Technical analysis Chart analysis

Double Top: A Reversal Pattern. Checking the History

Elena Berseneva 04 March 2022 337 4

In the proposed article, we will talk about paired patterns of graphical analysis “Double Top” and “Double Bottom”.


Jack Schwager characterises in his book «Technical Analysis. Full Course» these patterns the following way:

“Double tops and double bottoms are exactly what their names imply. Of course, the two tops (or bottoms) that make up the pattern need not be exactly the same, only in the same general price vicinity. Double tops and bottoms that materialize after large price moves should be viewed as strong indicators of a major trend reversal”.

Hypothesis
To conclusion

The formation of «Double top» and «Double bottom» indicates a trend reversal.

К выводам

Double top reminds the «М» letter on charts as it includes two consequent peaks of almost the same price level with a correction between them.

 

Double bottom reminds the «W» letter: 


Method of event measurement

 

We will use the ZigZag indicator in our study to measure tops and bottoms on charts with materialization of the considered patterns.

 

ZigZag is a trend indicator that is why it shows the lines on the chart connecting local minimums and maximums which delineate the trend’s direction. This indicator includes three parameters. It determines the performance of ZigZag and which minimums and maximums it will take into account. Changes in parameters influence the sensibility rate of the indicator to the price movement. If we increase the values for a calculation, the number of local minimums and maximums will decrease respectively the least number of lines will be displayed, and theoretically less patterns will be materialized but larger in size (price movements are also being enlarged).

 

For the research, we will take ZigZag with parameters of 5.3.3 (small patterns will be materialized), and with parameters of 12.5.3 (major patterns will be materialized). The second group of parameters is set in the ZigZag indicator by default.

“Double top”: a sell signal


ZigZag [0] < ZigZag [1]

ZigZag [0] < ZigZag [2]

ZigZag [2] < ZigZag [1]

ZigZag [3] > ZigZag [2]

Close [i] < ZigZag [2]

W <= WMAX

“Double bottom”: a buy signal


ZigZag [0] > ZigZag [1]

ZigZag [0] > ZigZag [2]

ZigZag [2] > ZigZag [1]

ZigZag [3] < ZigZag [2]

Close [i] > ZigZag [2]

W <= WMAX



Besides, we will carry out the test against patterns in two combinations regulating a notional parameter:

 

W, Distality of Tops/Bottoms.

 

Distality W in % must not raise the threshold value of WMax:

 

= ( Max( ZZ[1], ZZ[3] ) - Min( ZZ[1], ZZ[3] ) ) /

( Max ( Max ( ZZ[1], ZZ[3] ), ZZ[2] ) – Min ( Min ( ZZ[1], ZZ[3] ), ZZ[2] ) ) * 100

 

Let us show the “Double top” pattern with the W parameter indicated above:

What does the W notional parameter show?

 

The less W is, the closer the prices of tops and bottoms, and the more explicit the “Double top” formation.

 

For the “Double bottom”, the situation is mirrored.

 


Now, we specify conditions of the opening and closing of a trading position.

 


Opening a trading position:

After the pattern’s materialization, a position opens at the open of the next bar:

  • Double top: a sell;
  • Double bottom: a buy.

 

Closing a position:

The lifetime of the position is set at 5, 10 ,or 15 in all bars.

 

Let us carry out the test on a large amount of historical data of various financial instruments and on the basis of two timeframes against signals which are generated by the “Double top” and “Double bottom” patterns.

Data used

Let us specify the list of financial instruments and their timeframes against which we will carry out the test of trading signals:

  • 25 currency pairs (Forex);
  • 6 commodity futures (Commodities);
  • 2 US stock indices (US indices);
  • 30 US stocks (US stocks);
  • 58 RF stocks (RF stocks);
  • 1 RF stock index (RF index).


Timeframes used:

  • H1 (1 hour): the history for the period of 5 years,
  • D1 (1 day): the history for the period of 10 years.


The total is 1 981 114 values.

Having specified all the conditions and set necessary parameters, we can start testing!

 


Analysis of the results

 

First, we will estimate the results based on the sample size.

 


Small patterns (ZigZag (5.3.3)):

 

W <= 5%

 

For the 1-hour timeframe (H1):


Market segment
Number of candlesticks
Number of events
Forex
655777
1634
Commodities
115959
224
US indices
52783
107
RF index
11421
26
US stocks
234556
591
RF stocks
612555
1582
Total
1683051
4164



For the 1-day timeframe (D1):


Market segment
Number of candlesticks
Number of events
Forex
67432
199
Commodities
15463
41
US indices
5455
15
RF index
2519
6
US stocks
72925
209
RF stocks
134269
355
Total
298063
825



W <= 10%

 

For the 1-hour timeframe (H1):


Market segment
Number of candlesticks
Number of events
Forex
655777
3467
Commodities
115959
455
US indices
52783
219
RF index
11421
53
US stocks
234556
1243
RF stocks
612555
3045
Total
1683051
8482



For the 1-day timeframe (D1):


Market segment
Number of candlesticks
Number of events
Forex
67432
403
Commodities
15463
98
US indices
5455
33
RF index
2519
10
US stocks
72925
442
RF stocks
134269
792
Total
298063
1778



Major patterns (ZigZag (12.5.3)):


W <= 5%

 

For the 1-hour timeframe (H1):


Market segment
Number of candlesticks
Number of events
Forex
655777
826
Commodities
115959
115
US indices
52783
68
RF index
11421
11
US stocks
234556
324
RF stocks
612555
704
Total
1683051
2048



For the 1-day timeframe (D1):


Market segment
Number of candlesticks
Number of events
Forex
67432
94
Commodities
15463
22
US indices
5455
9
RF index
2519
5
US stocks
72925
88
RF stocks
134269
133
Total
298063
351



W <=10%

 

For the 1-hour timeframe (H1):


Market segment
Number of candlesticks
Number of events
Forex
655777
1691
Commodities
115959
260
US indices
52783
148
RF index
11421
19
US stocks
234556
675
RF stocks
612555
1419
Total
1683051
4212



For the 1-day timeframe (D1):


Market segment
Number of candlesticks
Number of events
Forex
67432
183
Commodities
15463
41
US indices
5455
19
RF index
2519
5
US stocks
72925
190
RF stocks
134269
315
Total
298063
753



The total number of candlesticks and events:


Event
Number of candlesticks
Number of events
Small patterns
W <= 5%
1981114
4989
W <= 10%
1981114
10260
Major patterns
W <= 5%
1981114
2399
W <= 10%
1981114
4965



Then, we will measure the share of Tops and Bottoms in % in the total number of initial candlesticks on the basis of timeframes:

 

Small patterns (ZigZag (5.3.3)):

 

For the 1-hour timeframe (H1):


Parameters of Tops/Bottoms
Forex
Commodities
US indices
RF index
US stocks
RF stocks
W <= 5 %
0.25
0.19
0.20
0.23
0.26
0.26
W <= 10 %
0.53
0.39
0.41
0.46
0.53
0.50



For the 1-day timeframe (D1):


Parameters of Tops/Bottoms
Forex
Commodities
US indices
RF index
US stocks
RF stocks
W <= 5 %
0.30
0.27
0.27
0.24
0.29
0.26
W <= 10 %
0.60
0.63
0.60
0.40
0.61
0.59



Major patterns (ZigZag (12.5.3)):

 

For the 1-hour timeframe (H1):


Parameters of Tops/Bottoms
Forex
Commodities
US indices
RF index
US stocks
RF stocks
W <= 5 %
0.13
0.10
0.13
0.10
0.14
0.11
W <= 10 %
0.26
0.22
0.28
0.17
0.29
0.23



For the 1-day timeframe (D1):


Parameters of Tops/Bottoms
Forex
Commodities
US indices
RF index
US stocks
RF stocks
W <= 5 %
0.14
0.14
0.16
0.20
0.12
0.10
W <= 10 %
0.27
0.27
0.35
0.20
0.26
0.23


Let us note that the more explicit the patterns are and the larger the figures, the less their share in the total number of candlesticks and the less likely they can appear on charts. 

 


Now, we will view the results of the performance of trading signals obtained as a result of materialized Tops and Bottoms.

 

We will assess the results with the two following criteria:

  • Momentum (m) reflects the average change in quotes of financial instruments at the moment of closing a position, in %. A positive value of the momentum indicates profitability of the signal performance, a negative value indicates loss-making.
  • SPP, the share of profitable positions, %.

 

We take the following notations:

«H1 / 5», closing a position at the 5th candlestick over the 1-hour timeframe;

«H1 / 10», closing a position at the 10th candlestick over the 1-hour timeframe;

«H1 / 15», closing a position at the 15th candlestick over the 1-hour timeframe;

«D1 / 5», closing a position at the 15th candlestick over the 1-day timeframe;

«D1 / 10», closing a position at the 10th candlestick over the 1-day timeframe;

«D1 / 15», closing a position at the 15th candlestick over the 1-day timeframe;

W, distality of Tops/ Bottoms, %;

 

Volatility coefficient:

  • For the daily timeframe: a ratio between the average volatility of 5 candlesticks after the opening of a position and the average volatility of 20 candlesticks preceding the opening a position.
  • For the 1-hour timeframe: a ratio between the average volatility of 5 candlesticks after the opening of a position and the average volatility of the same hours during the following 4 days.


If the value of volatility coefficient is more than 1, it indicates a greater volatility after the signal in comparison with volatility before the signal, if the value is less than 1, it is the opposite. 

 


Small patterns (ZigZag (5.3.3)):

 

The Number of Tops/Bottoms, the Momentum in %, and the Share of profitable positions, and Volatility coefficient on a term-to-term basis of the hold of positions, timeframes, and market segments with distality of Tops/Bottoms at most 5%


W<=5%
Indicator
Forex
Commodities
US indices
RF index
US stocks
RF stocks
All
Н1/5
Number of signals
1634
224
107
26
591
1582
4164
Momentum
0.011
-0.042
0.007
0.159
0.073
-0.028
0.006
SPP
50.7
53.0
50.5
53.9
50.3
42.9
47.0
Volatility coefficient
1.00
0.98
1.04
0.94
1.05
1.17
1.09
Н1/10
Number of signals
1634
223
107
26
591
1580
4161
Momentum
0.000
0.033
0.008
0.313
0.007
0.012
0.012
SPP
50.3
57.2
52.3
65.4
48.3
44.6
47.6
Volatility coefficient
1.00
0.98
1.04
0.94
1.05
1.17
1.09
Н1/15
Number of signals
1632
223
107
26
591
1578
4157
Momentum
-0.001
0.089
0.031
0.365
-0.059
-0.047
-0.029
SPP
50.0
60.8
51.4
61.5
47.1
45.5
47.8
Volatility coefficient
1.00
0.98
1.04
0.94
1.05
1.17
1.09


W<=5%
Indicator
Forex
Commodities
US indices
RF index
US stocks
RF stocks
All
D1/5
Number of signals
199
41
15
6
209
355
825
Momentum
-0.003
-0.039
0.472
-0.810
-0.095
0.632
0.276
SPP
47.1
38.4
55.0
33.3
49.3
46.0
46.7
Volatility coefficient
1.03
1.06
1.30
0.74
1.08
1.24
1.14
D1/10
Number of signals
199
41
15
6
208
355
824
Momentum
0.024
0.604
0.265
0.528
-0.184
0.877
0.415
SPP
50.4
56.0
60.0
33.3
47.9
51.7
50.7
Volatility coefficient
1.03
1.06
1.30
0.74
1.08
1.24
1.14
D1/15
Number of signals
197
41
15
6
208
354
821
Momentum
0.145
0.602
0.221
0.116
-1.025
0.710
0.149
SPP
52.1
51.5
50.0
50.0
44.9
49.9
49.2
Volatility coefficient
1.03
1.06
1.30
0.74
1.08
1.24
1.14



The Number of Tops/Bottoms, the Momentum in %, and the Share of profitable positions, and Volatility coefficient on a term-to-term basis of the hold of positions, timeframes, and market segments with distality of Tops/Bottoms at most 10%


W<=10%
Indicator
Forex
Commodities
US indices
RF index
US stocks
RF stocks
All
Н1/5
Number of signals
3467
455
219
53
1243
3045
8482
Momentum
0.007
0.072
-0.045
0.197
0.050
-0.032
0.003
SPP
49.9
53.1
45.2
60.4
50.3
44.9
47.8
Volatility coefficient
1.01
0.99
1.05
1.00
1.07
1.17
1.10
Н1/10
Number of signals
3467
454
219
53
1243
3042
8478
Momentum
-0.006
0.126
-0.049
0.462
-0.020
0.022
0.013
SPP
49.7
55.5
47.5
66.0
48.6
45.1
47.6
Volatility coefficient
1.01
0.99
1.05
1.00
1.07
1.17
1.10
Н1/15
Number of signals
3464
454
219
53
1242
3040
8472
Momentum
-0.007
0.237
-0.003
0.442
-0.128
-0,047
-0.040
SPP
50.4
57.5
47.0
64.2
47.1
45.6
47.7
Volatility coefficient
1.01
0.99
1.05
1.00
1.07
1.17
1.10


W<=10%
Indicator
Forex
Commodities
US indices
RF index
US stocks
RF stocks
All
D1/5
Number of signals
403
98
33
10
442
792
1778
Momentum
0.050
-0.133
0.656
-0.137
-0.061
0.354
0.167
SPP
48.3
45.0
54.9
40.0
48.6
48.1
48.2
Volatility coefficient
1.06
1.01
1.20
0.93
1.07
1.24
1.14
D1/10
Number of signals
402
98
33
10
441
791
1775
Momentum
0.089
0.406
0.795
1.916
-0.304
0.191
0.083
SPP
53.8
53.8
55.8
60.0
45.7
47.6
48.9
Volatility coefficient
1.06
1.01
1.20
0.93
1.07
1.24
1.14
D1/15
Number of signals
400
98
33
10
441
788
1770
Momentum
0.185
0.528
1.009
1.201
-0.580
0.072
-0.018
SPP
52.6
50.6
61.1
60.0
46.8
47.5
48.8
Volatility coefficient
1.06
1.01
1.20
0.93
1.07
1.23
1.14



Major patterns (ZigZag (12.5.3)):

 

The Number of Tops/Bottoms, the Momentum in %, and the Share of profitable positions, and Volatility coefficient on a term-to-term basis of the hold of positions, timeframes, and market segments with distality of Tops/Bottoms at most 5%


W<=5%
Indicator
Forex
Commodities
US indices
RF index
US stocks
RF stocks
All
Н1/5
Number of signals
826
115
68
11
324
704
2048
Momentum
0.012
0.012
-0.007
-0.149
0.001
-0.048
-0.021
SPP
48.7
62.2
53.0
36.4
48.3
45.0
47.5
Volatility coefficient
1.07
0.98
0.99
1.15
1.15
1.43
1.26
Н1/10
Number of signals
826
115
68
11
324
703
2047
Momentum
0.013
-0.090
0.044
-0.152
-0.017
0.100
0.041
SPP
47.9
64.2
51.3
36.4
48.9
46.7
48.3
Volatility coefficient
1.07
0.98
0.99
1.15
1.15
1.43
1.26
Н1/15
Number of signals
825
115
68
11
324
703
2046
Momentum
0.002
-0.205
0.088
-0.121
0.025
0.140
0.064
SPP
50.0
59.6
56.3
54.6
50.0
47.9
49.6
Volatility coefficient
1.07
0.98
0.99
1.15
1.15
1.43
1.26


W<=5%
Indicator
Forex
Commodities
US indices
RF index
US stocks
RF stocks
All
D1/5
Number of signals
94
22
9
5
88
133
351
Momentum
0.281
0.313
-0.939
-0.020
-0.405
0.978
0.396
SPP
58.1
55.8
33.3
60.0
40.9
52.9
50.9
Volatility coefficient
1.12
1.10
1.11
0.84
1.07
1.27
1.17
D1/10
Number of signals
93
22
9
5
88
133
350
Momentum
0.518
0.163
-0.375
0.319
0.168
0.864
0.546
SPP
64.5
63.3
50.0
60.0
45.7
53.7
54.6
Volatility coefficient
1.12
1.10
1.11
0.84
1.07
1.27
1.17
D1/15
Number of signals
93
22
9
5
88
132
349
Momentum
0.532
-0.774
-0.482
0.145
-0.412
0.604
0.233
SPP
58.9
37.8
58.3
60.0
47.7
57.5
54.3
Volatility coefficient
1.12
1.10
1.11
0.84
1.07
1.26
1.17



The Number of Tops/Bottoms, the Momentum in %, and the Share of profitable positions, and Volatility coefficient on a term-to-term basis of the hold of positions, timeframes, and market segments with distality of Tops/Bottoms at most 10%


W<=10%
Indicator
Forex
Commodities
US indices
RF index
US stocks
RF stocks
All
Н1/5
Number of signals
1691
260
148
19
675
1419
4212
Momentum
0.022
0.097
-0.015
0.324
0.005
0.006
0.016
SPP
51.2
55.2
46.6
52.6
50.6
44.1
47.8
Volatility coefficient
1.08
1.01
0.99
1.40
1.16
1.41
1.25
Н1/10
Number of signals
1691
260
148
19
675
1418
4211
Momentum
0.017
0.108
-0.016
0.156
-0.013
0.075
0.043
SPP
51.1
58.4
47.9
42.1
46.7
44.9
47.3
Volatility coefficient
1.08
1.01
0.99
1.40
1.16
1.41
1.25
Н1/15
Number of signals
1689
260
148
19
675
1418
4209
Momentum
0.014
0.083
0.010
-0.368
-0.036
0.127
0.056
SPP
51.3
55.5
48.2
52.6
47.6
44.8
47.5
Volatility coefficient
1.08
1.01
0.99
1.40
1.16
1.41
1.25


W<=10%
Indicator
Forex
Commodities
US indices
RF index
US stocks
RF stocks
All
D1/5
Number of signals
Commodities
41
19
5
190
315
753
Momentum
US indices
0.537
-0.153
-0.020
-0.413
0.205
0.056
SPP
RF index
55.8
46.7
60.0
45.2
50.0
50.4
Volatility coefficient
US stocks
1.09
1.20
0.84
1.07
1.32
1.20
D1/10
Number of signals
RF stocks
40
19
5
190
315
751
Momentum
0.357
0.368
0.452
0.319
-0.144
0.363
0.239
SPP
60.6
57.5
52.2
60.0
44.8
49.5
51.1
Volatility coefficient
1.10
1.08
1.20
0.84
1.07
1.32
1.20
D1/15
Number of signals
182
40
19
5
190
313
749
Momentum
0.417
-0.496
0.226
0.145
-0.119
0.428
0.240
SPP
57.1
44.6
58.3
60.0
51.3
52.7
53.0
Volatility coefficient
1.10
1.08
1.20
0.84
1.07
1.31
1.20



Let us summarize the obtained results using the following diagrams:


Small patterns (ZigZag (5.3.3)):

Major patterns (ZigZag (12.5.3)):

Conclusion

Momentums


The highest momentum is both for small (0.415%) and for major (0.546%) patterns shown by signals of Tops and Bottoms over the daily timeframe with the distance of Tops/Bottoms no more than 5% and with fixating a position at the 10th candlestick.


Momentums of well-pronounced patterns of “Double top” and “Double bottom” raise minimum significant values by 0.3% with the module for the daily timeframe.


The minimum value of the momentum of 0.15% with the module has not been reached over the hourly timeframe.



SPP


The share of profitable positions of signals of the 1-hour timeframe vary between 47.0% and 49.6%, signals of the daily timeframe vary between 46.7% and 54.6%.



Volatility


The volatility raises by 5% after the signal in comparison with volatility before the signal for all timeframes and parameters of patterns.



The use of patterns of “Double top” and “Double bottom” in the market forecasting over the daily timeframe has been identified.

Detailed results are shown in the Appendix:

XLSX (0.11 MB)Application to the article 'Double top and double base a reversal formation. Check the history'.xlsx

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