This document summarizes a paper that investigates the presence of structural breaks and long memory in the volatility of Volatility Index (VIX) exchange-traded funds (ETFs) returns. Using daily data from 2011 to 2013, the study examines for structural changes in the variance of VIX ETF series and models their relationship by incorporating identified breaks into ARFIMA and FIGARCH models to measure long memory. The results show dual long memory in VIX ETFs is related to their term structure and incorporating structural breaks leads to better estimation, providing evidence for or against market efficiency.
Co integration and causality analysis of dynamic linkagesprj_publication
This document analyzes the relationship between the Indian stock market and equity markets of developed countries like the U.S., U.K., France, Germany, Japan, Hong Kong, and Australia for the period after the global recession from 2010 to 2013. Johansen cointegration analysis found evidence of a long-term relationship between the markets, though some pairwise comparisons did not show cointegration. Granger causality tests also found short-term relationships between some country pairs. Specifically, the analysis indicates funds from Germany, Japan, and the U.S. could benefit from diversifying into India, while India does not qualify as a diversification opportunity for some other countries due to cointegration.
Management of shock and volatility spillover effects across equity marketsprj_publication
This document analyzes shock and volatility spillover effects between the stock markets of India, Singapore, and South Korea during three periods: a pre-crisis boom period, the global recession period, and a post-recession period. Using a multivariate BEKK-GARCH model on daily stock index returns, it finds that the markets exhibit strong own shock and volatility effects in all periods. Regarding cross-market spillovers, India plays a leading role in transmitting both shocks and volatility to Singapore and South Korea markets. The findings suggest international investors should consider this strong integration when assessing potential gains from international portfolios.
The Predictive Power of Intraday-Data Volatility Forecasting Models: A Case S...inventionjournals
The purpose of this study was to compare the predictive power of various volatility forecasting models. Using intraday high-frequency data, this study investigated the influence of time frequency on the predictive power of a volatility forecasting model. The empirical results revealed that the realized volatility increased when the time frequency of forecasts reduced. The overall results showed that when the forecast range was 1 day, among various volatility forecasting models, the autoregressive moving average-generalized autoregressive conditional heteroskedasticity(1, 1) model presented the optimal forecasting performance and the implied volatility model presented the worst forecasting performance for all time frequencies.
11.exchange rate volatility and stock market behaviour the nigerian experienceAlexander Decker
The study examines the relationship between exchange rates and stock market performance in Nigeria from 1985 to 2009 using cointegration and causality tests. The results show:
1) Exchange rates and stock market performance are cointegrated, indicating a long-run equilibrium relationship.
2) The long-run relationship between exchange rates and stock market performance is negative - exchange rate fluctuations negatively impact stock market performance.
3) Granger causality tests show exchange rates cause stock market performance in Nigeria, implying exchange rate volatility explains variations in the stock market.
Testing the Weak–Form Market Efficiency on the Borsa Istanbul (BIST) Sustaina...inventionjournals
An efficient market is a concept discussed and maintained in the financial literature. This concept expressed as the instant reflection of all the information concerning the stocks defends that there shouldn’t be any stocks that are low or overvalued on the market. The purpose in this study is the weak-form efficiency of stock market in Turkey to be analyzed with the help of Runs Test. In the research, daily session closing prices of the stocks being currently traded in the Borsa Istanbul (Istanbul Stock Exchange) Sustainability Index within a 12–month period between the dates 01.12.2015 and 30.11.2016 have been employed and tested whether or not the consecutive price changes in said range of time were independent from each other. The fact that consecutive price changes were independent from each other has revealed that the Random Walk Hypothesis was not applicable in terms of the index examined. The outcome acquired contains findings that BIST stock market is not a weak–form efficient market.
Effect of equity derivatives trading on spot market volatility in indiaAlexander Decker
This document discusses a study examining the effect of equity derivatives trading on spot market volatility in India. It provides context on the growth of derivatives trading in India. The author reviews previous literature which has found mixed results on the impact of derivatives introduction on underlying volatility in other markets. Some studies found increased volatility, others found decreased volatility, and some found no significant impact. The present study aims to help resolve these inconsistent findings by analyzing the impact of equity derivatives introduction on spot market volatility in India, using statistical models to account for asymmetric responses to news.
Co integration and causality analysis of dynamic linkagesprj_publication
This document analyzes the relationship between the Indian stock market and equity markets of developed countries like the U.S., U.K., France, Germany, Japan, Hong Kong, and Australia for the period after the global recession from 2010 to 2013. Johansen cointegration analysis found evidence of a long-term relationship between the markets, though some pairwise comparisons did not show cointegration. Granger causality tests also found short-term relationships between some country pairs. Specifically, the analysis indicates funds from Germany, Japan, and the U.S. could benefit from diversifying into India, while India does not qualify as a diversification opportunity for some other countries due to cointegration.
Management of shock and volatility spillover effects across equity marketsprj_publication
This document analyzes shock and volatility spillover effects between the stock markets of India, Singapore, and South Korea during three periods: a pre-crisis boom period, the global recession period, and a post-recession period. Using a multivariate BEKK-GARCH model on daily stock index returns, it finds that the markets exhibit strong own shock and volatility effects in all periods. Regarding cross-market spillovers, India plays a leading role in transmitting both shocks and volatility to Singapore and South Korea markets. The findings suggest international investors should consider this strong integration when assessing potential gains from international portfolios.
The Predictive Power of Intraday-Data Volatility Forecasting Models: A Case S...inventionjournals
The purpose of this study was to compare the predictive power of various volatility forecasting models. Using intraday high-frequency data, this study investigated the influence of time frequency on the predictive power of a volatility forecasting model. The empirical results revealed that the realized volatility increased when the time frequency of forecasts reduced. The overall results showed that when the forecast range was 1 day, among various volatility forecasting models, the autoregressive moving average-generalized autoregressive conditional heteroskedasticity(1, 1) model presented the optimal forecasting performance and the implied volatility model presented the worst forecasting performance for all time frequencies.
11.exchange rate volatility and stock market behaviour the nigerian experienceAlexander Decker
The study examines the relationship between exchange rates and stock market performance in Nigeria from 1985 to 2009 using cointegration and causality tests. The results show:
1) Exchange rates and stock market performance are cointegrated, indicating a long-run equilibrium relationship.
2) The long-run relationship between exchange rates and stock market performance is negative - exchange rate fluctuations negatively impact stock market performance.
3) Granger causality tests show exchange rates cause stock market performance in Nigeria, implying exchange rate volatility explains variations in the stock market.
Testing the Weak–Form Market Efficiency on the Borsa Istanbul (BIST) Sustaina...inventionjournals
An efficient market is a concept discussed and maintained in the financial literature. This concept expressed as the instant reflection of all the information concerning the stocks defends that there shouldn’t be any stocks that are low or overvalued on the market. The purpose in this study is the weak-form efficiency of stock market in Turkey to be analyzed with the help of Runs Test. In the research, daily session closing prices of the stocks being currently traded in the Borsa Istanbul (Istanbul Stock Exchange) Sustainability Index within a 12–month period between the dates 01.12.2015 and 30.11.2016 have been employed and tested whether or not the consecutive price changes in said range of time were independent from each other. The fact that consecutive price changes were independent from each other has revealed that the Random Walk Hypothesis was not applicable in terms of the index examined. The outcome acquired contains findings that BIST stock market is not a weak–form efficient market.
Effect of equity derivatives trading on spot market volatility in indiaAlexander Decker
This document discusses a study examining the effect of equity derivatives trading on spot market volatility in India. It provides context on the growth of derivatives trading in India. The author reviews previous literature which has found mixed results on the impact of derivatives introduction on underlying volatility in other markets. Some studies found increased volatility, others found decreased volatility, and some found no significant impact. The present study aims to help resolve these inconsistent findings by analyzing the impact of equity derivatives introduction on spot market volatility in India, using statistical models to account for asymmetric responses to news.
This thesis investigates volatility spillovers between five major stock indices from 2002-2015. It finds that during the Great Financial Crisis, linkages and spillovers between the S&P 500, FTSE 100, Nikkei 225, DAX 30, and Toronto 300 Composite intensified. Using multivariate models, it provides evidence that market linkages and volatility spillovers have increased over time. The author aims to determine if volatility in one market leads others, and whether spillovers rise in crises or over the long-run. Geography's role as a determinant of co-movements is also examined.
Financial integration between BRICS and developed stock marketsinventionjournals
International Journal of Business and Management Invention (IJBMI) is an international journal intended for professionals and researchers in all fields of Business and Management. IJBMI publishes research articles and reviews within the whole field Business and Management, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
This document reviews empirical studies on initial public offering (IPO) activity and pricing behavior in Korea. It summarizes that Korean IPOs exhibit significant underpricing on average, with initial returns averaging 57.6% from 2000-2007. Several hypotheses have been proposed to explain this underpricing, including asymmetric information, price stabilization by underwriters, and behavioral factors like investor irrationality. However, no single hypothesis fully accounts for the large initial returns observed. The document also notes that Korean IPO markets exhibit cyclical "hot issue markets" and that IPO stocks often underperform in the long run.
Co movements of u.s. eu and indian equity markets-portfolio diversification ...Alexander Decker
This document discusses research on the co-movements of equity markets in the US, EU, and India and the implications for international portfolio diversification. It provides an extensive literature review on previous research examining the integration and correlations between developed and emerging stock markets over time. The literature review covers studies investigating the co-movement and integration patterns between markets in North America, Europe, Asia, and other regions. The present study aims to focus on the co-integration relationship between the American, European and Indian equity markets.
This document analyzes volatility patterns in various sectoral indices in the Indian stock market from 2008-2013 using autoregressive conditional heteroskedasticity (ARCH) models. It finds that the realty sector witnessed higher volatility than any other sector during the period. The study uses statistical tools like mean, standard deviation and econometric tools like unit root tests and ARCH modeling to measure and compare volatility in the NIFTY index and 11 sectoral indices of the National Stock Exchange of India. Diagnostic tests on the ARCH models show that residuals exhibit ARCH effects and non-normal distributions.
This document summarizes a study examining the "day of the week effect" on stock returns in the Pakistani stock market between 2006-2010. The study finds evidence of a "Tuesday effect", with average returns on Tuesdays found to be significantly higher than other days of the week. Descriptive statistics show the mean Tuesday return was 164.88 compared to 100.25 on other days. Regression analysis also indicates returns were significantly higher on Tuesdays, violating the assumption of efficient market hypothesis that returns should be constant across all days. Therefore, the study concludes there is a day of the week effect in the Pakistani stock market with abnormal returns observed on Tuesdays.
Exchange Rate Overshooting and its Impact on the Balance of Trade for the Tur...Hüseyin Tekler
Exchange rate overshooting is the short run phenomenon under the Dornbusch Model presented in 1976. We are really desiderative to find out whether the overshoots are for the short run or for the long run period for the Turkish economy. The estimated result using the Johansen Julius method and VECM, we have found that overshooting is for the short run period as opposed to the findings of Bahmani-Oskooee & Orhan (2000) while the Purchasing power parity [PPP] does not hold for the Turkish economy.
Impact of macroeconomic variables on stock returnsMuhammad Mansoor
The document discusses the impact of macroeconomic factors on stock returns. It provides background information on financial markets, primary and secondary markets, and stock market returns. It then summarizes several empirical studies that have examined the relationship between macroeconomic variables like interest rates, inflation, GDP, exchange rates, and stock market returns in countries like Pakistan, Japan, Nigeria, and others. The studies found both positive and negative relationships between different macroeconomic factors and stock returns in various markets. The document aims to contribute to this area of research by examining the impact of macroeconomic variables on stock returns in the Pakistani stock market.
1) The document examines the relationship between stock market liquidity and stock returns in 27 emerging markets from 1992 to 1999.
2) It finds that stock returns are positively correlated with measures of market liquidity such as turnover ratio, trading value, and turnover-volatility multiple, in both cross-sectional and time-series analyses.
3) This positive correlation between returns and liquidity in emerging markets differs from theories and findings in developed markets, and may be due to emerging markets having a lower degree of integration with the global economy.
Co movements of u.s. eu and indian equity markets-portfolio diversification ...Alexander Decker
This document discusses research on the co-movements of equity markets in the US, EU, and India and the implications for international portfolio diversification. It provides an extensive literature review on previous research examining correlations and co-integration between developed and emerging stock markets. The literature review covers studies investigating the degree of integration between markets over time and how globalization has impacted opportunities for diversification. The present study aims to focus on the co-integration relationship between the American, European, and Indian equity markets.
Tangible market information and stock returns the nepalese evidence synopsisSudarshan Kadariya
This is a synopsis of the work done for the academic fulfillment purpose. The study have assumptions. The findings are suggested to related with its assumptions. I believe this work will help the financial / stock market in Nepal and it will also be accessible and share some features to the international financial market researchers.
This document summarizes a study that examines the statistical properties and predictive factors of the VKOSPI, South Korea's implied volatility index derived from options on the KOSPI 200 stock index. The study finds that an augmented heterogeneous autoregressive (HAR) model describes the dynamics of the VKOSPI well and some domestic macroeconomic variables help explain it. Most importantly, it determines that US stock market returns and implied volatility (from S&P 500 options) play a dominant role in predicting VKOSPI levels and dynamics, more so than domestic factors. Specifically, while US stock returns significantly predict VKOSPI, Korean stock returns do not. The study thus provides evidence that global factors have substantial influence over implied volatility in emerging markets like
JUMPING RISK IN TAIWAN AND TAIEX OPTION RETURN IN TAIWAN ijcsit
With low-interest environment in recent years, investment of financial commodity was unable to meet the requirements of necessary paid by society. Therefore, the traditional financial tool were replacing with derivative financial commodity which were high risk, high lever, and high complex; including option, forward contract, futures, credit default swap, and collateralized debt obligations. Global Board Options Exchanges were founded in 1983 that S&PS00 (SPX) index option which launched by the Chicago Board Options Exchange (CBOE). Moreover CBOE was the option which target on trade index at the earliest, and CBOE was the most popular exchange with option trade. Taiwan Futures Exchange (TFE) launched Taiwan weighted index options (TXO) in December 2001 and, and launched stock options in 2003. Currently TXO was the most actively traded options market in Taiwan, but almost had no stock options trading volume due to the release of warrants market. However warrants market and individual stock options had higher homogeneous and better mobility to influence the stock options market. Although Taiwan options market started lately, develops quite fast, the option of Taiwan index was the sixth volume in the global select token name in 2013, that showed that Taiwan index options was a good target on the options-related research. Due to the globalization of financial markets, the single original market waved turn into the global storm which that affected financial asset prices were no longer continuous fluctuations, and it showed a leaps of change by the Butterfly Effect. Because the price process included continuity and discontinuity, the spread and jump process was more accurate than Brownian motion (BM). Currently the derivatives study biased on interest rate futures, foreign futures or foreign exchange futures options and Taiwan index futures options. By the way, the study about the jumping risks related to Taiwan index options effects is rare.
This document analyzes the relationship between stock market liquidity and stock returns in 27 emerging equity markets from January 1992 to December 1999. It finds that stock returns are positively correlated with measures of market liquidity, including turnover ratio, trading value, and turnover-volatility multiple, in both cross-sectional and time-series analyses. This relationship holds even after controlling for other factors and contrasts with theories supported by studies of developed markets, where liquidity and returns are negatively correlated. The findings suggest emerging markets have a lower degree of integration with the global economy.
Forecasting Stocks with Multivariate Time Series Models.inventionjournals
This work seeks to forecast stocks of the Nigerian banking sector using probability multivariate time series models. The study involved the stocks from six different banks that were found to be analytically interrelated. Stationarity of the six series were obtained by differencing. Model selection criteria were employed and the best fitted model was selected to be a vector autoregressive model of order 1. The model was subjected to diagnostic checks and was found to be adequate. Consequently, forecasts of stocks were generated for the next two years.
This document examines multi-style and rotation equity investment strategies in European markets from 1994-2004 using fundamental ratios. It finds that market capitalization was the primary factor for constructing portfolios, while price-to-earnings and price-to-book ratios showed risk-efficient results only for medium and large capitalization stocks. The study also finds that an active portfolio manager would need high accuracy to outperform passive strategies. It analyzes single-style and multi-style strategies using fundamental data for 104 European companies across different industries.
This study investigates the impact of the introduction of index options on emerging market volatility in the context of Malaysia. Company specific daily closing prices for 29 listed companies were examined to determine the conditional volatility shifts before and after the introduction of index options. Multiple window periods are examined to avoid year-end effects.The exponential generalized autoregressive conditional heteroskedasticity (EGARCH) (1.1) model is used to determine the conditional volatility shift before and after the introduction of index options in Malaysia. The findings of this study suggest that the introduction of index options reduced market volatility in the Malaysia equity market at the 0.01 level of statistical significance. Further, this study contributed to extant literature because it uses company-specific daily equity price data and no such previous study exists on the impact of index options for this important emerging market. The study will be useful for academics, researchers, domestic and foreign investors and policy-makers, among others.
Using a unique short selling setting in Hong Kong stock market, we test the Chen and Singal (2003) hypothesis that speculative short sellers add to the selling pressure on Mondays and hence add to the weekend effect. We document that, first, the weekend effect exists in Hong Kong stock market, regardless of the existence of short sale constraints; second, after introducing short selling, the individual stocks face more significant weekend effect. The reported result is robust over different estimation models, and over different choices of control groups. Our findings strongly support the Chen and Singal (2003) hypothesis.
A Comparison of Hsu &Wang Model and Cost of Carry Model: The case of Stock In...iosrjce
The study empirically tests and compares the pricing performance of two alternative futures pricing
models; the standard Cost of Carry Model and Hsu & Wang Model (2004) for three futures indices of National
Stock Exchange (NSE), India – CNX Nifty futures, Bank Nifty futures and CNX IT futures. It is found that, the
Hsu & Wang Model with an argument of incomplete arbitrage mechanism and real capital markets are
imperfect, provides much better pricing performance than the standard Cost of Carry Model for all the three
futures markets. On the basis of Mean Absolute Pricing Error (MAPE), CNX Nifty Futures contract with highest
trading history and trading volume is preferred, followed by Bank Nifty futures and CNX IT futures contract for
both the pricing models. This result implies that Indian futures markets are imperfect and arbitrage process
cannot complete. Degree of market imperfection might influence the pricing error. Therefore, investors should
know the degree of market imperfection of the futures markets in which they would like to participate.
Fund performance persistence and competition keswanibfmresearch
This document summarizes a study that examines how competition within a sector affects mutual fund performance persistence at the sector level in the UK market. The study uses data on UK unit trusts from 1991-2001 that includes annual returns, assets, and sector classifications. Several variables are constructed to measure competition within each sector, such as the number of funds, proportion of mature funds, and concentration of assets. The main finding is that performance persistence is higher in sectors where concentration of assets under management is higher, indicating less competition is associated with greater persistence. This suggests the degree of persistence exhibited by a sector's funds depends on how competitive that sector is.
This document analyzes the impact of futures trading on market volatility in the Indian equity market, specifically looking at the S&P CNX IT index. It first reviews previous literature which reports mixed findings on the effect of derivatives introduction on volatility. The document then outlines the GARCH methodology used to model conditional volatility in the index returns series before and after the introduction of futures trading in India. Preliminary results found increased market volatility after futures listing, but sensitivity of returns to domestic and global markets remained unchanged. The nature of volatility also altered, with prices becoming more dependent on recent innovations post-derivatives, indicating improved efficiency.
11.efficient market hypothesis and nigerian stock marketAlexander Decker
This document discusses a study that examined the weak-form efficient market hypothesis in the Nigerian stock market from 1986 to 2010. The researchers tested for stationarity using the Augmented Dickey Fuller and Philip Perron tests, and used serial auto-correlation and regression analysis to test for random walks in stock prices. The results showed that stock prices do not exhibit random walks and are not informationally efficient. The study recommends stronger regulation and policies to develop the Nigerian stock market and enhance its informational efficiency.
This thesis investigates volatility spillovers between five major stock indices from 2002-2015. It finds that during the Great Financial Crisis, linkages and spillovers between the S&P 500, FTSE 100, Nikkei 225, DAX 30, and Toronto 300 Composite intensified. Using multivariate models, it provides evidence that market linkages and volatility spillovers have increased over time. The author aims to determine if volatility in one market leads others, and whether spillovers rise in crises or over the long-run. Geography's role as a determinant of co-movements is also examined.
Financial integration between BRICS and developed stock marketsinventionjournals
International Journal of Business and Management Invention (IJBMI) is an international journal intended for professionals and researchers in all fields of Business and Management. IJBMI publishes research articles and reviews within the whole field Business and Management, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
This document reviews empirical studies on initial public offering (IPO) activity and pricing behavior in Korea. It summarizes that Korean IPOs exhibit significant underpricing on average, with initial returns averaging 57.6% from 2000-2007. Several hypotheses have been proposed to explain this underpricing, including asymmetric information, price stabilization by underwriters, and behavioral factors like investor irrationality. However, no single hypothesis fully accounts for the large initial returns observed. The document also notes that Korean IPO markets exhibit cyclical "hot issue markets" and that IPO stocks often underperform in the long run.
Co movements of u.s. eu and indian equity markets-portfolio diversification ...Alexander Decker
This document discusses research on the co-movements of equity markets in the US, EU, and India and the implications for international portfolio diversification. It provides an extensive literature review on previous research examining the integration and correlations between developed and emerging stock markets over time. The literature review covers studies investigating the co-movement and integration patterns between markets in North America, Europe, Asia, and other regions. The present study aims to focus on the co-integration relationship between the American, European and Indian equity markets.
This document analyzes volatility patterns in various sectoral indices in the Indian stock market from 2008-2013 using autoregressive conditional heteroskedasticity (ARCH) models. It finds that the realty sector witnessed higher volatility than any other sector during the period. The study uses statistical tools like mean, standard deviation and econometric tools like unit root tests and ARCH modeling to measure and compare volatility in the NIFTY index and 11 sectoral indices of the National Stock Exchange of India. Diagnostic tests on the ARCH models show that residuals exhibit ARCH effects and non-normal distributions.
This document summarizes a study examining the "day of the week effect" on stock returns in the Pakistani stock market between 2006-2010. The study finds evidence of a "Tuesday effect", with average returns on Tuesdays found to be significantly higher than other days of the week. Descriptive statistics show the mean Tuesday return was 164.88 compared to 100.25 on other days. Regression analysis also indicates returns were significantly higher on Tuesdays, violating the assumption of efficient market hypothesis that returns should be constant across all days. Therefore, the study concludes there is a day of the week effect in the Pakistani stock market with abnormal returns observed on Tuesdays.
Exchange Rate Overshooting and its Impact on the Balance of Trade for the Tur...Hüseyin Tekler
Exchange rate overshooting is the short run phenomenon under the Dornbusch Model presented in 1976. We are really desiderative to find out whether the overshoots are for the short run or for the long run period for the Turkish economy. The estimated result using the Johansen Julius method and VECM, we have found that overshooting is for the short run period as opposed to the findings of Bahmani-Oskooee & Orhan (2000) while the Purchasing power parity [PPP] does not hold for the Turkish economy.
Impact of macroeconomic variables on stock returnsMuhammad Mansoor
The document discusses the impact of macroeconomic factors on stock returns. It provides background information on financial markets, primary and secondary markets, and stock market returns. It then summarizes several empirical studies that have examined the relationship between macroeconomic variables like interest rates, inflation, GDP, exchange rates, and stock market returns in countries like Pakistan, Japan, Nigeria, and others. The studies found both positive and negative relationships between different macroeconomic factors and stock returns in various markets. The document aims to contribute to this area of research by examining the impact of macroeconomic variables on stock returns in the Pakistani stock market.
1) The document examines the relationship between stock market liquidity and stock returns in 27 emerging markets from 1992 to 1999.
2) It finds that stock returns are positively correlated with measures of market liquidity such as turnover ratio, trading value, and turnover-volatility multiple, in both cross-sectional and time-series analyses.
3) This positive correlation between returns and liquidity in emerging markets differs from theories and findings in developed markets, and may be due to emerging markets having a lower degree of integration with the global economy.
Co movements of u.s. eu and indian equity markets-portfolio diversification ...Alexander Decker
This document discusses research on the co-movements of equity markets in the US, EU, and India and the implications for international portfolio diversification. It provides an extensive literature review on previous research examining correlations and co-integration between developed and emerging stock markets. The literature review covers studies investigating the degree of integration between markets over time and how globalization has impacted opportunities for diversification. The present study aims to focus on the co-integration relationship between the American, European, and Indian equity markets.
Tangible market information and stock returns the nepalese evidence synopsisSudarshan Kadariya
This is a synopsis of the work done for the academic fulfillment purpose. The study have assumptions. The findings are suggested to related with its assumptions. I believe this work will help the financial / stock market in Nepal and it will also be accessible and share some features to the international financial market researchers.
This document summarizes a study that examines the statistical properties and predictive factors of the VKOSPI, South Korea's implied volatility index derived from options on the KOSPI 200 stock index. The study finds that an augmented heterogeneous autoregressive (HAR) model describes the dynamics of the VKOSPI well and some domestic macroeconomic variables help explain it. Most importantly, it determines that US stock market returns and implied volatility (from S&P 500 options) play a dominant role in predicting VKOSPI levels and dynamics, more so than domestic factors. Specifically, while US stock returns significantly predict VKOSPI, Korean stock returns do not. The study thus provides evidence that global factors have substantial influence over implied volatility in emerging markets like
JUMPING RISK IN TAIWAN AND TAIEX OPTION RETURN IN TAIWAN ijcsit
With low-interest environment in recent years, investment of financial commodity was unable to meet the requirements of necessary paid by society. Therefore, the traditional financial tool were replacing with derivative financial commodity which were high risk, high lever, and high complex; including option, forward contract, futures, credit default swap, and collateralized debt obligations. Global Board Options Exchanges were founded in 1983 that S&PS00 (SPX) index option which launched by the Chicago Board Options Exchange (CBOE). Moreover CBOE was the option which target on trade index at the earliest, and CBOE was the most popular exchange with option trade. Taiwan Futures Exchange (TFE) launched Taiwan weighted index options (TXO) in December 2001 and, and launched stock options in 2003. Currently TXO was the most actively traded options market in Taiwan, but almost had no stock options trading volume due to the release of warrants market. However warrants market and individual stock options had higher homogeneous and better mobility to influence the stock options market. Although Taiwan options market started lately, develops quite fast, the option of Taiwan index was the sixth volume in the global select token name in 2013, that showed that Taiwan index options was a good target on the options-related research. Due to the globalization of financial markets, the single original market waved turn into the global storm which that affected financial asset prices were no longer continuous fluctuations, and it showed a leaps of change by the Butterfly Effect. Because the price process included continuity and discontinuity, the spread and jump process was more accurate than Brownian motion (BM). Currently the derivatives study biased on interest rate futures, foreign futures or foreign exchange futures options and Taiwan index futures options. By the way, the study about the jumping risks related to Taiwan index options effects is rare.
This document analyzes the relationship between stock market liquidity and stock returns in 27 emerging equity markets from January 1992 to December 1999. It finds that stock returns are positively correlated with measures of market liquidity, including turnover ratio, trading value, and turnover-volatility multiple, in both cross-sectional and time-series analyses. This relationship holds even after controlling for other factors and contrasts with theories supported by studies of developed markets, where liquidity and returns are negatively correlated. The findings suggest emerging markets have a lower degree of integration with the global economy.
Forecasting Stocks with Multivariate Time Series Models.inventionjournals
This work seeks to forecast stocks of the Nigerian banking sector using probability multivariate time series models. The study involved the stocks from six different banks that were found to be analytically interrelated. Stationarity of the six series were obtained by differencing. Model selection criteria were employed and the best fitted model was selected to be a vector autoregressive model of order 1. The model was subjected to diagnostic checks and was found to be adequate. Consequently, forecasts of stocks were generated for the next two years.
This document examines multi-style and rotation equity investment strategies in European markets from 1994-2004 using fundamental ratios. It finds that market capitalization was the primary factor for constructing portfolios, while price-to-earnings and price-to-book ratios showed risk-efficient results only for medium and large capitalization stocks. The study also finds that an active portfolio manager would need high accuracy to outperform passive strategies. It analyzes single-style and multi-style strategies using fundamental data for 104 European companies across different industries.
This study investigates the impact of the introduction of index options on emerging market volatility in the context of Malaysia. Company specific daily closing prices for 29 listed companies were examined to determine the conditional volatility shifts before and after the introduction of index options. Multiple window periods are examined to avoid year-end effects.The exponential generalized autoregressive conditional heteroskedasticity (EGARCH) (1.1) model is used to determine the conditional volatility shift before and after the introduction of index options in Malaysia. The findings of this study suggest that the introduction of index options reduced market volatility in the Malaysia equity market at the 0.01 level of statistical significance. Further, this study contributed to extant literature because it uses company-specific daily equity price data and no such previous study exists on the impact of index options for this important emerging market. The study will be useful for academics, researchers, domestic and foreign investors and policy-makers, among others.
Using a unique short selling setting in Hong Kong stock market, we test the Chen and Singal (2003) hypothesis that speculative short sellers add to the selling pressure on Mondays and hence add to the weekend effect. We document that, first, the weekend effect exists in Hong Kong stock market, regardless of the existence of short sale constraints; second, after introducing short selling, the individual stocks face more significant weekend effect. The reported result is robust over different estimation models, and over different choices of control groups. Our findings strongly support the Chen and Singal (2003) hypothesis.
A Comparison of Hsu &Wang Model and Cost of Carry Model: The case of Stock In...iosrjce
The study empirically tests and compares the pricing performance of two alternative futures pricing
models; the standard Cost of Carry Model and Hsu & Wang Model (2004) for three futures indices of National
Stock Exchange (NSE), India – CNX Nifty futures, Bank Nifty futures and CNX IT futures. It is found that, the
Hsu & Wang Model with an argument of incomplete arbitrage mechanism and real capital markets are
imperfect, provides much better pricing performance than the standard Cost of Carry Model for all the three
futures markets. On the basis of Mean Absolute Pricing Error (MAPE), CNX Nifty Futures contract with highest
trading history and trading volume is preferred, followed by Bank Nifty futures and CNX IT futures contract for
both the pricing models. This result implies that Indian futures markets are imperfect and arbitrage process
cannot complete. Degree of market imperfection might influence the pricing error. Therefore, investors should
know the degree of market imperfection of the futures markets in which they would like to participate.
Fund performance persistence and competition keswanibfmresearch
This document summarizes a study that examines how competition within a sector affects mutual fund performance persistence at the sector level in the UK market. The study uses data on UK unit trusts from 1991-2001 that includes annual returns, assets, and sector classifications. Several variables are constructed to measure competition within each sector, such as the number of funds, proportion of mature funds, and concentration of assets. The main finding is that performance persistence is higher in sectors where concentration of assets under management is higher, indicating less competition is associated with greater persistence. This suggests the degree of persistence exhibited by a sector's funds depends on how competitive that sector is.
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Efficient market hypothesis and nigerian stock marketAlexander Decker
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1. Proceeding - Kuala Lumpur International Business, Economics and Law Conference 4 (KLIBEL4)
Vol. 1. 31 May – 1 June 2014. Hotel Putra, Kuala Lumpur, Malaysia. ISBN 978-967-11350-3-7
Long Memory and Structural Breaks in Modelling the Volatility
Dynamics of VIX-ETFs
Jo-Hui Chen
Professor, Department of Finance,
Chung Yuan Christian University, Chung-li, Taiwan
Tel:88632655108
Fax:88632655749
johui@cycu.edu.tw
Yu-Fang Huang
PhD Program in Management,
Chung Yuan Christian University,
Chung-li, Taiwan
g9904601@cycu.edu.tw
Abstract
This paper investigates for the presence of structural breaks in Volatility Index (VIX) ETFs
returns. Using daily data that spans from October 3, 2011 to December 31, 2013, the study
examine the existence of structural changes in tested VIX-ETFs series variance via Iterated
Cumulative Sums of Squares (ICSS). Then, the study continues to investigate the implication of
structural breaks in VIX-ETFs volatility clustering estimation process. The study employs
ARFIMA and FIGARCH models to measure the long memory in VIX-ETFs returns, and
compares with and without the structural break. Imposing identified the breaks in the variance of
returns series, the study models their relationship by incorporating those breaks in the volatility
clustering procedure, like ICSS-ARFIMA-FIGARCH. The results of dual long memory in VIX-ETFs
are relation with term structure of VIX-ETFs and are better estimation with imposing
structure breaks model.
1. Introduction
The Exchange Traded Funds (ETFs) has grown substantially worldwide. By 2013, they
consisted of 8,200 funds with a combined market capitalization approximated to $11.5 trillion
worldwide (World Federation of Exchanges, 2013)1. ETFs are hybrids of mutual funds and close-end
funds. ETFs were launched in the United States in 1993, and the study of Guedj and Huang
(2009) indicated the first ETFs listed in U.S. in order to replicate the Standard and Poor’s (SP)
500 indexes. On the whole, there are three groups of ETFs. First, normal ETFs are those whose
goal return is equal to the return on the underlying asset or index. Second, inverse ETFs whose
return are in the opposite direction of the underlying asset or index. Third, leveraged ETFs are
those whose return is multiple times of the return on the underlying asset or index.
ETFs have received much attention in the last past decade, their research file focus on the
international stock market indexes (Ackert and Tian, 2008), commodities (Lixia et al., 2010;
Ivanov, 2013), bonds (Drenovak, 2012), and real estate market (Ivanov, 2012). In the equity
market, the tradeoff between return and volatility is one of the most interesting issues in finance.
Therefore, other stem of studies have considered the demand various issues, i.e., the efficiency and
the pricing structure of index funds (Lin et al., 2006), ETF performance relative to traditional
funds (Barnhart and Rosenstein, 2010), and risk exposure through international index ETFs
(Hughen and Mathew, 2009; Krause and Tse, 2013).
1 Data Source: http://world-exchanges.org.
2. Proceeding - Kuala Lumpur International Business, Economics and Law Conference 4 (KLIBEL4)
Vol. 1. 31 May – 1 June 2014. Hotel Putra, Kuala Lumpur, Malaysia. ISBN 978-967-11350-3-7
A popular indicator of short-term market volatility, namely the VIX, which represents a
market consentience speculation of future 30 days stock market volatility in U.S. stocks market
(Fleming et al., 1995; Whaley, 2000). The VIX was published by the Chicago Board Options
Exchange (CBOE) and has become the standard measure of volatility risk in the US stock market.
The goal of the VIX index is to calculate the volatility of the Standard and Poor’s 500 (SP 500)
over 30 days implied in stock index option prices. The VIX is modern as a major asset
classification with investors for two reasons. First, the VIX provides diversification profits to
investors because it’s negative relationship with SP 500. Second, there are some productions
(e.g. ETF and Exchange Traded Note (ETN)) offering investors approach to evaluate asset
classification for the first time. The VIX tracked the underlying of ETF as a matter of course,
because it is relation with SP 500 index.
If the forecasting models do not consider structural breaks, the results yielded unstable
forecasts as compared to models with structural breaks (Bai and Perron, 2003; Pesaran and
Timmermann, 2004). On the empirical front has proved that structural breaks impacted on the time
series behaviors and estimation accuracy. Structural breaks possess of characteristic a flock of
time series containing interest rates (Esteve et al., 2013), exchange rate (Cerrato et al., 2013),
commodities price (Zainudin and Shaharudin, 2011), stock market (Badhani, 2008; Chunxia et al.,
2012), treasury bond (Covarrubias et al., 2006), futures market (Ewing and Malik, 2013), and
others (Abu-Qarn and Abu-Bader, 2008). Moreover, Jouini and Boutahar (2005) employed the
U.S. time series to examine structural number, showing that the performance of model with
multiple structural breaks is better than the model with single structural break.
The precious financial theory, the efficient market hypothesis (EMH) was proposed by Fama
(1965). The purpose of the efficient market hypothesis is to prove that all information reflects in
the stock market, and nobody can get excess returns from the efficient market. Specially, the
efficient market had three forms i.e. weak, semi-strong, and strong form. The weak-form
efficiency assumes that investors can not apply past price to predicate future price. In other words,
somebody can depend on history price, volume, and other information to get excess profit,
implying that the random walk of stock market failed. A large volume of literature deals with long
memory and financial return series dynamics: volatility index (Wiphatthanananthakul and
Sriboonchitta, 2010), commodity (Kyongwook and Shawkat, 2009; Arouri et al., 2012), stock
market (Kang and Yoon, 2007; Caporale and Gil-Alana, 2008), and exchange rate (Choi et al.,
2010). Indeed, Herzberg and Sibbertsen (2004) confirmed that the pricing of financial derivatives
with well forecasting capability must be considered financial time series with long memory.
The study examines VIX-ETFs applying multiple structure breaks proposed by Inclan and
Tiao (1994), which evaluated long memory models proposed by Granger and Joyeux (1980),
Hosking (1981), and Baillie et al. (1996). To the best of our knowledge, no study has specifically
investigated the structural break and long memory process of VIX-ETFs that aim to evidence the
efficient market hypothesis. There are three contributes in this study. First, the work increases the
existing literature on ETFs in the following distinct ways. Second, the study offers some
suggestions for academic and market practitioners to decide whether to practice the efficient
market hypothesis or not. Third, the work testes and verifies structural break date conforming to
important economic shocks.
The rest of this paper is structured as follows. Section 2 presents a review of related
literature. Section 3 describes the data and explains the methodology. Section 4 summarizes the
empirical results. Section 5 provides the conclusions.
3. Proceeding - Kuala Lumpur International Business, Economics and Law Conference 4 (KLIBEL4)
Vol. 1. 31 May – 1 June 2014. Hotel Putra, Kuala Lumpur, Malaysia. ISBN 978-967-11350-3-7
2. Related Literature
The exchange traded funds (ETFs) have become widespread investment instruments and have
increased fast among financial products. According Investment Company Institute2 (ICI), there is
more than 1,200 ETFs trading on the U.S. exchanges. ETF assets under management in the U.S.
have reached to nearly 1.3 trillion dollars. ETFs are provided with lower costs, trading flexibility,
tax efficiency, and exposure to a variety of markets. There are a number of papers that studied the
performance of ETFs tracking different country’s equity indexes (Jares and Lavin, 2004; Ackert
and Tian, 2008; Blitz and Swinkels 2012), others underlying instruments (Ivanov, 2012; Mukul et
al., 2012; Padungsaksawasdi and Daigler, 2013; Daigler et al., 2014), and fix income/bonds
(Drenovak et al., 2012; Houweling, 2012). For the U.S. equity indexes, the study of Ackert and
Tian (2008) examined the pricing of the U.S. ETFs and country ETFs listed in the United States.
The result provided that the U.S. funds are negative relation among fund premium and market
liquidity. They also indicated that the mispricing of country funds derived from momentum,
illiquidity, and size effects. In addition, Bum (2011) compared with the U.S. ETFs and Asia-
Pacific ETFs across the U.S., Japan, South Korea, Hong Kong, Taiwan, Singapore, Australia, New
Zealand and China to demonstrate the causality and spillover effects from 2004 to 2010. He
exhibited that the U.S. equity market caused of Asia-Pacific equity market, but Asia-Pacific equity
market cannot cause of the U.S. equity market. He also confirmed the Asia-Pacific region has a
sensitive link with the U.S. economy. On the other hand, Blitz and Swinkels (2012) used ETFs and
mutual funds were listed in Europe to evaluate their performance. Those instruments tracked the
major equity market indexes for the U.S., Europe, Japan, and emerging markets. They
corroborated that dividend taxes were important factor for the performance of index funds and
ETFs.
A large volume of literature deals with commodity ETFs, the empirical study of Ivanov
(2012) compared the profit effect between the Vanguard REIT-ETFs and iShares Dow Jones US
REIT-ETFs during the financial crisis. The results revealed that the REIT-ETFs did not track the
Dow Jones U.S. Real Estate Index before the financial crisis, but the REIT-ETFs were robust
tracking their underlying indexes during and after the crisis. Padungsaksawasdi and Daigler (2013)
employed commodity option VIXs for the euro, gold, and oil to evaluate the return-implied
volatility. The analysis showed that the return of gold ETF presented significantly positive
relation, and price change relation between the commodity ETFs and their option VIX changes.
Recently, Daigler et al. (2014) applied the eurocurrency ETFs (FXE) and the euro option VIX
(EVZ) to calculate the return-implied volatility. The return-implied volatility relation is not
significant and the asymmetric return sometimes was positive for the currency market.
A few study focused on fixed income ETFs, for example Houweling (2012) researched the
return of fixed income (plain vanilla) ETFs tracking treasury bonds, corporate and non-corporate
bonds. The results showed that tracking the benchmarks ability of treasury ETFs was higher than
others, and the performances of (non) corporate bonds ETFs were lower than their benchmarks.
They also expressed that the transaction costs of the underlying bonds impacted on the return of
ETFs. To extend the issue of ETFs, Johnson (2009) evaluated the tracking errors between 20
foreign ETFs and the underlying home index returns. The variable of positive foreign indexes
returns relative to the US index was a significant source of tracking error among the ETFs and the
underlying indexes. Wong and Cheong (2010) disclosed the performances of 15 ETFs worldwide
in bearish and bullish markets from 1999 to 2007. They validated that ETFs always generated
underperformance in a bearish market than in a bullish market.
There is an abundance of literature exploring the returns of ETFs using different
methodologies and data sets, with various conclusions being drawn. Therefore, forecasting and
modeling financial market volatility have been the topic of recent theoretical researches in
2 Data retrieved from www.ici.org, on November 30, 2013.
4. Proceeding - Kuala Lumpur International Business, Economics and Law Conference 4 (KLIBEL4)
Vol. 1. 31 May – 1 June 2014. Hotel Putra, Kuala Lumpur, Malaysia. ISBN 978-967-11350-3-7
academia as well as in financial markets. On the basis of theories of model building, financial
price forecasting models divided into two types. In the first type is models based on statistical
theories, such as Autoregressive Integrated Moving Average (ARMA), General Autoregressive
Conditional Heteroskedasticity (GARCH), Smooth Transition Autoregressive Model (STAR),
Markov Switching Model (MS) and Stochastic Volatility Model (SV). In the second type is
models based on artificial intelligence, such as the Artificial Neural Network (ANN) and the
Support vector Machine (SVM). The study of Kumah (2011) applied Markov-Switching (MS)
model to measure exchange market pressure (EMP) in the Kyrgyz Republic from 1996 to 2006. In
light of the recent findings reported by Zhu and Wei (2013) used autoregressive integrated moving
average (ARIMA) model and the Least Squares Support Vector Machine (LSSVM) to predicate
carbon prices under the EU Emissions Trading Scheme (EU ETS). Above past studies can know
many methods seek accurate trend forecasting.
Indeed, several studies have shown that forecasting models are subject to instabilities, leading
to imprecise and unreliable forecasts. Guo and Wohar (2006) that evidenced multiple structural
breaks in the volatility indexes were published by the Chicago Board Options Exchange. The
available data series for the VIX is from 1990 to 2003 and for the VXO3 is from 1986 to 2003.
The empirical study confirmed that the means of lowest market volatility during 1992-2007 is the
lowest volatility. Covarrubias et al. (2006) exercised multiple structural changes to recognize the
switches in the volatility of the interest rate shifts on the 10-year Treasury bond. Time points of
shifts in volatility and the endogenously determined by time series utilizing iterated cumulative
sums of squares (ICSS) algorithm proposed by Inclan and Tiao (1994) provided an important
conclusion of correct predicting model with structural breaks. In addition, Ewing and Malik
(2013) used gold and oil futures data to identify the volatility dynamics cover the period 1993:1 to
2010:1. They also employed ICSS approach to calculate volatility shifts. The results showed
statistically significant structural breaks in volatility.
In this context, Gadea et al. (2004) advocated the risk of neglecting structural breaks and
found that long memory phenomenon for identifying non-linear dependence in the conditional
mean and variance was significantly affected in the face of structural breaks. They not only
emphasize structural breaks, but also confirm long memory phenomenon. Moreover, Sadique and
Silvapulle (2001) explored the presence of long memory in the stock returns for seven countries.
The result expressed that equity market with long memory will generate nonrandom walk
occurrence, implying long memory in the time series is associated with the high autocorrelation
function.
There are numerous studies explaining the sources of long memory observed in different
market. Recently, Huskaj (2013) illustrated the present of long memory in the VIX futures returns,
and applied three models to evaluate the predicating power in the volatility process. The models
included the GARCH, Asymmetric Power ARCH (APARCH), Fractionally Integrated GARCH
(FIGARCH) and FIAPARCH models. This article showed that statistically significant results of
the best out-of-sample VaR (value at risk) forecasts are FIGARCH and FIAPARCH models. To
analyze the presence of structural breaks in financial time series, Fernandez (2005) combined
ICSS and GARCH models to examine four stock indices4 and interest rates series by Chilean
banks. The study provided that the importance of mixing model could offer significant results
which were better than testing for variance homogeneity. Further, Kang et al. (2009) explored
Japanese and Korean stock markets covering the 1986–2008 period to examine whether the
persistence of volatility in variance or not. They used ICSS-GARCH and ICSS-FIGARCH models
and corroborated incorporate sudden changes and volatility in variance models which can enhance
forecasting ability. The green ETFs did not exist in long memory process, but non-green ETFs
3 VXO was based on SP 100 Index (OEX) option prices volatility.
4 Four countries include Emerging Asia, Europe, Latin America, and North America.
5. Proceeding - Kuala Lumpur International Business, Economics and Law Conference 4 (KLIBEL4)
Vol. 1. 31 May – 1 June 2014. Hotel Putra, Kuala Lumpur, Malaysia. ISBN 978-967-11350-3-7
existed long memory process in volatility were provide by Chen and Diaz (2013). The
methodology of the study applied the ARFIMA and FIGARCH models.
3. Data and Methodology
The CBOE published the volatility Index (VIX) in March 2004. Later, some relative
instruments such as ETFVIX and individual equity VIX based on volatility were developed in the
financial market. This study investigates the return and volatility of VIX-ETFs. In the work
employs the multiple structure breaks model measured by ICSS to evaluate structural breaks and
applies ARFIMA-FIGARCH estimate long memory. Finally, this study performs the models to
evaluate the return and volatility dynamics of VIX-ETFs.
s j , 0,1, , , T J = K N where NT is the total number of variance changes in T
3.1. Data
The paper considers VIX-ETFs closing prices as shown in Table 1. The study utilizes daily ETF
price data from October 3, 2011 to December 31, 2013. The data were obtained from Yahoo
Finance, for five popular VIX-ETFs (i.e. ProShares VIX Mid-Term Futures ETF (VIXM),
ProShares VIX Short-Term Futures ETF (VIXY), PowerShares SP 500 Low Volatility Portfolio
(SPLV), ProShares Trust Ultra VIX Short Term Futures ETF (UVXY), and ProShares Short VIX
Short Term Futures ETF (SVXY)).
Table 1. The Sample Size and Period of VIX-ETFs
ETF Name Symbol Track delivery Period
ProShares VIX Mid-
Term Futures ETF
VIXM
SP 500 VIX Mid-Term
Futures Index
2011/01/03
ProShares VIX Short-
Term Futures ETF
VIXY
SP 500 VIX Short-Term
Futures Index
2011/01/03
PowerShares SP 500
Low Volatility Portfolio
SPLV
SP 500 Low Volatility
Index
2011/05/05
ProShares Trust Ultra
VIX Short Term Futures
ETF
UVXY
SP 500 VIX Short-Term
Futures Index
2011/10/03
ProShares Short VIX
Short Term Futures ETF
SVXY
SP 500 VIX Short-Term
Futures Index
2011/10/03
Source: Yahoo Finance-various dates up to December 31, 2013.
3.2. Structural break: The Iterated Cumulative Sums of Squares (ICSS)
The methodology used in this study to identify sudden shifts in the variance of a time series
is on the basis of the iterated cumulative sums of squares (ICSS) algorithm developed by Inclan
and Tiao (1994).
The analysis supposes that the time series shows a stationary variance over an initial period
until a sudden shift in variance occurs. The break in the variance specification is proposed by
Inclan and Tiao (1994). The variance is still stationary again during the time until the next abrupt
shift. The process is repeated over time, yielding a time series of observations with an unknown
number of changes in the variance.
Let t e
be a series with zero mean and with unconditional variance . 2
t s
The variance in each
interval is denoted by 2
observations. By letting k k K T NT K
1 2 1 are the change points.
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t k
, 1
k t k
k t C e where k=1,…,T. (6)
= k=1,…,T, D0=Dt=0, (7)
max surpasses the
s
s
=
k t T
NT NT
t
,
,
2
1 2
2
1
1
2
0
2
s
s
M
(5)
To estimate the number of changes in variance and the point in time of each variance shift. The
cumulative sum of the squared observations from the start of the series to the kth point in time is
expressed as:
,
2
=
1
=
k
t
The Dk statistic is defined as follows:
k
,
T
C
k −
C
D
k
T
where CT is the sum of the squared residuals from theentire sample period.
If there are no shifts in variance for the sample period, the Dk statistic waves around zero and
it can be drawing as a horizontal line against k. However, if there are abrupt variance changes in
the series, the statistic values fluctuate up or down near zero. Based on the distribution of Dk
calculated the critical values under the null hypothesis of homogeneous variance provide upper
and lower boundaries to distinguish a significant change in variance with a known level of
probability. In this context, the null hypothesis of constant variance is accepted if the maximum
absolute value of DK is smaller than the critical value. So, if ( ) k k T D
2
predetermined boundary, then the value of k is taken as an estimate of the change point. The
critical value at the 95th percentile is 1.36; therefore the boundaries can be set at ±1.36 in the Dk
draw.
In the context of multiple change points, the Dk operation lonely is not enough to recognize
the breakpoints. Therefore, Inclan and Tiao (1994) developed an algorithm that uses the Dk
operation to systematically seek for change points at different points of the series. The algorithm
functions by estimating the Dk operation for different time periods and those different periods are
determined by breakpoints, which are recognized by the Dk plot. Once the shift points are
recognized using the ICSS algorithm, the periods of shifts in volatility are tested with potential
factors.
3.3. ARFIMA-FIGARCH
Long memory generalizations of model short-memory time series models are suitable for the
ARFIMA and FIGARCH model. With the previous findings of Baillie et al. (1996) who suggested
the modeling of conditional variance of high frequency financial data associated with Fractionally
Integrated GARCH (FIGARCH) model.
3.3.1. ARFIMA
The ARFIMA ( p,d,q ) model is a common parametric method to examine the long memory
property in financial time series (Granger and Joyeux, 1980; and Hosking, 1981). The ARFIMA
( p,d,q ) model can be expressed as a generalization of the ARIMA model as follows:
, t t t e = zs z ~ N(0,1) t , (8)
( )(1 ) ( ) ( ) , t t y L L y μ L e x − − = Q (9)
where t eis independent and identically distributed (i.i.d) with variance, and L denotes the lag
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G −
1
1 = −xL − x −x L2 − x −x −x L3 −L (10)
d j L − L e = w + − b L n (11)
qj L º j L +j L +L +j L and ( ) p
pb L º b L + b L2 +L + b L
t t t n º e −s The{ } t n
operator. x ,μ , i y
and i q
are the parameters of the model. ( ) n
y L = −y L −y L − −y nL 2 L
1 2 1 and
( ) s
sQ L = +q L +q L2 +L+q L
1 2 1 are the Autoregressive (AR) and Moving Average (MA)
polynomials with standing in outside of unit roots, respectively. The fractional differencing
operator, ( )x 1 − L , is described by the binomial series formation:
( ) ( )
( ) ( )
k
k
L
k
k
L ¥
= G + G −
− =
0 1
1
x
x x
( ) (1 )(2 ) ,
6
1
1
2
where G(•)denotes the gamma function. Following Hosking (1981), when − 0.5 x 0.5, the t y
process is stationary and invertible. For such processes, the effect of shocks to t e
on t y decay at a
slow rate to zero. If x = 0, the process is stationary, the the effects of shocks to t e
on t y decay
geometrically. For x =1, the process follows a unit root process. If − 0.5 x 0.5, the process
presents negative dependence between far observations, so named anti-persistence.
3.3.2. FIGARCH
Engle (1982) proposed the Autoregressive Conditional Heteroscedasticity (ARCH) to describe
the variance of the residuals changes over time. And time series variable has a phenomenon with
volatility clustering. Bollerslev (1986) proposed the Generalize Autoregressive Conditional
Heteroscedasticity (GARCH model) and set conditional variance not only influenced by the
square of prior residual, but also the prior variance. In modeling conditional variance, GARCH is
more flexible than ARCH.
The Fractional Integrated Generalized Autoregressive Conditional Heteroskedasticity model
(FIGARCH) to capture the long memory in volatility return was proposed by Baillie et al. (1996).
The FIGARCH ( p,d,q ) can be expressed as follows:
( )(1 ) [1 ( )] , 2
t t
where ( ) , 2
1 2
q
1 2 and . 2 2
process can be expressed as the innovations for the conditional variance, and it has zero mean
sequentially uncorrelated. All the roots of j (L) and [1− b (L)]lie outside the unit root circle.
Where 0 d 1, and all the roots of f (L) and [1 − b (L)] lie outside the unit circle. Thus, the
characteristic of the FIGARCH model is that, 0 d 1, it is adequately flexible to allow for an
intermediate range of persistence. The FIGARCH model offers greater flexibility for modeling the
conditional variance, because it conforms with the covariance stationary GARCH model ( d = 0 )
and the nonstationary IGARCH model (d = 1).
4. Empirical Results
4.1. Summary Statistics
Table 2 shows the descriptive statistics properties of the returns from the five VIX-ETFs. Over
the sample period, the UVXY is the most volatile with the standard deviation at 7.42% followed
by the VIXY with 3.08%, while SPLV displays to be most stable with standard deviation being
0.35%. The analysis shows that they do not correspond with the assumption of normality. The
return series tend to have a fatter-tail distribution and a higher peak than a normal distribution
which was verified by the kurtosis statistics.
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Vol. 1. 31 May – 1 June 2014. Hotel Putra, Kuala Lumpur, Malaysia. ISBN 978-967-11350-3-7
Table 2. Descriptive Statistics of Variables for VIX-ETFs
RVIXM RVIXY RSPLV RUVXY RSVXY
Mean -0.08187 -0.05899 0.018913 -0.05531 0.089851
Std. Dev. 0.864121 3.082134 0.346635 7.421735 2.139912
Skewness 0.495906 15.3332 -0.40921 9.659103 -5.07858
Kurtosis 5.611043 344.7322 7.820725 121.6383 67.79446
Jarque-Bera 244.7637*** 3693506*** 666.4692*** 339533.8*** 101085***
Obs. 753 753 669 564 564
Note: *, ** and *** are significance at 10, 5 and 1% levels, respectively; p-values are in parentheses.
Before testing for the long memory property, all series are checked by applying Augmented
Dickey Fuller (ADF) test. The empirical results shows in the Table3, the stationary test reject the
null of a unit root in the logarithm of price series at the 1% significance level. The results imply
VIX-ETFs are stationary processes I (0). Additionally, the study employs that the minimum value
of AIC (Akaike information Criterion) is used to identify the optimal model of ARMA. After
selecting the optimal ARMA, the work applies the Breush-Godfrey LM test to investigate whether
the residuals have series correlation or not. The work also examines ARCH effect, showing that all
series do not have the auto-correlation, but VIXM and SPLV exist in ARCH effect. So VIXM and
SPLV must further estimate the GARCH model.
Table 3. Summary Statistics of Unit Root, LM, and ARMA-LM tests for VIX-ETFs
VIX-ETF ADF ARMA AIC LM ARCH-LM GARCH AIC ARCH-LM
VIXM -27.8541*** (1,2) 2.5401 0.6103 4.756047*** (1,3) 2.4547 0.00541
VIXY -26.6363*** (1,2) 5.0939 0.4103 0.0004 - - -
SPLV -28.2862*** (2,2) 0.6786 1.1178 14.38395*** (3,3) 0.4445 0.0008
UVXY -22.6005*** (3,3) 6.8310 26.8075 0.0503 - - -
SVXY -24.6038*** (3,3) 5.7891 0.5554 0.0001 - - -
Note: *, ** and *** are significance at 10, 5 and 1% levels, respectively.
4.2 Sudden Change in Volatility
The return series of a shift in volatility as detected by the ICSS algorithm are given in Table 4.
Another, the return graphs presented in Figure 1, several volatility periods can clearly be observed.
There are two change points were detected in among VIXM, VIXY, UVXY and one shift also was
detected in SPLV and UVXY. Referring to Table 4, the time points of sudden shift in volatility are
correlated to a perceived degree with domestic and foreign economic events. As for instance, there
was a significant increase in volatility detected by ICSS algorithm at the end of 2011 in the SPLV,
UVXY, and SVXY. This could be due to the fact that the Eurozone’s debt crisis deeply and
extensively spread to other Europe countries. Another, Tohoku earthquake and tsunami and
Standard Poor’s downgrades the US credit rating from AAA to AA+ also were a significant
impact shift in 2011 for VIXM and VIXY. Some events that occurred around the time of these
change points in volatility are presented in the last column of Table 4. For instance, the Federal
Reserve System decided to extend Operation Twist in order to provide and have a “modest”
impact on helping the economy achieve a better rate of growth at the end of Jun in 2012. There
was shocking news that United States federal government shutdown has impacted on financial
market and produced a sudden change for VIXY and UVXY.
Table 4. Structural Breaks in Volatility
Variables Change points Interval Events
VIXM
2011.03.21 2011/01/04-2011/06/13
Tohoku earthquake and
tsunami
2012.07.02 2011/06/14-2013/01/31 The Federal Reserve System
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extends Operation Twist
VIXY
2011.08.05 2011/01/04-2013/06/07
Standard Poor’s
downgrades the US credit
rating from AAA to AA+
2013.10.17 2013/06/10-2013/12/31
United States federal
government shutdown of 2013
SPLV
- 2011/08/09-2013/03/11 -
2011.12.21 2013/06/20-2013/07/02 The Eurozone’s debt crisis
UVXY
2011.11.10 2011/10/04-2012/03/07 The Eurozone’s debt crisis
- 2012/03/08-2012/09/06 -
- 2012/09/07-2013/06/07 -
2013/10/17 2013/06/10-2013/12/31
United States federal
government shutdown of 2013
SVXY
2011.11.10 2011/10/04-2012/10/04 The Eurozone’s debt crisis
2013.04.23 2012/10/05-2013/12/31 Boston Marathon bombings
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Figure 1. The Returns for VIX-ETFs
4.3 ARFIMA and ARFIMA-FIGARCH models
The next step explains these sudden changes in variances via dummy variables in the ARFIMA
and ARFIMA-FIGARCH models. The results of long memory are summarized in Table 5. Firstly,
the results of the ARFIMA model without sudden changes in panel A illustrated that all series do
not have long memory effect. It clearly indicates that there is no evidence of long memory in
among VIX-ETFs. It implies the return series shows weak-form market efficiency. Furthermore,
the research investigates if there is dual long-term memory in mean return and conditional
variance exists for VIX-ETFs by applying ARFIMA-FIGARCH model.
-6
-4
-2
0
2
4
6
1/04/2011
2/10/2011
3/21/2011
4/26/2011
6/02/2011
7/12/2011
8/16/2011
9/22/2011
10/27/2011
12/02/2011
1/12/2012
2/22/2012
3/29/2012
5/07/2012
6/12/2012
7/19/2012
8/24/2012
10/02/2012
11/08/2012
12/19/2012
1/29/2013
3/08/2013
4/16/2013
5/22/2013
6/27/2013
8/05/2013
9/11/2013
10/17/2013
11/21/2013
12/30/2013
RVIXM
-20
0
20
40
60
80
1/04/2011
2/10/2011
3/21/2011
4/26/2011
6/02/2011
7/12/2011
8/16/2011
9/22/2011
10/27/2011
12/02/2011
1/12/2012
2/22/2012
3/29/2012
5/07/2012
6/12/2012
7/19/2012
8/24/2012
10/02/2012
11/08/2012
12/19/2012
1/29/2013
3/08/2013
4/16/2013
5/22/2013
6/27/2013
8/05/2013
9/11/2013
10/17/2013
11/21/2013
12/30/2013
RVIXY
-3
-2
-1
0
1
2
1/04/2011
2/10/2011
3/21/2011
4/26/2011
6/02/2011
7/12/2011
8/16/2011
9/22/2011
10/27/2011
12/02/2011
1/12/2012
2/22/2012
3/29/2012
5/07/2012
6/12/2012
7/19/2012
8/24/2012
10/02/2012
11/08/2012
12/19/2012
1/29/2013
3/08/2013
4/16/2013
5/22/2013
6/27/2013
8/05/2013
9/11/2013
10/17/2013
11/21/2013
12/30/2013
RSPLV
-20
0
20
40
60
80
100
1/04/2011
2/10/2011
3/21/2011
4/26/2011
6/02/2011
7/12/2011
8/16/2011
9/22/2011
10/27/2011
12/02/2011
1/12/2012
2/22/2012
3/29/2012
5/07/2012
6/12/2012
7/19/2012
8/24/2012
10/02/2012
11/08/2012
12/19/2012
1/29/2013
3/08/2013
4/16/2013
5/22/2013
6/27/2013
8/05/2013
9/11/2013
10/17/2013
11/21/2013
12/30/2013
RUVXY
-30
-20
-10
0
10
1/04/2011
2/10/2011
3/21/2011
4/26/2011
6/02/2011
7/12/2011
8/16/2011
9/22/2011
10/27/2011
12/02/2011
1/12/2012
2/22/2012
3/29/2012
5/07/2012
6/12/2012
7/19/2012
8/24/2012
10/02/2012
11/08/2012
12/19/2012
1/29/2013
3/08/2013
4/16/2013
5/22/2013
6/27/2013
8/05/2013
9/11/2013
10/17/2013
11/21/2013
12/30/2013
RSVXY
11. Proceeding - Kuala Lumpur International Business, Economics and Law Conference 4 (KLIBEL4)
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Table 5. ARFIMA and ARFIMA-FIGARCH without and with Dummy Variables for Sudden Changes in Variance
VIX-ETF
ARFIMA
ARCH-LM
ARFIMA-FIGARCH
model d-coeff. AIC d-coeff. model d-coeff. AIC
Panel A: Without Dummy Variables for Sudden Changes in Variance
VIXM (1,2)
-0.0319
[0.474]
2.5440
4.5178
[0.0339]*
-0.0122
[0.8190]
(2,3)
0.2096
[0.1589]
2.4619
VIXY (2,2)
0.0061
[0.845]
5.0976
0.0005
[0.9830]
- - - -
SPLV (3,3)
-0.0569
[0.130]
0.6892
14.902
[0.0001]**
-0.0805
[0.0302]*
(2,3)
0.5477
[0.0000]***
0.4291
UVXY (1,0)
-0.034
[0.394]
6.8473 0.0127 - - - -
SVXY (1,0)
-0.0703
[0.248]
4.3673
3.0645e-005
[0.9956]
- - - -
Panel B: With Dummy Variables for Sudden Changes in Variance
VIXM (1,2)
-0.0371
[0.416]
2.5491
4.3442
[0.0375]*
-0.0206
[0.6628]
(2,3)
0.1964
[0.0093]**
2.4662
VIXY (2,2)
0.0060
[0.848]
5.1032
0.0005
[0.9827]
- - - -
SPLV (3,3)
-0.0463
[0.121]
0.7272
16.444
[0.0001]**
-0.1153
[0.0000]***
(2,3)
0.5111
[0.0000]***
0.4430
UVXY (2,1)
-0.9933
[0.000]***
6.8653
0.0270
[0.8695]
- - - -
SVXY (1,0)
-0.0749
[0.231]
4.3760
2.5398e-005
[0.9960]
- - - -
Note: *, ** and *** are significance at 10, 5 and 1% levels, respectively; p-values are in parentheses.
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The finding reveals that VIXM does not exhibit long memory or persistence, as d parameter is
statistically insignificant; but SPLV shows long memory or persistence as d parameter is
statistically significant for mean returns while it does for conditional variance.
From an extensive analysis of the ARFIMA model with sudden changes in panel B; the result of
UVXY present that the process is not mean-reverting in the sense that any shock to the process
will displace it from its starting point. We also join the structure breaks in mean return and
conditional variance by ARFIMA-FIGARCH model. The results revealed that VIXM and SPLV
existed long memory, as d parameter is statistically significant. An important implication of this
finding is that considering structure breaks can provide the return series existing in inefficient
market, so one can use past price to predicate their future price for VIXM and SPLV.
This article showed statistically significant results of dual long memory in VIXM and SPLV.
VIXM tracks SP 500 VIX mid-term futures index and SPLV tracks SP 500 low volatility
index but VIXY, UVXY, and SVXY track SP 500 VIX short-term Futures Index. The finding
implies that VIX short-term volatility trend cannot predicate in opposition different period and
pattern. In other words, VIX measure the volatility of the Standard and Poor’s 500 (SP 500) so it
caused VIXpossess weak-form efficiency market in short-term VIX-ETFs.
5. Conclusion
This study investigated sudden shifts of volatility and examined long memory for VIX-ETFs.
The results of ARFIMA model displayed that there was no long memory property in the VIX-ETF
returns, implying the weak-form efficiency market. Next, this study also tested the long memory
property in conditional variance series of VIX-ETFs. The estimation results indicated that
ARFIMAR-FIGARCH with structure breaks model have better exposes long memory property in
conditional variance of return series.
Roughly speaking, the work failed to reject weak-form market efficiency, because the presence
of long memory in the volatility appears, and VIXM and SPLV presented reverting to its mean.
The returns of VIXM and SPLV can be predicted due to the facts that dependence between distant
observations was evident. Thus, fund managers and investors may apply the empirical results by
possessing a position on VIXM and SPLV.
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