Crude Oil Price as a Determinant of Industry Stock Returns

Crude Oil is the crucial input of modern economies. As countries urbanize and renovate their demand for oil raises drastically. Potential demand for oil is hard to forecast but is usually highly correlated with the growth in industrial production. Therefore, countries experiencing hasty economic growth are the ones probably to significantly amplify their demand for crude oil. Increases in oil demand without equalizing increases in supply lead to higher crude oil prices. Higher crude oil prices act like an inflation tax on consumers and producers by 1) plummeting the amount of disposable income consumers have left to spend on other goods and services and 2) increasing the costs of non-oil producing companies and, in the absence of fully passing these costs on to consumers, sinking profits and dividends which are key drivers of stock prices. In addition to worldwide demand and supply conditions, crude oil prices also respond to geopolitics, institutional arrangements (OPEC), and the dynamics of the futures market (Sadorsky, 2004). Unanticipated changes in any of these four factors can create volatility, and hence risk, in oil futures prices. Oil Price volatility increases risk and uncertainty which negatively impacts stock prices and reduces wealth and investment.

One macroeconomic factor that is receiving increasing empirical attention is crude oil. A key factor input, crude oil prices have the potential to dramatically alter the financial performance of national economies and the firms that operate therein. it is reasonable to expect that stock markets are profoundly influenced by oil price changes, remarkably little empirical evidence exists. Sadorsky (2001) argues that there has been a large volume of work investigating the links among international financial markets, and some work has also been devoted to the interaction among crude oil spot and future prices. In contrast, little work has been done on the relationship between oil spot/futures prices and stock indices. Even the findings of the extant work are mixed. Poon and Taylor (1991) found no evidence of an oil price factor in the U.S. and Japan, respectively. In contrast, Sardorsky (1999) concluded that oil prices were a significant factor in the U.S. Jones and Kaul (1996), Faff and Brailsford (1999), Sardorsky and Henriques (2001), and Sardorksy (2001) have also examined the impact of oil price factors with disparate results. While these studies have provided at least some evidence that oil prices constitute a source of systematic asset price risk, and that the exposure to this risk varies across industries, no recent work is known in the Pakistani context.

Statement of Problem

At least since the development of the capital asset pricing model, a literature has sought to identify the determinants of asset prices and returns. Given the capital asset pricing model rests on the premise that assets are priced according to their covariance with the market portfolio, the increasing acceptance that other pricing factors, especially macroeconomic factors, should also be modeled has led to yet further refinements, most notably in the form of the arbitrage pricing theory. With this multifactor specification as a starting point, an increasing number of empirical studies have sought to investigate whether macroeconomic variables constitute a source of systematic asset price risk at the market and industry level ((Antoniou et al. (1998), Faff and Chan (1998), Canova and Nicolo (2000)). The fundamental endeavor of this analysis is to find out whether macroeconomic information, particularly crude oil prices, gives incremental information beyond the market portfolio about the behavior of industry stock returns

Hypotheses:

Crude oil being the core input of productions it has been assumed that changes in crude oil price significantly changes the cost of production. Therefore an increase in crude oil price leads to higher cost of production. Consequently higher cost of production leads to lower profit margins or it forces producer to increase the price of the goods. And increase in price of goods leads lower demand for the good resultantly sales of the firm goes down and overall profitability suffer. Further more firm making tiny or negative profit loses investors’ confidence and its stocks price go down which leads to negative stock returns and vice versa. Following hypotheses are suggested:

H1: change in oil prices has significantly impact on the stock returns of Automobile and Parts sector of Pakistan

H2: change in oil prices has significantly impact on the stock returns Energy sector of Pakistan

H3: change in oil prices has significantly impact on the stock returns Chemical and Pharmaceutical sector of Pakistan

H4: Change in oil price has different impact on the stocks return of different industrial sectors.

CHAPTER 2: LITERATURE REVIEW

Asset prices are generally believed to respond sensitively to macroeconomic news. Every day experience gives the impression to support the observation that individual asset prices are influenced by a broad range of unpredicted events and that various events have a more persistent impact on asset prices than do others (Faff and Chan, 1998). Therefore macroeconomic news is important factor in the explanation of stock returns at the industry level.

In recent years there have been numerous studies which argued that stock prices not only replicate changes in current and future cash flows and anticipated returns, but are also determined by speculative dynamics that is investor attitude and/or overreaction to news. Many researchers have claimed that the strong predictability of stock returns over various horizons is proof of such fads. In an endeavor to measure whether the predictability of stock returns is rational, several recent studies tested whether using Capital Asset Pricing Model (CAPM) or a more general asset pricing model like the Arbitrage Pricing Theory (APT) could eliminate or ex-plain their predictability. If factors and/or their coupled risks can explain the predictability of stock returns then the market is convincing, and vice versa (Fama and French, 1989).

The approach taken in this paper uses a global multi-factor model that permits for both unconditional and conditional risk factors. This approach is related to the international capital asset pricing model (CAPM), the implications of which have been studied by Brealey & Myers, (2002). Whereas the focus of the CAPM is on market risk, the multi-factor model includes multiple sources of risk (Ross, 1976). The CAPM and multi-factor models are essential building blocks of contemporary portfolio theory. In both models, expected returns are linearly connected to risk factors and risk premiums. So far the CAPM has been broadly tested both domestically and internationally and the general agreement is that the CAPM explains no statistically significant correlation between systematic risk (beta) and returns (Berk, 1995).

Modern economies are more energy efficient nowadays than they were 40 years ago with oil usage per dollar of GDP less than half of what it was in the 1970s. This increase in energy efficiency has happened because of cheap energy intensity through technological modernization and more dependence on a broadened range of energy sources (like a greater mix between non-renewable and renewable energy sources). Emerging and new economies tend to be more energy intensive than more developed economies and are therefore more exposed to high oil prices. Consequently, oil price changes are likely to have a larger impact on earnings and stock prices in emerging economies.