上周看了方正金工的《夜空中最亮的星:十字星形态的选股研究》,这里简单实现一下
这里比较可惜的是得到的样本比较少,计算又超慢········
所谓十字星,就是指实体柱很短、上下影线较长的蜡烛图形态。这里认为是多空双方争夺激烈、僵持不下,前期趋势已成强弩之末,趋势反转即将来临。以底部十字星为例,在股票价格经历较长下跌之后,如果出现十字星形态,表明市场空方力量已开始衰竭,多方在逐步蓄积反攻的力量,多空博弈从空方占优演变为势均力敌,股价走势转向的可能性也迅速升高。
超额十字星的计算方法
为了定义超额十字星,我们首先需计算每只股票的超额蜡烛图(或称超额K线)。对于特定股票第T日的超额蜡烛图,其计算步骤如下:
(1)以股票第T-1日的收盘价P(T-1,Close)为基准,计算股票第T日中截止至第t分钟的累积收益率:Rs(T,t) = P(T,t)/P(T-1,Close)-1;
(2)以指数第T-1日的收盘价Q(T-1,Close)为基准,计算指数第T日中截止至第t分钟的累积收益率:Ri(T,t) = Q(T,t)/Q(T-1,Close)-1;
(3)基于上述两个变量,计算股票第T日中第t分钟的累积超额收益:Re(T,t)= Rs(T,t)-Ri_(T,t);
(4)取第T日累积超额收益的开盘值、最高值、最低值、收盘值,构成第T日的超额蜡烛图。
Out[6]:
| No | bar | close | downline | high | low | next20 | open | pre20 | upline |
---|
2016-10-18 | 27 | 0.00079774 | -0.003770 | 0.00249208 | 0.008187 | -0.006262 | -0.005002 | -0.002972 | 0.001894 | 0.0111595 |
---|
2016-10-21 | 30 | 0.000970781 | 0.001413 | 0.00504358 | 0.006563 | -0.003631 | 0.010432 | 0.002383 | -0.010142 | 0.00418013 |
---|
2016-10-27 | 34 | 0.000818754 | 0.004157 | 0.00332732 | 0.012912 | 0.000829 | 0.013692 | 0.004975 | 0.007205 | 0.00793644 |
---|
2016-11-15 | 47 | 0.000267991 | 0.001232 | 0.00740224 | 0.002138 | -0.006438 | NaN | 0.000964 | 0.005002 | 0.000906188 |
---|
2016-09-12 | 8 | 0.000636764 | 0.001410 | 0.012914 | 0.005389 | -0.011504 | -0.000744 | 0.002047 | NaN | 0.00334192 |
---|
2016-09-21 | 13 | 0.000564488 | -0.003969 | 0.00486459 | 0.000500 | -0.008833 | -0.030573 | -0.003404 | NaN | 0.00390405 |
---|
2016-10-18 | 27 | 0.000214608 | 0.003807 | 0.00628861 | 0.007978 | -0.002696 | 0.011139 | 0.003592 | 0.007759 | 0.00417093 |
---|
2016-11-01 | 37 | 0.000138128 | -0.001252 | 0.00456401 | 0.005113 | -0.005816 | NaN | -0.001114 | 0.015419 | 0.00622715 |
---|
2016-11-02 | 38 | 0.000211409 | -0.002675 | 0.0071915 | -0.000543 | -0.009867 | NaN | -0.002464 | 0.004020 | 0.00192073 |
---|
2016-11-07 | 41 | 0.000305295 | 0.000848 | 0.00701669 | 0.005692 | -0.006168 | NaN | 0.001154 | -0.001203 | 0.0045387 |
---|
2016-10-14 | 25 | 0.000845177 | -0.000488 | 0.00356247 | 0.009963 | -0.004050 | 0.030127 | 0.000357 | -0.011280 | 0.00960517 |
---|
2016-10-20 | 29 | 0.000700113 | -0.003276 | 0.0155403 | 0.002995 | -0.018816 | -0.006919 | -0.002576 | 0.016067 | 0.00557018 |
---|
2016-11-24 | 54 | 0.000586006 | -0.004261 | 0.00522788 | 0.001193 | -0.009489 | NaN | -0.003675 | 0.018970 | 0.0048682 |
---|
2016-09-08 | 6 | 0.000105506 | -0.000450 | 0.00607526 | 0.007156 | -0.006525 | 0.007919 | -0.000344 | NaN | 0.00750053 |
---|
2016-09-21 | 13 | 0.000564488 | -0.003377 | 0.00545054 | 0.005326 | -0.008828 | 0.010758 | -0.002813 | NaN | 0.00813856 |
---|
2016-10-14 | 25 | 0.000369214 | 0.004267 | 0.00896215 | 0.025011 | -0.004696 | -0.011524 | 0.004636 | -0.003037 | 0.0203752 |
---|
2016-10-20 | 29 | 0.00023063 | 0.000511 | 0.0135073 | 0.013321 | -0.012996 | -0.067991 | 0.000742 | -0.048191 | 0.0125796 |
---|
2016-10-24 | 31 | 0.000727063 | -0.005178 | 0.00838323 | 0.001363 | -0.014288 | -0.005292 | -0.005905 | -0.036011 | 0.00654016 |
---|
2016-10-12 | 23 | 3.48944e-05 | 0.000568 | 0.00690284 | 0.003820 | -0.006369 | -0.010141 | 0.000533 | 0.006049 | 0.00325187 |
---|
2016-11-02 | 38 | 0.000659388 | 0.000575 | 0.00797619 | 0.003527 | -0.008061 | NaN | -0.000085 | 0.004066 | 0.00295236 |
---|
2016-11-11 | 45 | 0.000193605 | -0.001089 | 0.00256766 | 0.003306 | -0.003851 | NaN | -0.001283 | 0.007974 | 0.0043954 |
---|
2016-11-18 | 50 | 0.000641578 | 0.000647 | 0.00764976 | 0.006352 | -0.007644 | NaN | 0.000005 | 0.002954 | 0.00570539 |
---|
2016-11-25 | 55 | 0.000100626 | -0.004495 | 0.00260213 | 0.007634 | -0.007097 | NaN | -0.004394 | 0.005382 | 0.0120279 |
---|
2016-09-05 | 3 | 0.00020701 | -0.003016 | 0.0043616 | -0.000573 | -0.007378 | -0.008153 | -0.002809 | NaN | 0.00223569 |
---|
2016-09-14 | 10 | 0.000829046 | 0.002123 | 0.00548877 | 0.008352 | -0.003366 | 0.006859 | 0.002952 | NaN | 0.00540016 |
---|
2016-10-19 | 28 | 0.000776833 | 0.000612 | 0.00469935 | 0.005156 | -0.004864 | -0.006480 | -0.000164 | -0.003246 | 0.00454413 |
---|
2016-11-07 | 41 | 0.000305295 | -0.002535 | 0.0112942 | 0.003538 | -0.013829 | NaN | -0.002229 | 0.034357 | 0.00576718 |
---|
2016-11-08 | 42 | 0.000579561 | -0.002164 | 0.00544842 | 0.003421 | -0.007612 | NaN | -0.001584 | 0.001299 | 0.00500517 |
---|
2016-11-09 | 43 | 0.000404826 | -0.000740 | 0.00124617 | 0.010240 | -0.001986 | NaN | -0.000335 | -0.005877 | 0.0105754 |
---|
2016-11-17 | 49 | 0.000716673 | -0.002889 | 0.00742067 | 0.002564 | -0.010310 | NaN | -0.002172 | 0.001174 | 0.00473643 |
---|
… | … | … | … | … | … | … | … | … | … | … |
---|
2016-09-29 | 19 | 0.000405036 | 0.005248 | 0.00857541 | 0.009771 | -0.003732 | 0.002637 | 0.004843 | NaN | 0.00452285 |
---|
2016-10-10 | 21 | 0.000353476 | -0.000871 | 0.00492891 | 0.001998 | -0.005800 | -0.012189 | -0.000518 | 0.005951 | 0.00251583 |
---|
2016-10-11 | 22 | 0.000893326 | -0.002983 | 0.00294019 | 0.005045 | -0.006817 | 0.006228 | -0.003877 | -0.005929 | 0.00802837 |
---|
2016-11-01 | 37 | 0.000513696 | 0.003787 | 0.00332305 | 0.008657 | -0.000049 | NaN | 0.003274 | 0.007069 | 0.0048698 |
---|
2016-11-04 | 40 | 0.000221849 | -0.000236 | 0.00261349 | 0.002844 | -0.003072 | NaN | -0.000458 | -0.002671 | 0.00308066 |
---|
2016-11-21 | 51 | 0.000401302 | -0.000547 | 0.00694253 | 0.003594 | -0.007489 | NaN | -0.000146 | -0.006729 | 0.00374009 |
---|
2016-09-29 | 19 | 4.13928e-05 | -0.002787 | 0.00617661 | 0.003703 | -0.008964 | -0.014448 | -0.002746 | NaN | 0.00644853 |
---|
2016-10-10 | 21 | 0.000586688 | -0.002809 | 0.00825505 | 0.003330 | -0.011651 | -0.001846 | -0.003396 | -0.003616 | 0.00613935 |
---|
2016-10-31 | 36 | 4.9729e-05 | -0.001628 | 0.00403167 | 0.013651 | -0.005709 | NaN | -0.001678 | -0.015054 | 0.0152788 |
---|
2016-11-01 | 37 | 0.00053519 | 0.002917 | 0.00402879 | 0.014210 | -0.001112 | NaN | 0.003452 | 0.005603 | 0.0107579 |
---|
2016-09-02 | 2 | 0.000854168 | 0.000524 | 0.00902901 | 0.004768 | -0.009359 | 0.001063 | -0.000330 | NaN | 0.0042435 |
---|
2016-09-21 | 13 | 0.000257833 | 0.000035 | 0.00455663 | 0.004762 | -0.004522 | -0.007117 | 0.000293 | NaN | 0.00446928 |
---|
2016-09-22 | 14 | 0.000494773 | -0.001697 | 0.00362974 | 0.007605 | -0.005327 | -0.000656 | -0.001202 | NaN | 0.00880745 |
---|
2016-09-28 | 18 | 0.000565111 | 0.000581 | 0.00406779 | 0.005105 | -0.003486 | 0.003188 | 0.001147 | NaN | 0.00395864 |
---|
2016-09-29 | 19 | 4.13928e-05 | -0.000279 | 0.00292331 | 0.009352 | -0.003203 | -0.002042 | -0.000238 | NaN | 0.0095905 |
---|
2016-10-10 | 21 | 0.000575985 | 0.002825 | 0.00304836 | 0.007299 | -0.000800 | 0.000411 | 0.002249 | 0.014439 | 0.00447417 |
---|
2016-10-24 | 31 | 0.000760739 | -0.003781 | 0.00282309 | 0.000378 | -0.007365 | -0.019246 | -0.004542 | 0.003395 | 0.00415886 |
---|
2016-10-27 | 34 | 0.000895743 | -0.001041 | 0.00390836 | 0.003683 | -0.004949 | -0.004304 | -0.000145 | 0.000656 | 0.00382803 |
---|
2016-11-03 | 39 | 0.000534562 | 0.001763 | 0.00312974 | 0.008293 | -0.001367 | NaN | 0.002297 | 0.002042 | 0.00599582 |
---|
2016-11-24 | 54 | 0.000213575 | 0.003263 | 0.00553358 | 0.005765 | -0.002271 | NaN | 0.003477 | 0.004304 | 0.00228796 |
---|
2016-09-12 | 8 | 5.17113e-05 | -0.007713 | 0.00675064 | 0.005134 | -0.014464 | -0.047022 | -0.007661 | NaN | 0.0127952 |
---|
2016-09-19 | 11 | 0.00021113 | 0.002253 | 0.0101472 | 0.007446 | -0.008105 | -0.001974 | 0.002042 | NaN | 0.00519277 |
---|
2016-09-27 | 17 | 0.000428801 | -0.005663 | 0.00498969 | 0.001271 | -0.011081 | -0.001716 | -0.006092 | NaN | 0.00693369 |
---|
2016-09-12 | 8 | 0.000539117 | -0.011235 | 0.00905839 | -0.007475 | -0.020293 | -0.001961 | -0.010696 | NaN | 0.0032207 |
---|
2016-09-14 | 10 | 0.000328796 | -0.001067 | 0.0096075 | 0.004199 | -0.010674 | 0.003107 | -0.000738 | NaN | 0.00493743 |
---|
2016-10-26 | 33 | 0.000189334 | 0.001176 | 0.00405326 | 0.006450 | -0.002877 | 0.010020 | 0.001365 | 0.012747 | 0.00508488 |
---|
2016-11-01 | 37 | 0.000489511 | 0.001344 | 0.0048214 | 0.006146 | -0.003967 | NaN | 0.000854 | -0.013650 | 0.00480187 |
---|
2016-11-10 | 44 | 0.000318871 | -0.002922 | 0.00446798 | 0.001373 | -0.007390 | NaN | -0.002603 | -0.033727 | 0.00397611 |
---|
2016-11-11 | 45 | 0.000504047 | 0.012624 | 0.00349084 | 0.038857 | 0.008629 | NaN | 0.012120 | 0.015919 | 0.0262325 |
---|
2016-11-18 | 50 | 0.000674624 | -0.002607 | 0.00560334 | 0.002171 | -0.008211 | NaN | -0.001933 | 0.001567 | 0.00410374 |
---|
2003 rows × 10 columns
Out[8]:
| Unnamed: 0 | No | bar | close | downline | high | low | next20 | open | pre20 | upline |
---|
0 | 2016-10-18 | 27 | 0.000798 | -0.003770 | 0.002492 | 0.008187 | -0.006262 | -0.005002 | -0.002972 | 0.001894 | 0.011159 |
---|
1 | 2016-10-21 | 30 | 0.000971 | 0.001413 | 0.005044 | 0.006563 | -0.003631 | 0.010432 | 0.002383 | -0.010142 | 0.004180 |
---|
2 | 2016-10-27 | 34 | 0.000819 | 0.004157 | 0.003327 | 0.012912 | 0.000829 | 0.013692 | 0.004975 | 0.007205 | 0.007936 |
---|
3 | 2016-11-15 | 47 | 0.000268 | 0.001232 | 0.007402 | 0.002138 | -0.006438 | NaN | 0.000964 | 0.005002 | 0.000906 |
---|
4 | 2016-09-12 | 8 | 0.000637 | 0.001410 | 0.012914 | 0.005389 | -0.011504 | -0.000744 | 0.002047 | NaN | 0.003342 |
---|
5 | 2016-09-21 | 13 | 0.000564 | -0.003969 | 0.004865 | 0.000500 | -0.008833 | -0.030573 | -0.003404 | NaN | 0.003904 |
---|
6 | 2016-10-18 | 27 | 0.000215 | 0.003807 | 0.006289 | 0.007978 | -0.002696 | 0.011139 | 0.003592 | 0.007759 | 0.004171 |
---|
7 | 2016-11-01 | 37 | 0.000138 | -0.001252 | 0.004564 | 0.005113 | -0.005816 | NaN | -0.001114 | 0.015419 | 0.006227 |
---|
8 | 2016-11-02 | 38 | 0.000211 | -0.002675 | 0.007191 | -0.000543 | -0.009867 | NaN | -0.002464 | 0.004020 | 0.001921 |
---|
9 | 2016-11-07 | 41 | 0.000305 | 0.000848 | 0.007017 | 0.005692 | -0.006168 | NaN | 0.001154 | -0.001203 | 0.004539 |
---|
10 | 2016-10-14 | 25 | 0.000845 | -0.000488 | 0.003562 | 0.009963 | -0.004050 | 0.030127 | 0.000357 | -0.011280 | 0.009605 |
---|
11 | 2016-10-20 | 29 | 0.000700 | -0.003276 | 0.015540 | 0.002995 | -0.018816 | -0.006919 | -0.002576 | 0.016067 | 0.005570 |
---|
12 | 2016-11-24 | 54 | 0.000586 | -0.004261 | 0.005228 | 0.001193 | -0.009489 | NaN | -0.003675 | 0.018970 | 0.004868 |
---|
13 | 2016-09-08 | 6 | 0.000106 | -0.000450 | 0.006075 | 0.007156 | -0.006525 | 0.007919 | -0.000344 | NaN | 0.007501 |
---|
14 | 2016-09-21 | 13 | 0.000564 | -0.003377 | 0.005451 | 0.005326 | -0.008828 | 0.010758 | -0.002813 | NaN | 0.008139 |
---|
15 | 2016-10-14 | 25 | 0.000369 | 0.004267 | 0.008962 | 0.025011 | -0.004696 | -0.011524 | 0.004636 | -0.003037 | 0.020375 |
---|
16 | 2016-10-20 | 29 | 0.000231 | 0.000511 | 0.013507 | 0.013321 | -0.012996 | -0.067991 | 0.000742 | -0.048191 | 0.012580 |
---|
17 | 2016-10-24 | 31 | 0.000727 | -0.005178 | 0.008383 | 0.001363 | -0.014288 | -0.005292 | -0.005905 | -0.036011 | 0.006540 |
---|
18 | 2016-10-12 | 23 | 0.000035 | 0.000568 | 0.006903 | 0.003820 | -0.006369 | -0.010141 | 0.000533 | 0.006049 | 0.003252 |
---|
19 | 2016-11-02 | 38 | 0.000659 | 0.000575 | 0.007976 | 0.003527 | -0.008061 | NaN | -0.000085 | 0.004066 | 0.002952 |
---|
20 | 2016-11-11 | 45 | 0.000194 | -0.001089 | 0.002568 | 0.003306 | -0.003851 | NaN | -0.001283 | 0.007974 | 0.004395 |
---|
21 | 2016-11-18 | 50 | 0.000642 | 0.000647 | 0.007650 | 0.006352 | -0.007644 | NaN | 0.000005 | 0.002954 | 0.005705 |
---|
22 | 2016-11-25 | 55 | 0.000101 | -0.004495 | 0.002602 | 0.007634 | -0.007097 | NaN | -0.004394 | 0.005382 | 0.012028 |
---|
23 | 2016-09-05 | 3 | 0.000207 | -0.003016 | 0.004362 | -0.000573 | -0.007378 | -0.008153 | -0.002809 | NaN | 0.002236 |
---|
24 | 2016-09-14 | 10 | 0.000829 | 0.002123 | 0.005489 | 0.008352 | -0.003366 | 0.006859 | 0.002952 | NaN | 0.005400 |
---|
25 | 2016-10-19 | 28 | 0.000777 | 0.000612 | 0.004699 | 0.005156 | -0.004864 | -0.006480 | -0.000164 | -0.003246 | 0.004544 |
---|
26 | 2016-11-07 | 41 | 0.000305 | -0.002535 | 0.011294 | 0.003538 | -0.013829 | NaN | -0.002229 | 0.034357 | 0.005767 |
---|
27 | 2016-11-08 | 42 | 0.000580 | -0.002164 | 0.005448 | 0.003421 | -0.007612 | NaN | -0.001584 | 0.001299 | 0.005005 |
---|
28 | 2016-11-09 | 43 | 0.000405 | -0.000740 | 0.001246 | 0.010240 | -0.001986 | NaN | -0.000335 | -0.005877 | 0.010575 |
---|
29 | 2016-11-17 | 49 | 0.000717 | -0.002889 | 0.007421 | 0.002564 | -0.010310 | NaN | -0.002172 | 0.001174 | 0.004736 |
---|
… | … | … | … | … | … | … | … | … | … | … | … |
---|
1973 | 2016-09-29 | 19 | 0.000405 | 0.005248 | 0.008575 | 0.009771 | -0.003732 | 0.002637 | 0.004843 | NaN | 0.004523 |
---|
1974 | 2016-10-10 | 21 | 0.000353 | -0.000871 | 0.004929 | 0.001998 | -0.005800 | -0.012189 | -0.000518 | 0.005951 | 0.002516 |
---|
1975 | 2016-10-11 | 22 | 0.000893 | -0.002983 | 0.002940 | 0.005045 | -0.006817 | 0.006228 | -0.003877 | -0.005929 | 0.008028 |
---|
1976 | 2016-11-01 | 37 | 0.000514 | 0.003787 | 0.003323 | 0.008657 | -0.000049 | NaN | 0.003274 | 0.007069 | 0.004870 |
---|
1977 | 2016-11-04 | 40 | 0.000222 | -0.000236 | 0.002613 | 0.002844 | -0.003072 | NaN | -0.000458 | -0.002671 | 0.003081 |
---|
1978 | 2016-11-21 | 51 | 0.000401 | -0.000547 | 0.006943 | 0.003594 | -0.007489 | NaN | -0.000146 | -0.006729 | 0.003740 |
---|
1979 | 2016-09-29 | 19 | 0.000041 | -0.002787 | 0.006177 | 0.003703 | -0.008964 | -0.014448 | -0.002746 | NaN | 0.006449 |
---|
1980 | 2016-10-10 | 21 | 0.000587 | -0.002809 | 0.008255 | 0.003330 | -0.011651 | -0.001846 | -0.003396 | -0.003616 | 0.006139 |
---|
1981 | 2016-10-31 | 36 | 0.000050 | -0.001628 | 0.004032 | 0.013651 | -0.005709 | NaN | -0.001678 | -0.015054 | 0.015279 |
---|
1982 | 2016-11-01 | 37 | 0.000535 | 0.002917 | 0.004029 | 0.014210 | -0.001112 | NaN | 0.003452 | 0.005603 | 0.010758 |
---|
1983 | 2016-09-02 | 2 | 0.000854 | 0.000524 | 0.009029 | 0.004768 | -0.009359 | 0.001063 | -0.000330 | NaN | 0.004243 |
---|
1984 | 2016-09-21 | 13 | 0.000258 | 0.000035 | 0.004557 | 0.004762 | -0.004522 | -0.007117 | 0.000293 | NaN | 0.004469 |
---|
1985 | 2016-09-22 | 14 | 0.000495 | -0.001697 | 0.003630 | 0.007605 | -0.005327 | -0.000656 | -0.001202 | NaN | 0.008807 |
---|
1986 | 2016-09-28 | 18 | 0.000565 | 0.000581 | 0.004068 | 0.005105 | -0.003486 | 0.003188 | 0.001147 | NaN | 0.003959 |
---|
1987 | 2016-09-29 | 19 | 0.000041 | -0.000279 | 0.002923 | 0.009352 | -0.003203 | -0.002042 | -0.000238 | NaN | 0.009590 |
---|
1988 | 2016-10-10 | 21 | 0.000576 | 0.002825 | 0.003048 | 0.007299 | -0.000800 | 0.000411 | 0.002249 | 0.014439 | 0.004474 |
---|
1989 | 2016-10-24 | 31 | 0.000761 | -0.003781 | 0.002823 | 0.000378 | -0.007365 | -0.019246 | -0.004542 | 0.003395 | 0.004159 |
---|
1990 | 2016-10-27 | 34 | 0.000896 | -0.001041 | 0.003908 | 0.003683 | -0.004949 | -0.004304 | -0.000145 | 0.000656 | 0.003828 |
---|
1991 | 2016-11-03 | 39 | 0.000535 | 0.001763 | 0.003130 | 0.008293 | -0.001367 | NaN | 0.002297 | 0.002042 | 0.005996 |
---|
1992 | 2016-11-24 | 54 | 0.000214 | 0.003263 | 0.005534 | 0.005765 | -0.002271 | NaN | 0.003477 | 0.004304 | 0.002288 |
---|
1993 | 2016-09-12 | 8 | 0.000052 | -0.007713 | 0.006751 | 0.005134 | -0.014464 | -0.047022 | -0.007661 | NaN | 0.012795 |
---|
1994 | 2016-09-19 | 11 | 0.000211 | 0.002253 | 0.010147 | 0.007446 | -0.008105 | -0.001974 | 0.002042 | NaN | 0.005193 |
---|
1995 | 2016-09-27 | 17 | 0.000429 | -0.005663 | 0.004990 | 0.001271 | -0.011081 | -0.001716 | -0.006092 | NaN | 0.006934 |
---|
1996 | 2016-09-12 | 8 | 0.000539 | -0.011235 | 0.009058 | -0.007475 | -0.020293 | -0.001961 | -0.010696 | NaN | 0.003221 |
---|
1997 | 2016-09-14 | 10 | 0.000329 | -0.001067 | 0.009608 | 0.004199 | -0.010674 | 0.003107 | -0.000738 | NaN | 0.004937 |
---|
1998 | 2016-10-26 | 33 | 0.000189 | 0.001176 | 0.004053 | 0.006450 | -0.002877 | 0.010020 | 0.001365 | 0.012747 | 0.005085 |
---|
1999 | 2016-11-01 | 37 | 0.000490 | 0.001344 | 0.004821 | 0.006146 | -0.003967 | NaN | 0.000854 | -0.013650 | 0.004802 |
---|
2000 | 2016-11-10 | 44 | 0.000319 | -0.002922 | 0.004468 | 0.001373 | -0.007390 | NaN | -0.002603 | -0.033727 | 0.003976 |
---|
2001 | 2016-11-11 | 45 | 0.000504 | 0.012624 | 0.003491 | 0.038857 | 0.008629 | NaN | 0.012120 | 0.015919 | 0.026232 |
---|
2002 | 2016-11-18 | 50 | 0.000675 | -0.002607 | 0.005603 | 0.002171 | -0.008211 | NaN | -0.001933 | 0.001567 | 0.004104 |
---|
2003 rows × 11 columns
Out[11]:
| Unnamed: 0 | No | bar | close | downline | high | low | next20 | open | pre20 | upline |
---|
1 | 2016-10-21 | 30 | 0.000971 | 0.001413 | 0.005044 | 0.006563 | -0.003631 | 0.010432 | 0.002383 | -0.010142 | 0.004180 |
---|
9 | 2016-11-07 | 41 | 0.000305 | 0.000848 | 0.007017 | 0.005692 | -0.006168 | NaN | 0.001154 | -0.001203 | 0.004539 |
---|
10 | 2016-10-14 | 25 | 0.000845 | -0.000488 | 0.003562 | 0.009963 | -0.004050 | 0.030127 | 0.000357 | -0.011280 | 0.009605 |
---|
15 | 2016-10-14 | 25 | 0.000369 | 0.004267 | 0.008962 | 0.025011 | -0.004696 | -0.011524 | 0.004636 | -0.003037 | 0.020375 |
---|
16 | 2016-10-20 | 29 | 0.000231 | 0.000511 | 0.013507 | 0.013321 | -0.012996 | -0.067991 | 0.000742 | -0.048191 | 0.012580 |
---|
17 | 2016-10-24 | 31 | 0.000727 | -0.005178 | 0.008383 | 0.001363 | -0.014288 | -0.005292 | -0.005905 | -0.036011 | 0.006540 |
---|
25 | 2016-10-19 | 28 | 0.000777 | 0.000612 | 0.004699 | 0.005156 | -0.004864 | -0.006480 | -0.000164 | -0.003246 | 0.004544 |
---|
28 | 2016-11-09 | 43 | 0.000405 | -0.000740 | 0.001246 | 0.010240 | -0.001986 | NaN | -0.000335 | -0.005877 | 0.010575 |
---|
32 | 2016-11-16 | 48 | 0.000515 | 0.002750 | 0.007597 | 0.011324 | -0.004846 | NaN | 0.003265 | -0.001860 | 0.008059 |
---|
33 | 2016-10-18 | 27 | 0.000583 | -0.012786 | 0.002551 | 0.001859 | -0.015338 | -0.014888 | -0.012203 | -0.035546 | 0.014062 |
---|
40 | 2016-11-16 | 48 | 0.000469 | -0.002171 | 0.002159 | 0.002625 | -0.004330 | NaN | -0.001702 | -0.005952 | 0.004327 |
---|
45 | 2016-10-31 | 36 | 0.000909 | -0.001988 | 0.009070 | 0.003731 | -0.011059 | NaN | -0.001080 | -0.014830 | 0.004811 |
---|
47 | 2016-10-17 | 26 | 0.000013 | -0.003381 | 0.002299 | 0.002578 | -0.005693 | -0.080159 | -0.003393 | -0.011641 | 0.005958 |
---|
48 | 2016-11-08 | 42 | 0.000626 | 0.001609 | 0.006969 | 0.004473 | -0.005986 | NaN | 0.000983 | -0.002819 | 0.002864 |
---|
49 | 2016-11-07 | 41 | 0.000305 | -0.000963 | 0.002803 | 0.003681 | -0.003767 | NaN | -0.000658 | -0.037370 | 0.004339 |
---|
51 | 2016-11-02 | 38 | 0.000897 | 0.004901 | 0.011086 | 0.012621 | -0.007082 | NaN | 0.004004 | -0.046719 | 0.007720 |
---|
52 | 2016-11-03 | 39 | 0.000489 | -0.005506 | 0.014324 | -0.001247 | -0.020319 | NaN | -0.005995 | -0.038351 | 0.004260 |
---|
54 | 2016-11-18 | 50 | 0.000249 | -0.002399 | 0.007338 | 0.004994 | -0.009737 | NaN | -0.002150 | -0.012383 | 0.007144 |
---|
58 | 2016-10-21 | 30 | 0.000465 | -0.007672 | 0.007212 | -0.002406 | -0.014884 | -0.004436 | -0.007206 | -0.017141 | 0.004800 |
---|
65 | 2016-11-10 | 44 | 0.000187 | -0.001195 | 0.008200 | 0.004600 | -0.009395 | NaN | -0.001008 | -0.002904 | 0.005608 |
---|
67 | 2016-11-21 | 51 | 0.000617 | -0.010909 | 0.002643 | 0.000278 | -0.013552 | NaN | -0.010292 | -0.031027 | 0.010570 |
---|
71 | 2016-11-24 | 54 | 0.000018 | -0.013320 | 0.002637 | -0.006773 | -0.015957 | NaN | -0.013302 | -0.008206 | 0.006529 |
---|
81 | 2016-11-03 | 39 | 0.000377 | -0.002766 | 0.005016 | 0.004506 | -0.007781 | NaN | -0.002389 | -0.004435 | 0.006894 |
---|
82 | 2016-11-14 | 46 | 0.000374 | -0.002282 | 0.016615 | -0.000118 | -0.019271 | NaN | -0.002655 | -0.012659 | 0.002163 |
---|
83 | 2016-11-22 | 52 | 0.000475 | -0.001931 | 0.006439 | 0.000791 | -0.008846 | NaN | -0.002407 | -0.021723 | 0.002723 |
---|
92 | 2016-11-02 | 38 | 0.000197 | 0.000635 | 0.008563 | 0.002303 | -0.008125 | NaN | 0.000438 | -0.000260 | 0.001668 |
---|
95 | 2016-11-21 | 51 | 0.000668 | 0.000946 | 0.003725 | 0.012448 | -0.003446 | NaN | 0.000279 | -0.001767 | 0.011502 |
---|
96 | 2016-11-22 | 52 | 0.000439 | 0.001828 | 0.005100 | 0.009302 | -0.003272 | NaN | 0.002266 | -0.004495 | 0.007035 |
---|
97 | 2016-11-25 | 55 | 0.000080 | 0.000211 | 0.010224 | 0.006349 | -0.010094 | NaN | 0.000131 | -0.001785 | 0.006138 |
---|
103 | 2016-10-28 | 35 | 0.000133 | 0.005344 | 0.013268 | 0.011861 | -0.007923 | NaN | 0.005477 | -0.029642 | 0.006384 |
---|
… | … | … | … | … | … | … | … | … | … | … | … |
---|
1878 | 2016-10-17 | 26 | 0.000861 | 0.008709 | 0.007887 | 0.021834 | 0.000822 | -0.085675 | 0.009570 | -0.005388 | 0.012264 |
---|
1880 | 2016-11-21 | 51 | 0.000807 | 0.003567 | 0.012202 | 0.017646 | -0.009442 | NaN | 0.002760 | -0.037314 | 0.014079 |
---|
1882 | 2016-11-07 | 41 | 0.000305 | 0.001248 | 0.002353 | 0.011023 | -0.001105 | NaN | 0.001553 | -0.002848 | 0.009470 |
---|
1883 | 2016-11-14 | 46 | 0.000424 | 0.003397 | 0.009806 | 0.008098 | -0.006833 | NaN | 0.002973 | -0.005312 | 0.004700 |
---|
1888 | 2016-11-03 | 39 | 0.000666 | 0.000192 | 0.004033 | 0.006258 | -0.004508 | NaN | -0.000475 | -0.007908 | 0.006067 |
---|
1894 | 2016-11-23 | 53 | 0.000488 | -0.003042 | 0.008321 | -0.001185 | -0.011851 | NaN | -0.003530 | -0.020281 | 0.001857 |
---|
1896 | 2016-10-14 | 25 | 0.000811 | 0.002365 | 0.003132 | 0.009537 | -0.000767 | -0.014723 | 0.003177 | -0.019420 | 0.006360 |
---|
1900 | 2016-10-11 | 22 | 0.000039 | 0.004456 | 0.013314 | 0.008419 | -0.008857 | -0.037308 | 0.004495 | -0.000872 | 0.003923 |
---|
1905 | 2016-10-13 | 24 | 0.000241 | -0.002483 | 0.005701 | 0.001448 | -0.008184 | -0.002806 | -0.002242 | -0.029952 | 0.003691 |
---|
1908 | 2016-10-13 | 24 | 0.000241 | -0.000323 | 0.002504 | 0.002217 | -0.002827 | 0.012599 | -0.000083 | -0.011070 | 0.002300 |
---|
1915 | 2016-10-25 | 32 | 0.000507 | -0.002262 | 0.004349 | 0.002844 | -0.006611 | -0.003734 | -0.001755 | -0.021364 | 0.004599 |
---|
1929 | 2016-11-18 | 50 | 0.000070 | -0.000559 | 0.002831 | 0.005383 | -0.003460 | NaN | -0.000628 | -0.007454 | 0.005942 |
---|
1938 | 2016-11-02 | 38 | 0.000197 | -0.003543 | 0.002251 | 0.002900 | -0.005794 | NaN | -0.003346 | -0.000717 | 0.006246 |
---|
1941 | 2016-10-20 | 29 | 0.000665 | 0.003019 | 0.002862 | 0.007607 | 0.000157 | 0.012531 | 0.003685 | -0.023562 | 0.003922 |
---|
1943 | 2016-10-12 | 23 | 0.000007 | -0.003739 | 0.003059 | 0.007798 | -0.006806 | -0.019094 | -0.003747 | -0.022097 | 0.011537 |
---|
1946 | 2016-11-15 | 47 | 0.000720 | -0.003210 | 0.004632 | 0.003058 | -0.007841 | NaN | -0.002489 | -0.002776 | 0.005547 |
---|
1948 | 2016-10-10 | 21 | 0.000376 | 0.002255 | 0.003476 | 0.015210 | -0.001596 | 0.004594 | 0.001880 | -0.007343 | 0.012955 |
---|
1949 | 2016-10-18 | 27 | 0.000876 | -0.001043 | 0.005166 | 0.004163 | -0.006209 | -0.032124 | -0.000167 | -0.005427 | 0.004330 |
---|
1950 | 2016-10-25 | 32 | 0.000711 | -0.010319 | 0.006101 | -0.003082 | -0.017132 | -0.005389 | -0.011031 | -0.017904 | 0.007237 |
---|
1951 | 2016-10-26 | 33 | 0.000370 | -0.004374 | 0.007323 | -0.001106 | -0.011697 | 0.001434 | -0.004004 | -0.012735 | 0.002898 |
---|
1957 | 2016-10-20 | 29 | 0.000231 | -0.000459 | 0.001089 | 0.003078 | -0.001548 | -0.001621 | -0.000228 | -0.000899 | 0.003306 |
---|
1965 | 2016-11-22 | 52 | 0.000138 | -0.002269 | 0.007186 | 0.003832 | -0.009592 | NaN | -0.002407 | -0.007784 | 0.006101 |
---|
1970 | 2016-11-04 | 40 | 0.000206 | -0.001971 | 0.005055 | -0.000329 | -0.007026 | NaN | -0.001765 | -0.003460 | 0.001436 |
---|
1975 | 2016-10-11 | 22 | 0.000893 | -0.002983 | 0.002940 | 0.005045 | -0.006817 | 0.006228 | -0.003877 | -0.005929 | 0.008028 |
---|
1977 | 2016-11-04 | 40 | 0.000222 | -0.000236 | 0.002613 | 0.002844 | -0.003072 | NaN | -0.000458 | -0.002671 | 0.003081 |
---|
1978 | 2016-11-21 | 51 | 0.000401 | -0.000547 | 0.006943 | 0.003594 | -0.007489 | NaN | -0.000146 | -0.006729 | 0.003740 |
---|
1980 | 2016-10-10 | 21 | 0.000587 | -0.002809 | 0.008255 | 0.003330 | -0.011651 | -0.001846 | -0.003396 | -0.003616 | 0.006139 |
---|
1981 | 2016-10-31 | 36 | 0.000050 | -0.001628 | 0.004032 | 0.013651 | -0.005709 | NaN | -0.001678 | -0.015054 | 0.015279 |
---|
1999 | 2016-11-01 | 37 | 0.000490 | 0.001344 | 0.004821 | 0.006146 | -0.003967 | NaN | 0.000854 | -0.013650 | 0.004802 |
---|
2000 | 2016-11-10 | 44 | 0.000319 | -0.002922 | 0.004468 | 0.001373 | -0.007390 | NaN | -0.002603 | -0.033727 | 0.003976 |
---|
565 rows × 11 columns
Out[12]:
<seaborn.axisgrid.JointGrid at 0x7fb1604b9eb8>
不太明显,只有两个月的数据样本,但是回归明显向上偏,可见因子还是有效果
下面我选择了中证500成分股中的20支来计算
Out[5]:
| open | close | high | low | bar | upline | downline | No | pre20 | next20 |
---|
2014-01-07 | -0.001897 | -0.001943 | 0.006458 | -0.006651 | 4.55517e-05 | 0.00835467 | 0.00470884 | 4 | NaN | -0.001856 |
---|
2014-02-07 | -0.005527 | -0.006007 | 0.013378 | -0.009961 | 0.000480204 | 0.0189052 | 0.00395399 | 22 | 0.007638 | -0.000179 |
---|
2014-03-05 | 0.000421 | 0.001246 | 0.012940 | -0.006317 | 0.000824954 | 0.0116936 | 0.00673872 | 40 | 0.015679 | -0.003833 |
---|
2014-03-25 | -0.009716 | -0.009470 | 0.013240 | -0.010665 | 0.000246501 | 0.0227101 | 0.000949013 | 54 | -0.025961 | -0.018466 |
---|
2014-04-11 | 0.001609 | 0.001562 | 0.007111 | -0.001851 | 4.68696e-05 | 0.00550171 | 0.00341342 | 66 | 0.006432 | 0.004684 |
---|
2014-04-29 | -0.008551 | -0.008279 | 0.006034 | -0.012187 | 0.000271631 | 0.0143131 | 0.00363623 | 78 | -0.013229 | -0.004456 |
---|
2014-05-12 | 0.002395 | 0.002756 | 0.017588 | -0.004310 | 0.000360935 | 0.0148322 | 0.00670472 | 85 | 0.012006 | 0.001380 |
---|
2014-05-14 | 0.001632 | 0.002367 | 0.006712 | -0.002074 | 0.000734458 | 0.00434597 | 0.00370598 | 87 | 0.016891 | 0.009744 |
---|
2014-05-23 | -0.004080 | -0.004345 | 0.000119 | -0.008800 | 0.000265041 | 0.00419809 | 0.00445587 | 94 | -0.013341 | -0.000664 |
---|
2014-05-30 | 0.005732 | 0.006018 | 0.016081 | -0.000791 | 0.00028621 | 0.0100633 | 0.00652331 | 99 | 0.010092 | 0.015166 |
---|
2014-06-03 | 0.001756 | 0.001703 | 0.006032 | -0.003826 | 5.31727e-05 | 0.00427542 | 0.00552878 | 100 | -0.018557 | 0.003737 |
---|
2014-06-11 | -0.003509 | -0.003131 | 0.000217 | -0.008075 | 0.000377309 | 0.00334814 | 0.00456638 | 106 | -0.000009 | 0.008957 |
---|
2014-07-23 | -0.002892 | -0.002879 | 0.006577 | -0.005467 | 1.26583e-05 | 0.00945605 | 0.00257562 | 136 | -0.009436 | -0.012740 |
---|
2014-11-12 | -0.004968 | -0.004038 | 0.002243 | -0.008986 | 0.000930737 | 0.00628091 | 0.00401753 | 210 | -0.008778 | -0.024373 |
---|
2014-11-13 | 0.020005 | 0.019190 | 0.025552 | 0.014111 | 0.000815201 | 0.00554659 | 0.00507876 | 211 | 0.028630 | 0.031774 |
---|
2014-11-21 | -0.004224 | -0.004553 | -0.001483 | -0.009746 | 0.000329642 | 0.00274062 | 0.00519264 | 217 | -0.003224 | 0.000472 |
---|
2015-01-06 | 0.000965 | -0.000034 | 0.011175 | -0.012660 | 0.000998943 | 0.0102104 | 0.0126261 | 247 | 0.019187 | 0.002940 |
---|
2015-01-07 | -0.004445 | -0.003814 | 0.009787 | -0.012481 | 0.000631839 | 0.0136004 | 0.00803581 | 248 | -0.009749 | -0.002055 |
---|
2015-01-12 | -0.001993 | -0.001395 | 0.003410 | -0.008329 | 0.000597669 | 0.00480551 | 0.00633593 | 251 | 0.011189 | -0.008026 |
---|
2015-01-21 | -0.003244 | -0.004131 | 0.002246 | -0.008659 | 0.000887216 | 0.00548921 | 0.00452844 | 258 | -0.006634 | -0.003735 |
---|
2015-10-27 | -0.030401 | -0.030548 | -0.003477 | -0.061991 | 0.000146632 | 0.0269246 | 0.0314432 | 442 | -0.038208 | -0.068074 |
---|
2015-12-25 | -0.003435 | -0.004276 | 0.011034 | -0.009270 | 0.000841036 | 0.014469 | 0.00499451 | 485 | -0.050652 | -0.064786 |
---|
2016-02-16 | 0.008519 | 0.009004 | 0.013755 | -0.016159 | 0.000484969 | 0.00475163 | 0.0246778 | 516 | 0.019557 | 0.025104 |
---|
2016-02-18 | -0.000986 | -0.000500 | 0.014788 | -0.012698 | 0.000485495 | 0.0152881 | 0.0117118 | 518 | -0.042430 | -0.016038 |
---|
2016-08-04 | -0.002302 | -0.001616 | 0.009708 | -0.005003 | 0.000686598 | 0.0113239 | 0.00270023 | 634 | -0.016891 | -0.009812 |
---|
2016-08-05 | 0.000088 | 0.000812 | 0.007674 | -0.006572 | 0.000723881 | 0.00686153 | 0.00666059 | 635 | 0.006899 | -0.003935 |
---|
2016-08-12 | -0.002550 | -0.003317 | 0.015110 | -0.006441 | 0.000767386 | 0.0176602 | 0.00312398 | 640 | -0.022925 | -0.012306 |
---|
2016-08-18 | 0.000405 | 0.000585 | 0.028629 | -0.007071 | 0.000179878 | 0.0280438 | 0.00747644 | 644 | 0.014234 | 0.007435 |
---|
2016-08-24 | -0.001738 | -0.000990 | 0.002079 | -0.005246 | 0.000748208 | 0.00306858 | 0.00350864 | 648 | 0.036781 | -0.001524 |
---|
2016-09-19 | -0.006974 | -0.006850 | 0.008454 | -0.010255 | 0.00012408 | 0.0153043 | 0.00328066 | 664 | -0.007435 | -0.019789 |
---|
… | … | … | … | … | … | … | … | … | … | … |
---|
2014-03-14 | 0.005339 | 0.004651 | 0.011939 | -0.001552 | 0.000688738 | 0.00659919 | 0.00620248 | 47 | -0.034051 | 0.012145 |
---|
2014-03-26 | -0.001957 | -0.002595 | 0.000969 | -0.004665 | 0.000638664 | 0.00292573 | 0.00206933 | 55 | -0.018953 | -0.013884 |
---|
2014-04-02 | -0.001095 | -0.000655 | 0.001874 | -0.005735 | 0.000440058 | 0.00252931 | 0.0046401 | 60 | -0.002772 | 0.073600 |
---|
2014-06-27 | -0.009957 | -0.009092 | 0.000361 | -0.014798 | 0.000865306 | 0.00945291 | 0.00484102 | 118 | 0.046355 | -0.017387 |
---|
2014-07-30 | 0.005364 | 0.006136 | 0.008639 | -0.012577 | 0.000771817 | 0.00250293 | 0.0179418 | 141 | 0.035309 | 0.054842 |
---|
2014-08-18 | 0.001273 | 0.001144 | 0.008594 | -0.005845 | 0.00012896 | 0.00732149 | 0.00698941 | 154 | 0.013711 | 0.015067 |
---|
2014-09-11 | 0.004093 | 0.003650 | 0.014485 | 0.000533 | 0.000443532 | 0.010391 | 0.00311663 | 171 | 0.017122 | -0.009726 |
---|
2014-09-25 | -0.004175 | -0.003376 | 0.010172 | -0.009249 | 0.000799809 | 0.0135475 | 0.00507392 | 181 | 0.045331 | 0.019990 |
---|
2014-11-28 | -0.004615 | -0.003657 | 0.011943 | -0.016064 | 0.000958095 | 0.0156003 | 0.0114492 | 222 | 0.009065 | 0.011809 |
---|
2015-01-27 | -0.006059 | -0.005392 | 0.004997 | -0.023593 | 0.000667311 | 0.0103882 | 0.017534 | 262 | 0.010074 | 0.010936 |
---|
2015-04-16 | -0.021033 | -0.021159 | 0.023717 | -0.039796 | 0.000125134 | 0.0447502 | 0.018637 | 313 | -0.048245 | -0.027740 |
---|
2015-05-12 | -0.011428 | -0.012081 | 0.046723 | -0.014717 | 0.000653123 | 0.0581516 | 0.00263569 | 330 | -0.001851 | 0.011615 |
---|
2015-07-23 | -0.012344 | -0.011370 | 0.000708 | -0.025381 | 0.000973568 | 0.0120778 | 0.0130374 | 381 | 0.033617 | -0.004172 |
---|
2015-08-13 | 0.011248 | 0.011441 | 0.020079 | -0.001688 | 0.000193306 | 0.00863767 | 0.0129358 | 396 | -0.040084 | 0.042951 |
---|
2015-09-02 | -0.013187 | -0.012656 | 0.027920 | -0.036755 | 0.0005314 | 0.0405758 | 0.0235673 | 410 | 0.003805 | -0.061268 |
---|
2015-10-13 | -0.012480 | -0.012406 | 0.004185 | -0.018233 | 7.38099e-05 | 0.016591 | 0.00575265 | 432 | -0.067521 | 0.010086 |
---|
2015-12-17 | 0.006922 | 0.007816 | 0.015884 | -0.001925 | 0.000894005 | 0.00806864 | 0.00884642 | 479 | -0.010617 | 0.014929 |
---|
2016-02-04 | 0.003553 | 0.004552 | 0.014893 | -0.002413 | 0.000998968 | 0.0103405 | 0.00596647 | 513 | 0.018235 | -0.017088 |
---|
2016-03-03 | -0.001259 | -0.001851 | 0.020796 | -0.006639 | 0.00059226 | 0.0220553 | 0.0047874 | 528 | 0.003676 | 0.005921 |
---|
2016-03-25 | 0.003776 | 0.003463 | 0.006021 | -0.007714 | 0.000312261 | 0.00224559 | 0.0111773 | 544 | 0.046411 | 0.011860 |
---|
2016-04-14 | 0.004278 | 0.003922 | 0.012181 | -0.003184 | 0.000355497 | 0.00790288 | 0.00710585 | 557 | 0.005424 | 0.016256 |
---|
2016-04-15 | -0.004720 | -0.004970 | -0.002328 | -0.011955 | 0.000249798 | 0.00239256 | 0.00698465 | 558 | -0.025893 | -0.013047 |
---|
2016-04-26 | -0.004821 | -0.004057 | -0.000586 | -0.012377 | 0.000763958 | 0.00347106 | 0.00755643 | 565 | 0.005957 | -0.059779 |
---|
2016-06-01 | -0.006262 | -0.005929 | 0.003318 | -0.013084 | 0.00033289 | 0.0092476 | 0.00682147 | 590 | -0.001883 | 0.014125 |
---|
2016-07-11 | -0.001556 | -0.001341 | 0.013781 | -0.003138 | 0.000214684 | 0.0151221 | 0.00158217 | 616 | -0.021395 | 0.000101 |
---|
2016-08-18 | 0.000405 | -0.000315 | 0.003329 | -0.005805 | 0.000720212 | 0.00292416 | 0.00548998 | 644 | -0.012813 | 0.001219 |
---|
2016-08-30 | -0.002213 | -0.002587 | 0.006481 | -0.004237 | 0.000373993 | 0.00869423 | 0.00165023 | 652 | 0.000442 | -0.005860 |
---|
2016-09-28 | -0.002059 | -0.002126 | 0.001013 | -0.004687 | 6.68724e-05 | 0.00307291 | 0.00256019 | 671 | -0.004542 | 0.009323 |
---|
2016-10-12 | -0.000907 | -0.001598 | 0.004475 | -0.004918 | 0.000690257 | 0.00538284 | 0.00332033 | 676 | 0.002437 | 0.004999 |
---|
2016-10-13 | 0.000641 | 0.000400 | 0.005512 | -0.003841 | 0.000240639 | 0.00487045 | 0.00424137 | 677 | -0.014095 | -0.008323 |
---|
602 rows × 10 columns
Out[8]:
| open | close | high | low | bar | upline | downline | No | pre20 | next20 |
---|
2014-03-25 | -0.009716 | -0.009470 | 0.013240 | -0.010665 | 0.000246501 | 0.0227101 | 0.000949013 | 54 | -0.025961 | -0.018466 |
---|
2014-04-29 | -0.008551 | -0.008279 | 0.006034 | -0.012187 | 0.000271631 | 0.0143131 | 0.00363623 | 78 | -0.013229 | -0.004456 |
---|
2014-05-23 | -0.004080 | -0.004345 | 0.000119 | -0.008800 | 0.000265041 | 0.00419809 | 0.00445587 | 94 | -0.013341 | -0.000664 |
---|
2014-06-03 | 0.001756 | 0.001703 | 0.006032 | -0.003826 | 5.31727e-05 | 0.00427542 | 0.00552878 | 100 | -0.018557 | 0.003737 |
---|
2014-06-11 | -0.003509 | -0.003131 | 0.000217 | -0.008075 | 0.000377309 | 0.00334814 | 0.00456638 | 106 | -0.000009 | 0.008957 |
---|
Out[7]:
<seaborn.axisgrid.JointGrid at 0x7fbf5d5265c0>
虽然样本还是少了一些,但是应该已经足够说明问题了
这个因子是比较有效的
在用单因子做了一个策略,主要逻辑就是用这个因子选股,然后持有一个月,看起来效果是不错的
”’第1部、参数控制及打印”’
”’第1部、股票选择 ”’
def pick_stocks(context):
#剔除市值前1%和3%以后的股票
df=context.df.T
stock_list = list(df.index)
logger.info(len(stock_list))
stock_list = filter_paused_stock(stock_list)
logger.info(len(stock_list))
stock_list = filter_st_stock(stock_list)
logger.info(len(stock_list))
stock_list = filter_crossstar_stock(stock_list)
logger.info(len(stock_list))
stock_list = filter_minus_rate(stock_list)
logger.info(len(stock_list))
logger.info(stock_list)
# 选取指定可买数目的股票
if len(stock_list) > context.buy_list_count:
stock_list = stock_list[:context.buy_list_count]
return stock_list
”’第8部、功能控件”’
# 过滤停牌股票
def filter_paused_stock(stock_list):
return [stock for stock in stock_list if not is_suspended(stock)]
# 过滤ST及其他具有退市标签的股票
def filter_st_stock(stock_list):
return [stock for stock in stock_list if not is_st_stock(stock)]
# 筛选符合超额十字星的股票
def filter_crossstar_stock(stock_list):
stock_list_1 = []
index_pr = history(240, ‘1m’, ‘close’)[‘399905.XSHE’]
index_t = history(2,’1d’,’close’)[‘399905.XSHE’][0]
Ri = index_pr/index_t-1
for stk in stock_list:
stk_pr = history(240, ‘1m’, ‘close’)[stk]
stk_t = history(2,’1d’,’close’)[stk][0]
Rs = stk_pr/stk_t-1
Re = Rs – Ri
High = Re.max()
Low = Re.min()
Open = Re.ix[0]
Close = Re.ix[-1]
bar = abs(Re.ix[0]-Re.ix[-1])
if Open>Close:
upline = High – Open
downline = Close – Low
else:
upline = High – Close
downline = Open – Low
if bar < 0.001 and upline > bar*3 and downline > bar*3:
stock_list_1.append(stk)
return stock_list_1
# 前20日涨幅为负的股票:
def filter_minus_rate(stock_list):
stock_list_2 = []
for stk in stock_list:
close = history(20,’1d’,’close’)[stk]
if close[0] > close[-1]:
stock_list_2.append(stk)
return stock_list_2
def init(context):
#调仓频率
context.period = 20
#定时器
context.day_count = 0
#是否调仓
context.adjust = False
#买入股票的数目
context.buy_list_count = 20
context.adjust_position_hour = 9
context.adjust_position_minute = 51
def before_trading(context):
context.df = get_fundamentals(query(fundamentals.eod_derivative_indicator.market_cap).order_by(fundamentals.eod_derivative_indicator.market_cap.asc() ))
context.day_count += 1
pass
def handle_bar(context,bar_dict):
hour = context.now.hour
minute = context.now.minute
if hour == context.adjust_position_hour and minute == context.adjust_position_minute:
do_handle_data(context, bar_dict)
def do_handle_data(context, bar_dict):
logger.info(“调仓日计数 [%d]” %(context.day_count))
if context.day_count % context.period == 0:
logger.info(“==> 满足条件进行调仓”)
buy_stocks = pick_stocks(context)
logger.info(“选股后可买股票: %s” %(buy_stocks))
if len(context.portfolio.positions)>0:
for stk in context.portfolio.positions.keys():
if stk not in buy_stocks:
order_target_percent(stk,0)
for stk in buy_stocks:
order_target_percent(stk,0.99/20)