Impact of World Oil Prices Volatility on Sectoral Stock Returns in Indonesia

THE IMPACT OF WORLD OIL PRICES VOLATILITY ON SECTORAL STOCK PRICE RETURN IN INDONESIA: GARCH-M APPROACH SetyoTri 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. 1 Variables Variable Definition The Profits or Loss obtained from the sectoral stock price index changes Measurement Return index of sectoral stock price ?? ??= ?? ?? 1 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 ARCH-GARCH: the model used to obtain volatility value 4 Volatility of World oil Price The situation connoted to instability and is unpredictable

METHODS 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 ??= ?0+ ?1?1?+ ?? 2 ??2= ?0+ ?1?? 1 2 + + ???? ? ARCH components

METHODS (2) GARCH model in mean (GARCH-M) ??= ?0+ ?1?1?+ ?? (1) ? ? 2 2(2) ??2= ? + ?=1 + ?=1 ???? ? ???? ? ?: constant varians ???? ? ???? ? Eq. 1: for mean equation Eq. 2: for varians equation. 2 : ARCH component 2 : GARCH component ??2 depend on residual and previous variant of residual. For positive variant and fulfilling the assumption of non-negativity constraint, so ? > 0 ; ?? and ?? 0 ; ??+?? < 1.

METHODS (2) GARCH model in mean (GARCH-M) ? + ?? ??? + ?? ??? + ?? ???? + ??,? ?= ??+ ????,? ? + ????,? ? ??,?= ??+ ????,? ??,? ? ? + ?????

RESULTS Table 1. Stasionarity Result Consumer Goods Industry Return Retail and Service Return Agricultu re Return Multi- industry Return Primary Industry Return Infrastruct ure Return Mining Return Finance Return Property Return Oil Price Kurs 0.8841 (Non- Stationary ) 0.000 (Stationar y) 0.9949 (Non- Stationary ) 0.000 (Stationar y) Level - - - - - - - - - 1st 0.000 (Stationar y) 0.000 (Stationary ) 0.000 (Stationar y) 0.000 (Stationar y) 0.000 (Stationar y) 0.000 (Stationar y) 0.000 (Stationar y) 0.000 0.000 differen ce (Stationary) (Stationary)

RESULTS Table 2. Assumption test Result Model Normality Q-stat ARCH-LM ARIMA (3,1,2) Abnormal White noise ARCH effect exists ARCH effect is non- existence GARCH (2,1) Abnormal White noise

RESULTS Table 3. Estimation result of GARCH (2,1) MULTI- INDUSTR Y Mean Equation -0.000756 0.214181 -0.090182 [0.9945] [0.1907] [0.4720] 6.12E-05 -0.003651 0.00289 [0.9675] [0.1820] [0.0816] 0.000837 0.001119 0.000521 [0.0000]* [0.0000]* [0.0097]* -0.00016 0.000305 -0.000242 [0.6472] [0.5303] [0.5154] -4.05E-05 -5.40E-05 -7.21E-05 [0.0000]* [0.0000]* [0.0000]* Variance 8.08E-06 1.07E-05 1.06E-05 [0.0000]* [0.0003]* [0.0000]* 0.076649 0.053937 0.09502 [0.0000]* [0.0000]* [0.0000]* 0.877487 0.911508 0.847587 [0.0000]* [0.0000]* [0.0000]* -5.11E-06 -5.16E-06 -2.90E-06 [0.0000]* [0.0208]* [0.0298]* 0.954136 0.965445 0.942607 0.7951 0.395 0.4202 Probability with *) has alfa significance of 5% CONSUMER GOODS INDUSTRY AGRICULTUR E PROPERT Y PRIMARY INDUSTRY INFRASTRUCTU RE RETAIL AND SERVICE RESULT MINING FINANCE 0.097163 [0.3855] -0.000862 [0.5941] 0.000426 [0.0492]* -4.92E-05 [0.8946] -2.82E-05 [0.0000]* -0.138643 [0.2253] 0.003289 [0.0296]* 0.000829 [0.0000]* -0.000276 [0.4357] -6.11E-05 [0.0000]* Equation 1.32E-05 [0.0000]* 0.134931 [0.0000]* 0.793973 [0.0000]* -3.01E-06 [0.0584] 0.928904 0.8593 0.045173 [0.6301] 0.000633 [0.6306] 0.000824 [0.0001]* -0.000122 [0.7287] -6.72E-05 [0.0000]* 0.028839 [0.7749] 0.000872 [0.4968] 0.000206 [0.2790] -8.27E-05 [0.7903] -3.19E-05 [0.0000]* 0.067915 [0.6265] 0.000271 [0.8668] 0.000433 [0.0128]* -0.000246 [0.4429] -3.80E-05 [0.0000]* 0.10202 [0.3477] 0.000884 [0.4260] 0.000534 [0.0004]* -0.000391 [0.1736] -3.52E-05 [0.0000]* SQRT(GARCH) C D(WTI) VOLATILITY D(KURS) 1.56E-05 [0.0000]* 0.130994 [0.0000]* 0.795961 [0.0000]* -6.99E-06 [0.0000]* 0.926955 0.6942 1.19E-05 [0.0000]* 0.158681 [0.0000]* 0.793013 [0.0000]* -4.52E-06 [0.0017]* 0.951694 0.7154 1.10E-05 [0.0000]* 0.157292 [0.0000]* 0.779635 [0.0000]* -1.03E-06 [0.4957] 0.936927 0.6511 6.37E-06 [0.0000]* 0.079107 [0.0000]* 0.868005 [0.0000]* -2.48E-06 [0.0011]* 0.947112 0.2826 7.67E-06 [0.0000]* 0.136431 [0.0000]* 0.798033 [0.0000]* -1.53E-06 [0.1136] 0.934464 0.0629 C RESID(-1)^2 GARCH(-1) D(WTI) ARCH+GARCH LM test

RESULTS Table 3. Estimation result of GARCH (2,1) Mean Equation Coefficient Variable C AR(1) AR(2) AR(3) MA(1) MA(2) Probability -0.016799 -0.583694 -1.009165 -0.035928 0.544275 0.99491 0.614 0.00 0.00 0.216 0.00 0.00 Variance Equation Coefficient Variable C RESID(-1)^2 RESID(-2)^2 GARCH(-1) Probability 0.03241 0.108535 -0.078945 0.95583 0.0001 0.00 0.0022 0.00

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 > =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> = 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.