Stock Return and Volatility in Asian Stock Markets - Research Proposal Example

Stock Return and Volatility in Asian Stock Markets Name: Students ID: Unit Code: Instructor: Table of Contents Introduction 2 Aims and Objectives 4 Research Questions 5 Literature Review 5 Methodology 13 Data 13 Research Design 13 Data Analysis 14 Bibliography 16 Introduction Over the past three decades, the world has experienced a great move towards globalisation. One key aspect that has been at the centre of the globalisation process is financial liberalisation, particularly in emergent and developing economies. This has resulted in external linkages in form of private investments, trade and capital mobility across different parts of the world. Capital mobility has been particularly high in the emerging Asian economies following the deregulation and thus opening up of these economies. This process has come under serious attack from some of the prominent economists. Most of these critics argue that free capital mobility engenders financial and macroeconomic shakiness in the emerging markets (Venetis and Peel, 2005). Stiglitz (2002), in criticising the U.S. Treasury and the International Monetary Fund (IMF), claims that compelling emerging economies to lessen checks on capital mobility all through the 1990s was greatly reckless. Stiglitz argues that the relaxing of capital mobility controls were the main if not the sole contributors to several financial crises in the emerging markets, such as Mexico 1994, Asian Financial Crisis 1997, and Russia 1998, among others. Even the IMF has condemned unrestricted capital mobility and has offered some support to capital controls. Rodrik and Kaplan (2003) indicates that the criticism has mainly been informed by the lack the institutional strength in most of the emerging markets to capitalise on an open capital account. They observe that poorly established capital markets plus weak financial organisation convert large changes in capital mobility to volatility. The volatility has major effects on the economy particularly on the cost of capital and investments decisions. This volatility of tends to increase when there is a financial crisis and stock market returns tend to behave in a similar way. Aims and Objectives Getting to understand the dynamics of volatility in a stock market is a key determinant for the cost of capital, leverage levels from companies and investors and for investment decisions. There has been considerable empirical research on stock-market behaviour, but this has mainly been focussed on the leading advanced stock markets or tend to compare emerging markets to industrialised markets. Only a few equivalent research works have been dedicated to investigating Asian Stock Markets. This research study’s interest in Asian markets is also driven by experienced speedy growth in gross national product across several countries apart from Hong Kong, Japan and Singapore. This has resulted in an increase in demand for international financial assets (Fletcher, 2000). Furthermore, from the time when the financial industry in most Asian countries was liberalised, capital movements and stock prices are sensitive to updates, technological advances, return differentials, and varying business environments in domestic markets as well as in outside sources. Consequently, the volatile behaviour of asset revenues relates vigorously with shudders in the rest of world through a contagion influence or other ways of transmission. So, the concern of volatility is not just a local occurrence, but also a central part of over-all risk analysis (Shin, 2005). Accordingly, the objectives of this research study is: To look at time-series conduct of seven Asian stock markets, including Hong Kong, Singapore, the Philippines, Thailand, South Korea, Malaysia and Taiwan. Specific attention is given to the empirical connexion between stock returns and volatility by using a TAR-GARCH model; To provide policy-makers with a more certain foundation on which to frame proper risk-management strategies. Research Questions Recent financial crises as well as their unexpected global effects have raised several issues regarding the global financial system. However, this research study seeks to answer whether there is an asymmetric association between returns and volatility at highs and lows that is manifest in emerging markets during financial crises. Literature Review There has been a lot of research work on the conduct of returns and volatilities in the stock markets of many countries. This research has mainly focused on asymmetry as an effect of the price variation on volatility. Other key areas that have been researched on are asymmetry as a reversion phenomenon being contingent on the prices of assets and as a variation of return correlation of different market indexes or assets (Shamsuddin, 2008). In general, studies on the stock market of numerous countries show that volatility attributable to positive shocks is less that that after negative shocks of the same intensity on the market. When a positive impacts occur (optimism, good news), returns are disposed to increase and volatility tends to fall. On the other hand, a negative impact (crises, bad news) pushes returns down while volatility goes up. Nonetheless, for an impact (positive or negative) of equal intensity, the negative effects are greater for both volatility and returns. This means that with the market tumbling, returns dip at a faster rate and volatility goes up more than when the market is at high (Park, 2010). The New York Stock Exchange (NYSE) experienced a major crash in 1987. This was the most volatile occurrence in the United States stock market. It also ended up affecting emerging stock markets mainly in Latin America, such as Mexico, Brazil, and Argentina. The event ended up sparking keen interest on the concern about stock returns and volatility. A research study conducted by French et al. (1987) in the U.S showing that stock volatility is very much persistent, hence an increase in present volatility persists for a longer period. They indicate that market surplus returns have a positive link to the anticipated volatility of stock returns, but negatively correlated to the sudden volatility of stock returns. French et al. (1987) provide an open examination of the link between surplus returns and volatility. Schwert (1990), using data from the U.S markets, show that the monthly stock volatility was greater for the duration of economic stagnation and after major banking crises from 1834 - 1987. Bekaert and Harvey (1997), and Imrohoroglu and De Santis (1997) study on volatility focussed on the emerging stock markets provide some sign for return predictability and persistence in uncertain volatility in these markets. They show that the opening up of capital markets in the emerging markets did not cause increased volatility in domestic markets. Their findings are rather intuitive in view of the fact that outsiders are allowed to invest in domestic stocks cannot be expected to increase volatility. Without a doubt, it might be the other way around. Foreign participation is conceivably expected to increase market size and liquidity that in return will help to ease return volatility. Nonetheless, the status of liberalisation starts up the process of integration of emerging markets into the world-wide financial system and so will make the local market exposed to effects from other markets (Badhani, 2009) In addition, numerous studies show that the link between stock markets of various countries has an asymmetrical behaviour. When there is a negative impact, the association between markets is likely to increase than when the prices go up. Black (1976) and Christie (1982) conducted the initial studies on the negative asymmetric link between returns and volatilities. Afterwards, many other research works have been published on the same topic. These include: Schwert (1989); Campbell and Hentschell (1992); Glosten et al. (1993); Shields (1997); Bekaert and Wu (2000); Chiang and Doong (2001), Daouk (2001); Venetis and Peel (2005); Shamsuddin (2008), Badhani (2009) and Chang (2009), among many others. But, Daouk (2001; p.2), stated that “volatility is still a puzzle”. Chiang and Doong (2001) study the empirical link between the stock market returns and volatility on seven Asian stock market indices. They use the approach suggested by French et al. (1987) and establish that out of the seven Asian stock markets, four have a noteworthy connection between stock returns and sudden volatility. In general, sudden volatility has a greater influence on stock returns than does the expected factor. They also analyse the connection between stock returns and time-varying volatility by means of a TAR-GARCH (1, 1)-in-mean model. Their results indicate that the GARCH parameters are very important in the daily return series for all of the Asian stock markets considered. But, the significance level and scope of the GARCH effect come to be reduced in the weekly-return series. With few exemptions, the study shows a slight GARCH effect on monthly data. An important finding their work is that there is a strong asymmetric effect and volatility tends to be persistent. Aggarwal et al. (1995) state that high volatility of emerging markets is manifest by recurrent unexpected changes in variance. The high volatility tends to be connected to key events in each country and not necessarily to global occurrences. They argue that the October 1987 crash in the U.S was the global event that considerably increased volatility in a number of markets between 1984 and 1994. Other events, such as the Gulf War, had a negligible effect. Bekaert and Harvey (1997) and Susmel (1997) also find that, in general, the fraction of variance attributable to global factors is infinitesimal for emerging markets. The results are consistent with the findings of Bailey and Chung (1995) who also find that key political events are likely to be connected to abrupt changes in volatility. These periods of high volatility are quite common for returns measured in dollar-adjusted returns and domestic currency. Daouk (2001) tends to indicate that there are four arguments/models that attempt to enlighten the asymmetry between stock returns and volatility. His first model is centred on work by Black (1976) and Christie (1982). Black (1976) indicated that financial leverage for companies may well partially explain such an association. He also indicates that once a company comes to be more leveraged, the value of its net worth is disposed to fall, and when it becomes less leveraged, the value of its net worth is disposed to rise. Daouk (2001) bases his second model on the risk premium. He argues that that an increase in the volatility of sudden returns will as well aggravate the future expected volatility to go up. This means that a greater apparent risk and demands for greater premiums. This is referred to as volatility feedback. Pindyck (1984) and French et al. (1987) pioneered research into this argument. Based on this disposition, it can be said that the variation in the volatility of future predictable returns is the cause stimulating fluctuations in stock prices. The returns plummet as a way of recompensing for the high risks expected. This notion is essentially dependent on the existence of abundant amount information obtainable by a high number of investors, a “sine qua non” situation for evaluating future volatility and major price movement. Schwert (1989) and Glosten et al. (1993) pave way for the third model of explaining the asymmetry between stock returns and volatility. They argue that the stock return volatility of a company is likely to be connected to the projected future cash flow volatility. An increased expectation among investors concerning the cash flow to be generated drives the value of the company down. As a result, perceived risk as well as volatility are likely to be high. Lastly, Daouk (2001) argues that the asymmetry is connected to the situations facing investors for the period of financial crises. The minute a financial crisis comes about, asset prices drop deeply and rapidly. Given this negative perspective, the investors transform their actions as they discuss under tense circumstances, consequently increasing the market volatility. Verma and Verma (2005) also came with another twist on the conceivable geneses for asymmetries between conducts of returns and volatilities in stock markets. He identified four arguments. First, they argue that asymmetries are connected to variances in expected returns between the investors given the probable influences in the international stock markets. For instance, if there is a small drop in the U.S stock market, which is an international orientation, the other markets possibly will be more affected, largely the emerging economies due to the panic or “disappointment” amid the investors. This shows that the mental effect on investors owing to the changes in American market is key for the asymmetry level than the force of the change itself. Among the pioneers of this thinking are Odier and Solnik (1993) and Erb et al. (1994). The second thinking tend to sprout from the works of Harvey (1995) and Aitken (1996). They argue that the asymmetries probably come from the use of investment strategies founded on imperfect, extraneous and/or inaccurate information. If there is no full precise information regarding a given market, foreign investors possibly will be led to adopt subjective positions due to the effect of illogical and/or biased decisions. This typically occurs in emerging markets. In fact, a lot of foreign investors are likely to perceive emerging markets vaguely if they cannot get hold of full precise information regarding a given market and its assets, generally in times of financial distress. Pettengil et al. (1995) and Fletcher (2000) started the investigation into the interactive feature between stock markets risk and returns. From this study, it can be argued that asymmetry between returns and volatilities would encompass an unknown risk factor entrenched in the prices of international stock markets. Given that there is no linear relationship between any risk factor and stock returns, a valued unknown risk factor can result in volatility disproportion in markets experiencing lows and highs. Out of the lack of precise information as well as the existence of an unknown risk factor, a number of researchers have focussed on a very remarkable joint explanation. Grossman (1988), Gennotte and Leland (1990), Jacklin et al. (1992), Romer (1993), Berry and Howe (1994), and Johnson and Westberg (2004), among others, argue that most of the investors neither are not well informed nor adequately informed. As a result, a condition arises necessitating a change of the opinions on the fair value of each asset as new information is considered by each investor. Once some impact, either positive or negative, hits the market, it is normal to expect investors to reassess their positions. Part of them will almost certainly talk about adjusting their investment portfolios. As the volume of business grows, material which had not been considered or promulgated is then observed and fused into the prices. This process is likely to aggravate prompt and critical changes in prices, which for the most part arise in situations of crisis with indiscriminate shrinkage in negotiated assets. This will probably result in the asymmetry between returns and volatilities. According to Verma and Verma (2005), the fourth and maybe last reason the asymmetry between returns and volatilities is associated with the psychological manifestation of investors. By and large, investors respond more to drops than to upswings in the market prices. The ordinary investor would find it hard to book the loss, but then again in a hurry to make gains, suspicion and anxiety diffuse much faster than optimism. In fact, markets collapse much faster than they rise. The absurd activities resulting from anxiety and aversion to risk is different from the self-conflicting deeds seen in those periods when markets are at high, even bearing in mind the absurdities bred by greediness. This behavioural imbalance would result in asymmetry. Hong and Stein (1999) and Gervais and Odean (2001) pioneered research into this area. In a nutshell various remarkable deliberations can be highlighted concerning studies on the phenomenon of asymmetry of stock market returns and volatilities. Junior et al. (2014) lists some of them: (i) literature insinuates to at least eight arguments that explain the occurrence of asymmetry that are founded on technical aspects and behavioural financial issues; (ii) occurrence of asymmetry is mainly identified in periods of domestic or international financial crises; (iii) the volatility escalates more after negative shocks than after positive shocks of the same intensity; (iv) investors respond faster and more seriously to negative impacts than positive impacts; (v) emerging markets are more volatile than the developed markets; (vi) sudden updates can disturb prices in short and very short term, while bad news have a more impact on prices in negative phases than in positive phases; (vii) volatility of returns is disposed to rise during negative phases. Methodology Data This research study will use data derived from the historical series of market stock indexes of the seven countries. Daily closing prices are used covering an 8-year period from 2006 to 2014. This period of time includes the 2008/09 global financial crisis including two years before and five years after. The data consist of the Hang Seng Index (Hong Kong), the Straits Times Industrial Index (Singapore), the Manila SE Composite Price Index (the Philippines), the Stock Exchange of Thailand Daily Index (Thailand), the Korea Composite Price Index (South Korea), the Kuala Lumpur Composite Price Index (Malaysia), and the Taiwan Stock Exchange Weighted Stock Index (Taiwan). Research Design This research study is to be conducted on a descriptive research design. Therefore, quantitative methods will be used to collect the data. A descriptive research design is preferred given its specific nature and the fact that it supports a general understanding and interpretation of the problem under study. The research design is not merely confined to the fact finding mission, but also may result in the formulation of pertinent principles of knowledge and solution specific to the problem. The descriptive research design is meticulously designed to guarantee a wholesome depiction of the situation and certifying minimum bias in collection of the data and trimming down the errors in analysing and interpreting the data collected. The statistics are used to provide an overall understanding of the nature of each market return and to relate the distinct properties across countries in Asia. The statistics include: mean, standard deviation, kurtosis, skewness, correlation analysis, as well as tabulations and graphical illustrations (Badhani, 2009). Data Analysis There has been a lot of research mainly concentrated on the study of the sensitivity of stock returns to risk and to the covariance of stock returns across different markets following the various financial crises. Empirical evidence indicates that stock returns have been analysed by using time series models. Two key approaches can be deduced from the research: (i) study of time-series patterns and cross correlations of stock returns; and (ii) study of the link between stock returns and conditional variance. The first approach focuses on ascertaining whether there exists a predictable pattern connected to stock-return series. This pattern connotes a lucrative trading rule, snubbing an efficient-market theory. The second approach focuses on the link connecting the stock returns to risk factors. Results indicate that stock volatility shows a clustering portent, that is, large fluctuations are disposed to be trailed by big changes and small fluctuations are likely to be followed by small changes (Badhani, 2009). These phenomenon are modelled using the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model. According to Bollerslev et al. (1992), the GARCH (1, 1) model seems to be adequate to define the volatility progression of stock-return series. Given that the GARCH model does not consider the unequal effect between positive and negative stock returns, the weighted improvement models such as exponential GARCH (Nelson, 1991) and Threshold Autoregressive GARCH (TAR-GARCH) (Glosten et al., 1993), henceforth, GJR; Engle & Ng, 1993; Tsay, 1998) have been developed. The TAR-GARCH model is striking as fewer parameters need to be estimated. In their study of daily stock returns in the Japanese market, Engle and Ng (1993) find that the parameterisation of TAR-GARCH is the most favourable one. The data will be analysed using STATA software. Bibliography Alper, C.E. Fendoglu, S. and Saltoglu, B.M. 2009, Volatility forecast performance under market stress: evidence from emerging and developed stock markets. Working Paper 04/2009. Turkey: Bogazici University, Department of Economics. 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