It will help to deconstruct the data (which will be a lot quicker if you take a look at FAQ: What's a reproducible example (`reprex`) and how do I create one? )
Look at Tech a
There a long periods of no activity, and the area fills in those periods until the next dip (Tech e doesn't seem to be well performing.'
> print(trades_e, n = Inf)
# A tibble: 73 x 3
Time Tech Values
<int> <chr> <dbl>
1 0 e 0
2 1 e 0
3 2 e 0
4 3 e 0
5 4 e 0
6 5 e 0
7 6 e 0
8 7 e 0
9 8 e 0
10 9 e 0
11 10 e -147.
12 11 e -220.
13 12 e -234.
14 13 e -226.
15 14 e -189.
16 15 e -133.
17 16 e -63.5
18 17 e 0
19 18 e 0
20 19 e 0
21 20 e 0
22 21 e 0
23 22 e 0
24 23 e 0
25 24 e 0
26 25 e 0
27 26 e 0
28 27 e 0
29 28 e 0
30 29 e 0
31 30 e 0
32 31 e 0
33 32 e 0
34 33 e 0
35 34 e 0
36 35 e 0
37 36 e 0
38 37 e 0
39 38 e -47.0
40 39 e -36.3
41 40 e 0
42 41 e 0
43 42 e 0
44 43 e 0
45 44 e 0
46 45 e 0
47 46 e 0
48 47 e 0
49 48 e 0
50 49 e 0
51 50 e 0
52 51 e 0
53 52 e 0
54 53 e 0
55 54 e 0
56 55 e 0
57 56 e 0
58 57 e 0
59 58 e 0
60 59 e 0
61 60 e -122.
62 61 e -152.
63 62 e -126.
64 63 e -80.4
65 64 e -33.6
66 65 e 0
67 66 e 0
68 67 e 0
69 68 e 0
70 69 e 0
71 70 e 0
72 71 e 0
73 72 e 0