Price, Quantity and Total Revenue

	C	D	E	F	G	H	I
1		by def	target corr to P	target corr to P
2	specified corr	100%	50%	75%
3	realized corr	100%	100%	100%
4	Price	Q0	Q1	Q2	TR1	TR2	TR3
5	10	10	10.5	11	100	105	109
6	20	20	20.7	20	400	414	404
7	30	30	30.7	31	900	920	924
8	40	40	41.0	40	1600	1639	1604
9	50	50	50.7	50	2500	2537	2513
10	60	60	60.8	60	3600	3648	3603
11	70	70	70.1	71	4900	4904	4940
12	80	80	80.2	81	6400	6416	6479
13	90	90	90.9	90	8100	8179	8138
14	100	100	100.9	101	10000	10088	10055
15	110	110	111.0	111	12100	12208	12171
16	120	120	120.2	121	14400	14427	14473
17	130	130	130.4	130	16900	16949	16958
18
19	Notes
20	1	starting point - static supply curve from micro 101
21	2	by design, the correl b/w Price and Q0 is 100%
22	3	aim - to investigate how the curvature of the TR (Total Revenue) curve changes when correl is not 100%
23	4	e.g. generate a series Q1, that has 50% correlation to Price and see what TR1 (=Price *Q1) would look like
24	5	same attempt with Q2, but using a 75% correl
25	6	I will also need to preserve the order of the series - e.g. if Q0 is monotonically increaseing, so should Q1 and Q2
26	7	if Price were random, then I could use cholseky - z1Target Correl + sqrt (1-TargetCorrel)^2z2
27	8	But price is static - and I'm thinking there's no way to impose a target correl and create a new Q series
28	9	by design, this correl will always be 100%
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100