By: Dr. Deddy P. Koesrindartoto
In his study, Dr. Dedy analyzed the dynamic behavior of institutional and individual traders in the Indonesia Stock Exchange (IDX) using all of their transactions during 2013–2015. Dr. Dedy emphasized the fact that the capital market is important. However, the number of investors in Indonesia did not experience a significant increase. Based on KSEI, the number of investors in IDX was indeed experiencing a significant increase from the year 2012- 2017, but the participation rate was still really low (below 1%).
The study tried to examine:
1. The dynamics relation of the trading behavior of various institutional and individual investors 2. The underlying strategy applied by each investor
type in its trading activities, i.e., contrarian and momentum
3. How the contemporaneous relationship among players trade and stocks return (herding behavior
He received Ph.D in Economics with a minor in Statistics and M.Sc in Industrial Engineering from the Iowa State University. He earned his undergraduate degree in Electrical Engineering from Institut Teknologi Bandung.
Investors Behavior and Trading Strategies:
Evidence from Indonesia Stock Exchange
By: Dr. Deddy P. Koesrindartoto
In his study, Dr. Dedy analyzed the dynamic behavior of institutional and individual traders in the Indonesia Stock Exchange (IDX) using all of their transactions during 2013–2015. Dr. Dedy emphasized the fact that the capital market is important. However, the number of investors in Indonesia did not experience a significant increase. Based on KSEI, the number of investors in IDX was indeed experiencing a significant increase from the year 2012- 2017, but the participation rate was still really low (below 1%).
The study tried to examine:
1. The dynamics relation of the trading behavior of various institutional and individual investors 2. The underlying strategy applied by each investor
type in its trading activities, i.e., contrarian and momentum
3. How the contemporaneous relationship among players trade and stocks return (herding behavior
What made the research performed by Dr. Deddy different was the use of microstructure methods in analyzing capital market, as review using such method was still rare in Indonesia. The paper also showed that among all of the investors, institutional investor accounts for 66% of the overall investor while the other 34% are by an individual investor, which meant it has a significant impact on the capital market.
The results showed that the dynamic relationship between institutional and individual investors were as follow:
1. Individual investors looked at the strategy of institutional investors and also the market return 2. While the institutional investors only looked at the
market return but not at the strategy of the individual investor
While in term of strategy, individual investors use contrarian strategy while institutional investors use momentum strategy. Contrarian strategy is the strategy where the investor action the next day will contradict the market condition in the previous day. For example, if the yesterday market is favorable, the investor will sell the share today, vice versa. While the momentum strategy is
Investors Behavior andTrading Strategies:
Evidence from Indonesia Stock Exchange
Deddy P. Koesrindartoto*, Aurelius Aaron, and Abdurrohman Arroisi School of Business and Management, Institut Teknologi Bandung, Indonesia
1
2
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
• The increasing importance of Capital Market in Indonesia Economy
• In term of structure, from year to year insignificance contributions in term of equity ownerships from individual investors compared to the institutional investors
• While the number of investor is raising, the significantly low participationrate compared of other pairing countries
• The development of using microstructure methods in analyzing capital market
• The relatively low number of analysis about capital market in Indonesia using market microstructures
• Very limited study the discuss the behavior and strategy in the termof institutional vs individual investors
1. Introduction : Background
What made the research performed by Dr. Deddy different was the use of microstructure methods in analyzing capital market, as review using such method was still rare in Indonesia. The paper also showed that among all of the investors, institutional investor accounts for 66% of the overall investor while the other 34% are by an individual investor, which meant it has a significant impact on the capital market.
The results showed that the dynamic relationship between institutional and individual investors were as follow:
1. Individual investors looked at the strategy of institutional investors and also the market return 2. While the institutional investors only looked at the
market return but not at the strategy of the individual investor
While in term of strategy, individual investors use contrarian strategy while institutional investors use momentum strategy. Contrarian strategy is the strategy where the investor action the next day will contradict the market condition in the previous day. For example, if the yesterday market is favorable, the investor will sell the share today, vice versa. While the momentum strategy is
Investors Behavior andTrading Strategies:
Evidence from Indonesia Stock Exchange
Deddy P. Koesrindartoto*, Aurelius Aaron, and Abdurrohman Arroisi School of Business and Management, Institut Teknologi Bandung, Indonesia
1
2
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
• The increasing importance of Capital Market in Indonesia Economy
• In term of structure, from year to year insignificance contributions in term of equity ownerships from individual investors compared to the institutional investors
• While the number of investor is raising, the significantly low participationrate compared of other pairing countries
• The development of using microstructure methods in analyzing capital market
• The relatively low number of analysis about capital market in Indonesia using market microstructures
• Very limited study the discuss the behavior and strategy in the termof institutional vs individual investors
1. Introduction : Background
1. Introduction : Background (Cont’d) 3
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
4
Type of Investor 2013 2014 2015
Individual 7.8% 6.4% 6.5%
Corporate 54.7% 50.9% 31.2%
Mutual Fund 22.6% 25.3% 15.7%
Securities
Company 4.3% 4.7% 8.6%
Insurance 6.0% 5.8% 3.8%
Pension Fund 8.6% 9.6% 6.8%
Financial Insttution 17.6% 17.6% 11.6%
Foundation 0.3% 0.4% 0.2%
Others 32.3% 31.2% 15.5%
Percentage of Equity by Investor Type 1. Introduction : Background (Cont’d)
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
5
Source : KSEI (2018) Number of Investors in IDX based on
Single Investor Identification (SID) Participation Rate (%)
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange 1. Introduction : Background (Cont’d)
6
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
No Author(s) Year Title Range Data
Type Topic Coverage 1 Roll 1995 An empirical survey of Indonesian equities 1985–1992 Jan1985-
Dec 1992 M General
2 Chang et al. 1995 Price volatility of Indonesian stocks Sep 1992 -
Feb 1994 T Opening & Closing 3 Bonser-Neal,
Linnan, and Neal 1999 Emerging market transaction costs: Evidence fromIndonesia Sep 1992 -
Jan 1995 T Transaction Costs 4 Comerton-Forde 1999 Do trading rules impact on market efficiency? A comparison of
opening procedures on the Australian and JakartaStock Exchanges
Nov 1995 -
June 1997 T Opening
5 Hanafi and Rhee 2004 The wealth effect of foreign investor presence: Evidence from
the Indonesian market May 1995 -
Aug 1998 D Financial Market Liberalization 6 Dvorak 2005 Do domestic investors have an information advantage?
Evidence from Indonesia Jan 1998-
Dec 2001 T Trading Performance of Domestic and Foreign 7 Agarwal,
Faircloth, Liu, and
Rhee 2009 Why do foreign investors underperform domestic investorsin trading activities? Evidence fromIndonesia May 1995 -
Dec 2003 T & O Clarifying the finding of Dvorak (2005) 8 Rhee and Wang 2009 Foreign institutional ownership and stock market liquidity:
Evidence from Indonesia Jan 2002-
Dec 2007 D Ownership & Stock Market Liquidity 9 Hanafi 2010 Unusual market activity announcements: A study ofprice
manipulation on the Indonesian Stock Exchange Jan 2008-
Dec 2008 D Unusual Market Activity (UMA) 2. Literature Review :
Market Microstructure Research in Indonesia
1. Introduction : Background (Cont’d) 3
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
4
Type of Investor 2013 2014 2015
Individual 7.8% 6.4% 6.5%
Corporate 54.7% 50.9% 31.2%
Mutual Fund 22.6% 25.3% 15.7%
Securities
Company 4.3% 4.7% 8.6%
Insurance 6.0% 5.8% 3.8%
Pension Fund 8.6% 9.6% 6.8%
Financial Insttution 17.6% 17.6% 11.6%
Foundation 0.3% 0.4% 0.2%
Others 32.3% 31.2% 15.5%
Percentage of Equity by Investor Type 1. Introduction : Background (Cont’d)
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
5
Source : KSEI (2018) Number of Investors in IDX based on
Single Investor Identification (SID) Participation Rate (%)
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange 1. Introduction : Background (Cont’d)
6
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
No Author(s) Year Title Range Data
Type Topic Coverage 1 Roll 1995 An empirical survey of Indonesian equities 1985–1992 Jan1985-
Dec 1992 M General
2 Chang et al. 1995 Price volatility of Indonesian stocks Sep 1992 -
Feb 1994 T Opening & Closing 3 Bonser-Neal,
Linnan, and Neal 1999 Emerging market transaction costs: Evidence from Indonesia Sep 1992 -
Jan 1995 T Transaction Costs 4 Comerton-Forde 1999 Do trading rules impact on market efficiency? A comparison of
opening procedures on the Australian and JakartaStock Exchanges
Nov 1995 -
June 1997 T Opening
5 Hanafi and Rhee 2004 The wealth effect of foreign investor presence: Evidence from
the Indonesian market May 1995 -
Aug 1998 D Financial Market Liberalization 6 Dvorak 2005 Do domestic investors have an information advantage?
Evidence from Indonesia Jan 1998-
Dec 2001 T Trading Performance of Domestic and Foreign 7 Agarwal,
Faircloth, Liu, and
Rhee 2009 Why do foreign investors underperform domestic investorsin trading activities? Evidence fromIndonesia May 1995 -
Dec 2003 T & O Clarifying the finding of Dvorak (2005) 8 Rhee and Wang 2009 Foreign institutional ownership and stock market liquidity:
Evidence from Indonesia Jan 2002-
Dec 2007 D Ownership & Stock Market Liquidity 9 Hanafi 2010 Unusual market activity announcements: A study ofprice
manipulation on the Indonesian Stock Exchange Jan 2008-
Dec 2008 D Unusual Market Activity (UMA) 2. Literature Review :
Market Microstructure Research in Indonesia
7
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
No Author(s) Year Title Range Data
Type Topic Coverage 10Henker and
Husodo 2010 Noise and efficient variance in the Indonesia Stock
Exchange Jan 2000 -
Dec 2007 T Separating Microstructure Noise from Volatility 11Agarwal, Chiu,
Liu, and Rhee 2011 The brokerage firm effect in herding: Evidence from
Indonesia May 1995 -
May 2003 T & O Brokerage Effect on Investor's Herding
Behavior 12Ekaputra and
Asikin 2012 Impact of tick size reduction on small caps price efficiency and execution cost on the Indonesia Stock
Exchange
Nov 2006 -
Feb 2007 T Implication of Tick Size Reduction 13Setiyono,
Tandelilin,
Hartono,Hanafi 2013 Detecting the existence of herding behavior in intraday data: Evidence from the Indonesia Stock Exchange Jan 2003 -
Dec 2005 T Investigating Herding Behavior 14Ekaputra 2014 Impact of foreign and domestic order imbalances on
return and volatility-volume relation Jan 2010 -
Dec 2010 T Order Imbalances &
Volatility-Volume Relation 15Aaron,
Koesrindartoto,
Takashima 2018 Micro-foundation investigation of price manipulation in Indonesian capital market Jan 2003 -
Dec 2004 T Unchecked Price
Manipulation 2. Literature Review (Cont’d)
3. Research Objectives 8
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
9 Where:
rp,t : portfolio return at period t wi,t : weight of stock i at period t ri,t: return of stock i at period t
𝐼𝐼𝑀𝑀𝐵𝐵𝑥𝑥,𝑡𝑡=𝐵𝐵𝑢𝑢𝑦𝑦𝑇𝑇𝑉𝑉𝑥𝑥,𝑡𝑡−𝑆𝑆𝑒𝑒𝑙𝑙𝑙𝑙𝑇𝑇𝑉𝑉𝑥𝑥,𝑡𝑡
𝐵𝐵𝑢𝑢𝑦𝑦𝑇𝑇𝑉𝑉𝑥𝑥,𝑡𝑡+𝑆𝑆𝑒𝑒𝑙𝑙𝑙𝑙𝑇𝑇𝑉𝑉𝑥𝑥,𝑡𝑡
Calculatingtradingimbalances Where:
IMBx,t : Trading imbalances of investor x at period t Buy (Sell )TVx,t : Buy (Sell) trading value of investor x at period t 4. Methodology
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
10
x = 1 ... 2 (general players) ; x = 1 … 8 (detailed players) Computing Vector Autoregression (VAR) with Newey-West correction using above equation
4. Methodology (cont’d)
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
7
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
No Author(s) Year Title Range Data
Type Topic Coverage 10Henker and
Husodo 2010 Noise and efficient variance in the Indonesia Stock
Exchange Jan 2000 -
Dec 2007 T Separating Microstructure Noise from Volatility 11Agarwal, Chiu,
Liu, and Rhee 2011 The brokerage firm effect in herding: Evidence from
Indonesia May 1995 -
May 2003 T & O Brokerage Effect on Investor's Herding
Behavior 12Ekaputra and
Asikin 2012 Impact of tick size reduction on small caps price efficiency and execution cost on the Indonesia Stock
Exchange
Nov 2006 -
Feb 2007 T Implication of Tick Size Reduction 13Setiyono,
Tandelilin,
Hartono,Hanafi 2013 Detecting the existence of herding behavior in intraday data: Evidence from the Indonesia Stock Exchange Jan 2003 -
Dec 2005 T Investigating Herding Behavior 14Ekaputra 2014 Impact of foreign and domestic order imbalances on
return and volatility-volume relation Jan 2010 -
Dec 2010 T Order Imbalances &
Volatility-Volume Relation 15Aaron,
Koesrindartoto,
Takashima 2018 Micro-foundation investigation of price manipulation in Indonesian capital market Jan 2003 -
Dec 2004 T Unchecked Price
Manipulation 2. Literature Review (Cont’d)
3. Research Objectives 8
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
9 Where:
rp,t : portfolio return at period t wi,t : weight of stock i at period t ri,t: return of stock i at period t
𝐼𝐼𝑀𝑀𝐵𝐵𝑥𝑥,𝑡𝑡=𝐵𝐵𝑢𝑢𝑦𝑦𝑇𝑇𝑉𝑉𝑥𝑥,𝑡𝑡−𝑆𝑆𝑒𝑒𝑙𝑙𝑙𝑙𝑇𝑇𝑉𝑉𝑥𝑥,𝑡𝑡
𝐵𝐵𝑢𝑢𝑦𝑦𝑇𝑇𝑉𝑉𝑥𝑥,𝑡𝑡+𝑆𝑆𝑒𝑒𝑙𝑙𝑙𝑙𝑇𝑇𝑉𝑉𝑥𝑥,𝑡𝑡
Calculatingtradingimbalances Where:
IMBx,t : Trading imbalances of investor x at period t Buy (Sell )TVx,t : Buy (Sell) trading value of investor x at period t 4. Methodology
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
10
x = 1 ... 2 (general players) ; x = 1 … 8 (detailed players) Computing Vector Autoregression (VAR) with Newey-West correction using above equation
4. Methodology (cont’d)
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
11
Period Trading Stocks Trading Trading Volume (in billion)
Trading Value Days Traded Frequency (in million) 2013 240 485 73,105,756 2,632.13 2,972,772.82
Q1 60 451 19,393,710 749.69 751,915.62
Q2 59 455 19,550,760 717.81 893,518.60
Q3 61 462 18,983,014 597.89 724,901.16
Q4 60 470 15,178,272 566.74 602,437.43
2014 242 570 103,714,922 2,712.37 2,908,436.33
Q1 60 517 25,813,196 581.73 714,970.69
Q2 59 520 24,344,006 596.07 711,822.75
Q3 60 529 25,947,892 734.29 760,149.79
Q4 63 536 27,609,828 800.28 721,493.11
2015 244 582 108,558,876 2,917.01 2,811,921.93
Q1 62 534 28,807,152 816.08 816,296.24
Q2 61 534 26,570,562 747.32 739,468.62
Q3 60 538 25,127,206 629.87 565,480.00
Q4 61 544 28,053,956 723.75 690,677.07
2013-2015 726 582 285,379,554 8,261.51 8,693,131.08 Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
5. Data Description
5. Data Description (cont’d) 12
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
5. Data Description (cont’d) 13
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
5. Data Description (cont’d) 14
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
11
Period Trading Stocks Trading Trading Volume (in billion)
Trading Value Days Traded Frequency (in million) 2013 240 485 73,105,756 2,632.13 2,972,772.82
Q1 60 451 19,393,710 749.69 751,915.62
Q2 59 455 19,550,760 717.81 893,518.60
Q3 61 462 18,983,014 597.89 724,901.16
Q4 60 470 15,178,272 566.74 602,437.43
2014 242 570 103,714,922 2,712.37 2,908,436.33
Q1 60 517 25,813,196 581.73 714,970.69
Q2 59 520 24,344,006 596.07 711,822.75
Q3 60 529 25,947,892 734.29 760,149.79
Q4 63 536 27,609,828 800.28 721,493.11
2015 244 582 108,558,876 2,917.01 2,811,921.93
Q1 62 534 28,807,152 816.08 816,296.24
Q2 61 534 26,570,562 747.32 739,468.62
Q3 60 538 25,127,206 629.87 565,480.00
Q4 61 544 28,053,956 723.75 690,677.07
2013-2015 726 582 285,379,554 8,261.51 8,693,131.08 Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
5. Data Description
5. Data Description (cont’d) 12
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
5. Data Description (cont’d) 13
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
5. Data Description (cont’d) 14
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
15
Panel A. Optimal Lag Selection
Lag General Players
-14.34# 28.58#
LR AIC
0 NA -14.24
1 93.28 -14.34
2 13.09 -14.34
3 25.36
4 3.86 -14.33
5 4.09 -14.31
6 -14.33
7 7.05 -14.31
8 10.79 -14.30
6. Results of GeneralPlayers
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
16
Panel C. Heteroscedasticity Test
General Players
La g 3 La g 6
Chi-Squared
(Joint-test) 780.8*
(0.000) 1848.2*
(0.000) 6. Results ofGeneral Players (cont’d)
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
6. Results ofGeneral Players (cont’d) 17
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
18
Variables Effect (t)
RETURN INSTITUTION INDIVIDUAL
Cause (t-i)
RETURN 2.296**
(0.033) 16.33***
(0.000) 16.94*** (0.000)
INSTITUTION 4.233***
(0.005) 9.381***
(0.000) 3.12** (0.025)
INDIVIDUAL 4.137*** (0.006) 1.817
(0.142) 10.44*** (0.000)
6. Results ofGeneral Players (cont’d)
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
15
Panel A. Optimal Lag Selection
Lag General Players
-14.34# 28.58#
LR AIC
0 NA -14.24
1 93.28 -14.34
2 13.09 -14.34
3 25.36
4 3.86 -14.33
5 4.09 -14.31
6 -14.33
7 7.05 -14.31
8 10.79 -14.30
6. Results of GeneralPlayers
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
16
Panel C. Heteroscedasticity Test
General Players
La g 3 La g 6
Chi-Squared
(Joint-test) 780.8*
(0.000) 1848.2*
(0.000) 6. Results ofGeneral Players (cont’d)
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
6. Results ofGeneral Players (cont’d) 17
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
18
Variables Effect (t)
RETURN INSTITUTION INDIVIDUAL
Cause (t-i)
RETURN 2.296**
(0.033) 16.33***
(0.000) 16.94***
(0.000)
INSTITUTION 4.233***
(0.005) 9.381***
(0.000) 3.12**
(0.025)
INDIVIDUAL 4.137***
(0.006) 1.817
(0.142) 10.44***
(0.000)
6. Results ofGeneral Players (cont’d)
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
Panel A. Optimal Lag Selection
Lag Detailed Players
LR AIC
0 N/A -9.74
-10.43#
124.57#
19
1 689.30
2 162.52 -10.39
3 124.60 -10.29
4 107.88 -10.17
5 122.76 -10.08
6 113.34 -9.97
7 98.129 -9.85
8 -9.76
7. Results of DetailedPlayers
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
7. Results of Detailed Players(cont’d) 20
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
7. Results of Detailed Players(cont’d) 21
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
22
Variables DEPENDENT VARIABLE (t)
RETURN INSTITUTION INDIVIDUAL
-1 (+) VS (-) VS
RETURN -2
-3
INDEPENDENT VARIABLE
(t-i)
-1
INSTITUTION -2 (+) W
-3 (-) VS (-) VS (+) VS
-1
INDIVIDUAL -2
-3 (-) VS (-) VS (+) VS
8. Conclusion
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
Panel A. Optimal Lag Selection
Lag Detailed Players
LR AIC
0 N/A -9.74
-10.43#
124.57#
19
1 689.30
2 162.52 -10.39
3 124.60 -10.29
4 107.88 -10.17
5 122.76 -10.08
6 113.34 -9.97
7 98.129 -9.85
8 -9.76
7. Results of DetailedPlayers
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
7. Results of Detailed Players(cont’d) 20
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
7. Results of Detailed Players(cont’d) 21
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
22
Variables DEPENDENT VARIABLE (t)
RETURN INSTITUTION INDIVIDUAL
-1 (+) VS (-) VS
RETURN -2
-3
INDEPENDENT VARIABLE
(t-i)
-1
INSTITUTION -2 (+) W
-3 (-) VS (-) VS (+) VS
-1
INDIVIDUAL -2
-3 (-) VS (-) VS (+) VS
8. Conclusion
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
23
Variables Effect (t)
RETURN INSTITUTION INDIVIDUAL
Cause (t-i)
RETURN VS VS VS
INSTITUTION VS VS S
INDIVIDUAL VS VS
8. Conclusion (cont’d)
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
8. Conclusion (cont’d) 24
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
25
Variables Effect (t)
RET ID CP IB SC OT IS MF PF FD
Cause (t-i)
RET VS W
ID VS
CP VS
IB VS S
SC W VS S W
OT
IS VS VS W
MF VS S
PF S W
FD S S W W
8. Conclusion (cont’d)
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
“
2623
Variables Effect (t)
RETURN INSTITUTION INDIVIDUAL
Cause (t-i)
RETURN VS VS VS
INSTITUTION VS VS S
INDIVIDUAL VS VS
8. Conclusion (cont’d)
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
8. Conclusion (cont’d) 24
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange
25
Variables Effect (t)
RET ID CP IB SC OT IS MF PF FD
Cause (t-i)
RET VS W
ID VS
CP VS
IB VS S
SC W VS S W
OT
IS VS VS W
MF VS S
PF S W
FD S S W W
8. Conclusion (cont’d)
Investors Behavior and Trading Strategies: Evidence from Indonesia Stock Exchange