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Does the stock market forecast movements in macroeconomic variables?

Introduction

The relationship between the stock market at different time scales and the micro-economy exists. The economic effects of stock market include effects on wealth, and pensions.

Early studies by various parties show that there are a number of variable that have extremely weak associations against the stock prices. Their influences on the stock market are also most negligible. For example, Ely &Robinson, (1237-1243), argue that variables like the country’s fiscal deficit or a country’s foreign institutional outlay in the capital market have unusually insignificant pressure on the stock market. This is in line with prior studies that show that during the post world war era, single variables such as money supplies and overall inflation rates are the dominant variable controlling the stock market. This therefore, sets out the study, as it tends to confirm the traditional belief in relations to the link between macroeconomic variable and the stock prices, that states that the real economic variable affect the stock market

Selection of Variables

According to Engsted, & Tanggaard, (22), the main macroeconomic variable, which are instrumental in the analysis of the correlation between the stock market and the macroeconomic variables includes variable such as prices of goods, supply of money, the real economic activities, the spot and predicted exchange rates, the prevailing interest rates. Other include political risks, the prices of oil, the trade sector, budgetary deficits, trade deficits, overall domestic consumption, rate of unemployment in the country, amount of imports and the overall regional stock market indices and real wage. However, not all variables listed above are relevant in the emerging stock market. It is therefore, necessary to narrow done according the level of importance to these emerging stock markets. This paper seeks to analyse the linkage between the macroeconomic variable, it is therefore, advisable to consider the above statement and balance the theoretical propositions while basing the argument on the prior evidences. In this view, there are only four macroeconomic variables that meet the above criteria. These variables are exchange rate, inflation rate, money supply, and interest rate (Ely, & Robinson, 173; Engsted, Tanggaard, 665; Gallagher, & Taylor, 212)

It is necessary to note that, in order to get an optimal results, the multiple regression must be run with the all the macroeconomic variable measured. It is also advisable to give the money supply and the overall rate of inflation one month lags. While available literature reveals a significant relationship between the variation in stock returns and the general level of inflation in countries, there is a negative correlation between the stock return and the expected inflation. On the other hand, common stock is an effective hedge, such that they are instrumental in the reduction of risks of any real return to investors. This stems from the general uncertainty associated with the future prices of goods.

Additionally, Geske, & Roll, (342), tried to examine the association between monthly stock turns against inflation during the post world war periods and realised that the correlation is negative. This was regarding both the expected and the unexpected inflation. However, it was quite exciting to note that the same negative correlation was realised using the US data. This is enough emphasis of the relationship between stock and inflation. However, the future level of consultation in a country and the price changes in a country can be effective in determining the movement of stocks. Stocks only appraise if the price of god in a country increases so is the level of consumption. Some of the countries in which the future prices of goods have become handy in determine the movement of stock includes Sri Lanka and Nigeria

The negative impact of the expected and unexpected inflation on the stock returns is as a result of the demand for money and the classical quantity theory of money. The relationship between the behaviour of stocks and unanticipated variation under alternative fiscal policy regimes is negative. This is because these countries have no fiscal policy changes and are uncertain abound the imminent changes in the value of their currencies. The negative impact of inflation of stock is due to real economic fluctuation. This fluctuation occurs due to the fluctuation in the economic variable or real and monetary fluctuation Ely, & Robinson. (237), argue that any rise in the value of the expected fluctuation has a reductive effect on the prices of equity in both India and USA

Money supply and stock

There are considerable debate of the relevance of money and its role as and indicators in the prices of stocks. According to Gjerde, & Saettem, (123), an increase in the money translates into an increase in the equity returns. There is consistency in the relationship between the leads or lags and cross spectra of returns on stocks and variations in the supply of money. This is also consistent with the classical; Efficient Market Model. Harvey, (199), also argues that this is also true with the monetary portfolio model. This is because; the returns in stock anticipate changes in the monetary returns. On the other hand, Gjerde, & Saettem, (123), argues that considering the past US data, The past changes in the supply of money do not provide a better predictive information on the future variation in the prices of stocks. Consequently, it is healthy to assume that any of the changes in the supply of money may not have considerable impact in the value of stocks and may not be used to predict the value of stocks. This view upholds the Efficient Market Hypothesis. However, Harvey (192), went on to confirm that the theory postulated by neoclassical economics that expansionary monetary policy can increase the stock returns holds

The relationship among stock returns, real activity, inflation and money supply changes

While investigating the relations among stock returns, real activity, inflation and money supply changes, used the US data to investigate the relationships. He argues that, the empirical results are consistent with the reversed causality model, when he administered the model on the US and Japanese market, Ely, & Robinson., (456), realise that the economic news has a significant systematic impact on the stock market returns. Additionally, term and risk premiums receive significant pricing in the US

In the European countries, found that there correlation between the macroeconomic variable and the stock prices are positive. This is due to the same relationship between industrial productivity, supply of money and the stock prices. However, the results also proved some of the original findings such as the negative correlation between inflation and interest rates. On the other hand, Asprem, (89), findings only supported the early findings by Ely, & Robinson. (121), he argues that there is a negative impact of the interest rates on the stock prices because, any changes in the interest rates attracts other investment options in various sectors. Nevertheless, money growth impact positively the stock returns.

The first impact of a fall in the stock market is that those with shares will see a fall in their wealth. For a significant fall, they will see their wealth affecting their financial outlook. Thus, they will be sceptic to spend more money if they are losing money on shares. This will result in falling consumer spending, even though people who buy shares are often prepared to lose money whichever way the stock markets move. The spending patterns are independent of share prices. The stock market movements indirectly affect those with private pension or investment trust. With significant investments of pension funds in the stock market, a serious fall in share prices reduces the value of the pension funds, thus future pension payouts will be lower. Share price movements are reflections of what is happening in the economy; falling share prices can affect consumer confidence by discouraging people from spending. Again falling share prices can hinder companies from raising finance in the stock market. For example, companies that are expanding and wish to borrow often do so by issuing more shares, which is more difficult. In some instances, a fall in the stock market makes other investments to bemore attractive. Government bonds or gold which offer better returns in times of uncertainty may attract people away from investing in shares.

The Stock Market Predicts Movements in Macroeconomic Variables

Finance is what makes the business go around in the world and aspects of the economy start and end with it. The easiest way for new, upcoming and promising ventures is to go public or turn to the masses through stock markets. That is, small savings of people if invested wisely in reliable businesses can make miracles. Only a small proportion of the total population invests in the stock market, but if something happens in these stock markets, it affects the whole population directly or indirectly. There is a strong correlation between stock markets and the real economy

Asprem, (89), argue that these macroeconomic variables are moving in the same direction but are not fundamentally caused by each other. There is no relationship effect of the stock exchange indicator and the real gross domestic product. There are some other exogenous variables which influence them. When the valuation of shares of firms traded in the stock market increases they have a positive influence on the gross domestic product of a country. Just like forex reserves causes gross domestic product of a country in a positive manner; the bulk of this foreign exchange reserves coming from foreign institutional investments. The presence of autocorrelation between the stock market and macroeconomic variables implies that there is evidence of bidirectional relationship between interest rate and stock market, exchange rate and stock market, etc. Any change of exchange rate, interest rate, and international market significantly affect the stock market in the economy and vice versa. Therefore, the changing behaviour of international market, exchange rate, and interest rate in the economy can be used to predict stock market price fluctuations. These relationships may differ from region to the region, as a positive relationship between stock returns and economic activities cannot be found in other markets.

Movements in Macro Variables provide information about the future direction of the stock market

According to Samarakoon, (1210), money supply can also have a significant impact on share prices. Therefore, stock prices should accurately reflect future economic activities, and is therefore, important in the formulation of a nation’s macroeconomic policy. Macroeconomic indicators determine the stock market efficiently to give a new approach to the foreign investors, policy makers, traders, domestic investors, and academic researchers in their decision making. The rate of inflation, money growth, interest rates, industrial production, reserves, and exchange rates are the most used macroeconomic indicators to explain the stock market movement. Inflation has negative effects on the stock market. Exchange rate movements initially affect the international competitiveness and trade position, then the real output of a country, and finishes with the current and future cash flow of companies. Using historical data of stock prices and microeconomic indicators may enable the traders and investors to strategize on more profitable trading and investment decision to take. Though, care should be taken so as to include more macroeconomic variables to add to the analysis so as to know the relationship between these factors and the nature of stock market volatility. It may also be that macroeconomic variables have a different impact on the stock market volatility depending on the trading mechanisms and regulatory environments (Wasserfallen, 19; Solnik, & Solnik, 137; Samarakoon, 360; Humpe, & Macmillan 113).

The Nature of the Dynamic Relationship

The returns of industry portfolios predict stock market movements. Retail, services, commercial real estate, metal, and petroleum predict the stock market. Stock markets react with a delay to the information contained in industry returns. Evaluating macroeconomic variables such as unemployment rates, nominal exchange rates, federal funds rates, aggregate output, money stocks, and inflation rates, the federal government debt, reveals that they can predict recessions in the stock market. Using both parametric and non parametric approaches can identify recessions periods in the stock market. It is easier to predict bear markets using macroeconomic variables when comparing bear market prediction and the stock return predictability (Canova, & De Nicol, 345-349).

A co integration analysis can be used to model the long term relationship between the consumer price index, industrial production, money supply, long term interest rates, and stock prices. Stock prices are positively related to industrial production and negatively related to both consumer price index and the long term interest rate. There is a small, insignificant positive relationship between money supply and stock prices. Property index and stock market form co-integrating relationship with changes in the short and long term interest rates (Booth, & Booth, 217; Bilson, Brailsford, & Hooper, 200).

Security prices adjust rapidly on arrival of new information thus current prices reflect all information about the security. Therefore, no investor should be able to employ available information so as to forecast stock price movements quickly in order to make a profit by trading in shares. National macroeconomic policies can be made so as to reflect future corporate performance, and corporate profits reflect the level of economic activities.

Barrows, & Naka, (1294), states that the dynamic interactions and the causal relations among macroeconomic variables and stock prices are crucial in the formulation of a country’s macroeconomic policy. Relevant information currently known about the changes in macroeconomic variables is fully reflected in current stock prices. Therefore, competition among the profit maximising investors in an efficient market will not be able to make abnormally high profits by predicting future stock market changes (Hong, Torous & Valkanov 368)

In regression models, if the stock market returns are used as dependent variables, and macroeconomic variables taken as independent variables, will reveal that only consumer price index have a significant effect. Crude oil prices, treasury bills, and exchange rate do not have significant influence on the stock market returns. This implies that there is a trade off between risk and return when investors withhold stocks. It also serves as a guide to risk management. Therefore, companies should undertake viable projects that boost performance over time. Most investors are motivated to invest in companies that have substantial financial performance. The shares become the preferred assets. The effect of macroeconomic variables on the stock market has implications on the financial markets. In forecasting stock market viability, insights on the formulation and implementation of appropriate monetary and fiscal policies could manage stabilize the financial markets (Asprem, 289).

Applying and employing vector error correction and co integration analysis provides more robust and consistent estimates of the effects of macroeconomic variables. With increasing share prices, it is worth considering the impact of the stock market on the economy. An in depth analysis should always be taken to decipher the impact of falling share prices on the economy and the average consumers (Samarakoon, 19).

Conclusion

The dynamic linkage can also be investigated using the Granger’s concept. The Granger’s type causality procedure when applied determines the direction of causation among variables. This procedure is based on a bivariate system time series.

The GARTH time series model has several constrained parameters. The confidence limit of the structural parameter is not constrained itself. Although, the confidence limits can be affected by estimates of the remaining parameters that occur in the region of their constrained areas. A survey of univariate models of conditional heteroskedasticity is the classical ARCH model, and various extensions of the standardized ARCH model. The Exponential GARCH model is stochastic in nature. The stochastic volatility in asset returns is a significant concern of financial economists. It is essential to consider risk, and investors want a premium for investing in risky assets. Value at risk models is mainly used by banks and other financial institutions to model and forecast volatility, or covariance structure of asset returns. Other aspects of return series especially their marginal distributions are leptokurtic. These returns are modelled as independent and identically distributed over time. Models of Autoregressive Conditional Heteroskedasticity (ARCH) form the most popular way of parameterizing this dependence.

Volatility forecasts obtained from a variety of mean and variance specifications in GARCH models is computed as a proxy of actual volatility calculated using daily data. An intriguing by-product is evidence of significantly negative relation between unexpected

Volatility and stock returns. Vector autoregresions are useful in finance because they give a concise way of summarizing data, have little serial correlation residuals, and can be used to examine complex relationships among variables. Vector auto regression is not an intelligent causal model of the data as it offers ways to summarize data for two or more variables. It summarizes correlations in data and especially useful if variables are serially correlated. Macroeconomics therefore, helps to describe and summarize macroeconomic data, make forecasts, quantify the structure of the macro economy, and advise the macroeconomic policy maker (Bilson, Brailsford, & Hooper, 21; Barrows, Naka, 194;.Asprem, 989-989).

In an investigation regarding the effects of the macroeconomic variable on the prices of stocks, the multiple regression models exhibited a rather exciting result. Because out of the 35 stocks analysed, 27, stocks showed higher explanatory power. This provides better evidence on the applicability of the macroeconomic variable on the stock prices. The stock prices have various relationships including inverse relationship between stock prices and the exchange rates, inflation rates and treasury rate. Negative and positive impacts of the macroeconomic variable on the stocks prices had a number of practical implications. From their study, Booth, & Booth, (1997), found that the prices of stocks react negatively to any rise in the interest rates of a country. This is probable due to the expected returns on stocks.

Stock prices only react negatively to any rises in the interest rates and not to fall in the interest rates. High interest rates affect the returns on the stocks; this causes the prices of the stocks. If the interest rates on the on the security issued by the treasury such as the T-bill increases, the investors switch out of those stocks that are responsible for the overall fall in the stock prices. This provides a certain level of certainty in the predictability of the stock prices by analysis of the behaviour of the treasury bills. On the other hand, money supply reacts to the stocks prices in a positive manner. For this, any changes in the money supply impact the prices of equity. The most influential macroeconomic variable that is useful has a strong link to the prices of stocks is the exchange rate. This is because, in an export dominant economy, appreciation in the currency has a positive boost on the stock market. However, any depreciation in the value of the country’s currency has a negative impact on the value of the stock prices. On this line, it is healthy to argue that the exchange rate has a high impact as a macroeconomic variable on the stock prices (Chen, 221).

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