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RESEARCH PAPERS ON THE IMPACT OF MACROECONOMIC VARIABLES ON

STOCK PRICES

PAPER I Relationship between Macroeconomic Variables and Singapore Stock Exchange

Summary:

It starts with Efficient Market Hypothesis (EMH) which states that financial markets are

informational efficient, i.e. , one cannot consistently achieve returns in excess of the average

market returns on a risk adjusted basis, given the information publically available at the time

the investment is made. There are 3 versions:

1. Weak: This says that Security Prices include the effect of all information publically

available in the past.

2. Semi-Strong: Claims that Security Prices include both effects of information available in

the past and they change instantly to any new information provided publically.

3. Strong: Claims that the prices reflect past information, new publically available

information and they even reflect hidden or insider information.

Weak and Semi-strong have evidences in their favour.

But then this is said to be only theory as empirical evidence contradicts the EMH. For example,

if EMH was true, then no investor would be able to make above normal returns consistently.

Thus, the writer picks up one variable at a time and studies the hypothetisized relationship

between Stock Prices and the variable making use of the Dividend Growth Model: P=D1/(k-g)

Interest rates:

Negative Relationship with Stock Prices. Lower Interest rates, higher corporate investment

and higher expected profits. Higher expected future returns and higher price(g). Also, high i-

rate, high cost of borrowing, stock transactions for you and me costly, lower demand, lower

price(k).

Inflation:

Negative. Again, demand side factor. Will reduce AD, lower demand, also make investor

borrowing costly, He will expect a higher rate of return and thus a higher K in the DD model

above. Thus stock price will be lower.

Exchange Rate:

The relationship will depend on the relative importance of import/export. If currency

appreciates , then the market will attract investments.

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Otherwise, say the country is a net exporter. A currency appreciation would mean that one unit

of foreign currency, will pay less of home currency. Say, Rs/$ exchange rate is 45. For, every

on dollar the US pays me, I will get Rs 45. Contract Finalized. Now, currency appreciates such

that I get Rs. 40 for every $. I lose Rs. 5 every dollar. Thus. for a net exporter, appreciation

leads to lower stock prices. Alternatively, a net importer will benefit from appreciation. Also,

currency depreciation promotes exports by making goods cheaper to foreigners, any

appreciation would hamper an exporting country and; currency appreciation promotes imports.

US as net importer should benefit from appreciation.

Methodology

Vector Error Correlation Model. (VECM)

PAPER II Impact of Oil Prices on the Stock Market by Omar L Caban

Summary:

The entire stock market does not get equally or at the same time affected by the fluctuation in

the oil prices.

The US industrial sectors that get most affected with rise in oil prices are:

1. The cyclical Services sector gets most negatively influenced. They constitute the general

retailers, support services, media, entertainment, leisure, hotels and transport.

2. The sector which follows next in order is Cyclical Consumer goods. These include

household goods, textiles, automobiles and parts.

3. The next negatively influenced sector is the Financials. They comprise of investment

companies, banks, life, assurance, insurance, real estate, specialty and other finance.

Conclusion: Impact of oil prices on the stock market is inversely proportional. During an oil

price rise, it is advisable to hold on to energy stocks shift focus from the mass market general

retailers.

Nilay Pandey Metrics4 Analtics

PAPER III The Impact of Oil Price Shocks on the U.S. Stock Market by Lutz Kilian,

University of Michigan and CEPR ,Cheolbeom Park, National University of Singapore

Summary:

Empirical evidence is mixed about whether the impact is negative or positive. This paper talks

about how the impact on stock price is actually dependent on the cause of change in Oil Price.

The cause can be:

i. Demand side:

a. Precautionary Demand: Negative Relation with Stock Price

b. Commodity Driven Demand: Positive Relation with Stock Price

ii. Supply Side, according to this research paper is not too important a factor as compared to

the demand side factors.

These structural shocks have very different effects on the real price of oil. For example, an

unexpected increase in precautionary demand for oil causes an immediate and persistent

increase in the real price of oil, an unexpected increase in aggregate demand for all industrial

commodities causes a delayed, but sustained increase in the real price of oil, whereas

unanticipated oil production disruptions cause a transitory increase in the real price of oil

within the first year.

Methodology:

1. trace fluctuations in the real price of oil to the underlying structural demand and supply

shocks in the crude oil market

2. estimate the dynamic responses of U.S. stock market aggregates to these shocks.

Further insights can be gained from responses of industry specific stock returns to demand and

supply shocks in the crude oil market.

Identify the sectors most sensitive to oil shocks and study the opportunities for adjusting

one’s portfolio in response to Oil market disturbances.

Oil Prices are endogenous to the model

Reverse Causality measurement

PAPER IV The Stock Market Reaction to Oil Price Changes by Sridhar Gogineni,

University of Oklahoma

Summary:

1. Oil price changes most likely caused by supply shocks have a negative impact while oil

price changes most likely caused by shifts in aggregate demand have a positive impact on

Nilay Pandey Metrics4 Analtics

the same day market returns. In addition to the returns of oil-intensive industries, returns of

industries that do not use oil to any significant extent are also sensitive to oil price changes.

2. Large oil price changes over a one-day horizon and oil price changes during war periods

have a large negative impact on the same day market returns. On the other hand, the stock

market is positively correlated with small daily oil price changes.

3. Most large oil price changes over a one-day horizon are due to supply shifts, changes in

expectations of future economic activity are likely spread out over time so that their impact

on oil prices in any one day is small.

4. Oil prices are reported daily and since stock prices usually respond quickly to relevant

public information, using daily data provides a more precise and timely measure of the

impact of oil price changes on the market. While a number of studies examine the relation

between oil price changes and the stock market over long horizons, if investors believe oil

has an important impact on the economy, then oil price changes should impact the stock

market almost immediately as stock prices usually respond very quickly to public

information.

Methodology:

Obtain daily value-weighted returns of NYSE/NASDAQ index.

Obtain daily cash price data of light crude oil.

Match daily market returns with the corresponding oil returns.

In depth Analysis.

PAPER V Do Oil Prices Directly Affect the Stock Market by Andrea Pescatori and Beth

Mowry

Summary:

Oil prices and stock market performance might be negatively correlated due to:

High transaction costs

Inflation fears

It is also possible to associate expensive crude with a booming economy as higher prices could

reflect stronger business performance and increased demand for fuel.

The data has been collected on Weekly basis, and the analysis infers that oil prices and the

S&P 500 index do not exhibit any of the above mentioned phenomena. Many a time, they

move in the opposite direction, many a time in the same.

Nilay Pandey Metrics4 Analtics

An in depth analysis on Daily, weekly and monthly data, matched with industries is called for

as on the whole Oil impacts specific industries in a similar manner. Many a time, we do see

news articles that Oil Price plummets stock markets, but that cannot be proved.

Correlation Table has been made using two different samples to see the impact on specific

industries and shows that:

The majority of correlations computed for the different indexes and frequencies of data are

relatively small or not significant, with the exception of the Dow Jones Transportation index.

Time Line

April 7 to April 10 Structure the project/ finalise data

April 11 to April 20 Data Analysis and Initial findings

April 21 to April 28 Conclusion, Modelling if any possible

April 28 onwards Documentation