HOW TO USE
ACKNOWLDGEMENT
DISCLAIMER
The authors do not recommend any investment advice based on the analysis done in the dashboard. This exercise is for educational purpose only. Share market is a risky investment hence advice of SEBI registered investment advisor should be taken before investing in the stock market.
[1] 8459 8456 8466 8530 8536 8551 8561 8574 8600 8597 8592 8590 8562 8539 8524
[16] 8503 8485 8424 8394 8374 8350 8286 8264 8255 8243 8239 8233 8226 8231 8231
Call:
lm(formula = pred ~ actual)
Residuals:
Min 1Q Median 3Q Max
-0.065328 -0.013999 -0.001073 0.011114 0.272880
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.306443 0.045517 6.732 2.56e-11 ***
actual 0.966587 0.004961 194.847 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.02628 on 1223 degrees of freedom
Multiple R-squared: 0.9688, Adjusted R-squared: 0.9688
F-statistic: 3.797e+04 on 1 and 1223 DF, p-value: < 2.2e-16
horizon mse rmse mae mape coverage
1 948 hours 0.0037764689 0.06145298 0.04808737 0.005193376 0.3750000
2 960 hours 0.0037657508 0.06136571 0.04782282 0.005164788 0.3958333
3 972 hours 0.0038003750 0.06164718 0.04825099 0.005211288 0.3958333
4 984 hours 0.0038009291 0.06165168 0.04826130 0.005212563 0.4166667
5 996 hours 0.0038278894 0.06186994 0.04868266 0.005258225 0.4166667
6 1008 hours 0.0038305829 0.06189170 0.04872517 0.005263042 0.4166667
7 1032 hours 0.0038454663 0.06201182 0.04897849 0.005290367 0.4166667
8 1044 hours 0.0038529009 0.06207174 0.04907885 0.005301411 0.4166667
9 1104 hours 0.0038983463 0.06243674 0.04973978 0.005372508 0.3958333
10 1116 hours 0.0038628963 0.06215220 0.04939420 0.005335339 0.3958333
11 1128 hours 0.0038915509 0.06238230 0.04982114 0.005381336 0.3958333
12 1140 hours 0.0037534334 0.06126527 0.04864473 0.005253851 0.4166667
13 1152 hours 0.0038044832 0.06168049 0.04942303 0.005337493 0.3958333
14 1164 hours 0.0036691831 0.06057378 0.04824768 0.005210198 0.4166667
15 1176 hours 0.0037011355 0.06083696 0.04875212 0.005264440 0.3958333
16 1188 hours 0.0035445824 0.05953640 0.04738429 0.005116228 0.4166667
17 1200 hours 0.0035637645 0.05969727 0.04784104 0.005165156 0.4166667
18 1212 hours 0.0034499832 0.05873656 0.04660829 0.005031878 0.4375000
19 1272 hours 0.0034479898 0.05871959 0.04641399 0.005011115 0.4375000
20 1284 hours 0.0032441415 0.05695737 0.04445056 0.004798415 0.4583333
21 1296 hours 0.0032435208 0.05695192 0.04442412 0.004795576 0.4583333
22 1308 hours 0.0031234952 0.05588824 0.04308239 0.004650573 0.4791667
23 1320 hours 0.0031229297 0.05588318 0.04305743 0.004647898 0.4791667
24 1332 hours 0.0030092818 0.05485692 0.04183014 0.004515332 0.5000000
25 1344 hours 0.0030085562 0.05485031 0.04181147 0.004513390 0.5000000
26 1356 hours 0.0029220376 0.05405587 0.04087046 0.004411879 0.5208333
27 1368 hours 0.0027829903 0.05275405 0.03925904 0.004237625 0.5416667
28 1440 hours 0.0027788954 0.05271523 0.03899944 0.004209919 0.5416667
29 1452 hours 0.0025829064 0.05082230 0.03718875 0.004013882 0.5625000
30 1464 hours 0.0025827258 0.05082053 0.03714938 0.004009666 0.5625000
31 1476 hours 0.0023610072 0.04859020 0.03507521 0.003785019 0.5833333
32 1488 hours 0.0023621202 0.04860165 0.03516095 0.003794134 0.5833333
33 1500 hours 0.0021035680 0.04586467 0.03285563 0.003544222 0.6041667
34 1512 hours 0.0021025283 0.04585334 0.03274603 0.003532515 0.6041667
35 1524 hours 0.0018836402 0.04340092 0.03085754 0.003327783 0.6250000
36 1536 hours 0.0018841080 0.04340631 0.03095361 0.003338019 0.6250000
37 1548 hours 0.0016231625 0.04028849 0.02890893 0.003116062 0.6458333
38 1608 hours 0.0016225456 0.04028083 0.02887182 0.003112054 0.6458333
39 1620 hours 0.0013218018 0.03635659 0.02668451 0.002874323 0.6666667
40 1632 hours 0.0011323662 0.03365065 0.02475177 0.002664941 0.6875000
41 1644 hours 0.0011362613 0.03370848 0.02490744 0.002681855 0.6875000
42 1668 hours 0.0009386355 0.03063716 0.02304433 0.002479888 0.7083333
43 1680 hours 0.0008162121 0.02856943 0.02169615 0.002333700 0.7291667
44 1692 hours 0.0008171536 0.02858590 0.02175802 0.002340523 0.7291667
45 1704 hours 0.0006961007 0.02638372 0.02037981 0.002191141 0.7500000
46 1716 hours 0.0006955955 0.02637415 0.02028096 0.002180593 0.7500000
47 1776 hours 0.0006254990 0.02500998 0.01920476 0.002064228 0.7708333
48 1788 hours 0.0006324493 0.02514855 0.01948279 0.002094401 0.7708333
49 1800 hours 0.0005704119 0.02388330 0.01838980 0.001976319 0.7916667
50 1812 hours 0.0005694774 0.02386372 0.01835399 0.001972742 0.7916667
51 1824 hours 0.0005171589 0.02274113 0.01745908 0.001875892 0.8125000
52 1836 hours 0.0005024797 0.02241606 0.01700939 0.001827808 0.8125000
53 1848 hours 0.0004665861 0.02160060 0.01627940 0.001748850 0.8333333
54 1860 hours 0.0004464348 0.02112900 0.01580847 0.001698502 0.8541667
55 1872 hours 0.0004248459 0.02061179 0.01537946 0.001652356 0.8750000
56 1884 hours 0.0003952338 0.01988049 0.01479932 0.001589698 0.8958333
57 1944 hours 0.0003600613 0.01897528 0.01435498 0.001541699 0.9166667
58 1956 hours 0.0003297156 0.01815807 0.01387176 0.001489318 0.9375000
59 1968 hours 0.0003046433 0.01745403 0.01351638 0.001450949 0.9583333
60 1980 hours 0.0002963133 0.01721375 0.01336056 0.001433966 0.9583333
61 1992 hours 0.0002573774 0.01604299 0.01287029 0.001381049 0.9791667
62 2004 hours 0.0002563445 0.01601076 0.01285243 0.001378872 0.9791667
63 2016 hours 0.0002221633 0.01490514 0.01228637 0.001317996 1.0000000
64 2028 hours 0.0002246952 0.01498984 0.01233585 0.001323132 1.0000000
65 2040 hours 0.0002181222 0.01476896 0.01222355 0.001310938 1.0000000
66 2052 hours 0.0002140739 0.01463127 0.01206485 0.001293815 1.0000000
67 2112 hours 0.0002353936 0.01534254 0.01272165 0.001363933 1.0000000
68 2124 hours 0.0002349709 0.01532876 0.01265575 0.001356838 1.0000000
69 2136 hours 0.0002443649 0.01563218 0.01292367 0.001385395 1.0000000
70 2160 hours 0.0002507513 0.01583513 0.01311120 0.001405070 1.0000000
71 2172 hours 0.0002503026 0.01582095 0.01308921 0.001402932 1.0000000
72 2184 hours 0.0002556965 0.01599051 0.01322359 0.001416811 1.0000000
73 2196 hours 0.0002523879 0.01588672 0.01312387 0.001406428 1.0000000
74 2208 hours 0.0002587614 0.01608606 0.01324506 0.001418719 1.0000000
75 2220 hours 0.0002685565 0.01638769 0.01361317 0.001458424 1.0000000
76 2280 hours 0.0002843879 0.01686381 0.01415399 0.001516075 1.0000000
77 2292 hours 0.0002938044 0.01714072 0.01442735 0.001545433 1.0000000
78 2304 hours 0.0003062398 0.01749971 0.01490901 0.001596755 1.0000000
79 2328 hours 0.0003202177 0.01789463 0.01537762 0.001646589 1.0000000
80 2340 hours 0.0003263203 0.01806434 0.01559811 0.001670524 1.0000000
81 2352 hours 0.0003395307 0.01842636 0.01610733 0.001724745 1.0000000
82 2364 hours 0.0003406772 0.01845744 0.01622402 0.001737383 1.0000000
83 2376 hours 0.0003678922 0.01918052 0.01675854 0.001794133 1.0000000
84 2388 hours 0.0003710869 0.01926362 0.01693602 0.001813377 1.0000000
85 2448 hours 0.0004551229 0.02133361 0.01798729 0.001925535 1.0000000
86 2460 hours 0.0004607603 0.02146533 0.01820863 0.001949579 1.0000000
87 2472 hours 0.0005462857 0.02337276 0.01924716 0.002060360 1.0000000
88 2484 hours 0.0005562601 0.02358517 0.01965166 0.002103980 1.0000000
89 2496 hours 0.0006627169 0.02574329 0.02084042 0.002230900 1.0000000
90 2508 hours 0.0006762780 0.02600535 0.02122614 0.002272396 1.0000000
91 2520 hours 0.0007678784 0.02771062 0.02236223 0.002393878 1.0000000
92 2532 hours 0.0007772799 0.02787974 0.02265419 0.002425262 1.0000000
93 2544 hours 0.0008824607 0.02970624 0.02392578 0.002561263 1.0000000
94 2556 hours 0.0008912965 0.02985459 0.02435104 0.002607054 1.0000000
95 2616 hours 0.0010044238 0.03169265 0.02575226 0.002756839 1.0000000
96 2628 hours 0.0010011828 0.03164147 0.02565618 0.002746378 1.0000000
97 2640 hours 0.0010981137 0.03313780 0.02703320 0.002893443 1.0000000
98 2652 hours 0.0011126789 0.03335684 0.02738582 0.002931285 1.0000000
99 2664 hours 0.0012087177 0.03476662 0.02864798 0.003066075 1.0000000
100 2676 hours 0.0012255534 0.03500790 0.02913613 0.003118571 1.0000000
101 2688 hours 0.0013500720 0.03674333 0.03060628 0.003275708 1.0000000
102 2700 hours 0.0013659154 0.03695829 0.03100780 0.003318871 1.0000000
103 2712 hours 0.0015481245 0.03934621 0.03267092 0.003496999 1.0000000
104 2724 hours 0.0015631058 0.03953613 0.03303797 0.003536453 1.0000000
105 2784 hours 0.0017803129 0.04219375 0.03464648 0.003708928 1.0000000
106 2796 hours 0.0017951985 0.04236978 0.03492698 0.003739050 1.0000000
107 2808 hours 0.0020231972 0.04497996 0.03661931 0.003920532 1.0000000
108 2820 hours 0.0020316536 0.04507387 0.03677720 0.003937505 1.0000000
109 2832 hours 0.0022925506 0.04788059 0.03859803 0.004132908 1.0000000
110 2844 hours 0.0022856652 0.04780863 0.03846150 0.004118297 1.0000000
111 2856 hours 0.0025718015 0.05071293 0.04058146 0.004345757 1.0000000
112 2868 hours 0.0025679084 0.05067453 0.04050328 0.004337403 1.0000000
113 2880 hours 0.0028378858 0.05327181 0.04238509 0.004539314 1.0000000
114 2892 hours 0.0028420893 0.05331125 0.04254844 0.004556901 1.0000000
115 2952 hours 0.0031690308 0.05629415 0.04457553 0.004774677 1.0000000
116 2964 hours 0.0031699520 0.05630233 0.04468428 0.004786403 1.0000000
117 2976 hours 0.0035584143 0.05965245 0.04707336 0.005043280 1.0000000
118 2988 hours 0.0035500143 0.05958200 0.04678658 0.005012904 1.0000000
119 3000 hours 0.0039402764 0.06277162 0.04944355 0.005298015 1.0000000
120 3012 hours 0.0039304716 0.06269347 0.04913504 0.005265339 1.0000000
121 3024 hours 0.0043973881 0.06631280 0.05197216 0.005570217 1.0000000
122 3036 hours 0.0043933077 0.06628203 0.05189775 0.005562800 1.0000000
123 3048 hours 0.0048485259 0.06963136 0.05455043 0.005847801 1.0000000
124 3060 hours 0.0048549100 0.06967718 0.05465628 0.005859751 1.0000000
125 3120 hours 0.0053979159 0.07347051 0.05756050 0.006172266 1.0000000
126 3132 hours 0.0054171884 0.07360155 0.05786398 0.006205418 1.0000000
127 3144 hours 0.0058995966 0.07680883 0.06053567 0.006493197 1.0000000
128 3156 hours 0.0059322543 0.07702113 0.06105320 0.006548787 1.0000000
129 3168 hours 0.0064754440 0.08047014 0.06393305 0.006859276 0.9791667
130 3180 hours 0.0065429478 0.08088849 0.06496908 0.006970475 0.9791667
131 3192 hours 0.0069620978 0.08343919 0.06723225 0.007214226 0.9791667
132 3204 hours 0.0070322381 0.08385844 0.06819600 0.007317621 0.9791667
133 3216 hours 0.0073495963 0.08572979 0.06974572 0.007484596 0.9791667
134 3228 hours 0.0073954407 0.08599675 0.07041685 0.007556689 0.9791667
135 3300 hours 0.0073601457 0.08579129 0.07011730 0.007525404 0.9791667
136 3312 hours 0.0078364307 0.08852362 0.07284148 0.007818302 0.9791667
137 3324 hours 0.0077758356 0.08818070 0.07234868 0.007766307 0.9791667
138 3336 hours 0.0081869694 0.09048187 0.07476916 0.008026239 0.9791667
139 3372 hours 0.0081341764 0.09018967 0.07430059 0.007976975 0.9791667
140 3384 hours 0.0085265941 0.09233956 0.07671869 0.008236591 0.9791667
141 3396 hours 0.0084611749 0.09198464 0.07615901 0.008177566 0.9791667
142 3456 hours 0.0088351430 0.09399544 0.07855397 0.008434679 0.9791667
143 3468 hours 0.0087577238 0.09358271 0.07788623 0.008364181 0.9791667
144 3480 hours 0.0091431063 0.09561959 0.08043260 0.008637682 0.9791667
145 3492 hours 0.0090807999 0.09529323 0.07986134 0.008577609 0.9791667
146 3504 hours 0.0095027667 0.09748214 0.08228113 0.008837831 0.9791667
147 3516 hours 0.0094663173 0.09729500 0.08198329 0.008807132 0.9791667
148 3528 hours 0.0099855177 0.09992756 0.08472371 0.009102473 0.9791667
149 3540 hours 0.0099333688 0.09966629 0.08434304 0.009062823 0.9791667
150 3552 hours 0.0103928095 0.10194513 0.08688497 0.009336493 0.9791667
151 3564 hours 0.0102816182 0.10139831 0.08616734 0.009260502 0.9791667
152 3624 hours 0.0106067449 0.10298905 0.08823148 0.009482095 0.9791667
153 3636 hours 0.0104719527 0.10233256 0.08746276 0.009400458 0.9791667
154 3648 hours 0.0107607359 0.10373397 0.08931856 0.009599578 0.9791667
155 3660 hours 0.0106088822 0.10299943 0.08844628 0.009506849 0.9791667
156 3672 hours 0.0109292133 0.10454288 0.09047009 0.009724152 0.9791667
157 3684 hours 0.0107350545 0.10361011 0.08938214 0.009608183 0.9791667
158 3696 hours 0.0111103634 0.10540571 0.09175843 0.009863615 0.9791667
159 3708 hours 0.0108956806 0.10438238 0.09056068 0.009735827 0.9791667
160 3720 hours 0.0112300992 0.10597216 0.09276381 0.009972437 0.9791667
161 3732 hours 0.0110390489 0.10506688 0.09172514 0.009861737 0.9791667
162 3816 hours 0.0114870586 0.10717770 0.09445046 0.010155182 0.9791667
163 3828 hours 0.0112625356 0.10612509 0.09336245 0.010038814 0.9791667
164 3840 hours 0.0116916296 0.10812784 0.09621313 0.010345593 0.9791667
165 3852 hours 0.0114322547 0.10692172 0.09503906 0.010219588 0.9791667
166 3864 hours 0.0118574354 0.10889185 0.09785796 0.010522931 0.9791667
167 3876 hours 0.0116039098 0.10772145 0.09669924 0.010398662 0.9791667
168 3888 hours 0.0119756208 0.10943318 0.09931084 0.010679400 0.9791667
169 3900 hours 0.0116347875 0.10786467 0.09782545 0.010519651 0.9791667
170 3960 hours 0.0119625111 0.10937326 0.09995841 0.010748758 0.9791667
171 3972 hours 0.0116659349 0.10800896 0.09872007 0.010615348 0.9791667
172 3996 hours 0.0118640669 0.10892230 0.10018172 0.010771676 0.9791667
173 4008 hours 0.0116277495 0.10783204 0.09935782 0.010682548 0.9791667
174 4020 hours 0.0118315477 0.10877292 0.10075979 0.010832350 0.9791667
175 4032 hours 0.0116744995 0.10804860 0.10020304 0.010772393 0.9791667
176 4044 hours 0.0118683880 0.10894213 0.10149569 0.010910460 0.9791667
177 4056 hours 0.0116044053 0.10772375 0.10055926 0.010809113 1.0000000
178 4068 hours 0.0118049460 0.10865057 0.10173109 0.010934081 1.0000000
179 4128 hours 0.0116666421 0.10801223 0.10121728 0.010878961 1.0000000
180 4140 hours 0.0118839463 0.10901351 0.10243997 0.011009277 1.0000000
181 4152 hours 0.0118691906 0.10894581 0.10238662 0.011004430 1.0000000
182 4164 hours 0.0121475672 0.11021600 0.10396552 0.011172613 1.0000000
183 4176 hours 0.0124665135 0.11165354 0.10568187 0.011357399 1.0000000
184 4188 hours 0.0123090364 0.11094610 0.10511632 0.011294983 1.0000000
185 4200 hours 0.0126963853 0.11267824 0.10710511 0.011509470 1.0000000
186 4224 hours 0.0124454670 0.11155925 0.10603614 0.011394146 1.0000000
187 4236 hours 0.0127083682 0.11273140 0.10761860 0.011562765 1.0000000
188 4296 hours 0.0123755367 0.11124539 0.10593282 0.011381014 1.0000000
189 4308 hours 0.0126048294 0.11227123 0.10737337 0.011534675 1.0000000
190 4320 hours 0.0122884319 0.11085320 0.10572557 0.011357055 1.0000000
191 4332 hours 0.0125884379 0.11219821 0.10750006 0.011546099 1.0000000
192 4344 hours 0.0122951396 0.11088345 0.10606825 0.011391646 1.0000000
193 4356 hours 0.0125815392 0.11216746 0.10780426 0.011576659 1.0000000
194 4368 hours 0.0122042945 0.11047305 0.10591791 0.011373027 1.0000000
195 4380 hours 0.0125219594 0.11190156 0.10760018 0.011551860 1.0000000
196 4392 hours 0.0120553937 0.10979706 0.10546497 0.011320853 1.0000000
197 4464 hours 0.0120484422 0.10976540 0.10540496 0.011313557 1.0000000
198 4476 hours 0.0119995880 0.10954263 0.10523924 0.011293154 1.0000000
199 4488 hours 0.0120092437 0.10958670 0.10531697 0.011300735 1.0000000
200 4500 hours 0.0121220132 0.11010001 0.10572527 0.011342553 1.0000000
201 4524 hours 0.0124381537 0.11152647 0.10722694 0.011501819 1.0000000
202 4536 hours 0.0122164899 0.11052823 0.10604872 0.011375042 1.0000000
203 4548 hours 0.0125111507 0.11185326 0.10750617 0.011529699 1.0000000
204 4560 hours 0.0122949241 0.11088248 0.10645001 0.011416039 1.0000000
205 4572 hours 0.0126268908 0.11236944 0.10807527 0.011588439 1.0000000
206 4632 hours 0.0123714109 0.11122684 0.10688672 0.011460345 1.0000000
207 4644 hours 0.0126604454 0.11251864 0.10838075 0.011618919 1.0000000
208 4668 hours 0.0127128491 0.11275127 0.10857704 0.011638120 1.0000000
209 4680 hours 0.0126961940 0.11267739 0.10844675 0.011623507 1.0000000
210 4692 hours 0.0125900959 0.11220560 0.10806345 0.011580058 1.0000000
211 4704 hours 0.0125607300 0.11207466 0.10786005 0.011557838 1.0000000
212 4716 hours 0.0124736758 0.11168561 0.10753999 0.011521330 1.0000000
213 4728 hours 0.0124096953 0.11139881 0.10709290 0.011472981 1.0000000
214 4740 hours 0.0123408771 0.11108950 0.10684182 0.011443738 1.0000000
215 4800 hours 0.0122716971 0.11077769 0.10634538 0.011390070 1.0000000
216 4812 hours 0.0122559729 0.11070670 0.10628600 0.011381626 1.0000000
217 4824 hours 0.0121761079 0.11034540 0.10566338 0.011314329 1.0000000
218 4836 hours 0.0122377162 0.11062421 0.10589404 0.011336829 1.0000000
219 4848 hours 0.0121144988 0.11006588 0.10499353 0.011239923 1.0000000
220 4872 hours 0.0119214520 0.10918540 0.10360564 0.011090995 1.0000000
221 4884 hours 0.0119728450 0.10942050 0.10380571 0.011110484 1.0000000
222 4896 hours 0.0117559577 0.10842489 0.10221394 0.010939791 1.0000000
223 4980 hours 0.0116995328 0.10816438 0.10198294 0.010913452 1.0000000
224 4992 hours 0.0114923695 0.10720247 0.10052430 0.010757036 1.0000000
225 5004 hours 0.0114782271 0.10713649 0.10046387 0.010749328 1.0000000
226 5016 hours 0.0112348246 0.10599446 0.09882962 0.010574294 1.0000000
227 5028 hours 0.0112645188 0.10613444 0.09894829 0.010585102 1.0000000
228 5040 hours 0.0110018243 0.10488958 0.09725500 0.010403847 1.0000000
229 5052 hours 0.0109098895 0.10445042 0.09689709 0.010363209 1.0000000
230 5064 hours 0.0106069356 0.10298998 0.09503555 0.010164137 1.0000000
231 5076 hours 0.0105807905 0.10286297 0.09493631 0.010150950 1.0000000
232 5160 hours 0.0102580816 0.10128219 0.09267844 0.009909423 1.0000000
233 5172 hours 0.0101689518 0.10084122 0.09235392 0.009871561 1.0000000
234 5184 hours 0.0099969862 0.09998493 0.09070367 0.009694544 1.0000000
235 5208 hours 0.0096934109 0.09845512 0.08836894 0.009444665 1.0000000
236 5220 hours 0.0099573467 0.09978651 0.08979562 0.009596787 1.0000000
237 5232 hours 0.0096869321 0.09842221 0.08756785 0.009358121 1.0000000
238 5244 hours 0.0099494084 0.09974672 0.08900922 0.009511833 1.0000000
239 5304 hours 0.0096127686 0.09804473 0.08638133 0.009230725 1.0000000
240 5316 hours 0.0097927010 0.09895808 0.08736323 0.009335422 1.0000000
241 5328 hours 0.0094716099 0.09732220 0.08480133 0.009061273 1.0000000
242 5340 hours 0.0096486174 0.09822738 0.08589454 0.009178278 1.0000000
243 5352 hours 0.0092703171 0.09628249 0.08315198 0.008885124 1.0000000
244 5364 hours 0.0093861488 0.09688214 0.08391162 0.008966660 1.0000000
245 5376 hours 0.0093210003 0.09654533 0.08290014 0.008858370 1.0000000
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247 5400 hours 0.0089692586 0.09470617 0.08041803 0.008593584 1.0000000
248 5412 hours 0.0086660414 0.09309158 0.07911913 0.008455707 1.0000000
249 5472 hours 0.0082502051 0.09083064 0.07622853 0.008146952 1.0000000
250 5484 hours 0.0082656430 0.09091558 0.07634122 0.008159278 1.0000000
251 5508 hours 0.0080060956 0.08947679 0.07512773 0.008030224 1.0000000
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253 5532 hours 0.0075719107 0.08701673 0.07209528 0.007706354 1.0000000
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390 7896 hours 0.0004233650 0.02057583 0.01631778 0.001744772 1.0000000
391 7908 hours 0.0003728770 0.01931002 0.01581529 0.001691780 1.0000000
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435 8724 hours 0.0346824017 0.18623212 0.11577739 0.012682480 1.0000000
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437 8748 hours 0.0378032819 0.19443066 0.12416968 0.013606835 1.0000000
438 8760 hours 0.0408620857 0.20214373 0.13196252 0.014467106 1.0000000
Dr AMITA SHARMA Post Doc from Erasmus University, Rotterdam, the Netherlands Assistant Professor Institute of Agri Business Management, Swami Keshwanand Rajasthan Agricultural University, Bikaner (Raj),India Blog: www.thinkingai.in
ARUN KUMAR SHARMA Machine Learning Enthusiast 13 Years of Financial Services Marketing Exp Blogger, Writer and Machine Learning Consutlant Certified Business Analytics Professional Certified in Predictive Analytics, Indian Institute of Mnamagement,IIMx Bangalore Certified in Macroeconomic Forecasting, International Monetary Fund(IMFx) Certified in Text Analytics, openSAP Email: aks10000@gmail.com Tel:9468567418
---
title: "FORECASTING WITH FACEBOOK PROPHET"
output:
flexdashboard::flex_dashboard:
orientation: rows
vertical_layout: fill
social : ["twitter","facebook","menu"]
source_code : embed
---
```{r}
# UPLOADING THE LIBRARIES
library(prophet)
library(lubridate)
library(ggplot2)
library(DT)
library(taRifx )
```
```{r}
setwd("C:\\Users\\arunkumar\\Desktop\\R\\flexdashboard\\ForecastingShareMarket")
data=read.csv("^NSEI.csv", header = TRUE, stringsAsFactors = FALSE)
```
HOW TO USE,AKNOWLEDGEMENT & DISCLAIMER
======================================================
HOW TO USE
* Go to Yahoo Finance website
* Write name of Share/Index in search box
* Once Share/Index ppears, click on historical data
* Set the "Time Period" as per your choice
* Click on "download Data" button to get the csv file
* Store the file in a folder which is accessible by working directory in R
* Download the source code from the upper right corner
>
ACKNOWLDGEMENT
* The historical data of NIFTY50 is used in the dashboard.
* The data used in the dashboard is downloaded from www.in.finance.yahoo.com
* The data hasn't been cleaned up and used as it is provided by the website.
* The dashboard is for educational purpose only.
DISCLAIMER
* > The authors do not recommend any investment advice based on the analysis done in the dashboard. This exercise is for educational purpose only. Share market is a risky investment hence advice of SEBI registered investment advisor should be taken before investing in the stock market.
DATA OVERVIEW {data-navmenu="MENU"}
=================================================
Column
------------------------------------------------
### DATA OVERVIEW
```{r}
datatable(data,caption="NIFTY 50 Hstorical Data",
filter="top",
rownames=TRUE,
options = list(pageLength=25))
```
PLOTS OF HISTORICAL PRICES 2015-2020 {data-navmenu="MENU"}
===========================================================
Column {.tabset}
---------------------------------
### Original Historial Prices Plot
```{r}
dat <- japply(data[,-1], which(sapply(data[,-1], class)=="character"), as.numeric )
dat$Date=ymd(data$Date)
qplot(Date,Close, data=dat, main="Historical Price Chart 2015-2020")
```
Column
-------------------------------------------
### Log Tanrsformed Historical Prices Plot
```{r}
ds <- dat$Date
y <-log(dat$Close)
df=data.frame(ds,y)
qplot(ds,y, data=df, main="NSE Historical Price (Log Transformed) Chart 2015-2020")
```
FORECASTING WITH FACEBOOK PROPHET {data-navmenu="MENU"}
=============================================
Column {data-width=350} {.tabset}
---------------------------------------------
### Plot of Forecast for Next 365 Days
```{r, fig.width=10, fig.height=7}
m=prophet(df, daily.seasonality = TRUE)
future<-make_future_dataframe(m, periods=365)
forecast <-predict(m,future)
dyplot.prophet(m,forecast)
```
COMPONENT PLOT OF FORECAST {data-navmenu="MENU"}
=====================================
Column
------------------------------------
### Component Plot of Forecasts
```{r}
prophet_plot_components(m, forecast)
```
FORECASTs {data-navmenu="MENU"}
========================================
Column {.tabset}
---------------------------------------
### PLOT Actual Vs Model Prediction
```{r}
l=length(m$history$y)
pred <- forecast$yhat[1:l]
actual <-m$history$y
plot(actual, pred)
abline(lm(pred~actual), col="red", lwd=2)
```
Column
-----------------------------------------
### Prediction for Next 30 Days
```{r}
roll=30
head(round(exp(pred),digits = 0),roll)
```
MODEL SUMMARY CROSS VALIDATION {data-navmenu="MENU"}
=================================
Column
----------------------------------------
### Facebook Prophet Model Summary
```{r}
summary(lm(pred~actual))
```
Column {.tabset}
--------------------------------------
### Molel Cross Validation
```{r}
x<-cross_validation(m, horizon=365, units="days")
performance_metrics(x,rolling_window = 0.1)
```
MODEL CROSS VALIDATION PLOT {data-navmenu="MENU"}
=================================================
Column
------------------------------------------------
### Model RMSE Cross Validation Plot
```{r}
plot_cross_validation_metric(x,metric="rmse",
rolling_window = 0.05)
```
About Us {data-navmenu="MENU"}
==============================================
### DASHBOARD PREPARED BY (CONTACT FOR MACHINE LEARNING TRAINING, COACHING & CONSULTING)
* Dr AMITA SHARMA
Post Doc from Erasmus University, Rotterdam, the Netherlands
Assistant Professor
Institute of Agri Business Management,
Swami Keshwanand Rajasthan Agricultural University,
Bikaner (Raj),India
Blog: www.thinkingai.in
* ARUN KUMAR SHARMA
Machine Learning Enthusiast
13 Years of Financial Services Marketing Exp
Blogger, Writer and Machine Learning Consutlant
Certified Business Analytics Professional
Certified in Predictive Analytics, Indian Institute of Mnamagement,IIMx Bangalore
Certified in Macroeconomic Forecasting, International Monetary Fund(IMFx)
Certified in Text Analytics, openSAP
Email: aks10000@gmail.com
Tel:9468567418