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Full-Text Articles in Business

A Closer Look At The Impact Of Quantitative Easing On The Capital Markets: Garch Analysis Of The Exchange Traded Funds Market, Nicholas R. Duafala Nov 2014

A Closer Look At The Impact Of Quantitative Easing On The Capital Markets: Garch Analysis Of The Exchange Traded Funds Market, Nicholas R. Duafala

Undergraduate Economic Review

This paper analyzes the effects of quantitative easing (QE) on the capital markets by modeling exchange traded funds (ETFs) returns using a generalized autoregressive conditional heteroskedasticity (GARCH) methodology. The results show that the 10-Year Treasury yields are significant in the returns of some sectors of the economy more so than others, and the Federal Funds Futures trading volume is significant in all ETFs return volatility. The implications of these results not only provide information about the reaction of the ETF market and QE, but also provide insight for developing investment strategies.


Studies In Volatility, Nazli Sila Alan Jun 2014

Studies In Volatility, Nazli Sila Alan

Dissertations, Theses, and Capstone Projects

This dissertation consists of five chapters that focus on the price discovery role of equity markets and examine the evolution of intraday stock price volatility as a key measure of market quality. Using six differentiated measures of intraday volatility (that mostly focus on the opening half-hour of trading), all common stocks listed at three stock exchanges with varying levels of fragmentation are analyzed: NYSE and NASDAQ stocks over the period 1993-2012, and Istanbul Stock Exchange (ISE) stocks over the period 2000-2011.

The results on the evolution of intraday volatility presented in Chapters 2 and 3 indicate the following: In 1993, …


Volatility Of The Utilities Industry: Its Causal Relationship To Other Nine Industries, Kuo-Hao Lee, Ahmed Y. Elkassabgi, Wei-Jen Hseih Jan 2014

Volatility Of The Utilities Industry: Its Causal Relationship To Other Nine Industries, Kuo-Hao Lee, Ahmed Y. Elkassabgi, Wei-Jen Hseih

Faculty Publications -School of Business

The goal of this study is to investigate the causality relationship between the Utilities industry and the nine other industries. Previous literatures show that volatility of stock prices is informative; Granger causality is applied in this research by using of a leveraged bootstrap test developed by Hacker and Hatemi-J (2006) to examine the behavior of the volatility. The results indicate that causality of the volatility of the Utilities industry on the volatility of seven other industries, except the Information Technology and Telecommunication Services industries. The data also suggest that Financials industry has impact on the Utilities industry.


Two Essays On The Low Volatility Anomaly, Timothy B. Riley Jan 2014

Two Essays On The Low Volatility Anomaly, Timothy B. Riley

Theses and Dissertations--Finance and Quantitative Methods

I find the low volatility anomaly is present in all but the smallest of stocks. Portfolios can be formed on either total or idiosyncratic volatility to take advantage of this anomaly, but I show measures of idiosyncratic volatility are key. Standard risk-adjusted returns suggest that there is no low volatility anomaly from 1996 through 2011, but I find this result arises from model misspecification. Caution must be taken when analyzing high volatility stocks because their returns have a nonlinear relationship with momentum during market bubbles.

I then find that mutual funds with low return volatility in the prior year outperform …


Modeling Stock Return Volatility In Mongolian Stock Market, Munkhtsog Altankhuu Jan 2014

Modeling Stock Return Volatility In Mongolian Stock Market, Munkhtsog Altankhuu

Theses

This paper is one of the first research works to examine the stock index volatility in the Mongolian Stock Exchange. The study utilizes the Generalized Autoregressive Conditional Heteroscedasticity (GAR CH) models to estimate volatility of stock market return of the Mongolian Stock Exchange. A number of prior research work demonstrated that ARCH and GARCH models are fruitful models for modeling volatility of time series data. However, they recommend using different versions of GARCH-type models for different distributions (Normal, Student's t, Skewed Student's t and Generalized Error Distribution) for emerging markets or developing markets. This paper compares the GARCH(l, 1) model …