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การพยากรณ์ดัชนีผลตอบแทนรวม SET50
นายวะชิระพงษ์ พงศ์กิจวิทูร
.. 2557
SET50 Total Return Index Forecasting
Mr. Wachirapong Pongkitwitoon
A Thesis Submitted in Partial Fulfillment of the Requirements for
the Degree of Master of Business Administration
School of Management Science
Sukhothai Thammathirat Open University
2014
SET50
2563003645
(1) (2)
2557
1) SET50 (SET50 TRI)
3 MA3), 5 MA5) 30 MA30) 2)
SET50 (SET50 TRI)
GM(1,1) 3) MA3,MA5,MA30 GM(1,1)
SET50 TRI
2 2545 23 2558
3 5 30 – 1 3 5 10 15
30 MA3,MA5, MA30 GM(1,1)
Mean Square Error: MSE)
1) 3 5 30
1
2)
GM(1,1) 3
3)
MSE) GM(1,1) MSE
GM(1,1) 1 3 5 10 MSE MA
15 30 MSE MA MSE GM(1,1)
GM(1,1) 10
10 GM(1,1)
Thesis title: SET50 Total Return Index Forecasting
Researcher: Mr.Wachirapong Pongkitwitoon; ID: 2563003645;
Degree: Master of Business Administration; Thesis advisors: (1) Achara Cheewatragoongit,
Associate Professor; (2) Dr.Apinya Wanaset, Assistant Professor; Academic year: 2014
Abstract
The objectives of this research are: (1) to study and forecast total return index of
SET50 (SET50 TRI) by using moving average 3-period (MA3) 5-period (MA5) and 30-period
(MA30); (2) to study and forecast SET50 TRI by using Grey Model GM(1,1); and (3) to compare
the efficiency of the models.
The methods of this research using SET50 TRI data from 2 January 2545 to 23 January
2558 chose period 3, 5 and 30 to forecast next 1 day, 3 days, 5 days, 10 days, 15 days, 30 days by
MA3, MA5, MA30, GM(1,1) and compared by mean square error (MSE).
The results reveal that: (1) MA can forecast the SET50 TRI only next one day, must
using more data to forecast in long term, and can show the trend when using more data but decrease
accuracy, while; (2) GM(1,1) uses only three recent data to forecast the SET50 TRI in long term,
and can show the good trend when using more data and increase accuracy; and (3) compared by
mean square error (MSE), the MSE of GM(1,1) to forecast next 1 day, 3 days, 5 days, 10 days are
less than MSE of MA, and 15 days 30 days the MSE of MA are less than MSE of GM(1,1), in
other words, forecasting in 10 days the Grey Model GM(1,1) has better accuracy than moving
average and next 10 days MA has better than GM(1,1).
Keywords: Moving Average (MA), Grey Model GM(1,1), Mean Square Error (MSE), Total
Return Index (TRI)
กิตติกรรมประกาศ
2558
สารบัญ
1 1
1
3
4
4
5
6
2 7
8
12
13
18
22
23
3 29
29
29
30
31
สารบัญ (ต่อ)
4 33
GM(1,1) MA3 3 34
GM(1,1) MA5 5 40
GM(1,1) MA30 30 46
5 54
54
57
58
60
64
(Total Return Index Calculation Methodology) 65
72
78
สารบัญตาราง
4.1 SET50 TRI 23 2556
5 2556 3
GM(1,1) MA3 34
4.2 MSE GM(1,1) MA3 1, 3, 5, 10,
15, 30 35
4.3 SET50 TRI 23 2555
92556 3
GM(1,1) MA3 37
4.4 GM(1,1) MA3
MSE 38
4.5 SET50 TRI 28 2551
9 2551 5
GM(1,1) MA5 40
4.6 GM(1,1) MA5
MSE 41
4.7 SET50 TRI 30 2555
12 2555 5
GM(1,1) MA5 43
4.8 GM(1,1) MA5
MSE 44
4.9 SET50 TRI 3 2551
15 2551 30
GM(1,1) MA30 46
4.10 GM(1,1) MA30
MSE 48
สารบัญตาราง (ต่อ)
411 SET50 TRI 13 2557
28 255730
GM(1,1) MA30 51
4.12 GM(1,1) MA30
MSE 52
5.1 GM(1,1) MA3 MA5 MA30
MSE 55
5.2 56
สารบัญภาพ
1.1 SET50 (SET50 TRI)
2
1.2 4
2.1 16
2.2 18
4.1 SET50 TRI 23 2556
5 2556 3
GM(1,1) MA3 35
4.2 SET50 TRI 23 2555
9 2555 3
GM(1,1) MA3 38
4.3 SET50 TRI 28 2551
9 2551 5
GM(1,1) MA5 41
4.4 SET50 TRI 30 2555
12 2555 5
GM(1,1) MA5 44
4.5 SET50 TRI 3 2551
15 2551 30
GM(1,1) MA30 48
4.6 SET50 TRI 13 2557
28 2557 30
GM(1,1) MA30 52
1
1.
-
2
SETSETTRI)
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000
10,000
TRI
SET50 Total Return Index
1 SETSETTRI)
SETSETTRI)
22545102557
SETSETTRI) -
3
-
Trend
SET
SETTRI)SETSETTRI)
Moving Average)
Grey Model)
2
Mean Square Error; MSE)
-
2.
2.1 SET50SETTRI)
3MA3), 5 MA5) 30 MA30)
2.2 SET50SETTRI)
GM(1,1)
2.3 MA3,MA5,MA30
GM(1,1)
4
3.
4.
SET50
SETSETTRI)
SETSETTRI)
SET50 TRI
MA3
MA5
MA30
GM (1,1)
5
SETSETTRI)
6
2
1GM(1,1
3MA3), 5 MA5) 30 MA30)
2MSE
5.
Securities Exchange of Thailand
The Stock Exchange of Thailand (SET)
SET50SET50 TRI)
SET50
Capital gain/Capital loss)
Rights) Dividends) (
2554: 2)
6
6.
6.1
6.2
2
SETSETTRI)
SETSETTRI)
SETSETTRI)
1.
2.
3.
4.
5.
6.
1.
1.1
1
(2504 - 2509)
2505
Bangkok Stock Exchange)
2511160 2512114
462515
8726
8
2 (2510 - 2514)
2512
2515
58
2517 2517
2518
30 2518
The Securities Exchange of Thailand)
The Stock
Exchange of Thailand (SET) 1 2534
2538
2
SET50 Index Underlying Index)
Index Future Index Options
(2558)
9
1.2 SET Index
Performance Benchmark)Underlying Index)
SET
Index) Composite Index)
(2554: 1)
SET Index (2554: 3)
Current Market Value (CMV)
Base Market Value (BMV)
Base Value
1.3 SET 100 Index
SET 100 Index
100
Underlying Index)
10
SET 100 Index
SET 100 Index 6
SET 100 Index
SET 100 Index
Current Market Value 10
Base Market Value 10
1,000 SET 100 Index
, ( SET 100 Index)
1.4 SET 50 Index
SET 50 Index
50
Underlying Index)
SETIndex
SETIndex
SETIndex
11
6
1.4.1
-
1.4.2
–
SET 50 Index
Current Market Value
Base Market Value
1,000 SET 50 Index
, ( SET 50 Index)
2.
Total Return Index: TRI)
SET TRI) SET50
(SET50 TRI) SET100 (SET100 TRI) SETHD
(SETHD TRI) MAI TRI)
Industry TRI) Sector TRI)
12
12
(2554: 2)
Daily Total Return Index)
Capital Gain/Loss) Dividends)
Reinvest)(
2554: 2)
(t)
(t-1)
(t)
(t)
13
3.
3.1
2552: 2
( 2544: 7)
2549: 1)
3.2
3 2549: 1)
3.2.1 Consumer Investment)
3.2.2 Business Investment)
3.2.3 Financial or Securities Investment)
BondStock
14
3.3
( 2544: 154)
( 2544: 155)
1. Yield
2. Capital Gain (Loss)
Price
Change
Yield 0 +
Price change 0 + –
(
2544: 155)
12549: 285
15
( 2544: 156)
3.4
( 2544: 198)
( 2544: 185) 1)
2)
Systematic Risk)
1)
2) Interest Rates Risk)
16
3) Purchasing
Power Risk or Inflation Risk)
Unsystematic Risk)
1)
Business Risk)
2)
Financial Risk)
2549: 269
3.5
2552: 18
2.1
17
2.1
4.
4.1
2549: 1)
1. Secular TrendT
2. Seasonal Variation
3. Cyclical Variation
4. (Irregular Variation)
18
4.2
2
1 Qualitative Forecasting Methods)
2 Quantitative Forecasting Methods)
2545: 14
2.2
2 1)
Time Series) 2) Casual or Explanatory)
Time Series) Moving Average)
Casual or Explanatory
Time Series
19
4.2.1 Moving Average)
Noise
(Vicente 2014: 1277-1281)
- (1)
;
3
- (2)
5
- (3)
30
- (4)
4.2.2
Sifeng & Yi
2006: 3
20
Grey System Theory) 1982Deng
Julong
The Application of Grey
System in Futures Price Forecasting XingYu2012), Application of Grey-Markov Model in
Forecasting Fire Accidents MAO Zhan-li (2011), Grey system theory-based models in time
series prediction Erdal Kayacan (2010)Applying the grey prediction model to the global
integrated circuit industry Li-Ching Hsu (2001), Applying the grey prediction model to
regional logistics demand scale Wei Xu (2008)
Grey Model)
GM(
+
Erdal 2010: 1784-1789
GM(1,1)
ขั้นตอนที่ 1
(5)
- (5)
ขั้นตอนที่ 2
(6) (7)
- (6)
- (7)
;
ขั้นตอนที่ 3 (6)
(8) (9)
- (8)
- (9)
21
(10)
(11)
- (10)
- (11)
ขั้นตอนที่ 4 (12)(13)
- (12)
- (13)
, ,
- (14)
5.
Mean Squared Error:MSE
Mean Squared Error:MSE
- (15)
;
22
โดยที่
Mean Squared Error:MSE
MSE
MSE
MSE
6.
Xuemei Shen, Zhengnan Lu (2014) The Application of Grey
Theory Model in the Predication of Jiangsu Province’s Electric Power Demand
GM(1,1)
1997-2012
GM(1,1) 2005-2012
Relative Error
2013-2015
XingYu, Yi Le, Meijuan Yang, & Zhenyan Li2012) The
Application of Grey System in Futures Price Forecasting
GM(1,1)
23
GM(1,1)
Relative Error
2
3a, b33
5 211
6 35115
3
2
MAO Zhan-li, SUN Jin-hua (2011) Application of Grey-
Markov Model in Forecasting Fire Accidents
2005-2009
GM(1,1)
- (Grey-Markov Model)
GM(1,1)-
(Grey-Markov Model)Relative Error
-
(Grey-Markov Model)
GM(1,1)
2005-2009
GM(1,1)
- (Grey-Markov Model)
LIU Lijun, ZHANG Rufei (2011) The Prediction of Energy
Consumption Based on GM(1,1) Model in Hebei Province
GM (1,1)
“HEBEI ECONOMIC YEAR BOOK”
1990-2009GM(1,1)
24
GM (1,1)
SET
-
-
SET
,
-
-
-
-
SET Index) SET
Index) SET Index)
25
MAE)
MSE) MAPE)
MAE) MSE)
MAPE)
,
-
26
(2549)
3 5 7
2
3
49
(MA)(WMA)Relative Strength Index (RSI) , Fast Stochastic,
Slow Stochastic Moving Average Convergence / Divergence (MACD)
2
1254031 2545 5
2 12546 152549 345
(MA)(WMA)
(2547)
Moving AverageOn Balance Volume
Relative Strength IndexSlow Stochastics
Momentum
3On Balance Volume
27
Moving AverageMomentum3
Moving AverageOn balance volumeMomentum
3On balance volumeMoving AverageMomentum
Moving Average
Time Series)
GM(1,1)
SET50
SETSETTRI)GM(1,1)
MA3, MA5 MA30
MSE
3
SET50 (SET50 TRI)
SET50 (SET50 TRI)
SET50 (SET50 TRI)
1.
SET50
(SET50 TRI)
22545 282558
2.
2.1 Moving Average) 3 (MA3), 5 (MA5)
30 (MA30)
2.2 Grey Model) 1 GM(1,1)
2.3 วิธีวัดค่าความผิดพลาดของการพยากรณ์
(MSE)
3.
SET50(SET50 TRI)
SET50(SET50 TRI)2254528
2558
29
3.1
SET(SET TRI)
SET(SET TRI)
3
15
301
3.1.1 ช่วงขาลง SET TRI GM(
MA
3.1.2 ช่วงขาขึ้น SET TRI GM(
MA
3.1.3 ช่วงขาลง SET TRI GM(
MA
3.1.4 ช่วงขาขึ้น SET TRI GM(
MA
3.1.5 ช่วงขาลง SET TRI GM(
MA
3.1.6 ช่วงขาขึ้น SET TRI GM(
MA
30
4.
MA3, MA5, MA30 GM(1,1)35 30
3
5
30
3
31
MSE
Mean Squared Error: MSE
;
MSE
MSE
MSE
MSE
4
SET50 (SET50
TRI)
1. MA3 GM(1,1) 2
1.1
SET TRI GM(MA
1.2
SET TRI GM(MA
2.5 MA5 GM(1,1) 2
2.1
SET TRI GM(MA
2.2
SET TRI GM(MA
33
3.0 MA30 GM(1,1) 2
3.1
SET TRI GM(MA
3.2
SET TRI GM(MA
GM(,MA
1.
SET TRI GM(MA
34
1 SET50 TRI 23 2556 5
2556 3 GM(1,1)
MA3
SET50TRI
GM
e = x-p
e2
MA3
e = x-p
e2
1
20-
2
21-
3
22-
23-
-
5
27-
-
-
6
28-
7
29-
-
68
8
30-
-
9
31-
-
10
03-
-
11
-
-
12
05-
-
13
06-
-
07-
-
15
10-
16
11-
-
17
12-
-
18
13-
-
-
19
-
20
17-
21
18-
-
22
19-
771
-
23
20-
-
21-
-
25
-
-
26
25-
69
27
26-
28
27-
29
28-
38220
35
1
SET50TRI
GM
e = x-p
e2
MA3
e = x-p
e2
30
02-
31
03-
-
32
-
78
-
33
05-
-
2 MSE GM(1,1) MA3 , , , , ,
1
3
5
10
15
30
MSE GM
MSE MA3
SET50 TRI 23 2556 5
2556 3 GM(1,1) MA3
36
1 SET50 TRI 23
2556 6 2556 3 20 21 22 2556
GM(1,1) MA3
GM(1,1) SET50
TRI MA3
MSE 2 MSE
1 MSE GM(1,1) MSE MA3
36, GM(1,1) 3
2 MSE GM(1,1) MSE MA3
MSE 2
MSE GM(1,1) MSE MA3
MSE MA3 MSE
GM(1,1) 1 GM(1,1)
3
MA3 MA3
3
MSE GM(1,1) MSE MA3
MSE MA3 MSE
GM(1,1)
2.
SET TRI GM(MA
37
3 SET50 TRI 23 2555 9
2556 3 GM(1,1) MA3
SET50TRI
GM
-p
e2
MA3
-p
e2
1
20-Nov-12
2
21-Nov-12
-
3
22-Nov-12
-
23-Nov-12
-
8
5
26-Nov-12
6
27-Nov-12
7
28-Nov-12
8
29-Nov-12
70
9
30-Nov-12
10
03-Dec-12
11
-Dec-12
12
06-Dec-12
18
13
07-Dec-12
11-Dec-12
15
12-Dec-12
16
13-Dec-12
7037
17
-Dec-12
18
17-Dec-12
19
18-Dec-12
20
19-Dec-12
21
20-Dec-12
22
21-Dec-12
-
23
-Dec-12
-
25-Dec-12
25
26-Dec-12
26
27-Dec-12
27
28-Dec-12
0
28
02-Jan-13
29
03-Jan-13
30
-Jan-13
31
07-Jan-13
1
32
08-Jan-13
33
09-Jan-13
38
GM(1,1) MA3
MSE
1
3
5
10
15
30
MSE GM
MSE MA3
1
SET50 TRI 23 2555 9
2555 3 GM(1,1) MA3
39
2 SET50 TRI 23
2555 9 2556 3 20 21 22 2555
GM(1,1) MA3
GM(1,1) SET50
TRI MA3
MSE MSE
1 MSE GM(1,1) MSE MA3
GM(1,1) 3
MSE GM(1,1) MSE MA3
5 MSE GM(1,1) 522 MSE MA3
10 MSE GM(1,1)
MSE MA3
MSE GM(1,1) MSE MA3
MSE MA3 MSE GM(1,1)
2 GM(1,1) 3
MA3
MA3
3
MSE GM(1,1) MSE MA3
MSE MA3 MSE
GM(1,1)
GM(,MA55
1.
SET TRI GM(MA5
5
40
5 SET50 TRI 28 2551 9
2551 5 GM(1,1) MA5
SET50TRI
GM
-p
e2
MA5
-p
e2
1
21-May-
2
22-May-
3
23-May-
26-May-
5
27-May-
6
28-May-
-
-
38231
7
29-May-
-
8
30-May-
-
9
02-Jun-08
-
-
10
03-Jun-08
-
-
11
-Jun-08
-
12
05-Jun-08
-
13
06-Jun-08
09-Jun-08
20
-
15
10-Jun-08
-
16
11-Jun-08
-
17
12-Jun-08
-
18
13-Jun-08
5
-
19
16-Jun-08
-
20
17-Jun-08
-
21
18-Jun-08
-
22
19-Jun-08
-
23
20-Jun-08
23-Jun-08
25
-Jun-08
-
26
25-Jun-08
27
26-Jun-08
28
27-Jun-08
29
30-Jun-08
-
30
02-Jul-08
-
31
03-Jul-08
-
32
-Jul-08
-
33
07-Jul-08
-
08-Jul-08
-
35
09-Jul-08
-
41
6 GM(1,1) MA5
MSE
1
3
5
10
15
30
MSE GM
MSE MA5
SET TRI
GM(MA
42
3 SET TRI
, , , ,
GM(MA
GM(1,1)
SET50 TRI MA5
MSE 6
MSE 1 MSE GM(1,1) MSE
MA5 GM(1,1)
3 MSE GM(1,1) MSE MA5
5 MSE GM(1,1) MSE
MA5 22,263 10 MSE GM(1,1)
MSE MA5 26
MSE GM(1,1) MSE MA5
15 MSE MA5
MSE GM(1,1) 30 MSE
MA5 MSE GM(1,1) MSE MA5
MSE GM(1,1) 3 GM(1,1)
5
MA5 MA5
5
MSE GM(1,1) MSE MA5
MSE MA5 MSE
GM(1,1)
2.
SET TRI GM(MA
5
43
7 SET50 TRI 30 2555 12
2555 5 GM(1,1) MA5
SET50TRI
GM
-p
e2
MA5
-p
e2
1
23-Jan-12
2
-Jan-12
3
25-Jan-12
-
26-Jan-12
-
5
27-Jan-12
-
6
30-Jan-12
-
7
31-Jan-12
-
8
01-Feb-12
-
9
02-Feb-12
-
1800
10
03-Feb-12
-
11
06-Feb-12
-
12
07-Feb-12
-
13
08-Feb-12
-
09-Feb-12
-
15
10-Feb-12
-
16
13-Feb-12
-
17
-Feb-12
5871
-
-
18
15-Feb-12
-
19
16-Feb-12
-
20
17-Feb-12
-
21
20-Feb-12
-
22
21-Feb-12
-
23
22-Feb-12
-
23-Feb-12
-
25
-Feb-12
-
26
27-Feb-12
-
-
27
28-Feb-12
-
28
29-Feb-12
-
29
01-Mar-12
-
30
02-Mar-12
-
31
05-Mar-12
-
32
06-Mar-12
-
-
33
08-Mar-12
-
09-Mar-12
-
-
35
12-Mar-12
-
62
-
44
8 GM(1,1) MA5
MSE
1
3
5
10
15
30
MSE GM
MSE MA5
SET TRI
GM(MA
45
SET TRI
, , , ,
GM(MA
GM(1,1)
SET50 TRI MA5
MSE 8 MSE
1 MSE GM(1,1) MSE MA5
GM(1,1) 3
MSE GM(1,1) MSE MA5
5 MSE GM(1,1) 1,61695 MSE MA5
6,36 10 MSE GM(1,1) 2,88550
MSE MA5 6,97806
MSE GM(1,1) MSE MA5
15 MSE MA5 5,89085
MSE GM(1,1) 7,793 30 MSE MA5
5,036 MSE GM(1,1) ,1617 MSE MA5 MSE
GM(1,1) GM(1,1)
5
MA5 MA5
5
MSE GM(1,1) MSE MA5
MSE MA5 MSE
GM(1,1)
46
GM(,MA30
1.
SET TRI GM(MA30
3 2551 15 2551 30
9 SET50 TRI 3 2551 15
2551 30 GM(1,1) MA30
SET50TRI
GM
-p
e2
MA30
-p
e2
1
21-May-08
2
22-May-08
3
23-May-08
26-May-08
5
27-May-08
6
28-May-08
-
7
29-May-08
8
30-May-08
9
02-Jun-08
-
10
03-Jun-08
-
11
-Jun-08
-
12
05-Jun-08
-
13
06-Jun-08
09-Jun-08
15
10-Jun-08
-
16
11-Jun-08
-
17
12-Jun-08
-
18
13-Jun-08
-
19
16-Jun-08
20
17-Jun-08
-
21
18-Jun-08
-
22
19-Jun-08
-
47
9
SET50TRI
GM
-p
e2
MA30
-p
e2
23
20-Jun-08
23-Jun-08
25
-Jun-08
26
25-Jun-08
27
26-Jun-08
28
27-Jun-08
29
30-Jun-08
30
02-Jul-08
31
03-Jul-08
-
96
32
-Jul-08
-
33
07-Jul-08
-
-
08-Jul-08
-
-
35
09-Jul-08
-
-
36
10-Jul-08
-
-
37
11-Jul-08
-
38
-Jul-08
-
39
15-Jul-08
3
-
-
16-Jul-08
-
-
18-Jul-08
-
-
21-Jul-08
-
-
22-Jul-08
-
-
23-Jul-08
-
-
-Jul-08
-
-
25-Jul-08
-
-
28-Jul-08
-
-
29-Jul-08
-
-
30-Jul-08
-
-
50
31-Jul-08
-
-
51
01-Aug-
-
52
-Aug-
-
53
05-Aug-
-
-
06-Aug-
-
48
9
SET50TRI
GM
-p
e2
MA30
-p
e2
55
07-Aug-
-
56
08-Aug-
6
-
57
11-Aug-
58
13-Aug-
59
-Aug-
60
15-Aug-
10 GM(1,1) MA30
MSE
1
3
5
10
15
30
MSE GM
MSE MA30
SET50 TRI 3 2551 15
2551 30 GM(1,1) MA30
49
5 SET50 TRI 3
2551 15 2551 30 21 2
2551 GM(1,1) MA30
GM(1,1)
SET50 TRI
MA30
MSE 10 MSE 1 MSE GM(1,1)
MSE MA30 GM(1,1)
3 MSE GM(1,1) 289
MSE MA30 91,25396 5 MSE GM(1,1)
69351 MSE MA30 97,67727 10
MSE GM(1,1) 6,56056 MSE MA30 110,68
15 MSE GM(1,1) MSE MA30
30 MSE GM(1,1)
MSE MA30
30 MSE GM(1,1) MSE MA30
5 GM(1,1)
30
MA30 MA30
30
MSE GM(1,1) MSE
MA30
2.
SET TRI GM(MA0
13 2557 28 2557 30
50
11 SET50 TRI 13 2557 28
255730 GM(1,1) MA30
SET50TRI
GM
-p
e2
MA30
-p
e2
1
29-Jan-
2
30-Jan-
-
3
31-Jan-
-
03-Feb-
5
-Feb-
-
6
05-Feb-
-
7
06-Feb-
8
07-Feb-
9
10-Feb-
-
10
11-Feb-
-
11
12-Feb-
12
13-Feb-
13
17-Feb-
18-Feb-
15
19-Feb-
7
16
20-Feb-
-
17
21-Feb-
-
18
-Feb-
-
19
25-Feb-
-
20
26-Feb-
21
-
21
27-Feb-
-
22
28-Feb-
-
23
03-Mar-
-Mar-
25
05-Mar-
26
06-Mar-
27
07-Mar-
28
10-Mar-
-
29
11-Mar-
30
12-Mar-
31
-
51
11
SET50TRI
GM
-p
e2
MA30
-p
e2
31
13-Mar-
32
-Mar-
33
17-Mar-
18-Mar-
-
35
19-Mar-
-
36
20-Mar-
-
37
21-Mar-
-
38
-Mar-
-
39
25-Mar-
-
26-Mar-
-
27-Mar-
-
28-Mar-
-
31-Mar-
-
01-Apr-
-
02-Apr-
03-Apr-
-
-Apr-
-
08-Apr-
-
09-Apr-
-
50
10-Apr-
-
51
11-Apr-
-
1
52
16-Apr-
-
53
17-Apr-
-
18-Apr-
-
55
21-Apr-
-37
56
22-Apr-
-
57
23-Apr-
-
58
-Apr-
-
59
25-Apr-
-
60
28-Apr-
-
52
12 GM(1,1) MA30
MSE
1
3
5
10
15
30
MSE GM
MSE MA30
SET50 TRI 13 2557 28
2557 30 GM(1,1MA30
6 SET50 TRI 13 2557
28 2557 30 12
2557 GM(1,1) MA30
GM(1,1)
SET50 TRI
MA30
MSE 12 MSE 1 MSE
GM(1,1) MSE MA30
53
GM(1,1) 3 MSE
GM(1,1) MSE MA30 5
MSE GM(1,1) MSE MA30
10 MSE GM(1,1) MSE MA30
15 MSE GM(1,1)
MSE MA30 30 MSE
GM(1,1) MSE MA30
30 MSE GM(1,1)
MSE MA30 6
GM(1,1) 30
MA30
MA30
30
MSE GM(1,1) MSE
MA30
บทที่ 5
สรุปการวิจัย อภิปรายผล และข้อเสนอแนะ
SET50
1.
SET50
(SET50 TRI)
1.1
SET50 (SET50 TRI)
Moving Average) MA
Moving Average) 5 MA5
(Trend) Moving Average)
3 MA3
Moving Average) 0 MA0
Trend
Moving Average) MA 5 MA5
30
Moving Average) 3 MA3) 5 MA5)
30 MA30) Trend
1
55
1.2
SET50 (SET50 TRI)
GM(, 3
Trend
GM(, 5
Trend
GM(1,1) 3
GM(, 30
TrendGM(1,1) 3 5
GM(1,1)
Trend
1.3
Moving Average) 3 MA3) 5 MA5) 30 MA30)
GM(,
GM(MA MA MA
MSE
MSE
1
3
5
10
15
30
3
MSE GM
MSE MA3
3
MSE GM
MSE MA3
5
MSE GM
MSE MA5
56
MSE
1
3
5
10
15
30
5
MSE GM
MSE MA5
30
MSE GM
MSE MA30
30
MSE GM
MSE MA30
GM(MSE
MSE GM(
MSE
MSE GM(
GM
MA
10
10
10
10
3
5
30
57
SET50 (SET50 TRI)
3510
10
30
1.4 -
Moving Average) MA MA
MA
5 MAMA
5 MA
MA
-
GM(, 3 5
30 -
GM(,
2.
SET50
(SET50 TRI) SET50 (SET50 TRI)
Moving Average) 3 MA3) 5 MA5) 30
MA30) GM(,
MSE
Moving Average) MA MA
MA
58
2549)
3 5 7
2549)
GM(,
XingYu, Yi Le, Meijuan Yang, & Zhenyan Li (
The Application of Grey System in Futures Price Forecasting
GM(,
2552)
3.
SETSET
TRI)
SETSETTRI)
SETSETTRI)
Grey Model)
59
SETTRI
3.2
3.2.1 ขยายผลการศึกษาด้วยการเลือกใช้ข้อมูลประเภทอื่นๆ
3.2.2 วิธีตัวแบบเกรย์ Grey Model)
(Exponential smoothing)
3
Grey-Markov Model
Moving Average Convergence/Divergence (MACD)
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. ().
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ภาคผนวก
65
ภาคผนวก ก
การค านวณดัชนีผลตอบแทนรวมของตลาดหลักทรัพย์แห่งประเทศไทย
(Total Return Index Calculation Methodology)
66
67
68
69
70
71
72
ภาคผนวก ข
หลักเกณฑ์การจัดท าดัชนีของตลาดหลักทรัพย์แห่งประเทศไทย
73
74
75
76
77
78
27 2514
2544
