Hello,
I have always been interested in technical analysis, but I have ran across something which just has me utterly confused... I am hoping someone can help me make sense out of... I am trying to use someone elses published method just to experiment with, but am having a heckuva time with the final piece....
Assuming I have the following closing prices I want to recognize trends in:
I expand this table with some "lag" data for the previous 1,2,3, and 4 days... For this I compute the price movement and the percent movement compared to the "Nth previous day".. So what I have are the same 12 rows as above, but now with 8 extra columns... For example:
All of this is fine-and-dandy, and I decide to add some patterns to this data, this is a bit trickier but I will try to explain what I did....
For each -N% field I compute the average percentage change and double it, so for example, -1% ends up with ".077"... I'll call this value "P"...
So, for each row, I compute a value as follows:
NOTE: CLOSE[N] is the CLOSE of the previous Nth day (N changes depending on which column I am computing, for example in -1 it is just the previous days close, for -4 it is the close which occurred 4 days ago)...
(CLOS-CLOS[N])
--------------------
(CLOS*P)
So I end up with the following when computed this way, adding 4 columns of data for each row:
Now up to this point everything is perfect... I have the output I should have and everything checks out... But, I get lost with the next statement:
"When the price advances by more than [THETA] percent, the day on which the lowest close was made is flagged as an ideal buy signal. When the price declines more than [THETA] percent, the day on which the highest close was made is flagged as an ideal sell signal."
From here, I believe that what is referred to as [THETA] percent is what I called "P" in my earlier example..... What I am confused about is what is meant by a "price advance" or "price decline"... If I assume that it is my -1% column (which may or may not be correct - BLECH!) then how am I to go about finding a reasonable time period for the "lowest low" and "highest high"...?... The data which I am playing with is for a couple of years, so surely it is not meant to be the "lowest low for the past year"....
Any ideas on how to make this complete?..
Thanks everyone!...
- Greg
I have always been interested in technical analysis, but I have ran across something which just has me utterly confused... I am hoping someone can help me make sense out of... I am trying to use someone elses published method just to experiment with, but am having a heckuva time with the final piece....
Assuming I have the following closing prices I want to recognize trends in:
Code:
Day | Close
1 | 550
2 | 525
3 | 500
4 | 510
5 | 490
6 | 490
7 | 500
8 | 540
9 | 580
10 | 560
11 | 580
12 | 600
Code:
DAY|CLOS| -1| -1%| -2| -2%| -3| -3%| -4| -4%
100| 550| N/A| N/A| N/A| N/A| N/A| N/A| N/A| N/A
101| 525| N/A| N/A| N/A| N/A| N/A| N/A| N/A| N/A
102| 500| N/A| N/A| N/A| N/A| N/A| N/A| N/A| N/A
103| 510| N/A| N/A| N/A| N/A| N/A| N/A| N/A| N/A
104| 490| 20.00| -0.041| 10.00| -0.020| 35.00| -0.071| 60.00| -0.122
105| 490| 0.00| 0.000| 20.00| -0.041| 10.00| -0.020| 35.00| -0.071
106| 500|-10.00| 0.020|-10.00| 0.020| 10.00| -0.020| 0.00| 0.000
107| 540|-40.00| 0.074|-50.00| 0.093|-50.00| 0.093|-30.00| 0.056
108| 580|-40.00| 0.069|-80.00| 0.138|-90.00| 0.155|-90.00| 0.155
109| 560| 20.00| -0.036|-20.00| 0.036|-60.00| 0.107|-70.00| 0.125
110| 580|-20.00| 0.034| 0.00| 0.000|-40.00| 0.069|-80.00| 0.138
111| 600|-20.00| 0.033|-40.00| 0.067|-20.00| 0.033|-60.00| 0.100All of this is fine-and-dandy, and I decide to add some patterns to this data, this is a bit trickier but I will try to explain what I did....
For each -N% field I compute the average percentage change and double it, so for example, -1% ends up with ".077"... I'll call this value "P"...
So, for each row, I compute a value as follows:
NOTE: CLOSE[N] is the CLOSE of the previous Nth day (N changes depending on which column I am computing, for example in -1 it is just the previous days close, for -4 it is the close which occurred 4 days ago)...
(CLOS-CLOS[N])
--------------------
(CLOS*P)
So I end up with the following when computed this way, adding 4 columns of data for each row:
Code:
DAY|X(1) | X(2)| X(3)| X(4)
100| N/A | N/A| N/A| N/A
101| N/A | N/A| N/A| N/A
102| N/A | N/A| N/A| N/A
103| N/A | N/A| N/A| N/A
104| -0.531| -0.197| -0.502| -0.638
105| 0.000| -0.394| -0.143| -0.372
106| 0.260| 0.193| -0.141| 0.000
107| 0.964| 0.894| 0.651| 0.290
108| 0.897| 1.332| 1.091| 0.809
109| -0.465| 0.345| 0.753| 0.651
110| 0.449| 0.000| 0.485| 0.719
111| 0.434| 0.644| 0.234| 0.521Now up to this point everything is perfect... I have the output I should have and everything checks out... But, I get lost with the next statement:
"When the price advances by more than [THETA] percent, the day on which the lowest close was made is flagged as an ideal buy signal. When the price declines more than [THETA] percent, the day on which the highest close was made is flagged as an ideal sell signal."
From here, I believe that what is referred to as [THETA] percent is what I called "P" in my earlier example..... What I am confused about is what is meant by a "price advance" or "price decline"... If I assume that it is my -1% column (which may or may not be correct - BLECH!) then how am I to go about finding a reasonable time period for the "lowest low" and "highest high"...?... The data which I am playing with is for a couple of years, so surely it is not meant to be the "lowest low for the past year"....
Any ideas on how to make this complete?..
Thanks everyone!...
- Greg