THE INFLUENCE OF DOW JONES INDEX, NIKKEI INDEX, HANG …

i

THE INFLUENCE OF DOW JONES INDEX, NIKKEI

INDEX, HANG SENG INDEX, EXCHANGE RATE ON

IDR, BI INTEREST RATE AND INFLATION TOWARDS

JAKARTA COMPOSITE INDEX

PERIOD 2010 – 2013

By Martin Febrianto

ID No. 014201000047

A skripsi presented to the

Faculty of Business President University

in partial fulfillment of the requirements for

Bachelor Degree in Economics Major in Management

February 2014

ii

PANEL OF EXAMINERS

APPROVAL SHEET

The Panel of Examiners declare that the skripsi entitled “THE

INFLUENCE OF DOW JONES INDEX, NIKKEI INDEX, HANG

SENG INDEX, EXCHANGE RATE ON IDR, BI INTEREST RATE

AND INFLATION TOWARDS JAKARTA COMPOSITE INDEX

PERIOD 2010 – 2013” that was submitted by Martin Febrianto majoring

in Management from the Faculty of Business was assessed and approved

to have passed the Oral Examinations on February 6, 2014.

Drs. Agus Burhan Adidi, M.A., C.CA

Chair - Panel of Examiners

Ir. Erny E. Hutabarat, MBA

Examiner I

Purwanto, S.T, M.M

Examiner II

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SKRIPSI ADVISER

RECOMMENDATION LETTER

This skripsi entitled “THE INFLUENCE OF DOW JONES INDEX,

NIKKEI INDEX, HANG SENG INDEX, EXCHANGE RATE ON IDR,

BI INTEREST RATE AND INFLATION TOWARDS JAKARTA

COMPOSITE INDEX PERIOD 2010 – 2013” prepared and submitted by

Martin Febrianto in partial fulfillment of the requirements for the degree of

Bachelor in the Faculty of Business has been reviewed and found to have

satisfied the requirements for a skripsi fit to be examined. I therefore

recommend this skripsi for Oral Defense.

Cikarang, Indonesia, February 6, 2014

Acknowledged by, Recommended by,

Vinsensius Jajat Kristanto SE., MM., MBA. Purwanto, S.T, M.M

Head of Management Study Program Skripsi Advisor

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DECLARATION OF ORIGINALITY

I declare that this skripsi, entitled “THE INFLUENCE OF DOW JONES

INDEX, NIKKEI INDEX, HANG SENG INDEX, EXCHANGE RATE

ON IDR, BI INTEREST RATE AND INFLATION TOWARDS

JAKARTA COMPOSITE INDEX PERIOD 2010 – 2013” is, to the best

of my knowledge and belief, an original piece of work that has not been

submitted, either in whole or in part, to another university to obtain a

degree.

Cikarang, Indonesia, February 6, 2014

MARTIN FEBRIANTO

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ABSTRACT

Jakarta Composite Index (JCI) is an index that used by Indonesia Stock Exchange to reflect the fluctuation all of the listed stocks in Indonesia Stock Exchange that currently happen in Indonesia capital market. Jakarta Composite Index are the reflection of the movement of the Indonesia capital market that are influenced by many factors. In this research, the independent variables used divided into two factors that has significant influence toward Jakarta Composite Index which are foreign market index and macroeconomic variables. Foreign market index that could have significant influence toward Jakarta Composite Index consist of Dow Jones Index, Nikkei Index and Hang Seng Index. While macroeconomic variables that could has significant influence toward Jakarta Composite Index consist of Exchange Rate on IDR, BI Interest Rate and Inflation. This research is a quantitative research that will analyze the influence of foreign market index and macroeconomics variables towards Jakarta Composite Index. The sample for this research is 46 sample for each variables which is monthly secondary data and the time period for this research is from January 2010 – October 2013. This research use SPSS version 18 and EViews 6 as the statistical tools. The result of this study is partially all of the factors has influence toward Jakarta Composite Index, but only Dow Jones Index, Exchange Rate on IDR and BI Interest Rate that have significant influence. Simultaneously all of the factors have significant influence toward Jakarta Composite Index with adjusted R-square 0.891 or 89 % of the factors in this multiple regression models can explain the dependent variable, while the remaining explained by the other factors outside this multiple regression model.

Keywords : Jakarta Composite Index (JCI), Dow Jones Index, Nikkei Index,

Hang Seng Index, the Exchange Rate on IDR, BI Interest Rate and

Inflation.

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ACKNOWLEDGEMENT

First of all, thanks to God because of his blessings, the researcher could finish

this skripsi as a requirement to obtain bachelor degree in President University

majoring in Banking and Finance. In this preface, the researcher would like to

express sincere gratitude to:

1. My father, mother and sister who always help and support me to

complete this skripsi. Without their help and support I might not be

able to complete this thesis.

2. Mr. Purwanto as my skripsi advisor who have taught and guide me to

complete this thesis

3. Harnessia Caroline Wijaya who always support me to complete this

skripsi.

4. IDX Marketing education division staff Mr. Taufiq Rochman, Mr.

Deri, Mrs. Mita, and Miss. Aulia who always help me to complete this

skripsi.

5. All of friends from Banking and Finance major as well as friends from

other major that helped the researcher while doing this skripsi

especially for Opat, Sinta, Livi, Ellen, James, Edwin, Yansen, Stefan,

Charles, Kristiawan, Ozzy, Stefanus, Nathan, Hendra and Ken.

Without them, the researcher would not be able to finish this skripsi. Last but not

least, the researcher would like to apologize for being unable to mention other

contributing person’s name one by one.

Best Regards,

Martin Febrianto

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TABLE OF CONTENT

COVER ………………………………………………………………………………i

PANEL OF EXAMINERS ........................................................................................ ii

SKRIPSI ADVISER .................................................................................................. iii

DECLARATION OF ORIGINALITY .................................................................... iv

ABSTRACT ................................................................................................................. v

ACKNOWLEDGEMENT ........................................................................................ vi

TABLE OF CONTENT ........................................................................................... vii

LIST OF TABLE ...................................................................................................... xi

LIST OF FIGURES ................................................................................................. xii

CHAPTER I INTRODUCTION .............................................................................. 1

1.1. Research Background ..................................................................................... 1

1.2. Problem Identification .................................................................................... 6

1.3. Statement of Problem ..................................................................................... 7

1.4. Research Objective ......................................................................................... 7

1.5. Research Limitation ....................................................................................... 8

1.6. Benefit of the study ........................................................................................ 9

1. For Researcher: .............................................................................................. 9

2. For Readers: ................................................................................................... 9

3. For Indonesia Stock Exchange: ...................................................................... 9

1.7. Assumptions and Hypothesis ......................................................................... 9

1.8. Theoretical Framework ................................................................................ 11

1.9. Research Outlines ......................................................................................... 12

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1.10. Definition of terms .................................................................................... 13

CHAPTER II LITERATURE REVIEW ............................................................... 16

2.1. Definition of Investment .............................................................................. 16

2.2. Definition of Capital Market ........................................................................ 17

2.3. Investment Products in Capital Market ........................................................ 18

2.4. Jakarta Composite Index (JCI) ..................................................................... 20

2.5. Dow Jones Index .......................................................................................... 21

2.6. Nikkei Index ................................................................................................. 22

2.7. Hang Seng Index .......................................................................................... 22

2.8. Exchange Rate on IDR ................................................................................. 23

2.9. BI Interest Rate ............................................................................................. 24

2.10. Inflation..................................................................................................... 25

2.11. Previous Journal........................................................................................ 26

CHAPTER III METHODOLOGY ......................................................................... 31

3.1. Research Method .......................................................................................... 31

3.2. Research Instruments ................................................................................... 32

3.2.1 Research Variables ................................................................................ 32

3.2.2 Type and source of data ........................................................................ 33

3.2.3. Data Analysis ........................................................................................ 38

3.3. Classic Assumption Test .............................................................................. 40

3.3.1. Statistic Descriptive test ........................................................................ 40

3.3.2. Normality Test ...................................................................................... 41

3.3.3. Autocorrelation test ............................................................................... 41

3.3.4. Multicollinearity test ............................................................................. 42

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3.3.5. Heteroscedastisity test ........................................................................... 43

3.3.6. Multiple Regression .............................................................................. 44

3.4. Hypothesis Testing ....................................................................................... 44

3.4.1 F-Test .................................................................................................... 45

3.4.2 T-Test .................................................................................................... 46

3.4.3 Coefficient of Determination (R2)......................................................... 48

3.5. Limitations ................................................................................................... 49

CHAPTER IV ANALYSIS OF DATA AND INTERPRETATION RESULTS 50

4.1. Statistics Descriptive of Research Variable ................................................. 50

4.2. Classic Assumption Test .............................................................................. 52

4.2.1. Normality Test ...................................................................................... 52

4.2.2. Autocorrelation Test ............................................................................. 54

4.2.3. Multicolinearity Test ............................................................................. 55

4.2.4. Heteroscedasticity Test ......................................................................... 56

4.2.5. Multiple Regression Analysis ............................................................... 57

4.3. Hypothesis Testing ....................................................................................... 60

4.3.1. F Test .................................................................................................... 60

4.3.2. T-Test .................................................................................................... 60

4.3.3. Coefficient of Determination ................................................................ 62

4.4. EViews 6 ...................................................................................................... 63

4.5. Interpretation of Results ............................................................................... 64

4.5.1. The Influence of Dow Jones Index towards Jakarta Composite Index. 64

4.5.2 The Influence of Nikkei Index towards Jakarta Composite Index........ 65

4.5.3. The Influence of Hang Seng Index towards Jakarta Composite Index. 65

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4.5.4. The influence of Exchange Rate on IDR towards Jakarta Composite

Index…… ............................................................................................................ 66

4.5.5. The influence of BI Interest Rate towards Jakarta Composite Index. .. 67

4.5.6. The influence of Inflation towards Jakarta Composite Index. .............. 68

4.5.7. The influence of Dow Jones Index, Nikkei Index, Hang Seng Index,

Exchange Rate on IDR, BI Interest Rate and Inflation towards Jakarta

Composite Index….. ............................................................................................ 68

CHAPTER V CONCLUSION AND RECOMMENDATION .............................. 70

5.1. Conclusion .................................................................................................... 70

5.2. Recommendation .......................................................................................... 72

REFERENCES .......................................................................................................... 74

APPENDICES ........................................................................................................... 78

1. Jakarta Composite Index .................................................................................. 78

2. Dow Jones Index .............................................................................................. 80

3. Nikkei Index ..................................................................................................... 82

4. Hang Seng Index .............................................................................................. 84

5. Exchange Rate on IDR ..................................................................................... 86

6. BI Interest Rate ................................................................................................ 87

7. Inflation ............................................................................................................ 88

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LIST OF TABLE

Table 1.1 Ownership of Indonesia Stock Exchange ..................................................... 3

Table 4.1 Descriptive Statistics ................................................................................... 50

Table 4.2 Durbin Watson Statistics............................................................................. 54

Table 4.3 Multicolinearity Test ................................................................................... 55

Table 4.4 Multiple Regression Analysis ..................................................................... 57

Table 4.5 F-Test .......................................................................................................... 59

Table 4.6 Coefficient of Determination ...................................................................... 61

Table 4.7 EViews Test ................................................................................................ 62

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LIST OF FIGURES

Figure 1.1 Jakarta Composite Index Growth ................................................................ 2

Figure 1.2 Theoretical Framework.............................................................................. 11

Figure 3.1 Jakarta Composite Index Closing Price Trend .......................................... 33

Figure 3.2 Dow Jones Index Closing Price Trend ...................................................... 33

Figure 3.3 Nikkei Index Closing Price Trend ............................................................. 34

Figure 3.4 Hang Seng Index Closing Price Trend ...................................................... 35

Figure 3.5 Exchange Rate on IDR Trend .................................................................... 35

Figure 3.6 BI Interest Rate Trend ............................................................................... 36

Figure 3.7 Inflation Trend ........................................................................................... 37

Figure 3.8 Research Framework ................................................................................. 38

Figure 4.1 Histogram of Normality Test ..................................................................... 52

Figure 4.2 P-P plot (Probability – Probability plot) .................................................... 53

Figure 4.3 Heteroscedasticity Test .............................................................................. 56

1

CHAPTER I

INTRODUCTION

1.1. Research Background Investment in Indonesia capital market nowadays is growing significant.

Capital market in Indonesia has exist long time before independence of

Indonesia on 1912 in Batavia during the Dutch colonial era. During those

period Indonesia capital market face various conditions such as become

inactive because of the world war and be merger with Surabaya Stock

Exchange and now become Indonesia Stock Exchange. Capital market hold

an important role for the economy of a country because capital market serves

two function all at once. First, capital market serves as an alternative for a

company’s capital resources from the public offering. Second, capital market

serves as an alternative for public investment. Can’t be denied economic

situation in this world full of uncertainly begin with subprime mortgage crisis

happened in US in 2007, the impact be perceived all investors in Indonesia

not only in US. Because of that crisis that happened and the uncertainly

economics situation, investors mostly fell doubts to do investment.

Nowadays Indonesia capital market already have 482 public companies that

listed their shares. In Indonesia Stock Exchange there are 14 stock price index

such as Jakarta Composite Index (JCI), MBX, KOMPAS100, LQ45, DBX,

Jakarta Islamic Index (JII), INFOBANK15, IDX30, PEFINDO25, BISNIS-

27, SMinfra18, SRI-KEHATI, MNC36, and ISSI. Consist of 10 sectorial

which is agriculture, mining, basic industry and chemicals, miscellaneous

industry, consumer goods industry, property and real estate, infrastructure

utilities and transportation, finance, and trade services and investment.

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Based on that stock price index, in this research the researcher will explore

more about Jakarta Composite Index. Jakarta Composite index describe

Indonesia capital market conditions, if Jakarta Composite Index was decline

means Indonesia capital market was declining condition with declining of

stock price and vice versa. To ensure that Jakarta Composite Index will

reflect fair market condition, Indonesia Stock Exchange has the right to

choose one or several listed companies from the calculation of Jakarta

Composite Index (Indonesia Stock Exchange, 2010).

Figure 1.1 Jakarta Composite Index Performance

Source: IDX Research Division

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In these year on Mei, Jakarta Composite Index set the highest level at

5214.976 point but after that Jakarta Composite Index was declining because

get impact from various factors until now Jakarta Composite Index looks

difficulty to going up again to 5214.976 point (Indonesia Stock Exchange,

2013). Since January 2010 until October 2013, Jakarta Composite Index have

a fluctuated improvement. In 2010 Jakarta Composite Index have a

significant improvement 46.13%, but in 2011 Jakarta Composite Index have

an improvement only 3.20%, in 2012 Jakarta Composite Index have

significant improvement than 2011 12.94%, and in 2013 until October Jakarta

Composite Index improve 5.33%. From that data, Jakarta Composite Index of

course have a good improvement even the improvement still fluctuated.

Table 1.1 Ownership of Indonesia Stock Exchange

Source: Indonesia Central Securities Depository (KSEI)

According the data in Indonesia Central Securities Depository (KSEI) that the

researcher got from IDX Research division, investor in Indonesia capital

market from January 2010 until September 2013 have a fluctuated

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improvement. Why the researcher said fluctuated? Because in 2010, 62.80%

of Indonesia capital market investor are foreigners while 37.20% is local

investor. In 2011 and 2012 the percentage of local investor better than in

2010 which is 40.14% and 41.21%. But the problem in 2013, the percentage

of local investor become smaller than in 2010 which is only 36.49%. Now the

question that come out, why in 2011 and 2013 Jakarta Composite Index have

only a little bit improvement, but if we see the percentage of local investor in

Indonesia Capital Market have an improvement? There are various factors

that will bring impact to Jakarta Composite Index such as Dow Jones Index,

Nikkei Index, Hang Seng Index, and the exchange rate on IDR, BI interest

rate and inflations.

A number of relevant information is required by investors who are interested

in investing money in a capital market, especially in stocks. An efficient

capital market is the market that provide all relevant information about stocks

(Yogi Permana, 2009). Capital market image and performance will become

one factor that determine investor decision to invest their money or no.

Indonesia Stock Exchange have many products that can investor choose for

investment such as equities which is stocks, the second one is bond that

consist of corporate bonds, government bonds, corporate sukuk, state sharia

securities, asset backed securities, the third product is derivatives which is

stock option and index futures contract, the next product is mutual fund and

the last product is sharia (Indonesia Stock Exchange, 2010). Investment in

capital market nowadays become famous for investor because of the return

rate that offered. Stock is one of the famous financial instrument from

Indonesia capital market for investor to invest their money because of the

investment principle “high risk, high return”. How big profit that you will get

it depend on yourself, stock price when you buy and your experiences as

investor. If you are a type of investor that risk taker, stock is the suitable

5

financial instrument for investment because of the profit that you get is

proportional with the risk that you take. But, for investor that have limited

money but want to invest in capital market without experiences, mutual fund

is the suitable product for this type of investor because in this product

investor no need to control their portfolios by themselves, but it controlled by

fund manager.

Investor behaviors formed by the level of confidence and expectation of

return and the risk on the investment they did. Differences level of confidence

and investor expectation generate capital market phenomenon which is

bullish market, the condition of capital market in growing up condition so the

level of confidence and investor expectation quite high make stock price and

market capitalization going up and the second phenomenon is bearish market,

the condition of capital market in declining conditions so the level of

confidence and investor expectation going down make stock price decline

until touch bottom level, even though fundamental factors and financial

condition of public companies quite healthy. According to Natalia Christanti

and Linda Ariany Mahastanti in her journal, the factor that considered

investor’s decisions is neutral information and accounting information factor.

But for female investor, they consider many factor than male investor. For

educational level with high educational level makes the investor pay attention

to the factor that associated with investment decision, but for the investors

who invest for 1-3 years old considering many factor before making

investment decision (Natalia Christanti, 2011). There are six factors that bring

positive influence on investor behavior such as expected corporate earnings,

get rich quick, stock marketability, past performance of the firm’s stock,

government holdings and the creation of the organized financial market.

There are five factor that bring the least influencing factor on investor

behavior like expected losses in other local investments, minimizing risk,

6

expected losses in international financial market, family member opinions

and good felling on economy (Al-Tamimi, 2005). Real investor are

influenced by the media, they tend to buy rather than sell, stocks when those

stocks are in the news. This attention based buying can lead investors to trade

too speculatively and has the potential to influence the pricing of stocks. In

theory, investors hold well diversified portfolios and trade infrequently so as

to minimize taxes and other investment costs, but in practice investors behave

differently, they trade frequently and have perverse stock selection ability,

incurring unnecessary investment costs and return losses (Brad M. Barber,

2011).

1.2. Problem Identification Based on the background of study before, Indonesia Stock Exchange from

January 2010 until October 2013 has a fluctuated improvement. On Mei

2013, Jakarta Composite Index set the highest record for Indonesia Capital

Market. Based on that problem, in this research the researcher want to know

or analyze what exactly the factor that bring significant influence toward

Jakarta Composite Index. For this research, researcher will used six

independent variables and one dependent variable. The variables that will be

used for this research are Dow Jones Index, Nikkei Index, Hang Seng Index,

the Exchange Rate on IDR, BI Interest Rate and Inflation as independent

variable and Jakarta Composite Index as dependent variable. Based on this

reason, in this research the researcher decided to make this skripsi with topic

“The influence of Dow Jones Index, Nikkei Index, Hang Seng Index,

Exchange Rate on IDR, BI Interest Rate and Inflation towards Jakarta

Composite Index period 2010 to 2013” to analyze what factors from that six

independent variables that has significant influence towards Jakarta

Composite Index.

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1.3. Statement of Problem There are many factors that could affect the Jakarta Composite Index. The

factors that are identified are:

1. Dow Jones Index

2. Nikkei Index

3. Hang Seng Index

4. Exchange Rate on IDR

5. BI Interest Rate

6. Inflation

The factors above might be has significant influence towards Jakarta

Composite Index. Based on the matter the problem can be composed as the

question below:

1. Partially, are there any significant influence of the following factors

towards Jakarta Composite Index?

a. Dow Jones Index

b. Nikkei Index

c. Hang Seng Index

d. Exchange Rate on IDR

e. BI Interest Rate

f. Inflation

2. How large the contribution simultaneously of Dow Jones Index,

Nikkei Index, Hang Seng Index, Exchange Rate on IDR, BI Interest

Rate and Inflation towards Jakarta Composite Index?

1.4. Research Objective In this research, there are several objectives that the researcher would like to

achieve:

8

1. Partially:

a. To find out is there any significant influence between Dow

Jones Index towards Jakarta Composite Index.

b. To find out is there any significant influence between Nikkei

Index towards Jakarta Composite Index.

c. To find out is there any significant influence between Hang

Seng Index towards Jakarta Composite Index.

d. To find out is there any significant influence between BI

Interest rates towards Jakarta Composite Index.

e. To find is there any significant influence from Exchange Rate

on IDR towards Jakarta Composite Index.

f. To find out is there any significant influence between inflation

towards Jakarta Composite Index.

2. Simultaneously:

a. To find out is there any simultaneously influence between

Dow Jones Index, Nikkei Index, Hang Seng Index, BI Interest

Rate, Exchange Rate on IDR and Inflation towards Jakarta

Composite Index.

1.5. Research Limitation For this research, the researcher will take data that needed from Indonesia

Stock Exchange and Yahoo Finance because all data about Indonesia capital

market is available in there. However, this research conducted focus in case

of Jakarta Composite Index as a dependent variable though Indonesia Stock

Exchange has 14 stock prices index exist. In this research, the researcher will

use six independent variables which are Dow Jones Index, Nikkei Index,

Hang Seng Index, BI Interest Rate, Exchange Rate on IDR and Inflation. The

data for this research will focus on case from January 2010 – October 2013.

9

1.6. Benefit of the study From this research, there are several benefits that will get such as:

1. For Researcher:

This research has important meaning for the researcher, not only as the

requirement that researcher have to fulfill in order to get bachelor degree

and to graduate from university, through this research also give chance for

researcher to apply and implement what researcher have learned in the

class into practical study. This research also gives researcher more

knowledge and information about the development of Indonesia capital

market.

2. For Readers:

a. This research could help readers to know and learn kind of factors

that bring influences to Jakarta Composite Index.

b. The readers also may find out the improvement of Jakarta

Composite Index from period 2010 - 2013.

3. For Indonesia Stock Exchange:

a. Indonesia Stock Exchange can determine dominant factors that

bring influence to Jakarta Composite Index, so company can

prepare the strategy to minimize the impact.

1.7. Assumptions and Hypothesis Based on the objective research above, there are six independent variables

that will be tested to Jakarta Composite Index. Those independent variables

are variables that could influence the movement of Jakarta Composite Index.

The assumptions of this research are as follow:

1. There is significant influence between Dow Jones Index towards Jakarta

Composite Index.

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2. There is significant influence between Nikkei Index towards Jakarta

Composite Index.

3. There is significant influence between Hang Seng Index towards Jakarta

Composite Index.

4. There is significant influence between Exchange Rate on IDR towards

Jakarta Composite Index.

5. There is significant influence between BI Interest rates towards Jakarta

Composite Index.

6. There is significant influence between inflation towards Jakarta Composite

Index.

7. There is simultaneously influence between Dow Jones Index, Nikkei

Index, Hang Seng Index, BI Interest Rate, Exchange Rate on IDR and

Inflation towards Jakarta Composite Index.

The hypothesis of this research are follows as:

Hypothesis 1: There is significant influence of Dow Jones Index towards


Hypothesis 2: There is significant influence of Nikkei Index towards Jakarta

Composite Index.

Hypothesis 3: There is significant influence of Hang Seng Index towards


Hypothesis 4: There is significant influence of Exchange Rate on IDR

towards Jakarta Composite Index

Hypothesis 5: There is significant influence of BI Interest Rate towards

Jakarta Composite Index

Hypothesis 6: There is significant influence of Inflation towards Jakarta

Composite Index

11

Hypothesis 7: There is simultaneously influence of Dow Jones Index Nikkei

Index, Hang Seng Index, Exchange Rate on IDR, BI Interest

Rate and Inflation towards Jakarta Composite Index

1.8. Theoretical Framework The movement of Jakarta Composite Index even it increases or decreases

influenced by many factors that can come from foreign factors and domestic

factors. In this research, the researcher will focus with foreign factors which

is foreign index that become benchmarks and domestic factors which is

related with Indonesia Economics.

Figure 1.2 Theoretical Framework

Source: Self developed by researcher

12

Based on the theoretical framework above, this research will focus on Jakarta

Composite Index as an independent variable and there are six dependent

variable which are Dow Jones Index, Nikkei Index, Hang Seng Index as part

of foreign market index and there are BI Interest Rate, Exchange Rate on IDR

and Inflation as part of macroeconomic variables.

1.9. Research Outlines To obtain the overall overview of the research, the researcher is being

outlined into five chapters as follows:

CHAPTER I : INTRODUCTION

This chapter gives the description of the background of the

study, problem identified, research objectives, significance of

study, theoretical framework, scope and limitations and

hypothesis of the research.

CHAPTER II : LITERATURE REVIEW

This chapter contains literature review which consists of the

financial market and its type and previous research are also

included in the chapter.

CHAPTER III : RESEARCH METHODOLOGY

This chapter contains the research methodology of the study.

It explains the research method, research instrument,

sampling design, testing the hypothesis and limitations of

doing the research.

13

CHAPTER IV : ANALYSIS OF DATA AND INTERPRETATION OF

RESULT

This chapter elaborates the analysis of the observed data

which contains descriptive statistics, classic assumption test,

path analysis and hypothesis testing.

CHAPTER V : CONCLUSION AND RECOMMENDATIONS

This chapter contains conclusion of the research analysis

from previous chapters and includes recommendations to be

concerned.

1.10. Definition of terms Some terms of this study are used according to the following operational

definitions for clearer and more meaningful interpretation of the concept used

in this study:

a. Investment: is an asset or item that is purchased with expectation that

will generate income, profit or appreciate in the future.

b. Capital market: is a market in which individuals and institutions trade

financial securities.

c. Merger: is the combining of two or more companies, generally by

offering the stockholders of one company securities in acquiring

company in exchange for the surrender of their stock.

d. Stock Price Index: is a figure based on the current market price of a

certain group of shares or stocks on a stock exchange.

e. Jakarta Composite Index (JCI): is an index of all stocks that trade on

the Indonesia Stock Exchange.

f. MBX: is a market capitalization weighted index that consists of all

stock that listed in main board.

14

g. KOMPAS100: is a market capitalization weighted index that consists

of 100 chosen stocks based on liquidity consideration and market

capitalization with the criteria determined before.

h. LQ45: is a market capitalization weighted index that captures the

performance of 45 most liquid companies listed on the Indonesia

Stock Exchange.

i. DBX: is a market capitalization weighted index that consists of all

stock listed in development board.

j. Jakarta Islamic Index (JII): is a market capitalization weighted index

that use 30 stocks that chosen from listed sharia stocks.

k. INFOBANK15: is a market capitalization weighted index that use 15

chosen bank stocks listed in financial sector.

l. IDX30: is a market capitalization weighted index that use 30 chosen

stocks based on transaction activities including transaction value,

frequency, transaction days and market capitalization.

m. PEFINDO25: is a market capitalization weighted index with

cooperation between Indonesia Stock Exchange and Pefindo that use

25 chosen stocks based on total assets, return on equity and public

accountant opinion.

n. BISNIS-27: is a market capitalization weighted index with

cooperation between Indonesia Stock Exchange and Bisnis Indonesia

that use 27 chosen stocks based on fundamental criteria, technical and

accountability.

o. SMinfra18: is a market capitalization weighted index with cooperation

between Indonesia Stock Exchange and PT Sarana Multi Infrastruktur

that use 18 chosen stocks in infrastructure sector.

p. SRI-KEHATI: is a market capitalization weighted index with

cooperation between Indonesia Stock Exchange and Yayasan

15

Keanekaragaman Hayati Indonesia that use 25 chosen stocks based on

total asset, price earnings ratio and free float criteria.

q. MNC36: is a market capitalization weighted index with cooperation

between Indonesia Stock Exchange and MNC that use 36 stocks based

on transaction liquidity, fundamental factor and market capitalization.

r. ISSI: is a market capitalization weighted index that consists of all

sharia stocks based on Daftar Efek Syariah (DES).

s. Bullish Market: is a financial market of a group of securities in which

price are rising or expected to rise.

t. Bearish Market: is a market condition in which prices of securities are

falling and widespread pessimism causes the negative sentiment to be

self-sustaining.

u. Dow Jones Index: is a price weighted average of 30 significant stocks

traded on the New York Stock Exchange and the NASDAQ.

v. Nikkei Index: is a price weighted index comparison of Japan’s top 225

blue chips companies on the Tokyo Stock Exchange.

w. Hang Seng Index: is a market capitalization weighted index of 40 of

the largest companies that trade on the Hong Kong Exchange.

16

CHAPTER II

LITERATURE REVIEW

2.1. Definition of Investment Investment is from invest means invest our money or capital. Investing

according to Warren Buffett is often described as the process of laying out

money now in the expectation of receiving more money in the future (Warren

Buffett, 2012). In economics, an investment is the purchase of goods that are

not consumed today but are used I the future to create wealth. While in

finance, an investment is a monetary asset purchased with the idea that the

asset will provide income in the future or appreciate and be sold at a higher

price. According to Ken Little investing is the proactive use of your money

to make more money or to say it another way, it is your money working for

you (Ken Little, 2009.). Investing is different from saving, saving is a passive

activity even though it uses the same principle of compounding. Saving is

more focuses on safety of principal (the amount you start out with) and less

concerned with return. While in investing out focus is on return and can run

the spectrum from conservative to very aggressive in term of return. For some

people, they thought if does saving means they do investment, that’s the

wrong concept of investment. Investment means we invest our money first,

before expense it not vice versa and investment have concept in expense we

buy the thing that needed not what you wants.

Investment can be divided into different types according to various theories

and principles. Investment in term of economics is defined as the per-unit

production of goods, which have not been consumed but will however, be

used for the purpose of future production. Investment in term of business

management refers to tangible assets like machinery and equipment’s and

17

buildings and intangible assets like copyrights or patents and goodwill.

Investment in terms of finance refers to the purchasing of securities or other

financial assets from the capital market. Investment in terms of personal

finance is the implementation of money for buying shares, mutual funds or

assets with capital risk. Investment in term of Real Estate is referred to as

money utilized for buying property for the purpose of ownership or leasing.

2.2. Definition of Capital Market Capital market is a market where buyers and sellers engage in trade of

financial securities. Capital market according to Mike Moffatt is simply any

market where a government or a company (usually a corporation) can raise

money (capital) to fund their operations and long term investment (Mike

Moffatt, 2009.). There are two types of capital market which are primary

market and secondary market. Primary market is the market where shares are

offered to investors by the issuer company to raise their capital. Secondary

market is the market where stocks are traded after they are initially offered to

the investor in primary market and get listed to stock exchange (what is

primary and secondary market, 2007). Capital market has been a leading

indicator of economy since capital market is a central function of a country

economic. The economic performance of the country could be measure from

the performance of the capital market in that country. The functions of capital

market are as follow:

a. Provide source of fund for business simultaneously enable

optimal fund allocation.

b. Provide investment media for investor and simultaneously

enable diversity effort.

c. Provide leading indicator for countries economic trend.

d. Spread the ownership of a firm to public.

18

e. Provide the opportunity to own a healthy and prospective firm.

f. Provide attractive job opportunity.

g. Provide security trading liquidity.

h. Spread of ownership, openness and professionalism and create

healthy business climate.

(Hazimi Bimaruci Hazrati Havidz, 2012)

2.3. Investment Products in Capital Market There are various investment products that can be used for an investor to

make their more wealth such as:

1. Share / Stocks: a sign of capital participation of an individual or

institution in a company or corporation.

a. Benefits that an investors can get by buying or having stocks:

i. Dividend: is profit sharing given by company and comes

from the income. Dividend is given after getting the

agreement from shareholders in the general meeting. If an

investor wants to receive dividend, they must own the stock

for a relatively long period, until the ownership term is in

the period where they is acknowledged as the shareholder

who has the right to obtain the dividend.

ii. Capital gain: Is the different buying price and selling price.

Capital gain is obtained through the trading activities

carried out the secondary market.

b. Risks of stocks:

i. Capital loss: it is a condition when the investor sells their

shares at lower price than its buying price.

19

ii. Liquidity risk: a company, whose shares are owned by

public, is started for bankruptcy by the Court or is being

dismissed.

2. Bonds: is a fixed interest financial asset issued by governments,

companies, banks, public utilities and other large entities. Bonds that

listed in Indonesia Capital Market consist of:

a. Corporate Bonds is bond issued by national private company

including BUMN and BUMD.

b. Government Bonds is bond issued by the government in

accordance with Law No. 22 Year 2002, including: State Bond

(Bond Retail/ORI) and Treasury Bills (T-Bills).

c. Corporate Sukuk is a fixed income instruments are issued based

on Sharia principles in accordance with Bapepam-LK Rule No.

IX. A. 13 concerning Sharia Securities.

d. State Sharia Securities/SBSN or Corporate Sukuk is Securities

issued by the government based on Sharia in Accordance with

Law No. 19 Year 2008 concerning Government Sharia Securities

(SBSN).

e. Asset- Backed Securities (ABS) is debt securities issued with

underlying assets as the basis.

3. Mutual Fund: is a mean to collect fund from the investment society to

be invested in portfolios by the fund manager.

a. Benefit of investing in Mutual Fund:

i. Investor with smaller budget can do investment

diversification in their securities to minimize the risks.

ii. Mutual Fund helps the investor to invest in capital market

easier.

20

iii. Time efficiency, since the fund invested in the mutual fund

is managed by a professional fund manager, investor no

need to monitor their investment performance all the time.

b. Risk of investing in Mutual Fund:

i. Risk of decreased value of participating unit: the risk is

influenced by the decrease price of securities that included

in the Mutual Fund portfolio.

ii. Liquidity risk: the risk is related to the difficulty faced by

the fund manager if most of the unit holders resell

(redemption) their unit.

iii. Default risk: the risk is the worst risk, which can emerge

when insurance company that insures the Mutual Fund’s

wealth does not pay the indemnity or pay lower than the

loading value when unwanted condition happens.

4. Derivatives: is a financial security whose value is derived from the

value of another security (underlying asset) such as equity or debt

instrument. In a more specific definition, derivative is a traded

financial contract between two or more parties to buy or sold an

asset/commodity on an agreed time and price.

5. Sharia: is part of the sharia finance industry such as sharia banking

and sharia insurance.

2.4. Jakarta Composite Index (JCI) Jakarta Composite Index is one of the market index that exist in Indonesia

Capital Market. Jakarta Composite index is a modified capitalization

weighted index of all stocks listed on the regular board of the Indonesia Stock

Exchange. One of the consideration to ensure that Jakarta Composite Index

will reflect fair market is the listed company’s public shares are owned only

by a few shareholders (small free float) while its market capitalization is

21

relatively high, and as a result the price change of the Listed Company’s

stock may potentially affect the reasonable fluctuation of the Jakarta

Composite Index.

Jakarta composite index is one of the main indicators that representative

capital market condition, it was bearish or bullish. Bearish means Indonesia

capital market performance in going down position, while bullish means

Indonesia capital market performance in going up position. The movement of

Jakarta Composite Index would influence investor interest in hold, sell or buy

the stocks. The formula to calculate the value of Jakarta Composite Index as

follow:

𝐽𝐶𝐼 = ∑(𝑅𝑒𝑔𝑢𝑙𝑎𝑟 𝐶𝑙𝑜𝑠𝑖𝑛𝑔 𝑃𝑟𝑖𝑐𝑒 ∗ 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑠ℎ𝑎𝑟𝑒𝑠)

𝐵𝑎𝑠𝑒 𝑉𝑎𝑙𝑢𝑒∗ 100

Where:

𝐵𝑎𝑠𝑒 𝑉𝑎𝑙𝑢𝑒 = �(𝐵𝑎𝑠𝑒 𝑃𝑟𝑖𝑐𝑒 ∗ 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑆ℎ𝑎𝑟𝑒𝑠)

To calculate the Jakarta Composite Index, Base Price and Base Value are

adjusted when bonus and rights issues, share splits and consolidations are

made. Base price for new listed companies is IPO Price.

2.5. Dow Jones Index Dow Jones Index is the best known U.S. index of stocks. A price weighted

average of 30 actively traded blue chip stocks, primarily industrials including

stocks that trade on the New York Stock Exchange. The Dow, as it is called,

is a barometer of how shares of the largest US companies are performing

(NASDAQ, 2010). Dow Jones Industrial Average Index introduced in May

1896, the index also referred to as The Dow. The index covers all industries

22

with the expectation of transportation and utilities, which are covered by the

Dow Jones Transportation Average and Dow Jones Utility Average.

2.6. Nikkei Index Nikkei 225 is the most popular benchmark for the Japanese and Asian stock

markets. The index consist of 225 largest companies on the Tokyo Stock

Exchange by market capitalization and liquidity. Japan’s economy is the third

largest in the world, behind the United States and China. And its primary

stock exchange is a very influential financial capital in Asia. Tokyo Stock

Exchange has about 2, 292 listed companies with a combined market

capitalization of US $3.8 trillion as of December 2010, making it the third

largest stock exchange in the word (Justin Kuepper, 2011.).

2.7. Hang Seng Index Hang Seng Index is the most popular stock market index in Hong Kong stock

exchange. Hang Seng Index is a market capitalization weighted index of 40 of

the largest companies that are trade on the Hong Kong Stock Exchange. The

Hang Seng is maintained by a subsidiary of Hang Seng Bank and has been

published since 1969. The index aims to capture the leadership of the Hong

Kong stock Exchange. Hang Seng Index formula to calculate it as follow:

Hang Seng Index

= ∑[𝑃(𝑡) ∗ 𝐼𝑆 ∗ 𝐹𝐴𝐹 ∗ 𝐶𝐹]

∑[𝑃9𝑡 − 1) ∗ 𝐼𝑆 ∗ 𝐹𝐴𝐹 ∗ 𝐶𝐹]∗ 𝑌𝑒𝑠𝑡𝑒𝑑𝑎𝑦 𝐶𝑙𝑜𝑠𝑠𝑖𝑛𝑔 𝐼𝑛𝑑𝑒𝑥

Where:

23

P (t) : Current Price at Day – t

P (t-1) : Closing Price at Day (t-1)

IS : Issued Shares (Only H-share portion is taken into calculation

in case of H-share constituents.

FAF : Freefloat-adjusted Factor, which is between 0 and 1, adjusted

quarterly.

CF : Cap Factor, which is between 0 and 1, adjusted quarterly.

2.8. Exchange Rate on IDR Exchange rate is the price of one country’s currency expressed in another

country’s currency (Exchange Rate definition, 2010). Mostly exchange rates

are determined by the foreign exchange market, known as forex. For this

reason, exchange rates vary on a moment by moment basis, depending on

what traders think the currency is worth (Kimberly Amadeo, 2009.).

Exchange rate is differentiated into two which are nominal exchange rate and

real exchange rate. Nominal exchange rate refers to currency relatively price

between two countries while real interest rate refers to goods relatively price

between two countries. Basically, there are three system of exchange rate

which are:

1. Fixed exchange rate that could be done by pegged to a currency or

pegged to a basket of currency. Pegged to a basket currency is a

weighted exchange rate of a currency that adjusted to the amount of

trade and investment relationship.

2. Floating exchange rate is an exchange rate system in which the value

of exchange rate are left to move by the power of supply and demand

in the market. Thus, the exchange will increase if the supply of

exchange rate is more than the demand of exchange rate.

24

3. Managing floating exchange rate is the combination of fixed exchange

rate and floating exchange rate system.

(Havidz, The influence of Domestic and Foreign factos to Indonesia

Composite Index, 2012).

2.9. BI Interest Rate The BI Rate is the policy rate reflecting the monetary policy stance adopted

by Bank Indonesia and announced to the public. The BI Rate is announced by

the Board of Governors of Bank Indonesia in each monthly Board of

Governors Meeting. It’s implemented in the Bank Indonesia monetary policy

operational target. The monetary policy operational target is reflected in

movement in the Interbank Overnight (O/N) rate. It is then expected that bank

deposit rates will track the movement in interbank rates, with bank lending

rates following suit. While the other factors in the economy are also taken

into account, Bank Indonesia will normally raise the BI Rate if future

inflation is forecasted ahead of the established inflation target. Conversely,

Bank Indonesia will lower the BI Rate if the future inflation is predicted

bellow the inflation target (Bank Indonesia, 2013.).

There are two types of interest rate, nominal interest and real interest rate. Real

interest rate is the rate that creates equilibrium between the supply of saving

and the demand of for investment funds in a perfect world without inflation,

where funds suppliers and demanders are indifferent to the term of loans or

investments because they have no liquidity preference and where all outcomes

are certain. Nominal interest rate us the actual rate of interest charged by the

supplier of fund and paid by the demander (Mike Moffatt, 2009). The increase

of interest rate is a negative indicator for share price because it would increase

the prices of capital thus increases firm’s expense that would affect to the shift

of investment from shares to saving. If interest rate increases, it will directly

25

increase the charge for interest rate. The increase of interest rate would make

investors move their fund to saving. It would happen because high interest rate

would increase the return of saving. In the other side saving is a free risk

investment like what investor wants.

2.10. Inflation According to Rahardja, 1997 Inflation is the tendency of prices to rise in

general and continuous. The increase in the price of one or two items not

called inflation, but if it extends to most of the increase in the price of the

goods then this is called inflation. According to Eachern, 2000 inflation is

persistent rise in the average price level. If the price level fluctuates, this

month and next month climbed down, every price level fluctuates not

necessarily mean an increase in the inflation. Sukirno, 2004 stated inflation is

a rise in the prices prevailing in an economy. There are various theories the

foundation of inflation can happen as follows;

1. Quantity Theory, inflation is caused by money supply exceeds the

needs and expectations of the public about trends or forecasts rise

in prices in the future.

2. Keynes theory, inflation caused by the total demand for goods and

services exceeds the ability of society to produce.

3. Structuralists theory, inflation is a natural accompaniment to

economic growth, so that inflation cannot be controlled through

fiscal or monetary policies without causing unemployment or

stagnation in economic growth.

In simple terms, inflation is understood as a persistent, ongoing rise across a

broad spectrum of prices. An increase in prices for one or two goods alone

can’t be described as inflation unless that increase spreads to (or leads to

26

escalating prices for) other goods. The reverse of inflation is deflation. The

indicator commonly used to measure the level of inflation is the Consumer

Price Index (CPI). Changes in the CPI over time are indicative of price

movement for packages of goods and services consumed by the public. Since

July 2008, the packages of goods and services in the CPI have been based on

the 2007 Cost of Living Survey conducted by the Statistics Indonesia (BPS).

The other inflation indicators used in international best practice include:

1. Wholesale Price Index: is the price of transactions taking place

between the first wholesaler and the next largest trader for

large quantities on the first market for a commodity.

2. The Gross Domestic Product (GDP) Deflator: the

measurement of price level for the final goods and services

produced within an economy. The GDP Deflator is derived by

dividing GDP base on nominal prices by GDP based on

constant prices.

2.11. Previous Journal 1. Fajar Budhi Darmawan, 2009 in his research with the title “Pengaruh

Indeks DJI, FTSE 100, NKY225, Dan HSI terhadap Indeks Harga

Saham Gabungan Sebelum, Ketika, Dan Sesusah Subprime

Mortagage Pada Tahun 2006 – 2009”. The global stock markets

represented by Dow Jones, FTSE100, Nikkei 225 and Hang Seng

Stock Index. This research results show that Dow Jones, FTSE, and

NKY 225 has influence towards Jakarta Composite Index. While

Hang Sheng Index doesn’t have Granger causality towards JCI and

vice versa.

2. Alkhairani, 2012, “Analisis Pengaruh Indeks Saham Asia Terhadap

Indeks Harga Saham Gabungan (IHSG) di Bursa Efek Indonesia

27

(BEI) Periode 2009-2011”. The simple sampling data of 36 months

during on January 2009 until Desember 2011. Tests carried out by the

method of multiple linear regression. The results indicate that Nikkei,

Hang Seng and Strait Times significant effect on the Jakarta

Composite Index (IHSG). Based on the test results the coefficient of

determination, the value of the adjusted R Square of 85.7% while the

remaining 14.3% is influence by other variables not included in this

research as state the global economy, trade relations between other

country, social, politic, security, and issued that provide certain

sentiment to the trade shares on the Indonesia Stock Exchange.

3. Ali Fikri Hasibuan and Taufik Hidayat, 2011, “Pengaruh Indeks

Harga Saham Global terhadap Pergerakan Indeks Harga Saham

Gabungan (IHSG)”. The sample that used in the research were Global

Index of during 2001 – 2008, total sample used amount to 96 sample.

Model the analysis used in this research is multiple regression

analysis. The result of the research stated that, simultaneously there

was a significant correlation between Global Index (Nasdaq, Taeix,

Nikkei, Kospi) to IHSG the Fhitung > Ftabel (392,507 > 4, 42). Partially

there was no significant correlation among taeix index and Nikkei

index to IHSG, but there was a significant correlation among Global

Index (Nasdaq and Kospi) to the IHSG the significance in 5%.

4. Budi Sutanto, Dr. Werner R. Murhadi, S.E.,M.M. and Endang

Ernawati, S.E.,M.Si, 2012, “Analisis Pengaruh Ekonomi Makro,

Indeks Dow Jones, Dan Indeks Nikkei 225 Terhadap Indeks Harga

Saham Gabungan (IHSG) di BEI Periode 2007 – 2011”. The results

indicates that the variables of SBI and World Crude Oil Prices affect

insignificant positive on IHSG. Variable World Gold Price, the Nikkei

28

225 Index and the Dow Jones Index effect on IHSG. While the

exchange rate have a significant negative effect on IHSG. The

coefficient of determination (R2) of 0, 6154. This Indicates that the

stock price index can be explained by variables such as SBI, Oil

prices, the World Gold Prices, Exchange Rate against the dollar, the

Nikkei 225 Index and Dow Jones Index by 61. 54%. While the

remaining 38.46% can be explained by variables outside variables.

5. Joven Sugianto Liaw and Trisnadi Wijaya, 2012, “Analisis Pengaruh

Tingkat Inflasi, Tingkat Suku Bunga SI dan Nilai Tukar Rupiah

terhadap Indeks Harga Saham Gabungan (IHSG) di Bursa Efek

Indonesia”. The results of this research show that the inflation

variable has a significant positive effect on Jakarta Composite Index,

while the variable SBI rate and the exchange rate have a significant

negative effect on the Jakarta Composite Index.

6. Ardy Haryogo, 2013, “Pengaruh Nilai Tukar dan Indeks Dow Jones

Terhadap Composite Index di Bursa Efek Indonesia”. The result

shows that partially the exchange rate has no significant effect to the

Jakarta Composite Index, but Dow jones significant influence the

Jakarta Composite Index. Overall the Exchange Rate and Dow Jones

have significant effect to Jakarta Composite Index.

7. Ria Astuti, Apriatni E. P and Hari Susanta, 2013, “Analisis Pengaruh

Tingkat Suku Bunga (SBI), Nilai Tukar (Kurs) Rupiah, Inflasi Dan

Indeks Bursa International Terhadap IHSG”. The results prove that

Interest Rate (SBI) and Exchange Rate of Rupiah had a negative effect

and significant to Composite Stock Price Index, Inflation had a

negative effect and not significant to Composite Stock Price Index.

29

Meanwhile Nikkei225 and Hang Seng Index had a positive and

significant effect to Jakarta Composite Stock Price Index.

8. Moh. Mansur, 2005, “Pengaruh Indeks Bursa Global Terhadap

Indeks Harga Saham Gabungan (IHSG) Pada Bursa Efek Jakarta

(BEJ) Periode Tahun 2000 – 2002”. The result of the study shows that

simultaneously the stock price index of global stock market

statistically affected the Jakarta Composite Index but individually is

only KOSPI, Nikkei 225, TAIEX and ASX.

9. Aditya Novianto, 2011, “Analisis Pengaruh Nilai Tukar (Kurs) Dolar

Amerika / Rupiah (US$ / Rp), Tingkat Suku Bunga SBi, Inflasi Dan

Jumlah Uang Beredar (M2) Terhadap Indeks Harga Saham

Gabungan (IHSG) di Bursa Efek Indonesia (BEI)”. Based on the

calculation results, can be concluded that the four independent

variables namely the exchange rate rupiah, the rate of 1 month,

inflation and money supply (M2) jointly affect the accepted the

Jakarta Composite Index (IHSG) in Bursa Efek Indonesia (BEI) is

accepted. Partial variable exchange rate rupiah and interest rates have

a significant influence, while the variable inflation and money supply

(M2) was not significant. And of the four variable are the most

dominant influence of Jakarta Composite Index in Bursa Efek

Idonesia (BEI) is variable exchange rate rupiah with count t value of -

9. 280776.

10. Andrew Hartanto, 2013, “Analisa Hubungan Indeks Saham Antar

Negara G20 dan Pengaruh terhadap Indeks Harga Saham

Gabungan”. The result showed that partial DJIA, Nikkei 225 and SSE

significant effect on IHSG and together DJIA, Nikkei 225, KOSPI,

30

Hang Seng, SSE, FTSE, DAX, CAC and ASX significant effect on

the index. Granger causality test performed 36 times Granger Pairwise

Causality Test. Results of causality test showed that many mutual

indices have correlation among them. However, it can be concluded

CAC, FTSE and Hang Seng Index is the most influential to IHSG

compared with others.

31

CHAPTER III

METHODOLOGY

3.1. Research Method In order to make this research, there are two method with different and

distinguish to each other’s which is quantitative and qualitative method. The

main difference thing between quantitative and qualitative method is

quantitative method is more focused on the number and utilizing of statistical

tools, while on the other side qualitative method is more focused on the

comparison and usage of many theories from various of source. However

even though this two method have difference thing but both of this method

have its own advantages and disadvantages. A quantitative method is often

used with aim to verify or prove existing theories or test hypothesis

developed based on the previous research. While in the other side qualitative

method is required it’s used to collecting, analyzing, have a deeper

understanding of the problem identification and interpreting that can’t be

stated in numbers.

For make this research, the researcher will used quantitative research as the

research method. According to Nokuthaba Sibanda quantitative research

focuses on gathering numerical data and generalizing it across groups of

people (Dr. Nokutbaha Sibanda, 2009). Quantitative research is a formal,

objective, systematic process in which numerical data are used to obtain

information about the world and this research method is used for to describe

variable, examine relationship among variables and to determine cause-effect

interactions between variable (Burns N and Grove S. K., 2005). According to

Aliaga and Gunderson, 2000 quantitative research is explaining phenomena

by collecting numerical data that are analyzed using mathematically based

32

method (in particular statistics). According to Cohen, L. quantitative research

is defined as social research that employs empirical methods and statements

(Cohen L and Manion L, 1980). Empirical method means research method in

which empirical observations or data are collected in order to answer

particular research questions (Daniel Moody, 2002). Empirical method also

means a descriptive statement about what is the case instead of what should to

be the case. Empirical method is based on observed and measured phenomena

and derives knowledge from actual experience rather than from theory or

belief (Dawn Amsberry, 2008).

Quantitative research usually used for explaining phenomena that happening.

For this quantitative research there are some steps to do, first is identify the

problem for this case. After first step collect the data that needed. Next is data

processing in this step the data that collected in first step by using excel. The

fourth step is research analysis in this step we make analysis of data that

already process by using Statistical software. The last step is make conclusion

and recommendation based on the problem that identified and the analysis

result.

3.2. Research Instruments

3.2.1 Research Variables

The research variables of this model are the variables which are

mentioned in the hypothesis of the research.

3.2.1.1 Independent Variable

Independent variable is the variable which explains or affects the

other variables. There are six independent variables consist of three

variables from foreign factors and three variables from domestic

factors in this research which are:

33

a. Dow Jones Index

b. Nikkei Index

c. Hang Seng Index

d. Exchange Rate on IDR

e. BI Interest Rate

f. Inflation

3.2.1.2 Dependent Variable

Dependent variable is the variable which is explained or affected

by the independent variables. There is only one dependent variable

in this research, which is Jakarta Composite Index. Through this

model, the researcher is trying to explain the factor that has

significant influence factors of Jakarta Composite Index.

3.2.2 Type and source of data

The data of this research are secondary data of Jakarta Composite

Index and its determinants 46 sample for each variable of this research

from the period of January 2010 to October 2013. The data which is

collected and used in this research is monthly secondary data, which

are:

1. Data of Jakarta Composite Index monthly in the period of January

2010 until October 2013, which the researcher take from Yahoo

Finance website. The figure 3.1 bellow shown the data observed

of Jakarta Composite Index in this research.

34

Figure 3.1 Jakarta Composite Index Closing Price Trend (January 2010 - October 2013)

Source: Yahoo Finance

2. Data of Dow Jones Index monthly in the period of January 2010

until October 2013, which the researcher take from Yahoo Finance

website. The figure 3.2 bellow shown the data observed of Dow

Jones Index in this research.

Figure 3.2 Dow Jones Index Closing Price Trend (January 2010 - October 2013)


35

3. Data of Nikkei Index monthly in the period of January 2010 until

October 2013, which the researcher take from Yahoo Finance

website. The figure 3.3 bellow shown the data observed of Nikkei

Index in this research.

Figure 3.3 Nikkei Index Closing Price Trend (January 2010 - October 2013)


4. Data of Hang Seng Index monthly in the period of January 2010

until October 2013, which the researcher take from Yahoo Finance

website. The Figure 3.4 bellow shown the data observed of Hang

Seng Index in this research.

36

Figure 3.4 Hang Seng Index Price Trend (January 2010 - October 2013)


5. Data of Exchange Rate on IDR monthly in the period of January

2010 until October 2013, which the researcher take from BI

website. The Figure 3.5 bellow shown the data observed of the

Exchange Rate on IDR in this research.

Figure 3.5 Exchange Rate on IDR Trend (January 2010 - October 2013)


0

2.000

4.000

6.000

8.000

10.000

12.000

14.000

Jan-

10

Apr-

10

Jul-1

0

Okt

-10

Jan-

11

Apr-

11

Jul-1

1

Okt

-11

Jan-

12

Apr-

12

Jul-1

2

Okt

-12

Jan-

13

Apr-

13

Jul-1

3

Okt

-13

the Exchange Rate on IDR

37

6. Data of BI Interest Rate monthly in the period of January 2010

until October 2013, which the researcher take from BI website.

The Figure 3.6 bellow shown the data observed of BI Interest Rate

in this research.

Figure 3.6 BI Interest Rate Trend (January 2010 - October 2013)


7. Data of Inflation monthly in the period of January 2010 until

October 2013, which the researcher take from BI website. The

figure 3.7 bellow shown the data observed of Inflation in this

research.

0,00%1,00%2,00%3,00%4,00%5,00%6,00%7,00%8,00%

8 O

kt 2

013

29 A

gust

201

313

Juni

201

311

-Apr

-13

12-F

eb-1

311

Des

201

211

Okt

201

29

Agus

t 201

212

Juni

201

212

-Apr

-12

9-Fe

b-12

8 De

s 201

111

Okt

201

19

Agus

t 201

19

Juni

201

112

-Apr

-11

4-Fe

b-11

3 De

s 201

05

Okt

201

04

Agus

t 201

03

Juni

201

06-

Apr-

104-

Feb-

10

BI Rate

38

Figure 3.7 Inflation Trend (January 2010 - October 2013)

Source: Bank of Indonesia

3.2.3. Data Analysis

Multiple regressions would researcher use to analyze the data of this

research in order to build the best model of this study and to explain

the influence partially and simultaneously of Dow Jones Index, Nikkei

Index, Hang Seng Index, Exchange Rate on IDR, BI Interest Rate and


The research process will be simply described as following in the

figure 3.8 Research Framework.

39

Figure 3.8 Research Framework


The research framework is explained as the following.

1. Identify the problem of this case or find out what researcher

want to achieve by this research.

2. Data collection

This is the first step that researcher will do in order to make

this research. The data collection that will be used in this

research is secondary data period January 2010 - October

2013.

a. Collection information related with theory that will be

useful in this resource from many sources such as

books, document in Internet or journal.

Problem Identification

Data Collection

Data Processing

Research Analysis

Conclusion and Recommendation

40

b. Collection previous research as much as possible to

support independent and dependent variables for this

research.

c. Collection data about independent and dependent

variables for period January 2010 – October 2013

3. Processing the data that already researcher collect in the first

step and process the data by using Ms. Excel.

4. Analyzing the data about dependent and independent variable

by using statistical software such as SPSS or EViews and

based on that analysis, the researcher will interpret the result.

5. Making a conclusion based on the result of the research and

statement of problem that already constructed in chapter one

and then make a recommendation based on researcher

experience in make this thesis.

3.3. Classic Assumption Test There are classic assumptions that should be satisfied in using multiple

regression analysis which are Statistic Descriptive test, normality test,

autocorrelation test, multicollinearity test and heteroscedasticity test, multiple

regression model.

3.3.1. Statistic Descriptive test

Descriptive statistics are used simply to describe the sample you are

concerned with. Descriptive statistics are used in the first instance to

get a feel for the data, in the second for use in the statistical tests and

in the third to indicate the error associated with results and graphical

output. Descriptive statistics is the discipline of quantitatively

describing the main features of a collection of data or the quantitative

description itself. Descriptive statistics are distinguished from

41

inferential statistics (or inductive statistics), in that descriptive

statistics aim to summarize a sample, rather than use the data to learn

about the population that the sample of data is thought to represents.

3.3.2. Normality Test

Normality test is test that used for determined whether the data is well

set – modeled by a normal distribution or not. Normality test could be

done by looking at normal probability plot that compare cumulative

distribution of observe data to cumulative distribution of normal

distribution. Graphical method visualized the distribution of a random

variable compare the distribution to a theoretical one using plot. These

method is either descriptive or theory driven. Normality test is the first

classic assumption test in order to use parametric statistic, which can

be used by implementing Kolmogorov-Smirnov(K-S) and can be seen

through graphic of Normal P-P of regression Standardized Residual

through statistical software application (Rini, 2007 cited by Hazimi

Bimaruci Hazrati, 2012, p. 32).

3.3.3. Autocorrelation test

One of the basic assumptions of regression is the independence of

errors. This assumption is sometimes violated when data are collected

over sequential time period because a residual at any one time period

may tend to be similar to residual at together time period, this pattern

in the residual called autocorrelation. The autocorrelation test is used

to determine whether any correlation between variables in t-period

with variables in prior period (t-1). This test us used only for time

series data and not for cross sectional data. If any correlation exists it

means there is an autocorrelation test (Imam Ghozali, 2009). To

42

determine the autocorrelation within the model, this research will use

Durbin Watson test (DW test).

Where if the number of Durbin Watson test is lower than -2 means

there is positive autocorrelation within the model, if the Durbin

Watson is between -2 until +2 means there is no autocorrelation

within the model and last if Durbin Watson test is greater than +2

means there is negative autocorrelation.

3.3.4. Multicollinearity test

Multicollinearity test is a test that used to know or detect whether any

independent variable that highly correlated to each other’s in the

multiple regression models. Multicollinearity test is an application test

for multiple regression analysis that involve the possible

multicollinearity of the independent variables. The method to measure

multicollinearity is used Variance Inflationary Factor (VIF) to

measure. Normally, Variance Inflationary Factor measure how much

the variance of the estimated coefficients is increased over the case of

no correlation among each independent variable.

According Ardian Agung Witjaksono, 2010 to identify whether

multicollinearity exist in regression model are as follow:

1. The result of R2 value of an empirical regression model estimation

is high but many of the variable independent does not significantly

influence the dependent variable.

2. If there are high correlation between independent variable (usually

above 0, 90) it indicates multicollinearity exist.

3. Multicollinearity could be identify from the value of variance

inflation factor. Multicollinearity exist if the value of VIF is

greater than 10. If there are two or more variable which has VIF

43

value around or greater than 10, it means that two variables has

strong correlation.

The equation of Variance Inflation Factor (VIF) is:

𝑉𝐼𝐹𝑘 = 1

1 − 𝑅 𝑘2

Where:

R2k = the R2 value obtained by regressing the kth predictor on

the remaining predictors. And 𝑅2 = 𝑆𝑆𝑅𝑆𝑆𝑇

SSR = Regression sum of squares

SST = Total sum of square

3.3.5. Heteroscedastisity test

Heteroscedasticity test is used to knowing whether the data is not

normally distributed and it also use to know if the variance terms of

errors are difference across observations. If the variance of the

observed data is different, it is called heteroscedasticity. To identify

the existence of heteroscedasticity is by looking a scatter plot between

distributions of dependent variable towards residual value. There is no

heteroscedastisity if the scatter plot between dependent variable

towards residual value is spread randomly without any systematic

pattern, then the data is passed the heterosscedasticity test (Imam

Ghozali, 2003).

44

3.3.6. Multiple Regression

Multiple regression analysis is one of most useful analysis that used

for type of research that has more than one variable. In this research

there are more than one variables, because of that the researcher used

multiple regression models in order to explain relationship between

dependent variable and those independent variables. The multiple

regression models for this research can be arranged as follows as:

Y= βo + β1X1 + β2X2 + β3X3 + β4X4 + β5X5 +β6X6 + ε

Where:

Y : Jakarta Composite Index

βo : Intercept / constant

β1 – β6 : Regression Coefficient

X1 : Dow Jones Index

X2 : Nikkei Index

X3 : Hang Seng Index

X4 : Exchange Rate on IDR

X5 : BI Interest Rate

X6 : Inflation

ε : Random Error

3.4. Hypothesis Testing Hypothesis testing would be conducted by using multiple regression analysis.

This analysis is used to examine the influence of Dow Jones Index, Nikkei



45

3.4.1 F-Test

F test is a test that uses to determine whether there is a significant

relationship between dependent variable and independent variable. F

test works by statistically test the null hypothesis that there is no linear

relationship between dependent variable and independent variable. In

this research, the researcher will use α = 0.05. H0 is accepted if the f

test value is greater than the level of significance α = 0.05. H0 is

rejected if the F test value is less than the level of significance α =

0.05.

F-Test in this research used to test the hypothesis as following as:

𝐻01:𝛽1 = 𝛽2 = 𝛽3 = 𝛽4 = 𝛽5 = 𝛽6 = 0

(There is no significant influence of X1, X2, X3, X4, X5 and X6 towards

Y)

Ha1: At least one coefficient ≠ 0

(There is significant influence of X1, X2, X3, X4, X5 and X6 towards

Y)

The equation of F-Test is as following:

𝐹 = 𝑀𝑆𝑅𝑀𝑆𝐸

= 𝑆𝑆𝑅/𝑘

𝑆𝑆𝐸/(𝑛 − 𝑘)

Where:

SSR = Sum of squares due to regression

SSE = sum of squares error

46

N = total of observation

K = total of parameter in this model

MSR = mean square due to regression

MSE = mean of squares due to error

(Mudrajad Kuncoro, 2007)

3.4.2 T-Test

T test is used to determine the partial relationship of each independent

variable towards dependent variable. In this research, T test performed

to test the hypothesis whether these variables are significant or not

towards Jakarta Composite Index. The level of significance α is 0.05.

H0: β = 0, if significant t > 0.05, accepted H0

Ha: β =0, if significant t < 0.05, rejected H0

T-Test in this research used to prove the hypothesis as following as:

H01: β1 = 0

(There is no significant influence of X1 towards Y)

Ha1: β1 ≠ 0

(There is significant influence of X1 towards Y)

H02: β2 = 0


Ha2: β2 ≠ 0


H03: β3 = 0

47


Ha3: β3 ≠ 0


H04: β4 = 0


Ha4: β4 ≠ 0


H05: β5 = 0


Ha5: β5 ≠ 0


H06: β6 = 0


Ha6: β6 ≠ 0


The equation of T-Test is as following:

𝑇𝑆𝑇𝐴𝑇 =x̅ − 𝜇𝑆√𝑛

48

Where:

x̅ = sample mean

µ = population mean

S = standard deviation for sample

n = sample size

3.4.3 Coefficient of Determination (R2)

The coefficient of determination test is used in order to see how strong

the influence of independent variable toward dependent variable and

also to know how far the dependent variable can be explained by

independent variables. In this test it will occurs at R2 value and

adjusted R square value. Coefficient determination (R2) can be

analyzed through either R square or adjusted R-square. R-square is

used when the number of independent variable is two. Adjusted R-

square is used when the number of independent variable is more than

two. The value of coefficient of determination (adjusted R-Square) is

range from 0 to 1.

The Value of adjusted R-square is a range from 0 till 1. If the value of

adjusted R-square is close to 0, means that the capability of

independent variables to explain the dependent variable is weak. In

the other side if the value of adjusted R-square is close to 1, means

that the capability of independent variable to explain the dependent

variable is this research is strong.

The scale that used to examine how strong the independent variables

could explain its dependent variable:

49

0 – 0.25 = Very weak correlation

>0.025 – 0.50 = Sufficient correlation

>0.50 – 0.75 = Strong correlation

>0.75 – 1.00 = Very strong correlation

The equation of R2 is as following:

𝑅2 =𝑇𝑆𝑆 − 𝑆𝑆𝐸

𝑇𝑆𝑆= 𝑆𝑆𝑅/𝑇𝑆𝑆

Or to calculate the best multiple regression model can used formula as

following:

𝐴𝑑𝑗𝑢𝑠𝑡𝑒𝑑 𝑅2 = 1 − (𝑛 − 1) �𝑆2

𝑇𝑆𝑆� = 1 − (1 − 𝑅2)[

𝑛 − 1𝑛 − 𝑘

]

(Mudrajad Kuncoro, 2007)

3.5. Limitations There are many factors that might affect the Jakarta Composite Index, such as

the foreign factors and domestic factors of a country itself. However, this

research, the factors which are observed and analyzed are Dow Jones Index,

Nikkei Index, Hang Seng Index, Exchange Rate on IDR, BI Interest Rate and

Inflation. The period of the study will cover in the period of 2010 to October

2013 with monthly data basis. The length period of data research is

considered sufficient to obtain the expected results. Researcher took this

period to understand how the independent variables would influence the


50

CHAPTER IV

ANALYSIS OF DATA AND INTERPRETATION OF

RESULTS

In this chapter, the data that already collected by researcher previously will be

analyze by using SPSS software. The data that will be analyze in this chapter

consists of one dependent variable and six independent variables. The

dependent variable is Jakarta Composite Index (Y) while the independent

variables are Dow Jones Index (X1), Nikkei Index (X2), Hang Seng Index

(X3), Exchange Rate on IDR (X4), BI Interest Rate (X5) and Inflation (X6).

The data series that used in this research is monthly data from the period of

January 2010 to October 2013. As a result, the total data series used to be

analyze is 46 monthly data for each variable. There is classic assumption test

and hypothesis testing that will be done in this chapter.

4.1. Statistics Descriptive of Research Variable Before do analyzing of classic assumption test and hypothesis testing data

which is used on this research, the researcher has to do the descriptive

statistics first. Descriptive statistic is a test that considered to give clearly

information about the variables of this research including mean, minimum

value, maximum value and standard deviation. As mentioned before, in this

research, the researcher will use six independent variables which are Dow

Jones Index, Nikkei Index, Hang Seng Index, BI Interest Rate, Exchange Rate

on IDR and Inflation and there will be one dependent variable which is

Jakarta Composite Index. The sample of the data is 46 data for each variables

51

that mentioned before. The descriptive statistics of this research is generated

by the SPSS software.

Table 4.1 Descriptive Statistics

N Minimum Maximum Mean Std. Deviation Variance

DowJones 46 9774.00 15545.75 12535.8880 1580.99347 2499540.362

Nikkei 46 8434.61 14502.35 10333.5589 1749.31191 3060092.156

HangSeng 46 17592.41 23729.53 21435.0024 1631.81635 2662824.610

ExchangeRate 46 8508.00 11613.00 9344.9130 658.78898 434002.926

BIRate 46 5.75 7.25 6.2826 .46431 .216

Inflation 46 3.43 8.79 5.3096 1.40659 1.979

JakartaComposite 46 2549.03 5068.63 3877.1492 633.69594 401570.545

Valid N (listwise) 46

Source: SPSS 18, 2013

Based on the data in table 4.1 above, there are seven variables that used in

this research consist of six independent variables and one dependent variable

which are Dow Jones Index, Nikkei Index, Hang Seng Index, Exchange Rate

on IDR, BI Rate and Inflation as independent variables and Jakarta

Composite Index as dependent variable. The data that used for this research

there are 46 data which is monthly data from seven variables above period

2010 until October 2013. The data in table 4.1 about minimum, maximum,

mean, standard deviation and variance of each variables that describes how

far the data value is far away from the average of the data value.

Based on the data in table 4.1 above can be describe as follows:

1. Dow Jones Index has mean 12535.89 and standard deviation

1580.99. The maximum value of Dow Jones Index is 15545.75

which happened in October 2013 and the minimum value of Dow

Jones Index is 9774.00 which happened in June 2010.

2. Nikkei Index has mean 10333.56 and standard deviation 1749.31.

The maximum value of Nikkei Index is 14502.35 which happened

52

in October 2013 and the minimum value of Nikkei Index is

8434.61 which is happened in November 2011.

3. Hang Seng Index has mean 21435.00 and standard deviation

1631.82. The maximum value of Hang Seng Index is 23729.53

which happened in January 2013 and the minimum value of Hang

Seng Index is 17592.41 which is happened in September 2011.

4. Exchange Rate on IDR has mean 9344.91 and standard deviation

658.79. The maximum value of Exchange Rate on IDR is

11613.00 which happened in September 2013 and the minimum

value of Exchange Rate on IDR is 8508.00 which is happened in

July 2011.

5. BI Interest Rate has mean 6.28 and standard deviation 0.46. The

maximum value of BI Interest Rate is 7.25 which happened in

September and October 2013 and the minimum value is 5.75

which happened in February 2012 until Mei 2013.

6. Inflation has mean 5.31 and standard deviation 1.41. The

maximum value of inflation is 8.79 which happened in August

2013 and the minimum value is 3.43 which happened in March

2010.

7. Jakarta Composite Index has mean 3877.15 and standard deviation

633.69. The maximum value of Jakarta Composite Index is

5068.63 which happened in May 2013 and the minimum is

2549.03 which happened in February 2010.

4.2. Classic Assumption Test

4.2.1. Normality Test Normality test is used to determine whether a set of data variable has

normally distributed or not. The regression model will be significant

if the data variable is normally distributed, thus the result of the

regression could be accepted. In this research, the researcher will used

53

P-P plot (Probability-Probability plot) to test the normality of each

variable. The result of normality test for this research in form of

histogram will be showed by figure 4.1 bellow

Figure 4.1 Histogram of Normality Test


Based on the histogram above, can be seen the curve made a bell

shape with concentrated in the middle while in left and right side has a

balance slope. It means the data is normally distributed in this

research, but histogram is not enough to prove the data distributed is

normal or not. For further prove of normality test, in this research the

researcher also use P-P Plot Regression Model to test the normality

data distribution that can be seen by Figure 4.2 bellow.

54

Figure 4.2 P-P plot (Probability-Probability plot)

Source: SPSS 18

Based on figure 4.2 above, the distribution of data are scatter close to

the diagonal line which means the distribution of data is normal.

4.2.2. Autocorrelation Test

Autocorrelation test is used to determine whether there is a correlation

in a set of data in the same variables. The major cause of

autocorrelation is a mistake in specifies data (specification phase)

such as ignoring a crucial variable or an improper form of function. In

testing the existence of autocorrelation, test that used is implemented

by using Durbin Watson statistic test (DW test).

55

Table 4.2 Durbin Watson Statistics

Model Summaryb

Model Durbin-Watson

1 .646

a. Predictors: (Constant), Inflation, DowJones, HangSeng,

ExchangeRate, BIRate, Nikkei

b. Dependent Variable: JakartaComposite


From Table 4.2, we can see that the Durbin Watson value is 0.646

which is located between -2 and +2 thus it means there is no

autocorrelation between variables with the variable in prior period.

4.2.3. Multicolinearity Test

Multicolinearity test is a test conducted to determine whether there are

autocorrelation between independent variable towards others

independent variable. To do the Multicolinearity test, the researcher is

going to use Variance Inflation Factor. Variance Inflation Factor or

has function to measure how much the variance of the estimated

coefficients is increased over the case of no correlation among the

variables. To see multicollinearity probles is exist or not according to

Render and Hana, a variable categorize or having a high collinearity if

Variance Inflation Factor value is more than 10 or it has tolerance

tend to approach 0.

56

Table 4.3 Multicolinearity Test

Coefficientsa

Model Collinearity Statistics

Tolerance VIF

1 DowJones .286 3.493

Nikkei .270 3.708

HangSeng .523 1.912

ExchangeRate .311 3.214

BIRate .380 2.628

Inflation .309 3.233

a. Dependent Variable: JakartaComposite


Based on table 4.3 above, shows that all the variable have Variance

Inflation Factor value which is less than 10 and higher than 0. It

means there is no indication of multicollinearity exist in this

regression model.

4.2.4. Heteroscedasticity Test

Heteroscedasticity is a phenomenon that often occurs in the process in

analyze if the data is not normally distributed or if the variance of the

error term differs across observation. The data will fulfill the

heteroscedasticity assumption test if the distribution of residual values

towards the predicted values is the scatter plot is spread randomly and

does not make certain pattern such as decreasing or increasing pattern.

57

Figure 4.3 Heteroscedasticity Test


From figure 4.3 above, it shows that there is no pattern that occurs

inside. The result or plot were spread randomly without make a

certain or systematic pattern such as decreasing or increasing pattern.

It means there is no heteroscedasticity exist between independent

variable and dependent variable.

4.2.5. Multiple Regression Analysis

There are more than one independent variables that use in this study,

because of that the researcher used multiple regression models in

order to explain relationship between dependent variable and those

independent variables. From this multiple regression analysis, there

are some specific information that be got from the table result such as

T table and Sig. table for each variable.

58

Table 4.4 Multiple Regression Analysis

Coefficientsa

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig. B Std. Error Beta

1 (Constant) 2476.182 1164.249 2.127 .040

DowJones .400 .037 .999 10.852 .000

Nikkei -.020 .034 -.056 -.594 .556

HangSeng .007 .026 .018 .259 .797

ExchangeRate -.206 .085 -.214 -2.425 .020

BIRate -300.281 108.972 -.220 -2.756 .009

Inflation 48.486 39.892 .108 1.215 .232

a. Dependent Variable: JakartaComposite


Based on the multiple regression test result that has been done in table

4.4 above, the researcher will use the model of the study as follow:

Y= 2467.182 + 0.400 Dow Jones Index – 0.020 Nikkei Index

+ 0.007 Hang Seng Index – 0.206 Exchange Rate on IDR –

300.281 BI Interest Rate + 48.486 Inflation

Based on the multiple regression analysis result in table 4.4 above,

from six independent variable used in this research, there are three

variable that prove has significant influence towards dependent

variable in this research. In order to get the best multiple regression

model for this research, the researcher make remodel for Multiple

Regression analysis of this research as follows:

59

Y = 2467.182 + 0.400 Dow Jones Index – 0.206 Exchange

Rate on IDR – 300.281 BI Interest Rate

Based on the model above, researcher can make conclusion as

following:

1. The constant value of the model is 2467.182. It means that if the

value of all independent variables such as Dow Jones Index,

Nikkei Index, Hang Seng Index, Exchange Rate on IDR, BI

Interest Rate and Inflation is zero, then the value of Jakarta

Composite Index (Y) is 2467.182.

2. The coefficient regression value of Dow Jones Index (X1) is 0.400.

Dow Jones Index (X1) also shown positive or significant influence

towards Jakarta Composite Index (Y). It means that if Dow Jones

Index (X1) increases one point, Jakarta Composite Index (Y) will

increase 0.400 point, and vice versa with the assumption of other

independent variable are constant.

3. The coefficient regression value of Exchange Rate on IDR (X4) is

-0.206. Exchange Rate on IDR (X4) also shown positive or

significant influence towards Jakarta Composite Index (Y). It

means that if Exchange Rate on IDR (X4) increases one point,

Jakarta Composite Index (Y) will decrease 0.206 point, and vice

versa with the assumption of other independent variable are

constant.

4. The coefficient regression value of BI Interest Rate (X5) is -

300.281. BI Interest Rate (X5) also showed positive or significant

influence towards Jakarta Composite Index (Y). It means that if BI

Interest Rate (X5) increases one point, Jakarta Composite Index

(Y) will decrease 300.281 point, and vice versa with the

assumption of other independent variable are constant.

60

4.3. Hypothesis Testing

4.3.1. F Test

F Test is used to test the effect of all independent variables towards

independent variable simultaneously.

Table 4.5 F-Test

ANOVAb

Model Sum of Squares df Mean Square F Sig.

Regression 1.636E7 6 2726899.632 62.219 .000a

Residual 1709276.753 39 43827.609

Total 1.807E7 45



b. Dependent Variable: JakartaComposite


The requirement value that has to achieve in this F-Test is the

significance value has to be less than 0.05 and has to be greater than

1-96. From table 4.5 above, can be seen that the significance value is

0.000 which is less than 0.05 and f value is greater than 1.96 which is

62.219. From that result, the researcher can make conclusion that all

of the independent variable in this research which are Dow Jones

Index, Nikkei Index, Hang Seng Index, Exchange Rate on IDR, BI

Interest Rate and Inflation has significant influence towards Jakarta

Composite Index. It means null hypothesis which is H0 is rejected and

H1 hypothesis is accepted.

4.3.2. T-Test

T Test is used to examine whether each independent variables factor

in this research which are Dow Jones Index (X1), Nikkei Index (X2),

61

Hang Seng Index (X3), the Exchange Rate on IDR (X4), BI Interest

Rate (X5) and Inflation (X6) has influence towards dependent variable

of Jakarta Composite Index. Each of independent variable will be

significance towards the dependent variable if each value of p of each

independent variable is less than 0.05.

From the table 4.4 above, it has shown each significance value of each

independent variable, the results as following:

1. Dow Jones Index (X1) has significance value of 0.000 which is

less than 0.05. It means that Dow Jones Index (X1) is significance

influence towards the dependent variable of Jakarta Composite

Index and H0 is rejected and accepted H1 from the hypothesis.

2. Nikkei Index (X2) has significance value of 0.556 which is greater

than 0.05. It means Nikkei Index (X2) is not significance towards

the dependent variable of Jakarta Composite Index and H0 is

accepted and rejected H2 from the hypothesis.

3. Hang Seng Index (X3) has significance value of 0.797 which is

greater than 0.05. It means Hang Seng Index (X3) is not

significance towards the dependent variable of Jakarta Composite

Index and H0 is accepted and rejected H3 from the hypothesis.

4. Exchange Rate on IDR (X4) has significance value of 0.020 which

is less than 0.05. It means that Exchange Rate on IDR (X4) is

significance influence towards the dependent variable of Jakarta

Composite Index and H0 is rejected and accepted H4 from the

hypothesis.

5. BI Interest Rate (X5) has significance value of 0.009 which is less

than 0.05. It means that BI Interest Rate (X5) is significance

influence towards the dependent variable of Jakarta Composite

Index and H0 is rejected and accepted H5 from the hypothesis.

62

6. Inflation (X6) has significance value of 0.232 which is greater than

0.05. It means that Inflation (X6) is not significance towards the

dependent variable of Jakarta Composite Index and H0 is accepted

and rejected H6 from the hypothesis.

4.3.3. Coefficient of Determination

Coefficient of determination (R-Square) is used to measure the

multiple regression model capability to explain the Jakarta Composite

Index based on the independent variables.

Table 4.6 Coefficient of Determination

Moded

R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .952a .905 .891 209.35045




Based on table 4.6 above, showed that the adjusted R-square value is

0.891 means 89% of the Jakarta Composite Index could be explained

by all of the independent variable which are Dow Jones Index, Nikkei


Inflation. The remaining 11% will be explained by the others variable

outside this multiple regression model. Which means there is a very

strong correlation between independent variable and dependent

variable in this multiple regression model.

63

4.4. EViews 6 EViews is the statistical software that the researcher used for this research to

make sure and prove the analysis that analysis that has been done used SPSS

software before is correct. By do test using EViews software, can support the

result form SPSS software. Coefficient, Std. Error, t-statistic, prob, R-

squared and etc is the result that the researcher can be get, the result will be

shown in Table 4.7 bellow.

Table 4.7 EViews Test

Variable Coefficient Std. Error t-Statistic Prob. C 2476.182 1164.249 2.126850 0.0398

DOWJONES 0.400329 0.036891 10.85182 0.0000 NIKKEI -0.020416 0.034351 -0.594339 0.5557

HANGSENG 0.006852 0.026442 0.259138 0.7969 EXCHANGERATE -0.205920 0.084932 -2.424515 0.0201

BI -300.2810 108.9720 -2.755581 0.0089 INFLASI 48.48555 39.89181 1.215426 0.2315

R-squared 0.905412 Mean dependent var 3877.149

Adjusted R-squared 0.890860 S.D. dependent var 633.6959 S.E. of regression 209.3504 Akaike info criterion 13.66516 Sum squared resid 1709277. Schwarz criterion 13.94344 Log likelihood -307.2988 Hannan-Quinn criter. 13.76941 F-statistic 62.21876 Durbin-Watson stat 0.646061 Prob(F-statistic) 0.000000

Source: EViews Software, 2013

From the table 4.7 above shown, simultaneously all independent variables in

this research have significant influence towards dependent variable with

result 0.000. While in partially three variables which is Dow Jones Index, BI

Interest Rate and the Exchange Rate on IDR has significant influence,

because result of that three variables is less than 0.05. Adjusted R-squared

result is show 0.891 means 89% of Jakarta Composite Index could be

explained by all of the independent variables used in this research, while the

rest 11% explained by the other variables outside this multiple regression

64

model in this research. Therefore, based on the result in table 4.7 above, the

result that has been done by using SPSS before proven correct.

4.5. Interpretation of Results

4.5.1. The Influence of Dow Jones Index towards Jakarta Composite

Index.

Based on Table 4.4 above, the significant value of Dow Jones Index is

0.000. This significant value indicates that Dow Jones Index has

significant influence towards Jakarta Composite Index. With the

coefficient value of positive 0.400, it means that the increasing one

point of Dow Jones Index will increase the Jakarta Composite Index

value for 0.400.

Dow Jones Index is the best known U.S. index of stocks. A price

weighted average of 30 actively traded blue chip stocks, primarily

industrials including stocks that trade on the New York Stock

Exchange. Because of the globalization and the high percentage of

Indonesia Stock Exchange is dominated by foreign investors, Dow

Jones Index has significant influence towards Jakarta Composite

Index.

The result of the model is supported by the research of Fajar Budhi

Darmawan (2009), Budi Susanto (2012) and Ardy Haryogo (2013)

which state that Dow Jones Index has significant influence towards

Jakarta Composite Index (JCI).

65

4.5.2 The Influence of Nikkei Index towards Jakarta Composite Index.

Based on Table 4.4 above, the significant value of Nikkei Index is

0.556. This significant value indicates that Nikkei Index has influence

towards Jakarta Composite Index, but the influence is not significant.

With the coefficient value of negative 0.020, it means that the

increasing one point of Nikkei Index will decrease the Jakarta

Composite Index value for 0.020.

Nikkei Index is the most popular benchmark for the Japanese and

Asian stock markets. The index consist of 225 largest companies on

the Tokyo Stock Exchange by market capitalization and liquidity.

Because of the globalization and the high percentage of Indonesia

Stock Exchange is dominated by foreign investors, Nikkei Index has

influence towards Jakarta Composite Index but the influence is not

significant.

The result of this model is supported by the research of Ali Fikri

Hasibuan and Taufik Hidayat (2011) which state that Nikkei Index

has influence towards Jakarta Composite Index (JCI), but the

influence is not significant.

4.5.3. The Influence of Hang Seng Index towards Jakarta Composite

Index.

Based on Table 4.4 above, the significant value of Hang Seng Index is

0.797. This significant value indicates that Hang Seng Index has

influence towards Jakarta Composite Index, but the influence is not

significant. With the coefficient value of positive 0.007, it means that

the increasing one point of Hang Seng Index will increase the Jakarta

Composite Index value for 0.007.

66

Hang Seng Index is the most popular stock market index in Hong

Kong stock exchange. Hang Seng Index is a market capitalization

weighted index of 40 of the largest companies that are trade on the

Hong Kong Stock Exchange. Because of the globalization and the

high percentage of Indonesia Stock Exchange is dominated by foreign

investors, Hang Seng Index has influence towards Jakarta Composite

Index but the influence is not significant.

The result of this model is supported by the research of Alkhairani

(2012) and Andrew Hartanto (2013) which state that Hang Seng Index

influence towards Jakarta Composite Index (JCI), but the influence is

not significant.

4.5.4. The influence of Exchange Rate on IDR towards Jakarta

Composite Index.

Based on Table 4.4 above, the significant value of the Exchange Rate

on IDR is 0.020. This significant value indicates that the Exchange

Rate on IDR has significant influence towards Jakarta Composite

Index. With the coefficient value of negative 0.206, it means that the

increasing one point of the Exchange Rate on IDR will decrease the

Jakarta Composite Index value for 0.206.

Exchange rate is the price of one country’s currency expressed in

another country’s currency. Mostly exchange rates are determined by

the foreign exchange market, known as forex. Because of the

globalization and the high percentage of Indonesia Stock Exchange is

dominated by foreign investors, so the exchange rate on IDR hold an

important role. Exchange Rate on IDR has significant influence


67

The result of this model is supported by the research of Aditya

Novianto (2011), Ria Astuti, Apriatni E. P and Hari Susanta (2013),

Joven Sugianto Liaw and Trisnadi Wijaya (2012) which state that the

Exchange Rate on IDR has a significant negative influence towards

Jakarta Composite Index (JCI).

4.5.5. The influence of BI Interest Rate towards Jakarta Composite

Index.

Based on Table 4.4 above, the significant value of BI Interest Rate is

0.009. The significant value indicates that BI Interest Rate has

significant influence towards Jakarta Composite Index. With the

coefficient value of negative 300.281, it means that the increasing one

point of BI Interest Rate will decrease the Jakarta Composite Index

value for 300.281.

The BI Rate is the policy rate reflecting the monetary policy stance

adopted by Bank Indonesia and announced to the public. The BI Rate

is announced by the Board of Governors of Bank Indonesia in each

monthly Board of Governors Meeting. It’s implemented in the Bank

Indonesia monetary policy operational target. BI Rate is the most

important aspect in Indonesia Economics, that why BI Rate has

significant influence towards Jakarta Composite Index.

The result of this model is supported by the research of Aditya

Novianto (2011),Ria Astuti, Apriatni E. P and Hari Susanta (2013),

Joven Sugianto Liaw and Trisnadi Wijaya (2012) which state that BI

Interest Rate has significant negative influence towards Jakarta

Composite Index (JCI).

68

4.5.6. The influence of Inflation towards Jakarta Composite Index.

Based on Table 4.4 above, the significant value of Inflation is 0.232.

This significant value indicates that Inflation has influence towards

Jakarta Composite Index, but the influence is not significant. With the

coefficient value of positive 48.486, it means that the increasing one

point of Inflation will increase the Jakarta Composite Index value for

48.486.

In simple terms, inflation is understood as a persistent, ongoing rise

across a broad spectrum of prices. An increase in prices for one or two

goods alone can’t be described as inflation unless that increase

spreads to (or leads to escalating prices for) other goods. Inflation is

one of the important aspect for Indonesia economics, Inflation has

influence towards Jakarta Composite Index, but the influence is not

significant.

The result of this model is supported by the research of Ria Astuti,

Apriatni E. P and Hari Susanta (2013) which state that Inflation has

influence towards Jakarta Composite Index (JCI), but the influence is

not significant.

4.5.7. The influence of Dow Jones Index, Nikkei Index, Hang Seng

Index, Exchange Rate on IDR, BI Interest Rate and Inflation


Based on the multiple regression analysis result, the significant value

of F-Test of this model is 0.000 (p-value is less than the α value =

0.05). It means tis model independent variables (Dow Jones Index,


69

Rate and Inflation) have significant influence towards Jakarta

Composite Index as a whole.

The result of this regression model is basically what researcher

expected to get because the ownership of Indonesia capital market is

highly dominated by foreign investors, as it has been explained in

chapter I, where in this model is represented by Dow Jones Index,


Rate and Inflation are proven have significant influence towards


Furthermore, by this multiple regression model, the journal by Fajar

Budhi Darmawan, 2009 about “Pengaruh Indeks DJI, FTSE 100, dan

HIS terhadap IHSG” and journal by Aditya Novianto about “Analisis

Pengaruh Nilai Tukar (Kurs) Dolar Amerika/Rupiah, Tingkat suku

bunga SBI, Inflasi dan Jumlah Uang Yang Beredar terhadap IHSG”

has been proven. Along with this multiple regression model, Dow

Jones Index, Nikkei Index, Hang Seng Index, Exchange Rate on IDR,

BI Interest Rate and Inflation are proven have significant influence


70

CHAPTER V

CONCLUSION AND RECOMMENDATION

5.1. Conclusion Based on the analysis that the researcher do for this research in the chapter

four, the independent variable which are Dow Jones Index, Nikkei Index,

Hang Seng Index, the Exchange Rate on IDR, BI Interest Rate and Inflation

influence the Jakarta Composite Index, here are some conclusion that the

researcher get as following:

1. Dow Jones Index has significant influence towards Jakarta

Composite Index with significance value of 0.000 which is less than

0.05. This might happen because Dow Jones Index is the stock price

index in U.S. that consist of 30 actively traded blue chip stocks in

New York Stock Exchange and the fact Indonesia Capital Market

dominated by foreign investors. As the impact of declining Dow

Jones Index, will decrease the investor interest in trade stocks in

Indonesia Stock Exchange and it will make Jakarta Composite Index

decline and vice versa.

2. Nikkei Index has influence towards Jakarta Composite Index but the

influence is not significance with significant value of 0.556 which is

greater than 0.05. This might happen because Nikkei Index is the

most popular benchmark for Japanese stock market and since the

research is based on the it’s relation towards Indonesian capital

market focusing in Jakarta Composite Index then it proofs that this

index didn’t have strong influence compare to the Japanese stock

market.

3. Hang Seng Index has influence towards Jakarta Composite Index but

the influence is not significance with significant value of 0.797 which

71

is greater than 0.05. Hong Kong capital market has less influence and

less popular compare to the western country, even though the China

economy nowadays has getting bigger and stronger apparently it

didn’t has much impact towards Hong Kong even though it’s part of

China. This can be seen by the result of this research that even

though the Hang Seng index globally has impact to the global capital

market, it didn’t do much towards Indonesia capital market.

4. Exchange Rate on IDR has significance influence towards Jakarta

Composite Index with significant value of 0.020 which is less than

0.05. Since this research is based on Jakarta Composite Index or the

Indonesian capital market, the influence of exchange rate on IDR are

not avoidable. The stronger exchange rate of IDR means the stronger

local investors ability to make the transaction thus resulting in higher


5. BI Interest Rate has significant influence towards Jakarta Composite

Index with significance value of 0.009 which is less than 0.05. The

bank interest in Indonesia are determined and decided by Bank of

Indonesia. Thus this particular factors are certainly affecting the

Jakarta Composite Index since most of the investors are doing the

capital trading activity to gain profit, the lower BI Interest Rate will

increase the activity of capital trading while if the bank interest is

getting higher, the investors tend to avoid the risk by not doing the

capital trading and preferred to save their money in the bank.

6. Inflation has influence towards Jakarta Composite Index but the

influence is not significant with significance value of 0.232 which is

greater than 0.05. During the inflation, the daily needs product price

are increased and make the investors tend to not doing the trading

activity while when there are no inflation people tend to do the

trading activity to gain more profit because at that time stock price

72

will also back to the normal average price compare to the higher

inflation price. Apparently when there are inflation and no inflation

period the changing or fluctuation in the Jakarta Composite Index are

not that much it can be seen by the result of this research where

inflation are influence but are not significant.

7. All of the independent variables Dow Jones Index, Nikkei Index,

Hang Seng Index, Exchange Rate on IDR, BI Interest Rate and

Inflation used in this research proven has significant influence

towards Jakarta Composite Index with significance value of 0.000

which is less than 0.05. Its means hypothesis Ha1 in this research is

accepted for the period of 2010 – 2013. Like what researcher already

explain in chapter 1, the ownership of Indonesia Stock Exchange

dominated by foreign investors.

5.2. Recommendation

Based on those conclusions drawn above and some finding in this study, there

are some possible course of action may be identified. The following

recommendations are offered as guidelines or suggestion for the next

researcher that want to make study or research about Jakarta Composite

Index. The following recommendations are made:

a. To Ordinary People

This research is expected to help the investors in making decision,

especially in trading activities. As this study has already proven that all

markets are highly related one to another, the trend of one market can

give a big picture of the other markets trend movement.

73

b. To Next Researcher

There are three variables of the independent variables in this research

to identify the movement of Jakarta Composite Index are Dow Jones

Index, Exchange Rate and BI Interest Rate are proven have significant

influence, the next researcher could focus more on Dow Jones Index,

Exchange Rate and BI Interest Rate with different period of time.

74

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78

APPENDICES

1. Jakarta Composite Index

Prices

Date Open High Low Close Avg Vol Adj Close*

1-Oct-13 4,314.96 4,611.26 4,314.96 4,574.88 3,614,314,500 4,574.88

2-Sep-13 4,196.72 4,791.77 4,012.68 4,316.18 4,551,425,800 4,316.18

1-Aug-13 4,618.96 4,718.10 3,837.74 4,195.09 3,978,387,800 4,195.09

1-Jul-13 4,757.18 4,815.73 4,403.80 4,610.38 2,176,566,800 4,610.38

3-Jun-13 5,053.54 5,055.83 4,373.38 4,818.90 2,380,549,400 4,818.90

1-May-13 5,020.20 5,251.30 4,907.60 5,068.63 2,258,713,300 5,068.63

1-Apr-13 4,927.12 5,034.07 4,864.86 5,034.07 2,756,592,400 5,034.07

1-Mar-13 4,798.49 4,940.99 4,721.32 4,940.99 2,740,009,600 4,940.99

1-Feb-13 4,458.60 4,795.79 4,457.45 4,795.79 2,449,262,700 4,795.79

2-Jan-13 4,322.58 4,472.11 4,298.61 4,453.70 2,581,742,000 4,453.70

3-Dec-12 4,277.19 4,340.26 4,222.13 4,316.69 2,074,262,900 4,316.69

1-Nov-12 4,331.75 4,381.75 4,255.27 4,276.14 1,725,779,900 4,276.14

1-Oct-12 4,249.69 4,366.86 4,214.52 4,350.29 2,852,821,400 4,350.29

3-Sep-12 4,052.89 4,272.83 4,047.28 4,262.56 2,106,506,800 4,262.56

1-Aug-12 4,129.81 4,183.03 3,978.08 4,060.33 1,457,684,500 4,060.33

2-Jul-12 3,976.71 4,149.71 3,963.47 4,142.34 1,805,897,500 4,142.34

1-Jun-12 3,820.38 3,971.08 3,635.28 3,955.58 1,583,296,200 3,955.58

1-May-12 4,181.09 4,234.73 3,810.39 3,832.82 2,666,426,000 3,832.82

2-Apr-12 4,121.82 4,232.92 4,109.32 4,180.73 3,673,109,400 4,180.73

1-Mar-12 3,985.03 4,129.33 3,929.19 4,121.55 1,582,071,000 4,121.55

1-Feb-12 3,941.78 4,040.08 3,838.54 3,985.21 2,791,622,600 3,985.21

3-Jan-12 3,808.69 4,038.78 3,808.69 3,941.69 2,954,255,900 3,941.69

1-Dec-11 3,715.44 3,825.96 3,666.25 3,821.99 1,911,550,700 3,821.99

1-Nov-11 3,790.11 3,859.10 3,618.97 3,715.08 2,557,527,800 3,715.08

3-Oct-11 3,548.12 3,875.11 3,256.44 3,790.85 3,770,432,200 3,790.85

2-Sep-11 3,841.73 4,028.48 3,217.95 3,549.03 2,610,060,400 3,549.03

1-Aug-11 4,131.73 4,195.72 3,590.94 3,841.73 3,810,505,300 3,841.73

1-Jul-11 3,888.20 4,177.74 3,888.20 4,130.80 3,703,415,800 4,130.80

1-Jun-11 3,837.18 3,896.16 3,704.58 3,888.57 3,233,468,900 3,888.57

2-May-11 3,819.80 3,872.95 3,760.79 3,836.97 4,407,107,500 3,836.97

1-Apr-11 3,679.05 3,824.07 3,671.18 3,819.62 2,588,791,200 3,819.62

79

1-Mar-11 3,470.63 3,683.47 3,465.60 3,678.67 2,452,225,600 3,678.67

1-Feb-11 3,411.08 3,521.63 3,336.83 3,470.35 1,981,020,400 3,470.35

3-Jan-11 3,704.44 3,789.47 3,309.62 3,409.17 2,846,015,800 3,409.17

1-Dec-10 3,530.93 3,788.56 3,530.93 3,703.51 3,099,489,000 3,703.51

1-Nov-10 3,635.52 3,777.92 3,529.85 3,531.21 5,221,298,500 3,531.21

1-Oct-10 3,501.20 3,667.01 3,501.20 3,635.32 5,022,649,800 3,635.32

1-Sep-10 3,081.49 3,524.32 3,081.49 3,501.30 4,078,938,800 3,501.30

2-Aug-10 3,070.28 3,150.16 2,959.75 3,081.88 4,063,138,000 3,081.88

1-Jul-10 2,912.88 3,104.08 2,860.91 3,069.28 3,884,965,400 3,069.28

1-Jun-10 2,796.66 2,981.28 2,698.28 2,913.68 4,259,397,500 2,913.68

3-May-10 2,971.75 2,996.42 2,502.05 2,796.96 4,925,558,700 2,796.96

1-Apr-10 2,777.70 2,972.92 2,777.70 2,971.25 5,273,440,300 2,971.25

1-Mar-10 2,548.83 2,818.94 2,545.89 2,777.30 3,888,145,400 2,777.30

1-Feb-10 2,610.59 2,613.67 2,431.84 2,549.03 3,202,115,300 2,549.03

4-Jan-10 2,533.95 2,689.77 2,532.90 2,610.80 4,242,926,200 2,610.80

* Close price adjusted for dividends and splits.

80

2. Dow Jones Index

Prices


1-Oct-13 15,132.50 15,721.00 14,719.40 15,545.75 1,008,900 15,545.75

3-Sep-13 14,801.60 15,709.60 14,777.50 15,129.70 1,246,900 15,129.70

1-Aug-13 15,503.90 15,658.43 14,760.40 14,810.30 1,119,700 14,810.30

1-Jul-13 14,911.60 15,634.30 14,858.90 15,499.50 1,258,200 15,499.50

3-Jun-13 15,123.60 15,340.10 14,551.30 14,909.60 1,579,500 14,909.60

1-May-13 14,839.80 15,542.40 14,687.10 15,115.60 1,354,700 15,115.60

1-Apr-13 14,578.50 14,887.50 14,434.40 14,839.80 1,394,700 14,839.80

1-Mar-13 14,054.50 14,585.10 13,937.60 14,578.50 1,350,000 14,578.50

1-Feb-13 13,860.60 14,149.20 13,784.00 14,054.50 1,402,400 14,054.50

2-Jan-13 13,104.30 13,970.00 13,104.30 13,860.60 1,394,800 13,860.60

3-Dec-12 13,027.70 13,365.90 12,883.90 13,104.10 1,406,200 13,104.10

1-Nov-12 13,099.20 13,290.80 12,471.50 13,025.60 1,359,500 13,025.60

1-Oct-12 13,437.70 13,661.90 13,017.40 13,096.50 1,243,200 13,096.50

4-Sep-12 13,092.20 13,653.20 12,977.10 13,437.10 1,499,000 13,437.10

1-Aug-12 13,007.50 13,330.80 12,778.90 13,090.80 1,037,800 13,090.80

2-Jul-12 12,879.70 13,128.60 12,492.30 13,008.70 1,287,600 13,008.70

1-Jun-12 12,391.60 12,898.90 12,035.10 12,880.10 1,483,400 12,880.10

1-May-12 13,214.20 13,338.70 12,311.60 12,393.50 1,479,600 12,393.50

2-Apr-12 13,211.40 13,297.10 12,710.60 13,213.60 1,351,300 13,213.60

1-Mar-12 12,952.30 13,289.10 12,734.90 13,212.00 1,533,900 13,212.00

1-Feb-12 12,632.80 13,055.80 12,632.80 12,952.10 1,447,300 12,952.10

3-Jan-12 12,221.20 12,842.00 12,221.20 12,632.90 1,574,500 12,632.90

1-Dec-11 12,046.20 12,328.50 11,735.20 12,217.60 1,508,600 12,217.60

1-Nov-11 11,951.50 12,187.50 11,231.40 12,045.70 1,690,400 12,045.70

3-Oct-11 10,912.10 12,284.30 10,404.50 11,955.00 1,949,200 11,955.00

1-Sep-11 11,613.30 11,716.80 10,597.10 10,913.40 2,195,100 10,913.40

1-Aug-11 12,144.20 12,282.40 10,604.10 11,613.50 2,796,900 11,613.50

1-Jul-11 12,414.30 12,753.90 12,083.50 12,143.20 1,661,600 12,143.20

1-Jun-11 12,569.40 12,569.50 11,862.50 12,414.30 1,843,800 12,414.30

2-May-11 12,810.20 12,876.00 12,309.50 12,569.80 1,803,000 12,569.80

1-Apr-11 12,321.00 12,832.80 12,093.90 12,810.50 1,849,800 12,810.50

1-Mar-11 12,226.50 12,383.50 11,555.50 12,319.70 1,755,600 12,319.70

1-Feb-11 11,892.50 12,391.30 11,892.50 12,226.30 1,800,000 12,226.30

81

3-Jan-11 11,577.40 12,020.50 11,573.90 11,891.90 1,944,100 11,891.90

1-Dec-10 11,007.20 11,625.00 11,007.20 11,577.50 1,521,000 11,577.50

1-Nov-10 11,120.30 11,451.50 10,929.30 11,006.00 1,924,700 11,006.00

1-Oct-10 10,789.70 11,247.60 10,711.10 11,118.50 1,893,700 11,118.50

1-Sep-10 10,016.00 10,948.90 10,016.00 10,788.10 1,895,000 10,788.10

2-Aug-10 10,468.80 10,719.90 9,936.60 10,014.70 1,987,700 10,014.70

1-Jul-10 9,773.30 10,585.00 9,614.30 10,465.90 2,119,700 10,465.90

1-Jun-10 10,133.90 10,594.20 9,753.80 9,774.00 2,353,000 9,774.00

3-May-10 11,009.60 11,177.70 9,774.50 10,136.60 2,924,700 10,136.60

1-Apr-10 10,857.30 11,258.00 10,844.10 11,008.60 2,139,300 11,008.60

1-Mar-10 10,326.10 10,955.50 10,326.10 10,856.60 1,993,700 10,856.60

1-Feb-10 10,069.00 10,438.60 9,835.10 10,325.30 2,400,900 10,325.30

4-Jan-10 10,430.70 10,729.90 10,043.80 10,067.30 2,495,500 10,067.30


82

3. Nikkei Index

Prices


1-Oct-13 14,517.98 14,799.28 13,748.94 14,502.35 140,600 14,502.35

2-Sep-13 13,438.07 14,817.50 13,407.53 14,455.80 153,200 14,455.80

1-Aug-13 13,674.50 14,466.16 13,188.14 13,388.86 150,600 13,388.86

1-Jul-13 13,746.72 14,953.29 13,562.70 13,668.32 196,800 13,668.32

3-Jun-13 13,551.36 13,724.44 12,415.85 13,677.32 249,400 13,677.32

1-May-13 13,837.72 15,942.60 13,555.66 13,774.54 355,700 13,774.54

1-Apr-13 12,371.34 13,983.87 11,805.78 13,860.86 307,000 13,860.86

1-Mar-13 11,464.71 12,650.26 11,464.71 12,397.91 221,600 12,397.91

1-Feb-13 11,193.72 11,662.52 11,046.92 11,559.36 290,300 11,559.36

4-Jan-13 10,604.50 11,145.38 10,398.61 11,138.66 242,700 11,138.66

3-Dec-12 9,484.20 10,433.63 9,376.97 10,395.18 191,300 10,395.18

1-Nov-12 8,931.71 9,492.91 8,619.45 9,446.01 135,500 9,446.01

1-Oct-12 8,815.07 9,075.59 8,488.14 8,928.29 130,600 8,928.29

3-Sep-12 8,836.61 9,288.53 8,646.03 8,870.16 133,600 8,870.16

1-Aug-12 8,622.04 9,222.87 8,513.20 8,839.91 117,100 8,839.91

2-Jul-12 9,103.79 9,136.02 8,328.02 8,695.06 123,600 8,695.06

1-Jun-12 8,465.47 9,044.04 8,238.96 9,006.78 128,200 9,006.78

1-May-12 9,471.66 9,472.25 8,455.13 8,542.73 136,900 8,542.73

2-Apr-12 10,161.72 10,190.35 9,388.14 9,520.89 135,600 9,520.89

1-Mar-12 9,771.34 10,255.15 9,509.10 10,083.56 165,600 10,083.56

1-Feb-12 8,789.06 9,866.41 8,780.10 9,723.24 173,100 9,723.24

4-Jan-12 8,549.54 8,911.62 8,349.33 8,802.51 120,600 8,802.51

1-Dec-11 8,581.20 8,729.81 8,272.26 8,455.35 104,100 8,455.35

1-Nov-11 8,880.75 8,946.00 8,135.79 8,434.61 120,100 8,434.61

3-Oct-11 8,567.98 9,152.39 8,343.01 8,988.39 125,200 8,988.39

1-Sep-11 9,017.01 9,098.15 8,359.70 8,700.29 140,600 8,700.29

1-Aug-11 9,907.04 10,040.13 8,619.21 8,955.20 154,900 8,955.20

1-Jul-11 9,878.69 10,207.91 9,824.34 9,833.03 129,800 9,833.03

1-Jun-11 9,708.05 9,849.69 9,318.62 9,816.09 137,500 9,816.09

2-May-11 9,964.39 10,017.47 9,406.04 9,693.73 138,500 9,693.73

1-Apr-11 9,757.28 9,849.74 9,405.19 9,849.74 157,400 9,849.74

1-Mar-11 10,676.24 10,768.43 8,227.63 9,755.10 226,300 9,755.10

1-Feb-11 10,281.55 10,891.60 10,245.75 10,624.09 166,800 10,624.09

83

4-Jan-11 10,352.19 10,620.57 10,182.57 10,237.92 151,600 10,237.92

1-Dec-10 9,939.80 10,394.22 9,918.55 10,228.92 130,700 10,228.92

1-Nov-10 9,166.85 10,157.97 9,123.62 9,937.04 144,500 9,937.04

1-Oct-10 9,440.52 9,716.92 9,179.15 9,202.45 154,400 9,202.45

1-Sep-10 8,833.32 9,704.25 8,796.45 9,369.35 131,200 9,369.35

2-Aug-10 9,574.64 9,750.88 8,807.41 8,824.06 121,500 8,824.06

1-Jul-10 9,296.86 9,807.36 9,091.70 9,537.30 147,800 9,537.30

1-Jun-10 9,747.26 10,251.90 9,347.07 9,382.64 122,200 9,382.64

6-May-10 10,847.90 10,847.90 9,395.29 9,768.70 182,700 9,768.70

1-Apr-10 11,178.92 11,408.17 10,865.92 11,057.40 144,200 11,057.40

1-Mar-10 10,128.73 11,147.62 10,116.86 11,089.94 116,000 11,089.94

1-Feb-10 10,212.36 10,449.75 9,867.39 10,126.03 136,800 10,126.03

4-Jan-10 10,609.34 10,982.10 10,198.04 10,198.04 190,400 10,198.04


84

4. Hang Seng Index

Prices


2-Oct-13 22,997.21 23,534.67 22,640.18 23,304.02 1,431,571,900 23,304.02

2-Sep-13 21,948.72 23,554.34 21,948.72 22,859.86 1,816,720,500 22,859.86

1-Aug-13 22,025.75 22,695.99 21,465.72 21,731.37 1,552,296,900 21,731.37

1-Jul-13 20,803.29 22,070.14 20,119.56 21,883.66 1,506,915,800 21,883.66

3-Jun-13 22,301.68 22,564.18 19,426.36 20,803.29 2,392,547,600 20,803.29

1-May-13 22,737.01 23,512.42 22,290.72 22,392.16 1,592,387,100 22,392.16

1-Apr-13 22,299.63 22,862.69 21,423.25 22,737.01 1,525,176,900 22,737.01

1-Mar-13 22,957.09 23,262.02 21,975.90 22,299.63 1,932,594,600 22,299.63

1-Feb-13 23,763.34 23,944.74 22,445.34 23,020.27 1,557,330,600 23,020.27

2-Jan-13 22,860.25 23,916.16 22,860.25 23,729.53 1,753,042,300 23,729.53

3-Dec-12 22,070.44 22,718.83 21,687.88 22,656.92 1,500,475,500 22,656.92

1-Nov-12 21,573.93 22,149.70 21,098.41 22,030.39 1,441,551,100 22,030.39

1-Oct-12 20,840.38 21,847.70 20,767.36 21,641.82 1,593,868,900 21,641.82

3-Sep-12 19,414.62 20,895.61 19,076.79 20,840.38 1,735,606,300 20,840.38

1-Aug-12 19,646.96 20,300.03 19,450.77 19,482.57 1,305,904,900 19,482.57

2-Jul-12 19,441.46 19,869.11 18,710.59 19,796.81 1,433,367,200 19,796.81

1-Jun-12 18,498.91 19,578.82 18,056.40 19,441.46 1,650,371,100 19,441.46

2-May-12 21,245.48 21,385.30 18,378.14 18,629.52 2,225,198,200 18,629.52

2-Apr-12 20,662.97 21,105.57 20,035.68 21,094.21 1,616,989,900 21,094.21

1-Mar-12 21,578.19 21,641.14 20,374.03 20,555.58 1,723,090,500 20,555.58

1-Feb-12 20,394.67 21,760.34 20,269.51 21,680.08 1,720,332,000 21,680.08

3-Jan-12 18,770.64 20,590.80 18,302.84 20,390.49 1,854,060,000 20,390.49

1-Dec-11 19,033.96 19,242.80 17,821.52 18,434.39 1,452,402,100 18,434.39

1-Nov-11 19,461.08 20,173.14 17,613.20 17,989.35 2,117,359,700 17,989.35

3-Oct-11 17,179.20 20,272.38 16,170.35 19,864.87 2,298,894,000 19,864.87

1-Sep-11 20,790.22 20,975.30 16,999.54 17,592.41 2,334,174,000 17,592.41

1-Aug-11 22,739.55 22,808.33 18,868.11 20,534.85 2,621,420,000 20,534.85

4-Jul-11 22,813.25 22,835.03 21,611.16 22,440.25 1,999,129,500 22,440.25

1-Jun-11 23,686.77 23,706.00 21,508.77 22,398.10 1,745,792,200 22,398.10

2-May-11 23,720.81 23,924.48 22,519.66 23,684.13 1,289,308,800 23,684.13

1-Apr-11 23,664.48 24,468.64 23,468.20 23,720.81 1,457,782,400 23,720.81

1-Mar-11 23,317.96 23,934.07 22,123.26 23,527.52 1,906,962,900 23,527.52

1-Feb-11 23,451.62 23,981.74 22,446.67 23,338.02 1,643,417,500 23,338.02

85

3-Jan-11 23,135.64 24,434.40 23,057.52 23,447.34 1,481,309,200 23,447.34

1-Dec-10 22,973.80 23,612.25 22,392.67 23,035.45 1,207,300,000 23,035.45

1-Nov-10 23,366.82 24,988.57 22,782.98 23,007.99 1,944,897,000 23,007.99

4-Oct-10 22,542.36 23,866.87 22,504.05 23,096.32 2,237,593,700 23,096.32

1-Sep-10 20,570.52 22,439.19 20,529.87 22,358.17 1,592,809,100 22,358.17

2-Aug-10 21,221.43 21,805.94 20,372.29 20,536.49 1,270,031,400 20,536.49

1-Jul-10 20,128.99 21,199.55 19,777.83 21,029.81 1,270,317,300 21,029.81

1-Jun-10 19,600.57 20,957.09 19,211.67 20,128.99 1,406,631,100 20,128.99

3-May-10 20,799.79 21,011.95 18,971.52 19,765.19 1,771,415,700 19,765.19

1-Apr-10 21,390.89 22,388.77 20,763.34 21,108.59 1,722,752,500 21,108.59

1-Mar-10 20,853.08 21,450.98 20,575.78 21,239.35 1,739,336,000 21,239.35

1-Feb-10 19,987.67 20,780.50 19,423.05 20,608.70 1,432,794,400 20,608.70

4-Jan-10 21,860.04 22,671.92 19,916.34 20,121.99 2,183,563,400 20,121.99


86

5. Exchange Rate on IDR

Bulan Tahun Kurs Oct-13 11,268

Nov-11 9,170 Sep-13 11,613

Oct-11 8,835

Aug-13 10,924

Sep-11 8,823 Jul-13 10,278

Aug-11 8,578

Jun-13 9,929

Jul-11 8,508 May-13 9,802

Jun-11 8,597

Apr-13 9,722

May-11 8,537 Mar-13 9,719

Apr-11 8,574

Feb-13 9,667

Mar-11 8,709 Jan-13 9,698

Feb-11 8,823

Dec-12 9,670

Jan-11 9,057 Nov-12 9,605

Dec-10 8,978

Oct-12 9,615

Nov-10 9,013 Sep-12 9,588

Oct-10 8,928

Aug-12 9,560

Sep-10 8,924 Jul-12 9,485

Aug-10 9,041

Jun-12 9,480

Jul-10 8,952 May-12 9,565

Jun-10 9,083

Apr-12 9,190

May-10 9,180 Mar-12 9,180

Apr-10 9,012

Feb-12 9,085

Mar-10 9,115 Jan-12 9,000

Feb-10 9,335

Dec-11 9,086

Jan-10 9,365

87

6. BI Interest Rate

Tanggal BI Rate

8 Okt 2013 7.25%

10-Nov-11 6.00%

12-Sep-13 7.25%

11 Okt 2011 6.50%

29 Agust 2013 7.00%

8-Sep-11 6.75%

11 Juli 2013 6.50%

9 Agust 2011 6.75%

13 Juni 2013 6.00%

12 Juli 2011 6.75%

14 Mei 2013 5.75%

9 Juni 2011 6.75%

11-Apr-13 5.75%

12 Mei 2011 6.75%

7 Maret 2013 5.75%

12-Apr-11 6.75%

12-Feb-13 5.75%

4 Maret 2011 6.75%

10-Jan-13 5.75%

4-Feb-11 6.75%

11 Des 2012 5.75%

5-Jan-11 6.50%

8-Nov-12 5.75%

3 Des 2010 6.50%

11 Okt 2012 5.75%

4-Nov-10 6.50%

13-Sep-12 5.75%

5 Okt 2010 6.50%

9 Agust 2012 5.75%

3-Sep-10 6.50%

12 Juli 2012 5.75%

4 Agust 2010 6.50%

12 Juni 2012 5.75%

5 Juli 2010 6.50%

10 Mei 2012 5.75%

3 Juni 2010 6.50%

12-Apr-12 5.75%

5 Mei 2010 6.50%

8 Maret 2012 5.75%

6-Apr-10 6.50%

9-Feb-12 5.75%

4 Maret 2010 6.50%

12-Jan-12 6.00%

4-Feb-10 6.50%

8 Des 2011 6.00%

6-Jan-10 6.50%

88

7. Inflation

Bulan Tahun Tingkat Inflasi

Oktober 2013 8.32%

November 2011 4.15% September 2013 8.40%

Oktober 2011 4.42%

Agustus 2013 8.79%

September 2011 4.61% Juli 2013 8.61%

Agustus 2011 4.79%

Juni 2013 5.90%

Juli 2011 4.61% Mei 2013 5.47%

Juni 2011 5.54%

April 2013 5.57%

Mei 2011 5.98% Maret 2013 5.90%

April 2011 6.16%

Februari 2013 5.31%

Maret 2011 6.65% Januari 2013 4.57%

Februari 2011 6.84%

Desember 2012 4.30%

Januari 2011 7.02% November 2012 4.32%

Desember 2010 6.96%

Oktober 2012 4.61%

November 2010 6.33% September 2012 4.31%

Oktober 2010 5.67%

Agustus 2012 4.58%

September 2010 5.80% Juli 2012 4.56%

Agustus 2010 6.44%

Juni 2012 4.53%

Juli 2010 6.22% Mei 2012 4.45%

Juni 2010 5.05%

April 2012 4.50%

Mei 2010 4.16% Maret 2012 3.97%

April 2010 3.91%

Februari 2012 3.56%

Maret 2010 3.43% Januari 2012 3.65%

Februari 2010 3.81%

Desember 2011 3.79%

Januari 2010 3.72%

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