Macroeconomic Variables and Domestic Factors Affecting Stock Market Index Finance Essay

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Similar to any other commodity, in the equity market, share prices are also reliant on some factors. One of the main domestic factors in determining a stock’s price is the macroeconomic variables of an economy. The theoretical framework of stock market and economic activity is rooted in Ross (1976), who launched the Arbitrage Pricing Theory (APT) that associates stock returns to numerous variables. To study the relationship between the market returns and macroeconomic factors such as industrial production, the money supply, inflation, interest rate and exchange rate variables, Chen, Roll and Ross (1986) used a multivariate APT. They concluded a strong association between the market returns and these variables.

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2.1.1 Studies done to test the association of macroeconomic variables with stock market returns

After Ross’s introduction of the APT in 1976 and his empirical findings in 1986, different authors started to test his theory. However, research into the relationship between stock market returns and multiple macroeconomic variables has been limited. Firslty, Dhakal, Kandil, and Sharma (1993) adopted a vector autoregression (VAR) model to test the impact of a change in the money supply on a change in the stock market index. In the US, a significant relationship between these two variables was discovered. Furthermore, a study by Abdullah and Haywarth (1993) found that a change in the market index was influenced by the rate of inflation and by both the change in the money supply. Another study was done by Fama (1981) who indicated that most economic factors, except inflation, exhibited a positive correlation with the stock market index. The Proxy hypothesis partially explained negative correlation between inflation and real equity returns. This is so because, inflation and real equity returns react inversely to news about future real output growth. On a contradictory point, Aarstol (2000) confirmed that this negative relationship persisted even when output growth was controlled. Even, Rapach (2001) examined the effects of money supply, aggregate spending, and aggregate supply shocks on real U.S. stock prices in a structural VAR model. One of his main findings was that real stock returns were negatively correlated with inflation. Additionally, Muradoglu et al. (2000) investigated possible causality between 19 emerging market returns and exchange rates, interest rates, inflation, and industrial production from 1976 to 1997. Their study demonstrated that the correlation between stock returns and macroeconomic variables were mainly due to the relative size of the respective stock market and their integration with world markets. Moreover, Wongbangpo and Sharma (2002) studied the relationship between the stock index and macroeconomic variables by observing both short and long run relationships between respective stock indexes and the macroeconomic variables of the consumer price index (CPI), gross national product (GNP), the interest rate, the money supply, and exchange rate. They found that in the long-run all five stock price indexes were positively related to growth in output and negatively to the aggregate price level. Surprisingly, a negative long-run relationship between stock prices and interest rates was noted for the Philippines, Singapore, and Thailand, and was found to be positive for Indonesia and Malaysia. In the end, causality tests detected an overall relationship between macroeconomic variables and stock prices for all five equity markets. Lastly, Mukhopadhyay and Sarkar (2003) conducted a systematic analysis of the Indian stock market returns prior to and after market liberalization and the influence of macroeconomic factors on returns. Specifically for the post-liberalization period, real economic activity, inflation, money supply growth, FDI, and the NASDAQ-index were significant in explaining variations in Indian stock return. Similarly, while significant during the pre-liberalization period, nominal Exchange rate was found not be significant after liberalization.

2.1.2 Summary of findings

In the empirical review, we noted that money supply is a variable that almost all the authors used and they eventually found that it is positively correlated with stock index. Likewise, variables such as CPI, exchange rate, industrial production, interest rate and others impacted on the equity market indices as noted by numerous authors. Remarkably, inflation is one macroeconomic variable which was found to be negatively correlated with the stock returns in most of the studies carried out.

2.2 Financial crises affecting stock markets worldwide

According to Mink and Mierau (2009), financial crises are characterized by the sudden and simultaneous materialization of risks that in times of tranquillity were believed to be independent. Therefore this can pose a substantial threat to the stability of the international financial system. These risk spreading opportunities in times of stock market crashes has induced investors to fear that during financial crises shift-contagion occurs. This has been defined by Allen and Gale (2001), Rigobon (2002), and Pericoli and Sbracia (2003) as a shift in the strength of the transmission of shocks from one country stock market to other. As an illustration, concentrated episodes of financial disorder in the last two decades, quickly spreading across borders, sometimes without apparent fundamental justification, caught the attention of financial researchers. Labeled as the Tequila crisis, the Asian flu, or the Russian virus, such colourful media designations depicted that each crisis propagated like a contagious disease, quickly affecting not only neighbouring but also distant markets. Following from these, the word contagion began to frequently appear in the financial literature as these events became the object of an increasing number of theoretical and applied analyses.

2.2.1 Financial contagion

In the existing literature, financial contagion has not obtained a consensual definition yet and each different concept varies with the specific nature of each study. The description adopted here was projected by Forbes and Rigobon (2001) and is particularly sufficient for analyses of stock markets’ crises. The authors identify financial contagion with ‘a significant increase in cross-market linkages after a shock to one country (or group of countries)’ and defend that such definition presents a number of operational advantages. To be precise, its usefulness for financial investors engaged in strategies of international diversification, or for monetary authorities who aim at justifying bailing out interventions in markets affected by foreign crises.

2.2.2 Transmission mechanisms of financial contagion

Remarkably, there are a number of different theories on how shocks are propagated internationally. However, it is useful to demarcate this broad set of theories into two groups: crisis-contingent and non-crisis-contingent theories. Crisis-contingent theories are those that clarify why transmission mechanisms change during a crisis and therefore why cross-market linkages increase after a shock. Non-crisis-contingent theories take the view that transmission mechanisms are the same during a crisis as during more stable periods, and therefore cross-market linkages do not increase after a shock.

2.2.2.1 Crisis-Contingent Theories

Crisis-contingent theories about how shocks are spread internationally can be divided into two mechanisms: multiple equilibria and endogenous liquidity. Multiple Equilibria This first mechanism occurs when a crisis in one country is used as a signal for imminent financial turmoil for other countries. In this perspective, Masson (1998) proved how a crisis in one country could lead investors’ expectations shifting from a good to a bad equilibrium for another economy and thereby causing a crash in the latter. Mullainathan (1998) argued that investors incorrectly remind past events. A crisis in one country could activate a memory of precedent crises, which would cause investors to recompute their priors and allocate a higher probability to a bad state. The resultant descending co-movement in prices would arise since memories are correlated. The movement from a good to bad equilibrium and the transmission of the first shock, in both above models, are initiated by a change in investor expectations or beliefs but not by any real linkages. This branch of theories demonstrates not only the contagion of crises, but also why speculative attacks occur in economies that appear to be fundamentally sound. These are called crisis-contingent theories as the change in the price of the second market is worsen during the shift between equilibria. Hence, subsequent to a crisis in the first economy, a change in investors expectations is triggered and the shock transmitted through a propagation mechanism that does not exist during stable periods. Endogenous liquidity Another group of crisis-contingent theories is endogenous liquidity shocks. Such a model is developed by Vald©s (1996) where a crisis in one country can reduce the liquidity of market participants. This would cause investors to recompose their portfolios and sell assets in other countries in order to continue operating in the market, to satisfy margin calls, or to meet regulatory requirements. Likewise, if the liquidity shock is large enough, a crisis in one country could increase the degree of credit rationing and force investors to sell their holdings of assets in countries not affected by the initial crisis. Calvo (1999) developped a different model of endogenous liquidity. Asymmetric information among investors is present in Calvo’s model. Sometimes investors do not have a complete picture of the conditions in every country that can affect their portfolios’ returns, owing partly to the cost of gathering and processing information. In the absence of adequate information, a financial crisis in one country may lead investors to believe that other countries could face similar problems. As a result, investors could sell assets in other countries, especially those with similar conditions to those in the country where the crisis originated. This kind of behavior can mirror rational as well as irrational behavior. If weak fundamentals are revealed by a crisis, investors may rationally conclude that comparable countries could also face similar problems, thus causing contagion. As an illustration, informed investors who are able to decode the fundamentals of an economy are also equally hit by liquidity shocks to sell their holdings. On the other hand, uninformed investors cannot distinguish between a liquidity shock and a bad signal, and therefore charge a premium when the informed investors are net sellers. What transpires from the above is that liquidity shock leads to an increased correlation in asset prices. Hence, this transmission mechanism does not seem to occur during stable periods but only occurs after the initial shock. The above theories propose varying channels through which shocks could be transmitted internationally: multiple equilibria based on investor psychology and endogenous-liquidity shocks leading to portfolio recomposition. Regardless of the diverse approaches and models used to widen these theories, they all share one significant implication: the transmission mechanism throughout (or directly after) the crisis is inherently dissimilar than that before the shock. This is a structural shift causing shocks to propagate via a channel that does not exist in stable periods. Hence, each of these theories could explain the existence of contagion.

2.2.2.2 Non-Crisis-Contingent Theories

On the other hand, there exists another school of thought where although shocks can propagate internationally but do not generate shift-contagion. These theories hold that transmission mechanisms are not significantly different after an initial shock. Instead, large cross-market correlations after a shock are attributed to a continuation of linkages that existed before the crisis which often called “real linkages”, since many (although not all) are based on economic fundamentals. These theories can be classified into four broad channels: trade; policy coordination; country reevaluation; and random aggregate shocks. However, we will shed light on one major theory which is trade. Trade This mechanism works through several related effects. For instance, a country in the process of devaluing its currency would have the direct effect of increasing the relative competitiveness of that country’s goods. Moreover, exports to a second country could increase, thereby adversely affecting domestic sales within the second country. Moreover, the initial devaluation indirectly leads to a reduction in export sales from other countries that compete in the same third markets. Either of these effects would not only have a direct impact on a country’s sales and output, but also, in case of strong competition, it would increase expectations of an exchange rate devaluation and/or lead to an attack on another country’s currency.

2.2.3 Studies done to detect contagion effects

The empirical literature testing if contagion is present is even further widespread than the theoretical literature defining how shocks can be transmitted across markets. The common approaches utilized to measure the transmission of shocks and test for contagion are: analysis of cross-market correlation coefficients; GARCH frameworks; cointegration; and probit models. There are also many studies examining the existence of contagion effect of various crises on different stock markets in the world using different methodologies. Virtually all of these papers conclude that contagion occurred during the crisis under investigation.

2.2.2.1 Cross-market correlation coefficients

The most uncomplicated tests are based on cross-market correlation coefficients. These tests compute the correlation in returns between two markets through a steady period and subsequently test for a significant increase in this correlation coefficient following a shock. If the correlation coefficient boosts up considerably, this advocates that the transmission mechanism between the two markets increased after the shock and contagion occurred. Most of these papers test for contagion immediately after the U.S. stock market crash of 1987. In the foremost major paper on this theme, King and Wadhwani (1990) tested for an increase in cross-market correlations between the U.S., U.K. and Japan and found that correlations increased notably after the U.S. crash. Lee and Kim (1993) extended this analysis to twelve major markets and found further proof of contagion: that average weekly cross-market correlations increased from 0.23 before the 1987 crash to 0.39 later. Moreover, Calvo and Reinhart (1995) used this approach to test for contagion after the 1994 Mexican peso crisis and found that the correlation in stock prices and Brady bonds between Asian and Latin American emerging markets increased significantly. Remarkably, Baig and Goldfajn (1998) presented the most thorough analysis using this framework and test for contagion in stock indices, currency prices, interest rates, and sovereign spreads in emerging markets during the 1997-98 East Asian crisis. They found that cross-market correlations increased during the crisis for many of the countries. To sum up, each one of these tests based on cross-market correlation coefficients comes up to the similar universal conclusion: correlations typically increase considerably after the appropriate crisis and consequently, contagion occurred during the period under investigation.

2.2.2.2 GARCH frameworks

Another approach to test for contagion is to make use of an ARCH or GARCH framework to approximate the variance-covariance transmission mechanism across countries. Chou et al. (1994) and Hamao et al. (1990) used this procedure and find evidence of significant spillovers across markets after the 1987 U.S. stock market crash. They also concluded that contagion does not occur evenly across countries and is fairly stable through time. In another study, Edwards (1998) examined the propagation across bond markets after the Mexican peso crisis by focusing on how capital controls affect the transmission of shocks. He showed that there were noteworthy spillovers from Mexico to Argentina, by estimating an augmented GARCH model but not from Mexico to Chile. His tests showed that volatility was transmitted from one country to the other, but they do not specify if this propagation changed throughout the crisis.

2.2.2.3 Cointegration

A third group of tests for contagion center on changes in the long-run relationship between markets, as an alternative of any short-run changes after a shock. These papers employ the same fundamental procedures as above, excluding test for changes in the co-integrating vector between stock markets instead of in the variance-covariance matrix. For example, Longin and Solnik (1995) considered seven OECD countries from 1960 to 1990 and reported that average correlations in stock market returns between the U.S. and other countries rose by about 0.36 over this time period. However, this approach is not an precise test for contagion given that it assumes that real linkages between markets stay constant over the entire period. If tests demonstrate that the co-integrating relationship increased over time, this could be a permanent shift in cross-market linkages instead of contagion. Furthermore, by centering on such long time periods, this series of tests could overlook brief periods of contagion (for instance after the Russian collapse of 1998).

2.2.2.4 Probit models

A last approach to testing for contagion utilizes easier assumptions and exogenous events to discover a model and straightforwardly gauge changes in the propagation mechanism. A first research was that of Baig and Goldfajn (1998) who studied the effect of daily news (the exogenous event) in one country’s stock market on other countries markets in the 1997-98 East Asian crisis. They found that a considerable proportion of a country’s news impacts neighboring economies. Secondly, Forbes (2000b) predicted the impact of the Asian and Russian crises on stock returns for individual businesses around the world. She found that trade was the most vital transmission mechanism. Moreover, Eichengreen, Rose and Wyplosz (1996) and Kaminsky and Reinhart (1998) anticipated probit models to test how a crisis in one country (the exogenous event) affects the probability of the occurrence of a crisis in other countries. Eichengreen, Rose and Wyplosz studied the ERM countries in 1992-3 and found that the likelihood of a country suffering a speculative attack increases when another country in the ERM is under attack. They also argued that the first shock is propagated principally via trade. In the same context, Kaminsky and Reinhart (1998) estimated the conditional probability that a crisis will take place in a given country and found that this probability increases when more crises are occurring in other countries (particularly in the same region).

2.2.3 Summary of findings

After the review of the numerous empirical findings on financial contagion, we found that financial disorder in one country can affect another’s country stock market through contagion effects. The same thing applied to the event of the financial crisis. It had spillover effects over stock markets globally through different contagion transmission mechanisms. Some mechanisms were due to the crisis and others were due to existing contagion irrespective of whether there is a crisis or not. To conclude, it is to be noted that a global event is a contributing factor to changes in stock market indices.

2.3 An empirical Framework applied for China & Hong Kong

In 2009, Tao Sun and Xiaojing studied the ‘spillovers of the U.S. subprime financial turmoil to Mainland China and Hong Kong SAR: Evidence from Stock Markets’ by taking China and HK’s stock price returns as from January 2007 to October 2008 as the sample period. They reflected in their model both the element of testing for contagion and the macroeconomic variables of the home countries. They had two groups of independent variables: Domestic control variables in China and Hong Kong, and Global financial market volatility variables The model specification takes the following form: Rt= constant + AŽAt Rt-1 + AŽA»X t-1 + A” Vtf + Aƒ°eventt + A”žt Where Rt = Price Return X t-1 = Control Variables Vtf = Measures of global financial market volatility eventt = Subprime events A”žt = Error Term The control variables (macroeconomic variables) that they used for China were: interest rate, industrial production, money supply, CPI and trade balance. However, for Hong Kong, they used only money supply, CPI and trade balance. On the other hand, for the measures of global financial market volatility, they made use of Chicago Board Options Exchange’s Volatility Index (VIX) to reflect the implied volatility of the S&P 500 index. For the ‘event’ variable, they used negative news on subprime crisis as a dummy variable i.e event=0 before the crisis and event=1 after the crisis. To conclude, they found that China’s stock market was not immune to the financial crisis, as evidenced by the price and volatility spillovers from the U.S. in addition, Hong Kong’s equity returns have exhibited more significant price and volatility spillovers from the US than China’s returns, reflecting HK’s role as an international financial center.

2.4 Loss in investor confidence: a major cause of the global financial crisis

According to Brian Perry (2009), an investment strategist at an asset management firm called Alexander Perry Corporation, poor performances in the bond and stock markets were the most visible reflections of the credit crisis. In his article called ‘Credit Crisis: Market Effects’, he added thatA more importantly, although less visible, was the impact on investor confidence. At its simplest level, the market depends on trust and confidence among investors. He said, “Without this trust, a dollar bill is just another piece of paper, and a stock certificate holds no value.” The most dangerous consequence of the credit crisis was the erosion of this trust and confidence which shook at the very foundation of the modern financial system when investors questioned theA solvencyA of banks and other financial institutions. This erosion of confidence ate away at the very base of the contemporary financial system and is the cause why the credit crisis posed such a serious danger. In this recent episode we have seen old-fashioned bank runs, with depositors lining up to get their deposits out of banks like Northern Rock in the U.K. and IndyMac in the United States. Diamond and Dyvbig (1983) in an influential model showed that a self-fulfilling loss of confidence in the banking system may lead depositors to seek to withdraw their funds from banks, causing widespread failure of the banking system. On the other hand, Chari and Jagannathan (1998) showed that asymmetric information about the quality of bank assets leads investors to withdraw their deposits.

2.3.1 Herd Behavior of investors

According to Wikipedia, “large stock market trends often begin and end with periods of frenzied buying (bubbles) or selling (crashes).” Numerous observers quote these episodes as obvious instances of herding behavior that is irrational and driven by emotion for example greed in the bubbles and panic in the crashes. Individual investors join the mass of others in a hurry to get in or out of the market. A basic remark about the human society is that people who communicate frequently with one another think alike. Part of the rationale people’s judgments are alike at similar times is that they are reacting to identical information. The social pressure has an enormous power on individual judgment. When people are met with the judgment of a huge group of people, they have a tendency to alter their “wrong” answers. They merely think that all the other people could not be wrong. As per Shiller (2000), they are reacting to the information that a large group of people had reached a decision dissimilar from theirs. This is a rational behavior. People are prejudiced by their social environment and they frequently feel pressure to conform. According to Fromlet (2001), fashion is a tiny form of herd behavior whereas an instance of the strong form is fads that comprise crashes. Herd behavior may be the most commonly recognized observation on financial markets in a psychological milieu. Many players on financial markets might believe that a currency or equity is not properly priced, but they refrain nonetheless from a contrary financial exposure. These people merely feel that it is not sensible to combat the herd. This is a case of enforced herd behavior. They follow the herd – not willingly, but to avoid being trampled and are thus enforced into following the herd. A further important variable to herding is the word of mouth. People usually trust friends, relatives and working colleagues more than they do the media. The conventional media, written information, televisions, and radio have an intense ability for spreading thoughts; however their capability to produce active behaviors is still limited. Discussing with other people and other types of interpersonal communication are in the midst of the most essential social connections humans have. It is thus probable that news regarding a buying opportunity will speedily spread. In a research done by Shiller and Pound (1986b), private investors were asked what first drew their interest to a company they recently had invested in. Simply six percent of the respondents specified newspapers and periodicals. The attention and actions of people appear to be more stimulated by interpersonal communications even if they read a lot. The conception that the level of market prices reflects the result of private investors’ aggregated assessments and accordingly the true value of the market may be erroneous. People can as an alternative be rationally choosing not to misuse their time and effort in exercising their judgment about the market and therefore choosing not to exert any independent impact on the market. Shiller (2000) pointed out that this can lead to herdlike behavior and act as a cause of stock market over- or under pricing.

2.3.2 Studies done to capture investors’ behavior

Conversely, only few studies have been made so far to investigate how financial crises shape the beliefs and behavior of individuals. A noteworthy exception is Kim and Wei (2002) who investigated foreign portfolio investors before and during the Korean currency crisis in late 1997. The outcomes illustrated that foreign investors outside Korea were engaged more in herding than actually did the branches of foreign institutions in Korea or foreign individuals inhabiting Korea. This was interpreted as proof that local investors have dissimilar information compared to those outside the country.

2.3.2.1 Investor Confidence Index

JPMorgan Asset Management India Pvt. Ltd. (JPMAMIPL) announced the launch of the first Investment Confidence Index (ICI) in India in July 2009. The primary purpose of the ICI is to quantify confidence in the investment environment among investors. With the aid of the survey intended to capture the ICI score, data was collected for eight cities across India. The survey was constructed in a way to include the following criteria which was opinion polled by individual investors inhabiting these cities.

Investor Confidence Index

Attributes (a)

Elements

Economic Environment Local Economic Environment, global economic environment Investment Atmosphere Fluctuations of stock market indices Investment Portfolios Prospect of individual investment portfolio, expected increase/decrease in the amount of investment Figure 1: Investment Confidence Index by JP Morgan The ICI was then computed as follows: Investment Confidence Score = a1 i . wi + a2 i . wi + a3 i . wi Where a1 i is the ith element of the 1st attribute, and wi is the corresponding weighting for that element Arun Jethmalani, Managing Director of ValueNotes said, “The Indian economic prospects drive confidence across the board. A Government with a strong majority was viewed as the most positive economic signal. The Investment Confidence Index at the end of July 2009 stood at 135.9. A deeper study of the indices throws up a recurring theme across India – consistently high levels of optimism on an improvement in the Indian economic situation. This is contrasted by a marked pessimism or significantly lower confidence on a global economic recovery.”

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