Abstract
This study aims at comparing the variance structure of high (daily) and low (weekly, monthly) frequencies of data. By employing ARCH (1) and GARCH (1, 1) models, the study finds evidence that the intensity of the shocks are not equal for all the series. The study first finds that statistical properties of the three data series of returns are substantially different from one another and the persistence of conditional volatility is also different for the three series. The presence of persistency are more in the daily stock returns as compared to other data sets, which shows that the volatility models are sensitive to the frequencies of data series. In simple the results reveal that the variance structure of high frequency data is dissimilar from the low frequencies of data and variance structure in the daily data is much linked with the stylized facts associated with stock returns volatility.
Keywords: ARCH, GARCH models, KSE 100-index, persistence.
1. Introduction
The most significant topic of research in the financial markets for the last three decades is the stock returns volatility. After the publication of Engle (1982) paper, on ARCH, the volatility has received considerable attention from researchers, practitioners and policy makers. This interest is due to the reason that the volatility is a risk measure and different participants use this for different reasons. The volatility is high for the developing and developed countries in recent years but is much higher for the developing countries. So volatility study is more important in the developing countries. After the crash of 1987, the need for volatility measurement is the focus ...
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Markets can be efficient even if stock prices exhibit greater volatility than it can be explained by fundamentals such as earnings and dividends. Chapter 11: Potshots at the Efficient –Market Theory and Why They Miss, presents an argument of stock market fluctuations that stock prices show far too much variability to be explained by an efficient-market theory of pricing. It also talks about how one must look to behavioral considerations and to crowd psychology to explain the actual process of price determination in the stock market. I agree with Malkiel’s proclaim about the demise of the efficient-market theory and how it reasons to show that market prices are indeed predictable. Such arguments are exaggerated and the extent to which the stock market is predictable is greatly overstated because market valuation rests on both logical and psychological
In 1998 Eugene F. Fama published a famous critique on long-term return anomalies. He infers that all anomalies that was pointed out in scientific papers up until then where a matter of chance. His argues that it is easy to show the weaknesses of behavioral models and proof of anomalies. If there is a more or less even split between over- and under-reaction, and continuation and reversal of returns, then this supports the market efficiency hypothesis that any abnormal returns are chance. He also infers that with a reasonable change in methodology used, the anomalies are severely reduced or disappears completely.
I introduce the research result on the market volatility and efficiency in the Korean market. Two approaches have been used to analyze the effect of index futures trading on stock market volatility and market efficiency. One approach is to compare the change on stock price volatility and efficiency before and after futures trading is introduced. The other approach is to compare stock price volatility differences and efficient trading between KOSPI 200 stocks and non-KOSPI 200 stocks.
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In turn everything in the present and the future is judged through the stocks as they hold a high importance in industrialized economies showing the healthiness of said countries economy. As investing discourages consumer spending over all decreases, it lead...
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We have devoted our study to apply statistical methods to stochastic differential equations, initially to estimate by the historical method, which uses the property of independence and normality of the outputs. The Black-Scholes model and its alternatives are largely used by the professionals. For that, the estimate of its parameters deserves that we interested in other techniques more adapted: discrete method. The discrete method makes it possible to estimate the parameters of Black-Scholes model in the case of the discrete paths. In this method, it is necessary to observe the process during a certain interval of time i.e. to use all the observations of the paths. The discrete method being based on the criterion which minimizes the variances of the estimators and the small errors with the true values of the share price of gold(Khaldi Khaled, 2010).
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Saudi Arabia’s capital market is considered to be young compared to other financial markets in the region. Saudi financial markets have been developing slowly because most enterprises in the country are either government owned or family-owned, most of which was funded through state budget, and as a result reduced the need for financing. In the recent past, Saudi Arabia has focused on a careful measurement for structural developments and regulatory changes. However, different phases of historical development of the capital market which can be classified into three phases; pre-industrialization phase, post industrialization phase and growth phase that sparked changes and shaped the kingdom 's capital market on
Sung C. Bae, Taekho Kwon, and Jongwon Park, 2004, Futures Trading, Spot Market Volatility, and Market Efficiency: The Case of the Korean Index Futures Markets, Journal of Futures Markets 24, 1195-1228
Chaos theory has numerous application including helping explain phenomena or helping to predict the future. Chaos theory is applicable in various fields ranging from weather, business to medicine. Chaos theory explains the reason why it is practically improbable to predict the weather with the current technology as well as providing a way for people to find patterns in the chaotic system of stock exchange. It also helps with the running of organisation by showing what sort of condition is needed for a profitable business as well as helping doctors predict when heart failure may occur. Fractals which is a concept of chaos theory also is portrayed in the natural world in examples such as lightning and neurons in the brains. Chaos theory has
Chapter 11 closes our discussion with several insights into the efficient market theory. There have been many attempts to discredit the random walk theory, but none of the theories hold against empirical evidence. Any pattern that is noticed by investors will disappear as investors try to exploit it and the valuation methods of growth rate are far too difficult to predict. As we said before the random walk concludes that no patterns exist in the market, pricing is accurate and all information available is already incorporated into the stock price. Therefore the market is efficient. Even if errors do occur in short-run pricing, they will correct themselves in the long run. The random walk suggest that short-term prices cannot be predicted and to buy stocks for the long run. Malkiel concludes the best way to consistently be profitable is to buy and hold a broad based market index fund. As the market rises so will the investors returns since historically the market continues to rise as a whole.
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Researchable task in this study is whether stock asset returns are predictable, which has been a question of great attention emerged with financial econometrics since the earliest times. Mathematical models of asset pricing have an unusually rich history as compared to every other aspect of economic analysis. For tests of return predictability, information set is defined as the past history of stock prices, company characteristics, market characteristics and the time of the year. The Efficient Market Hypothesis was first introduced by Louis Bachelier, a French mathematician in 1900 in his dissertation. Efficient Market Hypothesis (EMH) means that security prices fully reflect all available information. The efficient market hypothesis has been divided into three categories depending on the information set these are weak, semi-strong and strong form.
Volatility can occur in any security that rises or falls in value. The term is most often used in conjunction with the stock market, but foreign currencies can be volatile as well. When exchange rates are floating exchange rates, as opposed to fixed exchange rates, they are likely to go up and down in value depending upon the strength of the economies involved. As a result, volatility is something that affects any business undertaking involving two different countries.