Plot

library(tseries)
fun_calculation <- function(n=12*10){
  obj <- data.frame(n=seq(n),rw.blue = cumsum(rnorm(n)),rw.red = cumsum(rnorm(n)))
  smooth.lm <- lm(obj[,3]~obj[,2])
  adf.result <- apply(obj[,-1],2,adf.test)
  return.list <- list('obj'=obj,'smooth.lm'=smooth.lm,'adf.result'=adf.result)
  return(return.list)
}
calc.result <- lapply(seq(1,100),function(x)fun_calculation())

Table

No. slope Pr |r| adf test:p_value(blue) adf test:p_value(red)
1 0.8035316 5.982957e-11 0.553 0.7642235 0.5648874
2 -1.3081672 3.002262e-09 0.509 0.0429062 0.0815201
3 0.1081168 2.592895e-06 0.414 0.421714 0.6637106
4 2.2179152 1.955564e-13 0.607 0.0923243 0.99
5 -1.5714908 6.508733e-13 0.597 0.2510332 0.4403108
6 0.7304941 4.492955e-29 0.81 0.5235032 0.6105412
7 0.1195492 2.299186e-03 0.276 0.8058778 0.2988753
8 -0.0548652 6.529873e-01 0.041 0.5245151 0.5036518
9 -0.0140733 8.069698e-01 0.023 0.9584064 0.273405
10 -0.7335868 9.588894e-23 0.748 0.9751031 0.99
11 -0.5718341 2.300867e-04 0.33 0.6069056 0.9433991
12 -0.5296259 2.402715e-23 0.755 0.9192071 0.6198341
13 -0.4960908 2.938731e-08 0.48 0.6414107 0.4689209
14 -0.0622967 2.449254e-01 0.107 0.6993119 0.125423
15 -0.6494201 3.957949e-07 0.443 0.4402473 0.4973481
16 0.3382051 1.882923e-03 0.281 0.676758 0.7810358
17 -1.8788884 6.322589e-08 0.47 0.2740628 0.8546701
18 0.4044037 7.040839e-03 0.245 0.3538216 0.6815281
19 0.7103064 3.404168e-19 0.703 0.466706 0.9505637
20 -0.4266078 3.08711e-07 0.447 0.600324 0.086528
21 0.1361269 2.200873e-02 0.209 0.6640288 0.5369498
22 -0.5755876 1.870439e-24 0.767 0.2152505 0.735708
23 -0.0195266 6.941238e-01 0.036 0.5642373 0.5692277
24 0.7861324 4.403971e-09 0.504 0.8333925 0.6918459
25 0.5437694 9.574842e-29 0.807 0.8357726 0.6810395
26 -1.0594316 5.112192e-18 0.686 0.1955308 0.5774525
27 0.0774619 1.297273e-01 0.139 0.5747868 0.4608587
28 0.1633766 9.367579e-02 0.154 0.3888158 0.4570389
29 -1.1616583 2.747297e-09 0.51 0.6004074 0.4329438
30 -0.0411888 8.115718e-01 0.022 0.0590924 0.6230561
31 -0.0925068 1.543125e-04 0.339 0.4502076 0.9188801
32 0.1233765 7.202116e-01 0.033 0.0569609 0.5822959
33 -0.755627 1.073749e-16 0.666 0.9451838 0.2875912
34 0.501873 2.171803e-16 0.661 0.6099764 0.8850845
35 -0.1307527 7.685592e-03 0.242 0.6712208 0.1901776
36 0.3920144 5.024632e-02 0.179 0.074828 0.9273063
37 0.1204036 1.412714e-02 0.224 0.6234456 0.2051894
38 -0.2781732 8.713114e-02 0.157 0.2018695 0.250843
39 -0.7000225 3.171961e-11 0.559 0.7477797 0.4178992
40 -0.0679092 2.489985e-01 0.106 0.0605758 0.3314376
41 -0.5855411 4.260081e-05 0.365 0.1873522 0.1664911
42 0.7748168 9.771931e-19 0.697 0.7836257 0.4121992
43 -0.7465773 2.547002e-29 0.812 0.0915647 0.4994435
44 0.0377547 3.6853e-01 0.083 0.1719129 0.3400227
45 0.490487 4.625008e-08 0.474 0.2047744 0.7173546
46 0.7333582 5.237884e-02 0.178 0.1189388 0.9010844
47 0.4532947 2.093645e-19 0.706 0.713392 0.6339655
48 0.070073 3.841517e-01 0.08 0.7293226 0.6661846
49 0.0673777 2.071863e-01 0.116 0.0932853 0.5884111
50 1.1292044 9.012124e-11 0.548 0.4665112 0.8236941
51 0.8245454 3.911769e-10 0.532 0.6033931 0.6327007
52 0.1122703 3.031243e-01 0.095 0.5491501 0.2276994
53 -0.9955956 9.256828e-21 0.724 0.4559089 0.2236074
54 0.0002325 9.992336e-01 0 0.489212 0.854231
55 -0.6827764 2.703113e-05 0.373 0.1404077 0.5800606
56 0.0696218 9.115808e-02 0.155 0.3729639 0.7025377
57 0.0522959 2.934093e-01 0.097 0.077361 0.7856587
58 -0.0923022 1.197956e-02 0.229 0.7665426 0.7656264
59 -0.6183578 9.987129e-41 0.884 0.3301883 0.3740338
60 0.3338493 6.67622e-21 0.726 0.5766518 0.5564094
61 -0.3297309 4.109277e-06 0.406 0.5541702 0.7180208
62 0.2321872 9.564264e-04 0.298 0.3036353 0.0699658
63 0.66706 1.313522e-09 0.518 0.9353378 0.5324195
64 0.7297167 1.231908e-21 0.735 0.4765519 0.0842927
65 -0.2614087 2.029343e-02 0.212 0.2346867 0.1761533
66 -0.3264379 5.913243e-14 0.617 0.0942648 0.6790793
67 -1.0250715 2.250145e-14 0.625 0.3129024 0.5868382
68 -0.2266215 5.39002e-02 0.176 0.8361732 0.6541261
69 0.4612481 3.026957e-10 0.535 0.428447 0.46075
70 0.1563758 2.000204e-03 0.279 0.384392 0.2523032
71 -0.7923758 4.073753e-12 0.579 0.5531235 0.3882828
72 -0.7508856 1.66368e-25 0.777 0.1192192 0.6299227
73 -0.4977458 2.097511e-09 0.513 0.1585585 0.5340478
74 -0.4163333 5.470116e-04 0.311 0.5557722 0.9753503
75 -0.3452638 9.389693e-03 0.236 0.604286 0.6320787
76 -0.0264308 9.527001e-01 0.005 0.5627148 0.9307275
77 -0.5776291 1.27972e-12 0.59 0.8041881 0.3752757
78 -0.169825 3.030828e-02 0.198 0.7779067 0.99
79 -0.8424745 1.313553e-26 0.788 0.6099717 0.5804205
80 0.45089 2.53097e-16 0.66 0.4443606 0.5115167
81 1.1526263 5.913236e-28 0.8 0.0514127 0.5316413
82 -0.3926095 6.199612e-06 0.399 0.0618691 0.9205906
83 0.8047027 9.064711e-43 0.893 0.6670422 0.209327
84 0.46458 5.97194e-35 0.852 0.4311194 0.5582395
85 0.5272772 5.547491e-17 0.67 0.5280899 0.3997252
86 0.0032035 9.836e-01 0.002 0.7312186 0.8430514
87 -0.1327686 3.838251e-03 0.262 0.7925074 0.7174309
88 0.0865957 1.711521e-01 0.126 0.5093591 0.6041724
89 1.0338716 4.358386e-18 0.687 0.3967915 0.9192629
90 -0.363084 2.983552e-30 0.819 0.0925138 0.0484938
91 -0.4370589 2.217187e-10 0.539 0.99 0.3246671
92 0.4637779 9.756586e-20 0.711 0.6749628 0.3983755
93 0.7088743 1.15506e-16 0.665 0.6518651 0.8933223
94 0.9286628 1.573206e-27 0.796 0.3116577 0.9541358
95 -0.607105 4.445878e-19 0.702 0.971998 0.9396572
96 -0.5755062 4.322413e-15 0.638 0.7118288 0.4724056
97 -0.0906921 6.131996e-02 0.171 0.99 0.5776913
98 0.2689479 1.911525e-11 0.564 0.5903945 0.4767038
99 0.5933767 5.012332e-07 0.44 0.0186366 0.4048453
100 0.5716991 5.019164e-32 0.832 0.4632674 0.3457593