The Impact of World Oil Price Volatility on Sectoral Stock Returns in Indonesia

THE IMPACT OF WORLD OIL PRICES VOLATILITY ON SECTORAL STOCK

PRICE RETURN IN INDONESIA: GARCH- M APPROACH

Setyo Tri Wahyudi

Universitas Brawijaya

BACKGROUND

 World crude oil plays a vital role in world economy because it is considered as an important factor in the production function.

 Movements and shocks in oil prices can affect the real economic activity which will ultimately affect the economy of a country

(Adebiyi et.al, 2009):

 the supply side: company's production costs

 the demand side: ability of the consumers to buy

 Changes in oil prices can also have an impact on the capital market through the company's cash flow.

 Masih et al. (2010): shocks in oil prices can have a direct and

indirect negative impact on company profits .

THE PURPOSE

To analyze the effect of the movement of world oil prices and their volatility, as well as the risk of volatility on the

return of the nine sectoral stock index in Indonesia.

LITERATURES

 Volatility and Stock Price Movements

 The Role of Oil Prices in Economy

 The Efficient Market Theory

 Portfolio Theory

 Previous Empirical Research

METHODS

No. Variables Variable Definition Measurement 1 Return index of sectoral

stock price

The Profits or Loss

obtained from the sectoral stock price index changes 2 Volatility risk of Sectoral

Stock Price Index

The amount of risk

occurred when sectoral stock index is strongly fluctuated (volatile)

 

Deviation Standard from GARCH-M

3 World oil price Oil trade spot price It is formed from the supply and demand of oil trading

4 Volatility of World oil Price

The situation connoted to instability and is

unpredictable

ARCH-GARCH: the model used to obtain volatility value

No. Variables Variable Definition Measurement 1 Return index of sectoral

stock price

The Profits or Loss

obtained from the sectoral stock price index changes 2 Volatility risk of Sectoral

Stock Price Index

The amount of risk

occurred when sectoral stock index is strongly fluctuated (volatile)

 

Deviation Standard from GARCH-M

3 World oil price Oil trade spot price It is formed from the supply and demand of oil trading

4 Volatility of World oil Price

The situation connoted to instability and is

unpredictable

ARCH-GARCH: the

model used to obtain

volatility value

 This study employs two type of analysis model:

 (1) ARCH/GARCH model that is used to obtain the volatility value of the world oil price, and

 (2) GARCH model in mean (GARCH-M), which is used to identify the influence of the world oil volatility and price changes, as well as the volatility risk towards the sectoral stock return index.

METHODS

(1) ARCH/GARCH model

METHODS

 

ARCH components

(2) GARCH model in mean (GARCH-M)

METHODS

(1) (2)

 

: constant varians : ARCH component

: GARCH component Eq. 1: for mean equation Eq. 2: for varians equation.

depend on residual and previous variant of residual.

For positive variant and fulfilling the assumption of non-negativity constraint, so and .

 

(2) GARCH model in mean (GARCH-M)

   

METHODS

RESULTS

Table 1. Stasionarity Result

Oil

Price Kurs

Agricult ure Return

Mining Return

Multi- industr

y Return

Primary Industr

y Return

Finance Return

Infrastruc ture Return

Consume r Goods Industry

Return

Propert y Return

Retail and Service Return

Level

0.8841 (Non- Stationar

y)

0.9949 (Non- Stationar

y)

- - - - - - - - -

1st differe

nce

0.000 (Stationa

ry)

0.000 (Stationa

ry)

0.000 (Stationa

ry)

0.000 (Stationar

y)

0.000 (Stationa

ry)

0.000 (Stationa

ry)

0.000 (Stationa

ry)

0.000 (Stationary)

0.000 (Stationary

)

0.000 (Stationa

ry)

0.000 (Stationa

ry)

RESULTS

Table 2. Assumption test Result

Model Normality Q-stat ARCH-LM

ARIMA (3,1,2) Abnormal White noise ARCH effect exists

GARCH (2,1) Abnormal White noise ARCH effect is non-

existence

RESULTS

Table 3. Estimation result of GARCH (2,1)

RESULT AGRICULTUR

E MINING

MULTI- INDUST

RY

PROPERT

Y FINANCE PRIMARY INDUSTRY

CONSUMER GOODS INDUSTRY

INFRASTRUCT URE

RETAIL AND SERVICE

         Mean Equation        

SQRT(GARCH) 0.097163 -0.000756 0.21418

1 -0.090182

-0.138643 0.045173 0.028839 0.067915

0.10202

  [0.3855] [0.9945] [0.1907] [0.4720] [0.2253] [0.6301] [0.7749] [0.6265] [0.3477]

C -0.000862

6.12E-05

- 0.00365

1

0.00289 0.003289

0.000633 0.000872

0.000271

0.000884

  [0.5941] [0.9675] [0.1820] [0.0816] [0.0296]* [0.6306] [0.4968] [0.8668] [0.4260]

D(WTI) 0.000426 0.000837 0.00111

9 0.000521 0.000829

0.000824 0.000206 0.000433

0.000534

  [0.0492]* [0.0000]*

[0.0000]

* [0.0097]* [0.0000]* [0.0001]* [0.2790] [0.0128]* [0.0004]*

VOLATILITY -4.92E-05 -0.00016

0.00030

5 -0.000242 -0.000276 -0.000122 -8.27E-05 -0.000246 -0.000391

  [0.8946] [0.6472] [0.5303] [0.5154] [0.4357] [0.7287] [0.7903] [0.4429] [0.1736]

D(KURS) -2.82E-05 -4.05E-05 -5.40E-

05 -7.21E-05 -6.11E-05

-6.72E-05 -3.19E-05 -3.80E-05

-3.52E-05

  [0.0000]* [0.0000]*

[0.0000]

* [0.0000]* [0.0000]* [0.0000]* [0.0000]* [0.0000]* [0.0000]*

         Variance Equation        

C 1.56E-05 8.08E-06 1.07E-05 1.06E-05 1.32E-05 1.19E-05 1.10E-05 6.37E-06 7.67E-06

  [0.0000]* [0.0000]*

[0.0003]

* [0.0000]* [0.0000]* [0.0000]* [0.0000]* [0.0000]* [0.0000]*

RESID(-1)^2 0.130994 0.076649 0.05393

7 0.09502 0.134931

0.158681 0.157292 0.079107

0.136431

  [0.0000]* [0.0000]*

[0.0000]

* [0.0000]* [0.0000]* [0.0000]* [0.0000]* [0.0000]* [0.0000]*

GARCH(-1) 0.795961 0.877487 0.91150

8 0.847587 0.793973

0.793013 0.779635 0.868005

0.798033

  [0.0000]* [0.0000]*

[0.0000]

* [0.0000]* [0.0000]* [0.0000]* [0.0000]* [0.0000]* [0.0000]*

D(WTI) -6.99E-06 -5.11E-06 -5.16E-

06 -2.90E-06 -3.01E-06

-4.52E-06 -1.03E-06 -2.48E-06

-1.53E-06

  [0.0000]* [0.0000]*

[0.0208]

* [0.0298]* [0.0584] [0.0017]* [0.4957] [0.0011]* [0.1136]

ARCH+GARC

H 0.926955 0.954136 0.96544

5 0.942607 0.928904 0.951694 0.936927 0.947112 0.934464

LM test 0.6942 0.7951 0.395 0.4202 0.8593 0.7154 0.6511 0.2826 0.0629

Probability with *) has alfa significance of 5%  

RESULTS

Mean Equation

Variable Coefficient Probability

C -0.016799 0.614

AR(1) -0.583694 0.00

AR(2) -1.009165 0.00

AR(3) -0.035928 0.216

MA(1) 0.544275 0.00

MA(2) 0.99491 0.00

Variance Equation

Variable Coefficient Probability

C 0.03241 0.0001

RESID(-1)^2 0.108535 0.00

RESID(-2)^2 -0.078945 0.0022

GARCH(-1) 0.95583 0.00

Table 3. Estimation result of GARCH (2,1)

Volatility Risk of Sectoral Stock Return Index

 The higher volatility of sectoral stock return index implies that the sectoral index will have higher risk (more volatile).

 The result of this study supports the market efficiency theory in which the current price change does not depend on the past

price change, because the current price change happens according to the investors’ reaction to new information happening randomly (Tandelilin, 2010).

 Investors do not pay much attention to past stock volatility when they are investing, and

 It shows that in stock investment they pay more attention to

the information of economic condition.

World Oil Price Effect to Sectoral Stock Price Return

 World oil prices have significant effect (prob > α=5%) and has unidirectional relationship to the sectoral stock return index, except to the stock return index of consumer goods industry sector which shows insignificant effect:

 The movement in world oil prices is a market risk for the Indonesian stock market.

 When there is a reduction in world oil prices, the return index of the stock for the eight sectors will be also decreased, and

otherwise, although the effect can be said to be relatively small.

 World oil prices can affect the financial sector through

derivative products for long-terms contracts of commodity

owned by issuers in this sector.

Volatility of World Oil Prices on Sectoral Stock Price Return

 High volatility values indicate a large and fast price change.

 The results found that the volatility of world oil prices had no significant effect on sectoral return index (prob> α = 5%) for all sectoral stock indexes.

 An increase in volatility of world oil prices does not affect the

return of each sectoral stock index.

CONCLUSION

 The risk of volatility does not affect the return index of sectoral stock.

 The stock price moves randomly and cannot be predicted

based on historical prices ---- the increase in risk does not have an impact on the expected return.

 For an investor, the investment decisions are not only

determined by the volatility of stock return, but rather by

considering information of the circulating economic situation.

 Sectorally, the results of the study found that world oil prices affect the return index of sectoral stock.

 Volatility of world oil prices was found to have no effect on

return index of sectoral stock.