_x = i
???????????plot_flag = 0
???return buy_each_share, buy_cnt, [plot_flag, plot_x, plot_y],buy_total_share
gap = 5?# invest each week
cnt = 0
buy_each_share_regular_quota =np.zeros((len(data_index_p), 1))
buy_total_share_list_regular_quota =np.zeros((len(data_index_p), 1))
buy_total_money_list_regular_quota =np.zeros((len(data_index_p), 1))
buy_cnt_regular_quota = 0
plot_regular_quota =np.zeros((len(data_index_p), 3))
buy_each_share_regular_no_quota =np.zeros((len(data_index_p), 1))
buy_total_share_list_regular_no_quota =np.zeros((len(data_index_p), 1))
buy_total_money_list_regular_no_quota =np.zeros((len(data_index_p), 1))
buy_cnt_regular_no_quota = 0
plot_regular_no_quota =np.zeros((len(data_index_p), 3))
buy_each_share_no_regular_quota =np.zeros((len(data_index_p), 1))
buy_total_share_list_no_regular_quota =np.zeros((len(data_index_p), 1))
buy_total_money_list_no_regular_quota =np.zeros((len(data_index_p), 1))
buy_cnt_no_regular_quota = 0
plot_no_regular_quota =np.zeros((len(data_index_p), 3))
buy_each_share_no_regular_no_quota =np.zeros((len(data_index_p), 1))
buy_total_share_list_no_regular_no_quota =np.zeros((len(data_index_p), 1))
buy_total_money_list_no_regular_no_quota =np.zeros((len(data_index_p), 1))
buy_cnt_no_regular_no_quota = 0
plot_no_regular_no_quota =np.zeros((len(data_index_p), 3))
# idx_start = 974 #2011-1-4
idx_start = 1
for i in range(len(data_index_p)):
???valuation_len =all_data_index_g['pe'].values[len(all_data_index['close']) -calc_range-500:len(all_data_index['close']) - calc_range+i*calc_gap:calc_gap]
???val_loc = np.where(valuation_len < data_index_g[i])
???val_percentage = len(val_loc[0]) / (len(valuation_len))
???val_percentage_list.append(val_percentage)
???buy_each_regular_quota = 1000
???buy_each_share_regular_quota[i], buy_cnt_regular_quota,plot_regular_quota[i], buy_total_share_regular_quota\
???????= RegularQuota(val_percentage, data_index_p[i], buy_cnt_regular_quota,sum(buy_each_share_regular_quota))
???buy_total_share_list_regular_quota[i] =sum(buy_each_share_regular_quota) * data_index_p[i]
???buy_total_money_list_regular_quota[i] = buy_cnt_regular_quota *buy_each_regular_quota
earn_total_money_no_regular_quota =np.zeros((len(data_index_p), 1))
money_sell_no_regular_quota = 0
for i in range(len(data_index_p)):
???if buy_each_share_no_regular_quota[i] < 0:
???????money_sell_no_regular_quota = money_sell_no_regular_quota -buy_each_share_no_regular_quota[i] * data_index_p[i]
???earn_total_money_no_regular_quota[i] =sum(buy_each_share_no_regular_quota[0:i+1]) * data_index_p[i] +money_sell_no_regular_quota
earn_total_money_regular_no_quota =np.zeros((len(data_index_p), 1))
money_sell_regular_no_quota = 0
for i in range(len(data_index_p)):
???if buy_each_share_regular_no_quota[i] < 0:
???????money_sell_regular_no_quota = money_sell_regular_no_quota -buy_each_share_regular_no_quota[i] * data_index_p[i]
???earn_total_money_regular_no_quota[i] = sum(buy_each_share_regular_no_quota[0:i+1])* data_index_p[i] + money_sell_regular_no_quota
earn_total_money_regular_quota =np.zeros((len(data_index_p), 1))
money_sell_regular_quota = 0
for i in range(len(data_index_p)):
???if buy_each_share_regular_quota[i] < 0:
???????money_sell_regular_quota = money_sell_regular_quota -buy_each_share_regular_quota[i] * data_index_p[i]
???????print('')
???earn_total_money_regular_quota[i] =sum(buy_each_share_regular_quota[0:i+1]) * data_index_p[i] +money_sell_regular_quota
???print('')
earn_total_money_no_regular_no_quota =np.zeros((len(data_index_p), 1))
money_sell_no_regular_no_quota = 0
for i in range(len(data_index_p)):
???if buy_each_share_no_regular_no_quota[i] < 0:
???????money_sell_no_regular_no_quota = money_sell_no_regular_no_quota -buy_each_share_no_regular_no_quota[i] * data_index_p[i]
???earn_total_money_no_regular_no_quota[i] =sum(buy_each_share_no_regular_no_quota[0:i+1]) * data_index_p[i] +money_sell_no_regular_no_quota
plt_gap = 10
size_title = 28
size_label = 15
size_line = 3
size_rotation = 15
size_buy_plot = 5
#------------------------------------------------------------- #
plt.figure()
plt.rcParams["axes.grid"] = True
plt.rcParams['font.sans-serif'] =['Microsoft YaHei']
plt.rcParams['axes.unicode_minus'] = False
plt.rcParams["grid.linestyle"] =(3, 5)
plt.subplot(211)
income = 100 *(earn_total_money_regular_quota[-1][0] -buy_total_money_list_regular_quota[-1][0]) /buy_total_money_list_regular_quota[-1][0]
plt.title('定期定額 | 投資收益= ' + str("{:.2f}".format(income)) + '%',size=15)
v_max = max(data_index_p)
v_min = min(data_index_p)
for i in range(len(plot_regular_quota)):
???if plot_regular_quota[i][0] == 1:
???????plt.plot(plot_regular_quota[i][1], plot_regular_quota[i][2],color='tomato',marker='o',ms=(size_buy_plot*v_max/plot_regular_quota[i][2]))
???elif plot_regular_quota[i][0] == -1:
???????plt.plot(plot_regular_quota[i][1], plot_regular_quota[i][2],color='purple', marker='o',ms=10)
plt.plot(data_index_p)
plt_xticks =all_data_index['date'].values[len(all_data_index['close']) -calc_range:len(all_data_index['close']):calc_gap].tolist()
plt.xticks(range(len(plt_xticks),0,-math.floor(len(plt_xticks)/plt_gap)),plt_xticks[len(plt_xticks):0:-math.floor(len(plt_xticks)/plt_gap)],rotation=size_rotation)
plt.tick_params(labelsize=size_label)
plt.subplot(212)
plt.plot(buy_total_share_list_regular_quota,color='tomato')
font = {'size': 15, 'color': 'tomato','weight': 'black'}
plt.text(len(buy_total_share_list_regular_quota),buy_total_share_list_regular_quota[-1][0], str("{:.2f}".format(buy_total_share_list_regular_quota[-1][0])),fontdict=font)
plt.plot(len(buy_total_share_list_regular_quota)-1,buy_total_share_list_regular_quota[-1][0],color='tomato', marker='o')
plt.plot(buy_total_money_list_regular_quota,color='cornflowerblue')
font = {'size': 15, 'color':'cornflowerblue', 'weight': 'black'}
plt.text(len(buy_total_money_list_regular_quota),buy_total_money_list_regular_quota[-1][0],str("{:.2f}".format(buy_total_money_list_regular_quota[-1][0])),fontdict=font)
plt.plot(len(buy_total_money_list_regular_quota)-1,buy_total_money_list_regular_quota[-1][0],color='cornflowerblue', marker='o')
plt.plot(earn_total_money_regular_quota,color='red')
font = {'size': 15, 'color': 'red','weight': 'black'}
plt.text(len(earn_total_money_regular_quota),earn_total_money_regular_quota[-1][0],str("{:.2f}".format(earn_total_money_regular_quota[-1][0])),fontdict=font)
plt.plot(len(earn_total_money_regular_quota)-1,earn_total_money_regular_quota[-1][0],color='red', marker='o')
plt_xticks =all_data_index['date'].values[len(all_data_index['close']) -calc_range:len(all_data_index['close']):calc_gap].tolist()
plt.xticks(range(len(plt_xticks),0,-math.floor(len(plt_xticks)/plt_gap)),plt_xticks[len(plt_xticks):0:-math.floor(len(plt_xticks)/plt_gap)],rotation=size_rotation)
plt.tick_params(labelsize=size_label)
#----------------------------------------------------------------- #
plt.show()
文中用到的兩個文件鏈接: https://pan.baidu.com/s/13alPKvTP7Rw061UMcgtMXQ?pwd=s6dr 提取碼: s6dr
程序中用到的數據如果有問題，大家可以留言獲取帝际，歡迎大家一起交流溝通^_^
課程參考：網易云課堂? 基于Python的量化指數基金投資
