3rd Technical Analysis Training by Mohamed Elzayat

8/6/2019 3rd Technical Analysis Training by Mohamed Elzayat

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Relative strength curve

Entity x / Entity y

The curve is rising= entity x is outperforming y

The curve is declining= entity y isoutperforming x

Sectors analysis

262006

8 15 22 2 9 5 12February

1 9 2 6 5March

12 19 2 6 2April

9 16 2 3 30May

7 14 2 1 28 4June

11 18 2 5 2July

9 16 2 3 30 6August

13 2 0 2 7 3 10September

17 24 1 8October

1 5 22 2 9 5 1 2November

1 9 2 6 4 1 0 1 7December

24 3 1 72008

5000

10000

x10000

5000

10000

x10000

38003900

400041004200

43004400

450046004700

480049005000

38003900

400041004200

43004400

450046004700

480049005000

insurance sector

3500

4000

4500

5000

5500

6000

3500

4000

4500

5000

5500

6000

Dubai general index

0.80

0.85

0.90

0.95

1.00

1.05

1.10

0.80

0.85

0.90

0.95

1.00

1.05

1.10insurance sector compared with

dubai general index



262006

8 1 5 2 2 29 5 1 2February

1 9 2 6 5March

1 2 1 9 2 6 2April

9 1 6 23 3 0May

7 14 2 1 28 4June

1 1 1 8 2 5 2July

9 16 2 3 30 6August

1 3 20 2 7 3 1 0September

17 24 1 8October

1 5 22 2 9 5 1 2November

1 9 2 6 4 1 0 1 7December

2 4 3 1 72008

0000x100000 10000x100000

850090009500000005001000150020002500

300035004000

850090009500

100001050011000115001200012500

130001350014000

Real Estate & Construction Index

DFM.73 (13,890.17, 13,890.17, 13,890.17, 13,890.17, +137.280)

3500

4000

4500

5000

5500

6000

3500

4000

4500

5000

5500

6000

Dubai general index

2.15

2.20

2.25

2.30

2.35

2.40

2.45

2.50

2.15

2.20

2.25

2.30

2.35

2.40

2.45

2.50Real Estate & Construction Index

compared with Dubai general index

262006

8 15 22 2 9 5 12February

1 9 2 6 5March

1 2 1 9 2 6 2April

9 1 6 23 3 0May

7 14 2 1 28 4June

11 1 8 2 5 2July

9 16 2 3 30 6August

1 3 20 2 7 3 10September

17 24 1 8October

1 5 22 2 9 5 12November

1 9 2 6 4 1 0 1 7December

2 4 3 1 72008

20000x10000 20000x10000

4000

4500

5000

5500

6000

6500

7000

7500

8000

8500

9000

4000

4500

5000

5500

6000

6500

7000

7500

8000

8500

9000

Investment & Financial Services Index O

DFM.72 (8,370.51, 8,506.43, 8,347.55, 8,370.51, -135.920)

3500

4000

4500

5000

5500

6000

3500

4000

4500

5000

5500

6000

Dubai general index

O

1.10

1.15

1.20

1.25

1.30

1.35

1.40

1.45

1.50

1.10

1.15

1.20

1.25

1.30

1.35

1.40

1.45

1.50

Investment & Financial Services Index

compared with dubai general indexO



262006

8 1 5 22 2 9 5 1 2February

1 9 2 6 5March

1 2 1 9 2 6 2April

9 1 6 23 3 0May

7 14 2 1 28 4June

1 1 1 8 2 5 2July

9 16 2 3 30 6August

1 3 20 2 7 3 1 0September

17 24 1 8October

15 2 2 2 9 5 1 2November

1 9 2 6 4 1 0 1 7December

2 4 3 1 72008

750

800

850

900

950

1000

1050

1100

1150

1200

750

800

850

900

950

1000

1050

1100

1150

1200

Telecommunication Index

O

DFM.85 (1,187.70, 1,187.70, 1,187.70, 1,187.70, +42.0699)

3500

4000

4500

5000

5500

6000

3500

4000

4500

5000

5500

6000

Dubai general index

O

0.14

0.15

0.16

0.17

0.18

0.19

0.20

0.21

0.22

0.23

0.24

0.25

0.26

0.14

0.15

0.16

0.17

0.18

0.19

0.20

0.21

0.22

0.23

0.24

0.25

0.26

Telecommunication Index compared

with dubai general index

O

Two sectors comparison

262006

8 1 5 22 2 9 5 12February

1 9 2 6 5March

1 2 1 9 2 6 2April

9 16 2 3 30May

7 14 2 1 28 4June

1 1 1 8 2 5 2July

9 16 2 3 30 6August

13 2 0 2 7 3 10September

17 24 1 8October

1 5 22 2 9 5 1 2November

1 9 2 6 4 1 0 1 7December

2 4 3 1 72008

750

800

850

900

950

1000

1050

1100

1150

1200

750

800

850

900

950

1000

1050

1100

1150

1200

Telecommunication Index

O

DFM.85 (1,187.70, 1,187.70, 1,187.70, 1,187.70, +42.0699)

8500

9000

9500

10000

10500

11000

11500

12000

12500

1300013500

14000

8500

9000

9500

10000

10500

11000

11500

12000

12500

1300013500

14000

Real Estate & Construction Index

DFM.73 (13,890.17, 13,890.17, 13,890.17, 13,890.17, +137.280)

0.060

0.065

0.070

0.075

0.080

0.085

0.090

0.095

0.100

0.105

0.110

0.060

0.065

0.070

0.075

0.080

0.085

0.090

0.095

0.100

0.105

0.110

Telecommunication Index compared

with Real Estate & Construction Index



S ep te mb er Oc to be r N ove mb er De ce mb er 2 00 7 Fe br ua ry M arc h A pr il M ay Ju ne J ul y A ug us t S ep te mb er Oc to be r No ve mb er D ece mb er 2 00 8

5000

0000

x10000

5000

10000

x10000

4.5

5.0

5.5

6.0

6.5

7.0

7.5

4.5

5.0

5.5

6.0

6.5

7.0

7.5

O

Du Stock

DU (Emirates Integrated Telecommunications Co (7.38000, 7.56000, 7.31000, 7.44000, +0.10000)

3500

4000

4500

5000

5500

6000

3500

4000

4500

5000

5500

6000

O

Dubai general index

DFM General Index (6,069.14, 6,093.78, 5,989.93, 6,037.49, +9.33008)

0.001 0.001

O

DU stock compared with

Dubai general index

Relative Strength Comparative(DFM General Index) (0.0012323, +0.0000147)

27 3September

10 17 24 1October

8 16 2 2 29 5November

12 19 26 3December

10 17 24 312008

7

0.0185

0.0190

0.0195

0.0200

0.0205

0.0210

0.0215

0.0220

0.0225

0.0230

0.0235

0.0240

0.0245

0.0250

0.0255

SODIC versus CASE30

Relative Strength Comparative(CASE30) (0.0216337, -0.0004093)



Normalized relative strength

-Relative strength for ranking purposes.

To know by how much did the stock outperform or under perform the market.

The scale has the one in the middle.

(Entity x / base value of x) / Entity y/basevalue of y at the same date).

OCIC versus CASE30

n J ul Aug Sep O ct N ov D e c 2 0 05 Feb M ar Apr M ay J u n J ul Aug Sep O c t N ov D e c 20 06 M ar Apr Ma y J u n J ul Au g Sep O c t N ov D ec 2 0 07 Feb M a r Ap r M ay J un J ul Aug Sep O c t N ov D e c 2 0

5000

10000

15000

20000

25000

x100

50

100

150

200

250

300

350

400

450

500

550

600

ÇæÑÇÓßæã ááÇäÔÇÁ æÇáÕäÇÚÉ (564.980, 575.000, 563.500, 569.120, +9.62000)

-0.005

0.000

0.005

0.010

0.015

0.020

Normalized RS for ocic versus

case30

Relative Strength Comparative(CASE30) (0.021562, +0.000147)



Media versus case30

20032004 Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2005 Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2006 Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 Mar Apr May Jun Jul Aug Sep Oct Nov Dec 20

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

P

ÇáãÕÑíÉ áãÏíäÉ ÇáÇäÊÇÌ ÇáÇÚáÇãí (11.8500, 11.8900, 11.5400, 11.5500, -0.15000)

500100015002000250030003500400045005000550060006500700075008000850090009500

100001050011000

500100015002000250030003500400045005000550060006500700075008000850090009500

100001050011000

P

case30 rises 7.25 times since

june 2004

CASE30 (10,320.74, 10,476.64, 10,320.74, 10,469.78, +149.040)

-0.010

-0.005

0.000

-0.010

-0.005

0.000

P

Relative Strength Comparative(CASE30) (-0.010724, -0.000030)

Moving average

•5 day moving average=(Day1 price+Day2 price+day3price+day4 price+day5 price)/5.

•Smoothing trend•Simple crossover tactic ( buy when the price rises above

MA by two days or by a certain percentage(3-5%).

•Perform poorly during the trading range.



ne11 18 25 2

July9 16 24 30 6

August13 20 27 3

September 10 17 24 1 8

October 16 22 29 5

November 12 19 26 3

December 10 17 24 31

20087

10000

15000

2000025000

30000

x10000010000

15000

2000025000

30000

x100000

7300

7400

7500

7600

7700

7800

7900

8000

8100

8200

8300

8400

8500

8600

8700

8800

8900

9000

9100

9200

9300

9400

9500

9600

9700

9800

9900

10000

10100

10200

10300

10400

10500

10600

10700

7300

7400

7500

7600

7700

7800

7900

8000

8100

8200

8300

8400

8500

8600

8700

8800

8900

9000

9100

9200

9300

9400

9500

9600

9700

9800

9900

10000

10100

10200

10300

10400

10500

10600

10700

18 days SMA

Buy

Sell

Buy

4-9-2007

CASE30 (10,320.74, 10,476.64, 10,320.74, 10,469.78, +149.040), Moving Average (10,125.35)

19 26 5March

1 2 1 9 26 2April

1 0 16 2 3 30 7May

14 21 28 4June

11 18 25 2July

9 16 24 30 6August

13 2 0 2 7 3 10September

17 2 4 1 8October

16 22 29 5 12November

19 2 6 3 10December

17 31 72008

240

250

260

270

280

290

300

310

320

330

340

350

360

370

380

390

400

410

420

430

440

450

460

470

480

490

500

510

520

530

540

550

560

570

580

590

600

610

620

630

buy 8-3-2007

sell

buy

ÇæÑÇÓßæã ááÇäÔÇÁ æÇáÕäÇÚÉ (564.980, 575.000, 563.500, 569.120, +9.62000)



MA working poorly during trading range

25 2 9October

1 6 2 9 6 13November

2 0 27 4 1 1 18December

25 32007

1 5 2 2 2 9 5 1 2February

1 9 2 6 5March

1 2 1 9 2 6 2 1 0April

16 23 30 7May

1 4 2 1 2 8 4June

1 1 1 8 2 5 2July

9 1 6 24 3 0 6August

1 3 20 2 7 3 1 0 17September

2 4 1 8 1 6October


1 9 26 3 1 0 17December

2 4 3 1 72008

7.27.37.47.57.67.77.87.98.08.18.28.38.48.58.6

8.78.88.99.09.19.29.39.49.59.69.79.89.9

10.010.110.210.310.410.510.610.710.810.911.011.111.211.311.411.511.611.711.811.912.012.112.212.312.412.512.612.712.812.9

Moving average work poorly during trading range

Many whpsaws

ÇáÚÑÈíÉ áÍáíÌ ÇáÇÞØÇä (8.76000, 8.89000, 8.76000, 8.76000, -0.02000)

Momentum

•Measure rate of ascent or descent of price change

•Momentum= price today-price n days ago

•Zero crossover •Overbought and oversold by visual inspection



2 5 2 9October

1 6 2 9 6 1 3November

20 27 4 11 18December

25 32007

15 22 29 5 12February

19 26 5March

12 19 26 2 10April

16 23 30 7May

14 21 28 4June

11 18 25 2July

9 16 24 30 6August

13 20 27 3 10 17September

2 4 1 8 1 6October

22 29 5 12November

19 26 3 10 17December

24 31 72008

100

110

120

130

140

150

160

170

180

190

200

210

220

230

240

250

260P

ÇáÓÇÏÓ ãä ÇßÊæÈÑ ááÊäãíå æÇáÇÓÊËãÇÑ (228.990, 229.800, 226.240, 226.500, -1.00000)

-20

-15

-10

-5

0

5

10

15

20

P

mometum shows a weaknessbefore the price action

14 days momentum

2 5 2 9October

1 6 2 9 6 1 3November

2 0 27 4 1 1 18December

25 32007

1 5 2 2 2 9 5 1 2February

1 9 2 6 5March

1 2 1 9 2 6 2 1 0April

16 23 30 7May

1 4 2 1 2 8 4June

11 18 25 2July

9 1 6 24 3 0 6August

1 3 20 2 7 3 1 0 17September

2 4 1 8 1 6October


1 9 26 3 1 0 17December

2 4 3 1 72008

30

35

40

45

50

55

60

65

ÇáãÌãæÚå ÇáãÇáíå åíÑãÓ ÇáÞÇÈÖå (63.8700, 64.7800, 63.2100, 63.8700, +0.76000)

-25

-20

-15

-10

-5

0

5

10

15

20

25

14 days momentumoverbought by visual inspection

oversold by visual inspection



13r

20 2 7 4 11December

1 8 25 32007

15 22 29 5 12February

19 26 5March

12 19 26 2April

10 2June

9 16 24 30 6August

13 2 0 2 7 3 10September

17 24 1 8October

16 22 29 5 12November

19 26 3 10December

17 31 72008

10.5

11.0

11.5

12.0

12.5

13.0

13.5

14.0

14.5

15.0

15.5

16.0

16.5

17.0

17.5

18.0

18.5

19.0

19.5

20.0

Pprice followed momentum's

weakness by 14 days

P

ÇáÈäß ÇáæØäí ááÊäãíÉ (18.8000, 18.9500, 18.5100, 18.6000, -0.14000)

-35

-30

-25

-20

-15

-10

-5

0

5

10

15

20

25

30

35

40

momentum tells us a lot of information

oversold by visual inspection

P

P

J un e J ul y Au gu st Se pt em be r O ct ob er N ov em be r D ec em be r 2 00 7 F eb ru ar y M ar ch A pr il Ma y J un e J uly A ug us t Se pt em be r O ct ob er N ov em be r De ce mb er 2 00 8

4500

5000

5500

6000

6500

7000

7500

8000

8500

9000

9500

10000

10500

CASE30 (10,320.74, 10,476.64, 10,320.74, 10,469.78, +149.040)

-15

-10

-5

0

5

10

15

20

filtering system

Overbought and over sold area

by visual inspection



MACD

•Main line = 12 days exponential moving average – 26days exponential moving average .

•Signal line = 9 days exponential moving average of themain line.

A pr il M ay J un e J ul y A ug us t S ep te mb er Oc to be r N ov em be r D ec em be r 2 00 7 F eb ru ar y M ar ch A pr il M ay J un e J ul y A ug us t S ep te mb er O ct ob er N ov em be r D ec em be r 20 08

4500

5000

5500

6000

6500

7000

7500

8000

8500

9000

9500

10000

10500

P12-26 EMA

CASE30 (10,320.74, 10,476.64, 10,320.74, 10,469.78, +149.040)

-400

-350

-300

-250

-200

-150

-100

-50

0

50

100

150

200

250

P

downside zero crossover means

12 days EMA < 26 days EMA

MACD (221.487)



April May June July August September November 2006 February April May June July August September November 2007 February April May June July August September November 200

15

20

25

30

35

40

45

50

55

60

65

70

75

80

85

90

95

100

105

110

115

120

125ÇáÚÒ áÕäÇÚÉ ÍÏíÏ ÇáÊÓáíÍ (61.8300, 63.0000, 61.2000, 62.5200, +1.51000)

-8

-7

-6

-5

-4

-3

-2

-1

0

1

2

3

4

5

6

7

8

9

10

strong buy signal

extreme oversold

Sell

Sell

SellSell

BuyBuy

MACD (0.82376)

25 32006

8 15 22 2 9 5 12February

1 9 26 5March

1 2 1 9 2 6 2 1 0April

16 23 30 7May

1 4 2 1 2 8 4June

1 1 1 8 2 5 2July

9 1 6 24 30 6August

13 2 0 27 3 10September

17 2 4 1 8October

1 6 2 2 2 9 5 1 2November

1 9 26 3 10December

17 31 72008

1.05

1.10

1.15

1.20

1.25

1.30

1.35

1.40

1.45

1.50

1.55

1.60

1.65

1.70

1.75

1.80

1.85

1.90

O

Buy

ÇáÚÑÝÉ ááãäÓæÌÇÊ (1.75000, 1.80000, 1.74000, 1.80000, +0.04000)

-0.020

-0.015

-0.010

-0.005

0.000

0.005

0.010

0.015

0.020

0.025

0.030

0.035

0.040

0.045

0.050

0.055

0.060

Buy

Sell

O

Buy

Sell

zero line works as a support level overbought and over sold areasdetrmined by visual inspection

MACD (0.001774)



MACD Tactics

•Buy on the crossover between the main line and thesignal line to the upside and sell on reverse.

•Better buy or sell signals come from extreme overboughtor oversold areas.

ecember 2006 February March Apr il May June July August September October NovemberDecember2007 February March April May June July August SeptemberOctober NovemberDecember 200

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

O

price followed MACD trend line's violation

by almost 20 days

ÇáÚÒ ááÓíÑÇãíß æ ÇáÈæÑÓáíä - ÇáÌæåÑå (17.1100, 17.6000, 17.0000, 17.5000, +0.46000)

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

Better buy signal

Better sell signal

using trend lines for more confirmation

O

MACD (0.59882)



MACD histogram

•Vertical bars that show the difference between the twoMACD lines.

•It has a zero midline.

•Spot the widening and narrowing between the twoMACD line.

•Histogram bars starts to decline while it has been abovezero line = weakness and vice versa.

•It provides early warning. •It used mainly for spotting early exit signals from existingpositions.

J ul y A ug us t S ep te mb er O ct ob er No ve mb er D ec em be r 2 00 7 F eb ru ar y M ar ch A pr il M ay J un e J ul y A ug us t S ep te mb er O ct ob er N ov em be r D ec em be r 2 00 8

7

89

10

11

1213

14

15

16

1718ÇáÚÒ ááÓíÑÇãíß æ ÇáÈæÑÓáíä - ÇáÌæåÑå (17.1100, 17.6000, 17.0000, 17.5000, +0.46000)

-1.2-1.1-1.0-0.9-0.8-0.7-0.6-0.5-0.4-0.3-0.2-0.10.00.10.20.30.40.50.6

0.70.80.9

O

re cross over between the two MACD line

occures ofter many days

MACD (0.59882)

-0.20-0.15-0.10-0.050.000.050.100.150.200.250.300.350.400.450.500.550.60

two MACD lines are narrowingO

PS MACD Histogram (0.08063, 0.00000)



Using MACD with another oscillator

•Use the MACD to get a buy or sell signal whilestochastic oscillators for timing purpose.

•

13ber

2 0 27 4 1 1December

18 25 32007

1 5 2 2 2 9 5 1 2February

19 26 5March

12 19 26 2 10April

16 23 30 7May

14 21 28 4June

11 18 25 2July

9 1 6 24 30 6August

1 3 20 2 7 3 1 0 17September

2 4 1 8 1 6October



17 3 1 72008

8.08.59.09.5

10.010.511.011.512.012.513.0

13.514.014.515.015.516.016.517.017.518.0ÇáÚÒ ááÓíÑÇãíß æ ÇáÈæÑÓáíä - ÇáÌæåÑå (17.1100, 17.6000, 17.0000, 17.5000, +0.46000)

0

10

20

30

40

50

60

70

80

90

Actual entry timingO

O

O

P P Psell

buy

Stochastic Oscillator (90.1639)

-0.6-0.5-0.4

-0.3-0.2-0.10.00.10.20.30.40.50.60.7

O

O

Psell

buy

buy

MACD (0.59882)



13mber


18 25 32007

1 5 2 2 2 9 5 1 2February

1 9 2 6 5March

12 19 26 2 10April

16 23 30 7May

1 4 2 1 2 8 4June

11 18 25 2July

9 1 6 24 30 6August

1 3 20 2 7 3 1 0 17September

2 4 1 8 1 6October



17 31 72008

6000

6500

7000

7500

8000

8500

9000

9500

10000

10500

Buy

O

O

CASE30 (10,320.74, 10,476.64, 10,320.74, 10,469.78, +149.040)

0

10

20

30

40

50

60

70

80

90

100

O

OBuy

Buy

Stochastic Oscillator (68.3846)

-150

-100

-50

0

50

100

150

200

250

O

O

Buy

Buy

MACD (221.487)

Date post:	08-Apr-2018
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3rd Technical Analysis Training by Mohamed Elzayat

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