Presentation of the research article by Syed A. Bashir, 2006.... Oil prices and emerging stock markets

1. OIL PRICE AND
EMERGING STOCK
MARKETS
AUTHOR:
SYED A. BASHIR, PERRY SADORSKY (2006)
GLOBAL FINANCE JOURNAL

2. INTRODUCTION:
The purpose of this paper is to contribute to the literature of
stock market and energy prices, less research focused on
developing countries.
In 1973, cost of imported oil price increased from $3 to $13
(per barrel) for developing countries and price of export
products fell. IMF and World bank had to provide loans to
developing country increased by 550%.
Rising of oil prices are an indicative measure and control by
central bank by raising interest rate. Increases in oil demand
without offsetting increases in supply lead to higher prices.

3. CONT.…
The overall impact of rising oil prices on stock returns
depend on whether a company is consumer or producer.
Higher prices act like an inflation tax on consumer and
producer by:
1) Reducing the amount of disposable income consumers
have left to spend on other goods and services.
2) Raising the cost of non-oil producing companies and , in
the absence of passing these cost on consumer,
reducing the profits and dividend which are the key
drivers of stock prices. Higher production cost

4. LITERATURE REVIEW:
Sadorsky (1999) found that changes in oil prices have
impact on stock return by using monthly data.
Faff and Brailsford (1999) they find a positive impact
on the oil and Gas and diversified resource industries
and negative relation for transportation industries, and
paper & packaging.

5. RESEARCH OBJECTIVE
To find out the relationship between stock return and oil
prices by using the unconditional and conditional risk
factors.
HYPOTHESIS:
H0: POSITIVE RELATIONSHIP BETWEEN STOCK
RETURN AND OIL PRICES IN UP MARKET.

6. DATA:
 Daily closing price of stock market from December
31, 1992 to October 31, 2005.
 The countries Argentina, Brazil, Chile, Colombia,
India. Indonesia, Israel, Jordan, Korea, Malaysia,
Mexico, Pakistan, Peru, Philippines, Poland, South
Africa, Sri Lanka, Taiwan, Thailand, Turkey, and
Venezuela. Selected for long trade data.
 Total observation 3348.
 All the data are in US dollar and secondary data.
 The data are available for DataStream
www.nymex.com, www.research.stlouisfed.org/fed2/

7. METHODOLOGY:
Total Risk- Systematic and non-systematic (firm specific) risk.
Variance of market returns estimated over the same sample
period.
Stock Return: subtracting the daily stock return on a three month
U.S T-Bills.
Kurtosis, Skewness- Stock return not normally distributed.
Each country estimated by rolling regression. Estimation window
fixed at 1250 observation. For analysis 260 weeks and 60 months
observation. Five years of data is recommended (Brealey &
Myers, 2003).
In second step, unconditional (market, oil and exchange rate beta)
and conditional relationship(skewness, kurtosis, total risk)
regression are estimated for realized stock return and risk factor.

8. MODEL 1: relationship between return, exchange rate, market and oil risk.
Rit = C + B mit MRt + B oit OILt +Beit TWEXt +Eit
MODEL 2: relationship between market risk, oil price risk, squared market
price risk, and exchange rate risk.
Rit + Yo + Ym1 Bmit + Yo Boit + Ye1 Beit + E2t
MODEL 3: relationship between return, market risk, oil price risk, squared
oil price risk, and exchange rate risk.
R it = Yo + Ym2D1t Bmit+Ym3(1-D1t)Bmit+Yo2D2tBoit+Yo3(1-D2t)Boit+Ye1Beit+E3t

9. MODEL 4: relationship between return, market risk, oil price risk, total
risk, and exchange rate risk. Rit + Yo + Ym1 Bmit + Yo1 Boit + YT1 TRit +
Ye1Beit + E4t
MODEL 5: relationship between returns, market risk, oil price risk,
skewness and exchange rate risk. Rit=Yo+Ym2D1t Bmit+Ym3(1-
D1t)Bmit+Yo2D2tBoit+Yo3(1-D2t)Boit+YT2D1TTRit+Ye1Beit+E5t
MODEL 6: relationship between returns, market risk, oil price risk,
kurtosis, and exchange rate risk. Rit + Yo + Ym1 Bmit + Yo1 Boit + YS1
SKEWit + Ye1Beit + E4t
TECHNIQUE: CAPM Model, Pooled Regression, Correlation,
Symmetric test

10. RESULT AND ANALYSIS

11. RESULT AND ANALYSIS
MODEL 1: Strong positive relation between oil price and return
but only when oil price is high.
MODEL 2: Non-linear relations between market risk and return.
MODEL 3: Conditional and Unconditional relation between
squared oil price risk and return.
MODEL 4: Conditional relationship between total risk and returns.
MODEL 5: Skewness is negatively related to return.
MODEL 6: Kurtosis doesn’t show significant relation to returns.
Results same as (Tang and Shum, 2003)

12. CONCLUSION
It is concluded that there is a positive relationship between
stock return and oil prices in up market and negative relation
in down market. Oil consumption increases more in
developing countries. Developed economies are more energy
efficient today because of technological innovation.