Lucky Trends

can we predict the market

J. Ignacio Ulacia F. (15.6.2002)

 

It is important to know what is the probability of a trend to be in the market before it changes direction. This question can be answered in 2 parts. The first is what is the probability of having a continuos trend without the market changing direction. The second would be to consider anchor points from the most significant turning points and determine the number of days that the trend is in effect.

To answer the first question, we have computed the number of days form the closing in which the market does not change direction. This for the main indexes DJIA, SP500, NASDAQ and RUT. The results are presented in Table 2.1 that contains the frequency of occurrence as a function of the number of days. It is important to say that a trend of 4 days contains a trend of 3 days and a trend of 2 days and a trend of 1 day. It would be interesting to find the true frequency trends of the trends eliminating this effect and it is found on the columns on the right. As can be observed the values are very similar and because the former is much easier to calculate we will use those in the future.

Days
SP500
NQ
DJIA
RUT

SP500
NQ
DJIA
RUT

Average
1
49.80%
43.33%
47.58%
41.80%
48.26%
43.48%
45.70%
41.84%
45.63%
2
25.77%
24.49%
25.83%
24.31%
25.05%
23.49%
26.03%
25.64%
25.10%
3
13.30%
14.31%
13.45%
13.59%
14.43%
14.91%
14.20%
14.34%
13.66%
4
6.11%
7.85%
6.70%
7.60%
6.57%
8.15%
7.00%
6.83%
7.06%
5
2.83%
4.32%
3.36%
4.74%
3.34%
4.57%
3.67%
4.23%
3.82%
6
1.17%
2.34%
1.62%
2.97%
1.40%
2.10%
1.85%
2.71%
2.03%
7
0.48%
1.43%
0.73%
1.84%
0.44%
1.40%
0.77%
1.64%
1.12%
8
0.26%
0.83%
0.37%
1.16%
0.26%
1.03%
0.39%
0.85%
0.65%
9
0.13%
0.38%
0.18%
0.80%
0.07%
0.19%
0.19%
0.73%
0.37%
10
0.09%
0.30%
0.10%
0.50%
0.07%
0.28%
0.09%
0.62%
0.25%
11
0.05%
0.18%
0.05%
0.24%
0.07%
0.23%
0.06%
0.23%
0.13%
12
0.02%
0.08%
0.03%
0.14%
0.04%
0.09%
0.04%
0.17%
0.07%
13
0.00%
0.04%
0.01%
0.07%
0.00%
0.05%
0.01%
0.06%
0.03%
14
0.00%
0.02%
0.00%
0.05%
0.00%
0.00%
0.00%
0.00%
0.02%
15
0.00%
0.02%
0.00%
0.05%
0.00%
0.05%
0.00%
0.11%
0.02%
Table 2.1.- Percentage of appearance of trends. First columns contains the results for total frequency assuming that a trend of 5 days contains trends of 4, 3, 2,and 1 days. The second results consider that a trend of 5 days is only a trend for those number of days. It can be seen that results are very similar and the fist results can be used. As a rule of thumb the initial probability id about half of the time. The market is more likely to reverse. then on following days the probability halves for every additional day.

 

The data is plotted in Graph 2.2 in a logarithmic scale and it can be observed that data fits the equation

 

log(f(%)) = -0.25612294 Days &endash; 0.17508491

 

It is important to notice that about half the time it is most probable to find a reversal, then

 

  1. Stocks to the upper side of the line will tend to have longer periods of continuation than the ones underneath that will be more choppy.
  2. This study could be used to determine the best stocks to trade for swing trading. because it would allow the user to qualify the best stocks with continuation.
  3. As a rule of thumb the probability of having another day that continues a trend is about half as the day before. Being the probability for day one about 50% for a change. During long trends there must be some places for the market to rest before continuing its course.

 

To answer the second question we need to establish certain criteria to decide which are anchor points. Therefore we define an anchor point like a point that changes a market direction. either an oversold or overbought market.

 

 

 

Copyright 2005© J. Ignacio Ulacia F., All rights reserved