Copy of Inter-relationships Between Stock Index with Residential and

RESEARCH METHODOLOGY(Data Analysis done be Eviews 8)

Inter-relationships Between

Stock Index with Residential and Indirect

Property Investment

Property Data

(Residential & Indirect property)

LEE YOUNG YEE

MG 131 008

Scope of study

1. House Price Index - National, KL, Selangor, Penang, Johor

(2000Q1 -2013Q4, NAPIC)

2.KLCI stock index,

(2000Q1- 2013Q4, DataStream)

3. S&P Malaysia REIT

(2006Q4- 2013Q4, DataStream)

4. Exogenous factors - Malaysia GDP, T bill rate, CPI)

(2000Q1- 2013Q4, DataStream)

5. Contagion factors - Singapore GDP / STI stock index

(2000Q1- 2013Q4, DataStream)

Research Objectives

To identify the relationship between stock market and real estate market, for different property type, property market and property investment instruments, which includes the impact from exogenous factors.

To identify the causes and critical point for the transformation of the lead-lag relationship between stock index and housing price index.

To identify wealth effect and credit price effect in Malaysian stock market and real estate investment by causality test. To have details on the action and reaction for residential properties, property index and REIT to the stock index for ascertain the reason for the relationship.

CONCLUSIONS

Limitation

Interpretation of results

Correlation

& OLS

Correlation

• Broadly speaking, house price & stock index highly correlated with CPI & Malaysia GDP
• Malaysia stock index is close correlated with Singapore Stock index
• Malaysia house price & Stock index correlated with satisfactory level

OLS

• CPI & Malaysia GDP is important to both Malaysia stock index & house price index
• Singapore stock index is a major contribution factor to Malaysia stock index

Contagion effects

Structural break

Unforeseeable exogenous factors

Laspeyres indexes based may be not well representing the market

Typo error

Contagion effect exists in Malaysia house price index.

Granger causality test proven that short-term Granger caused by Singapore STI or GDP or both.

However, not significant in variance decomposition.

• All the house price index having structural break for the study period
• 1st break occurred at 2003~2005, and mostly close the gap during 2007, which is before the global financial crisis. The possible reason is stock index is surging after market confident restoration for property market is less sensitive to reduction in interests rate to stock index

Analysis on independent variable in relationship to Malaysia house price index

Shocks

Granger causes

Short term

• Relatively to long term, causality is lesser.
• More wealth effect than credit price effects
• Malaysia GDP, CPI & Singapore stock index Granger cause Malaysia house price index.
• Some cases were Granger caused from T-bills rate and Singapore GDP.

Short term shock (3 quarters)

• Malaysia GDP is the brought most short-term shocks to Malaysia house price, and followed by KLCI Malaysia.
• Contagion effect from Singapore GDP, observed at SemiD market in Johor, KL & Selangor.
• Bursa Property index having more short-term, shock from KLCI, relatively to REIT.
• Malaysia Highrise price index and Bursa Property index considered most short-term from KLCI.

Long Term

• Typically, it would appear with wealth effect for most of the market, however, Penang market appear with credit price effects.
• Bursa Property price with wealth effect
• S&P Malaysia REIT index appear with credit price effect

Long term shock (10 quarters)

• KLCI is brought most long-term shocks to Malaysia house price, and followed by T-bill rates.
• Contagion effects is not significant in long run.
• Bursa Property price index having more shock than KLCI, relatively to REIT

Long-term bilateral granger causes

• Only occurred in Malaysia Terrance, Penang overall, Penang highrise , Penang Detach house price index.
• This means that stock index and house price index compliment each others.

Recommendation

Raw data processing will be having better precision

Horizontal investigate for Eastern Malaysia or other states

Vertical investigation for various cities

Interrelationship among states

Analysis on independent variable in relationship to Malaysia stock index

Granger Causality Test

Test for relatively long term causal relation among the factors and observe the lead-lag relationship (Granger, 1969)

Variance Decomposition

1st differential to convert data into stationery

It is multivariate time series analysis

Validate all independents exogenous variable strength to Malaysia stock index & house price index, for short term and long term.

Shock will be represented in percentage.

Variance Decomposition

Ascertain number of co-integration among the variables.

Johansson

co-integration Test

Lag Selection

Ascertaining number of lag in order to perform vector error correction model (VECM)

Lag Selection

Unit Root Test

(Augmented Dickey-Fuller Test)

Ascertaining Data stationery

Unit Root Test

(Augmented Dickey-Fuller Test)

Descriptive statistics and Correlation Analysis

Descriptive statistics is merely explaining the relationship between stock market and real estate market

Correlation Analysis is to defined the tendency of 2 or more variables move in parallel

Wealth Effect

vs

Credit Price Effect

Wealth Effect (Markowitz, 1952)

Stock market lead the property market

Credit Price Effect (Chen, 2001)

Property market lead the stock market

Geographical Differences

Malaysia Context

Different geographical location lead to different market characteristics (Panayotis Kapopoilos & Sioks, 2005)

Thus, we can identify different location market characteristics in Malaysia

Contagion effects

1. Mixture of credit price and wealth effect in Malaysia

2. Time frame (2000-2010)

3. No further analysis on exogenous impact or its shocks

4. Using BLR , not T-bill rate

5. Contagion effect cross the country boundaries not taken into account

6. Last study on Selangor KL, Penang, lack of Johor.

7. Only direct property investment was studied, we further on indirect property investment vechicle.

CUSUM squared

The shock from country spillover effects (World bank, 2011 ; Calvo & Reinhart, 1966)

Singapore is the major trade counterpart for Malaysia, thus there would be expectation of influences.

As market in nature move in an expected direction, however, it may change because of some occurrence which deviated the original channel (Barnard, G.A, 1959)

Exogenous factors

CUSUM squared

Spillover effect (Hibers, 2008)

GDP, inflation, interest rate

(Chen, 2001 ; Peng and Hudson-Wilson)

Introduction

PROBLEM STATEMENT

Simplest linear regression

Ascertain the strengths of relationship between stock market and real estate market

Ordinary Least Square (OLS)

Descriptive statistics

Correlation Analysis is to defined the tendency of 2 or more variables move in parallel

Descriptive statistics

Both real estate market and stock markets are important investment vehicles.

Residential property represents a large portion of household investment portfolio and ex-post efficient portfolio in increasing with risk aversion of the investor in Malaysia (Ting 2003)

Residential property investment vs Indirect Property investment (REIT & Bursa Property index)

Correlation

Descriptive statistics is merely explaining the relationship between stock market and real estate market

Correlation

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