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A Multivariate GARCH Model of International Transmissions of Stock Returns and Volatility: The Case of the United States and Canada

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Abstract

This study examines the short-run dynamics of returns and volatility for stocks traded on the New York and Toronto stock exchanges. The main finding is that inferences about the magnitude and persistence of return innovations that originate in either market and that transmit to the other market depend importantly on how the cross-market dynamics in volatility are modeled. Also, much weaker cross-market dynamics in returns and volatility prevail during later subperiods and especially for Canadian stocks with dually listed shares in New York. Implications for international asset pricing, hedging strategies, and regulatory policy are discussed.

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... Karolyi et al. [20] indicated that the yen/dollar foreign exchange rates, the treasury bill returns, and the industry impacts have no measurable effect on the US and Japanese return correlations. Moreover, Antoniou et al. [21,22] found that futures' trading has a significant impact on co-movements across the markets. ...
... The study is an extension of the approach suggested by Karolyi et al. [20], Longin and Solnik [31] to examine the future contracts (such as foreign exchange rates, treasury bond, and index of stock prices). 9 The Primary Origin of the Financial Crisis DOI: http://dx.doi.org/10.5772/intechopen.86173 ...
... The study is an extension of the approach suggested by Karolyi [20], Longin, and Solnik [31] to examine the future contracts (such as foreign exchange rates, 11 The Primary Origin of the Financial Crisis DOI: http://dx.doi.org /10.5772/intechopen.86173 ...
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This paper examines the relationship between the stock return volatility, outside directors, independent directors, and variable control using simultaneous-equation panel data models for a panel of 89 France-listed companies on the SBF 120 over the period of 2006–2012. Our results showed that the outside directors (FD) and audit size increase the stock return volatility. Furthermore, the results indicate that the independent directors and ROA have a negative effect on the stock return volatility; this result indicates that these variables contribute to decrease and stabilize the stock return volatility. This study employs a variety of econometric models, including feedback, to test the robustness of our empirical results. Also, we examine the relationship between the corporate governance and the stock returns volatility, exchange rate, and treasury bill using GARCH-BEKK model for a panel of 99 French firms over the period of 2006–2013.
... Multivariate GARCH models are an extension of univariate GARCH models. It allows the conditional covariance matrix of the dependent variables to follow a flexible dynamic structure and allow the conditional mean to follow a vector autoregressive structure, [20] . MGARCH implements five commonly used parameterizations: the diagonal vector MGARCH (DVECH) model, the constant conditional correlation (CCC) MGARCH model, the dynamic conditional correlation (DCC) MGARCH model, BEKK-MGARCH and the timevarying conditional correlation (VCC) MGARCH model. ...
... The test statistic may be expressed as a function of the covariances between the residuals of the fitted model [8,17] . A multivariate version is given by (20) Where T is the number of observations, ...
Article
The price at which two distinct countries' currencies are traded varies in terms of volatility of exchange rate. Because exchange rate volatility is associated with risk and uncertainty, it is a major source of concern for macroeconomic policymakers. The main objective of this study was comparison of MGARCH models using volatility of daily Euro/Ethiopian birr and USD/ETB in Ethiopia. Secondary data were obtained from nation bank of Ethiopia and the sample data period runs from March 1, 2016 to February 24, 2020. The main variables considered under this study were USD/ETB and Euro/ETB daily exchange rates. There are 1,287 time series observations included and exclude Saturday and Sunday data from this study. Four types of multivariate GARCH models estimated in this study; namely: Constant Conditional Correlation (CCC), Dynamic Conditional Covariance (DCC), Dvech and Baba, Engle, Kraft and Kroner (BEKK) MGARCH models. The stationarity of sample data checked by Augmented Dickey Fuller (ADF) and Phillips-Perron (PP) test and the series were stationary after logarithm of first differenced. From estimated evidence that CCC-MGARCH (1, 2), DCC-MGARCH (1, 2), Dvech-MGARCH (1, 1) and BEKK-MGARCH (1, 1) models with Gaussian, student’s-t and skew student’s t-distribution are the best estimation models in terms of the volatility behavior of the series. Amongst these models, DCC-MGARCH (1, 2) with minimum value of information criteria and log-likelihood function was found to perform best in term of fit the volatility of Ethiopian Birr/USD and ETB/EUR. Hence, we recommend that future research works need to build on the current work and extend it a bit further currencies and models. For example, it would be interesting to consider fitting other MGARCH models of the major with other currencies the country uses in its international transactions.
... Multivariate GARCH models are an extension of univariate GARCH models. It allows the conditional covariance matrix of the dependent variables to follow a flexible dynamic structure and allow the conditional mean to follow a vector autoregressive structure, [20] . MGARCH implements five commonly used parameterizations: the diagonal vector MGARCH (DVECH) model, the constant conditional correlation (CCC) MGARCH model, the dynamic conditional correlation (DCC) MGARCH model, BEKK-MGARCH and the timevarying conditional correlation (VCC) MGARCH model. ...
... The test statistic may be expressed as a function of the covariances between the residuals of the fitted model [8,17] . A multivariate version is given by (20) Where T is the number of observations, ...
Article
The price at which two distinct countries' currencies are traded varies in terms of volatility of exchange rate. Because exchange rate volatility is associated with risk and uncertainty, it is a major source of concern for macroeconomic policymakers. The main objective of this study was comparison of MGARCH models using volatility of daily Euro/Ethiopian birr and USD/ETB in Ethiopia. Secondary data were obtained from nation bank of Ethiopia and the sample data period runs from March 1, 2016 to February 24, 2020. The main variables considered under this study were USD/ETB and Euro/ETB daily exchange rates. There are 1,287 time series observations included and exclude Saturday and Sunday data from this study. Four types of multivariate GARCH models estimated in this study; namely: Constant Conditional Correlation (CCC), Dynamic Conditional Covariance (DCC), Dvech and Baba, Engle, Kraft and Kroner (BEKK) MGARCH models. The stationarity of sample data checked by Augmented Dickey Fuller (ADF) and Phillips-Perron (PP) test and the series were stationary after logarithm of first differenced. From estimated evidence that CCC-MGARCH (1, 2), DCC-MGARCH (1, 2), Dvech-MGARCH (1, 1) and BEKK-MGARCH (1, 1) models with Gaussian, student’s-t and skew student’s t-distribution are the best estimation models in terms of the volatility behavior of the series. Amongst these models, DCC-MGARCH (1, 2) with minimum value of information criteria and log-likelihood function was found to perform best in term of fit the volatility of Ethiopian Birr/USD and ETB/EUR. Hence, we recommend that future research works need to build on the current work and extend it a bit further currencies and models. For example, it would be interesting to consider fitting other MGARCH models of the major with other currencies the country uses in its international transactions.
... The globalization of financial markets created a tendency for volatilities to move across financial markets without any regard for boundaries, as shown by the studies of Hafner and Herwartz (2006) and Bubak, Kocenda and Ikes (2011) using exchange rates, and Karolyi (1995) and Zhu (2009) in stock markets. Studies also have shown that financial asset returns volatility, correlations and covariances changed from time to time with persistent dynamics as concluded by Fleming, Kirby and Ostdiek (1998). ...
Article
This paper utilizes three Multivariate General Autoregressive Conditional Heteroscedasticity (MGARCH) models to determine variance persistence in the Greater China region from 2009 to 2014. The first approach applies the Baba, Engle, Kraft and Kroner (BEKK) model and shows that the Shanghai Stock Exchange Composite Index (SSEI), Taiwan Capitalization Weighted Stock Index (TAEIX) and the Hang Seng Stock Index (HSEI) stock returns are all functions of their lagged covariances and lagged cross-product innovations. The second MGARCH approach applies two methodologies, namely, dynamic conditional correlation (DCC), and constant conditional correlation (CCC) estimations. The DCC model concludes both short- and long-run persistencies between Taiwan’s TAIEX and Hong Kong’s HSEI. Alternatively, the CCC model confirms the initial findings of the BEKK model, and adds that the relationships among these three strong economies are stable in the long-run. The log-likelihood values determine that the DCC model is better in judging volatility dynamics in the Greater China region, because of economic clauses brought by the Closer Economic Partnership Arrangement (CEPA), the Economic Co-operation Framework Agreement (ECFA) and the Hong Kong - Taiwan Business Cooperation Committee (BCC).
... Since the advent of the multivariate approach, the MGARCH model has become the most popular tool to specify time-varying variances and 1 The International Energy Agency (IAE) predicts that India will burn through 4.1 mb/d in the second quarter of this year, edging out Japan's 3.8 mb/d (http://oilprice.com/Energy/Crude-Oil/India-Becomes-3rd-Largest-Oil-Importer.html). covariances among different stock market indices (Booth et al., 1997;Cha and Jithendranathan, 2009;Karolyi, 1995;Karolyi and Stulz, 1996;Lin et al., 1994), oil prices (Chang et al., 2010a;Cifarelli and Paladino, 2010;Malik and Hammoudeh, 2007;Sadorsky, 2006) and natural gas prices (Ewing et al., 2002). There are several MGARCH models discussed in econometric literature including the VECH models, the diagonal VECH models, and the BEKK, diagonal, and CCC models. ...
Article
This study investigates the extent of time-varying volatility and correlations between crude oil, natural gas, and stock prices in India using various multivariate generalized autoregressive conditional heteroskedasticity (MGARCH) models with and without asymmetry. Our empirical results reveal that there is no long-run coin-tegration between crude oil, natural gas, and stock prices in India. We find that the VARMA-DCC-GARCH model is more efficient compared to the CCC model with asymmetry in estimating time-varying correlations. We also analyze optimal portfolio weights and hedging ratios through pair trading between stocks and energy commodity futures. Our results have several implications for portfolio investors dealing with the Indian stock market and energy commodity futures for forecasting potential market risk exposure and determining the existence of portfolio diversification benefits.
... To explore a possible relationship between market returns and volatilities, a model to simultaneously estimate returns and volatilities is employed; specifically, we use vector autoregressive (VAR) models to understand the relationship between asset returns and employ multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) to estimate correlations between asset return volatilities (risks). Earlier studies such as Karolyi (1995) have used VAR and MGARCH models to separately estimate the international transmission of stock returns and risks; however, this approach fails to distinguish whether a correlation between these two aspects is a result of returns or risks. A VAR-MGARCH model was recently established; this model quantifies correlations among markets more comprehensively because returns and risks are concurrently endogenously determined. ...
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This study investigates the housing market in Taiwan, an emerging market with relatively severe housing price inflation. Using data from the first quarter of 1991 to the second quarter of 2017 for four cities in Taiwan, this study compares the risk transmission and sources of their housing prices. The results reveal that Taipei−Taiwan’s main financial hub−has the highest house prices among the four cities but maintains the lowest risk. Thus, in terms of price volatility risk, Taipei has the safest housing market among the studied cities. Other studies have discussed the potential housing price bubbles in regions with high housing prices but have been unable to explain the continual overheating of the housing markets. The findings of this study reveal that despite having the highest housing prices and the greatest potential bubble, the Taipei housing market has the lowest fluctuation risk, making it the safest market in terms of housing investment. The results of this study imply that Taiwan’s economic development is excessively concentrated in Taipei, causing people to bear low returns and high risk when purchasing real estate in other areas, in turn increasing the continual imbalance between regional housing markets.
... For stock return volatility, we follow Schwert (1989) and exploit the high-frequency (daily) data to construct our measure Stock Vol as the monthly standard deviation calculated from daily returns. For lower-frequency (monthly) data, we follow an extensive literature and use GARCH models to construct estimates of the one-step ahead conditional volatility (e.g., Chan, Chan, and Karolyi 1991;Karolyi 1995). We choose the most standard specification, GARCH(1,1), and estimate the following model for each variable x t : ...
Article
Stock return volatility during the Great Depression has been labeled a “volatility puzzle” because the standard deviation of stock returns was 2 to 3 times higher than any other period in American history. We investigate this puzzle using a new series of building permits and leverage. Our results suggest that volatility in building permit growth and financial leverage largely explain the high level of stock volatility during the Great Depression. Markets factored in the possibility of a forthcoming economic disaster. Received September 30, 2017; editorial decision August 27, 2018 by Editor Philip E. Strahan. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online
... Interlinkages among international stock markets are extensively researched in securities markets. Most of the studies have found that developed countries stock markets like United States, Japan, and significant European markets volatility spillover to emerging markets (Hamao et al. (1990), Theodossiou and Lee (1993), Karolyi (1995), Bekaert and Harvey (1997), Theodossiou et al. (1997), Liu and Pan (1997), Baele (2005), Ng (2002), Christiansen (2007), Worthington and Higgs (2004)). Bekaert and Harvey (2000) and Carrieri et al. (2007)) find significant movements between developed and developing markets. ...
Article
The present study examines the interaction of regional stock indices with developed countries' stock indices on stock markets of the Brazil, Russia, India, China, and South Africa (BRICS) countries. A total of 16 stock indices have been considered in this study. All daily data have been collected from August 2, 2002, to December 28, 2017, in terms of USD. The study period is subdivided into pre, during, and post‐global financial crisis periods. After ensuring the stationarity of the return series, the study employs Diebold and Yilmaz (2012) volatility spillover index to find the country having the net transmitter and net receiver of volatility. The study finds that the net volatility spillover has doubled during the crisis period, and it has come down to half in the post‐crisis period. The study depicts that in all the periods under study, the net volatility receivers are Brazil, Hong Kong, Germany, and Japan, whereas net volatility transmitters are South Africa, London, and the United States. The study also finds that China, Australia, Russia, and India are net volatility transmitters as well as net volatility receivers, depending on the crisis period. The result of this study may help the foreign portfolio investors to diversify their portfolio across BRICS countries.
... The author uses a basic aggregate shock model and an extended aggregate shock model using macroeconomic factors to model equity returns in country markets. Existing work by several authors like Hamao, Masulis, and Ng (1990), Karolyi (1995), and Ng (2000) indicate that there are ARCH in mean and volatility effects in equity markets. Some have attributed the phenomenon of volatility spillover to the integration of world capital markets. ...
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Editorial Financial instability: Contagion effects, risk premiums, and returns in equity and currency markets This special issue of the journal deals with international financial crises. 1 The papers are all related in the sense that they address issues surrounding instability in equity, currency, and credit markets in a range of countries. The papers explore the impact of financial instability on returns in equity markets and currency markets. Instability in financial markets triggers changes in required risk premiums as investors need to be compensated for increased risk taking. International financial markets have witnessed a series of financial and currency market crises over the last 10 years. These periods of instability have not been restricted to particular countries or to particular blocks of countries but have been widespread in their impact. They have been set in motion, mainly by events in developing countries, and the empirical papers explore the causes of international financial market instability with data, mainly from emerging market countries. This period was marked by developing countries having excessively high debt burdens and increased market liberalization with respect to cross-border capital flows. Crises were accompanied with or triggered by volatile capital flows and currency and stock market declines. The authors in this volume investigate (i) the reasons for the precipitation of these crises, (ii) measures for detecting a potential crisis, (iii) why crises spread across countries-the contagion effect, and (iv) how contagion is measured and its impact on risk premiums in credit, equity, and foreign exchange markets among other issues. The empirical analyses are conducted on financial instruments that include ADR's, stock market equity indexes and measures of market liberalization. The studies deal with
... These three EMH operations describe traditional market trade data representations. Different types of statistical related machine learning approaches are introduced traditionally to explore the efficiency of forecasting financial values related to stock market, all these techniques worked based on a linear process with statistical models [9], statistical data worked based on background analysis of stock trade data using auto-regressive integrated moving average model (ARIMA) [20] and with autoregressive conditional heteroscedasticity (ARCH), and also use generalized autoregressive conditional heteroscedasticity (GARCH) models, which are used to identify the financial market [10][11][12], all these approaches worked with statistical learning procedures but have some limitations, i.e., they have large trade related historical stock data [13]. Traditionally some of the neural networks are used to describe different metrics like time, recurrent delay in stock data, and also use some probabilistic approaches to exploit different training related methods of conjugate multi-stream extended delay of neural network analysis. ...
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In recent information technology relates to advanced computing, a high amount of information accumulated constantly. Mainly in the field of finance related computing technologies because all these computing technologies generate real time, tremendous data which consists different transactional records. Because of randomness and complexity in stock market related computing systems the stock price prediction is a hot concept and challenging the task. As information of web content improves in stock markets, researchers and investors usually extract different indicator factors, i.e., sentiments and events from prediction related stock market real time financial data. Because of the present scenario in financial and unknown factors in the stock market arena, prediction of stock price is a challenging task although traditional authors worked on neural networks to improve the prediction of stock prices in different financial areas. To improve the index based composite stock market movement's prediction in multi instance quantitative data, in this paper, propose a Novel Greedy Heuristic Optimized Multi-instance Quantitative (NGHOMQ) approach to explore required data from factors and discarding their parameter relations. It can be used to combine sentiments and events and evaluate quantitative information in the comprehensive manner, use novel heuristic calculation to represent successive stock price related events. To prevent stock price prediction according to optimized statistical performance in heuristic modes with the multi instance use Pareto optimization. In addition to that our proposed approach is able to identify input of data to making predictions in stock market price in financial computing technologies. Experimental results of Indian stock market data describes the effectiveness of NGHOMQ compared to traditional neural networks related frameworks/approaches.
... Furthermore, some of these stock markets are large compared to other stock markets in GCC countries 9 . On the other hand, the others depend on financial development 10 , 1 Percival Hurditt (2006). 2 King and Wadhwani (1990), G. Andrew Karolyi (1995), and Lin, Engle, and Ito (1994). 3 Some studies try to examine time zone differences among stock markets and analyze the effect of this difference. ...
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This study examines return volatility and the mechanism of transmission among GCC stock markets. In all cases, there is a significant interaction between the Saudi and Kuwait stock markets in their second moments. The Saudi stock market transmits its returns volatility to the Bahrain and Dubai stock markets. Since these stock markets are functioning in countries that follow well-developed financial system. Investors in these countries are assumed to be aware about the markets’ news with clarity and they implement it through asset prices. Only the Dubai stock market has clear direction of the volatility spillover, which is indirectly affected by Saudi stock market news, variance, and by direct variance volatility spillover.
... The relationship between exchange rates and stock markets has been explored in numerous studies (Aggarwal, 1981;Ajayi et al., 1999;Bahmani-Oskooee & Sohrabian, 1992;Bahmani-Oskooee & Saha, 2017;Bartov & Bodnar, 1994;Chiang & Yang, 2003: Donnelly & Sheehy, 1996Hamao et al., 1990;Jorion, 1990;Griffin & Stulz, 2001;Karolyi, 1995;King & Wadhwani, 1990;Lin, 2011;Lin et al., 1994;Ramasamy & Yeung, 2002;Schwert, 1990;Theodosiou & Lee, 1993). The market efficiency hypothesis has been challenged by researchers (Chuang & Lee, 2006;Daniel et al., 1998) who claim that overreactions, herd behaviors, positive feedback, investors' sentiments, and other factors oppose the hypothesis (Antoniou, Koutmos, & Pericli, 2005;Baker & Wurgler, 2006;Chiang & Zheng, 2010;Debondt & Thaler, 1985, 1987Kurov, 2008;Liao, Huang, & Wu, 2011;Nofsinger & Sias, 1999;Scharfstein & Stein, 1990;Schmeling, 2009). ...
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Journal: Financial Innovation (SSCI) We observe that the sharp movement in exchange rates including USDX, GBP/USD, and USD/CNY might result in stock market fluctuation due to investors’ sentiments aroused. To our knowledge, we argue that the subsequent performance of trading stocks right after the sharp movement in exchange rates seems seldom explored in the relevant studies, which may contribute to the existing literature. By employing the constituent stocks of DJ 30, FTSE 100, and SSE 50 as our targets due to these markets regarded as representative stock markets in the world, we then reveal that the share prices are more volatile after diverse sharp movements in Chinese Yuan, even though Chinese Yuan is less volatile due to Chinese Yuan likely managed by the authority; whereas, share prices would rise no matter what sharp depreciation or sharp appreciation occurs in US Dollar and British Pound rather impressive for investors.
... In contrast to the studies above, which focus on linkages in emerging markets in Asia, Europe and Latin America, Karolyi (1995) uses a bivariate GARCH model to test the transmission of stock returns and volatility between two neighboring developed markets -Canada and the US. He finds far weaker returns and volatility spillovers in later subperiods, especially for those Canadian stocks that are listed dually on the New York Stock Exchange. ...
Article
This article examines the dynamic linkages between Pakistan’s emerging stock market and (i) the US market and (ii) the regional markets of India and Japan. Using data for the daily returns and volatility spillovers of three market pairs (Pakistan-US, Pakistan-Japan and Pakistan-India), the study estimates a series of bivariate asymmetric VARMA(1,1)-GARCH(1,1) models. It also fits multivariate asymmetric VARMA(1,1)-GARCH(1,1) models for two groups of markets: Pakistan-India-US and Pakistan-India-Japan. Based on the mean spillovers, the results suggest that the global and regional equity markets (Granger) cause the Pakistani market. There are unidirectional volatility spillovers to Pakistan from the US and Japan, while India is the only regional market with a significant cross-asymmetric effect on Pakistan. In the multivariate case, the regional and global markets have significant joint mean and variance spillovers and asymmetric effects on the Pakistani market. This indicates a weak degree of integration between the Pakistani market and the global and regional markets, implying that local risk factors – either firm-specific or country-specific – explain the expected returns on investment in the Pakistani stock market.
... GMT) getirileri ile Londra 14-17 ve 15-17 saatleri arası getirileri baz alındığında ise Londra piyasasının New York piyasası açılış zamanı haberlerine aşırı tepki verdiği bulgularına erişmiş, 1987 piyasa krizi periyodunun ise yayılım üzerine bir etkisinin olmadığını belirtmişlerdir. Karolyi (1995) ABD ve Kanada piyasaları üzerine yaptığı çalışmada, tek değişkenli GARCH, M-GARCH CC ve M-GARCH BEKK modelleri ile VAR modeli ve etki-tepki analizlerini uygulamış, her iki piyasa için de getiri inovasyonlarının devamlılığı (persistence) ve büyüklüğü (magnitude) ile bunun diğer piyasalara yayılımının volatilite çapraz piyasa dinamiğinin nasıl modellendiği ile ilişkili olduğu, Amerika ve Kanada piyasaları arasındaki getiri ve volatilite yayılımının zamanla değişim gösterdiği, 1981-1989 yılları arası incelemelerine göre 80'lerin sonlarında ABD bazlı şokların Kanada piyasası üzerindeki etkisinin azaldığı, ayrıca ABD piyasası bazlı şokların büyüklüğü ve kalıcılığının Kanada bazlı tekli listelenen paylar ile ikili listelenen 1 paylar arasında farklılık gösterdiği ve ikili listelenen payların daha az bir şoka maruz kaldığı, diğer taraftan ABD piyasası bazlı fiyat hareketlerinin Kanada piyasası volatilitesi üzerindeki etkisinin önceki çalışmaların bulgularına göre daha zayıf olduğunu belirtmişlerdir. ...
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Bu çalışmada, Türkiye ve ABD pay piyasaları arasındaki getiri ve volatilite yayılımının araştırılması amaçlanmıştır. Bu bağlamda, BIST 30 ve S&P 500 endeksleri baz alınarak, 2010-2012 dönemi için günlük kapanıştan-kapanışa veriler kullanılmış ve Johansen eşbütünleşme testi ve VAR-GARCH(1,1)-BEKK modeli uygulanmıştır. Buna göre ABD ve Türkiye pay piyasaları arasında uzun dönem bir ilişki olmadığı ve ABD pay piyasalarından Türkiye pay piyasaları üzerine hem getiri hem de volatilite anlamında tek yönlü bir yayılımın olduğu bulgularına erişilmiştir. Dolayısıyla, ABD pay piyasaları kaynaklı bilginin Türkiye pay piyasası üzerinde önemli bir etki oluşturduğu sonucuna varılmıştır.
... incelemek yerine beraber değerlendirildiğinde farklı ampirik sonuçlara ulaşılabilmektedir (Bauwens ve Laurent, 2005). Koşullu korelasyon yöntemleri sayesinde finansal piyasaların ortak oynaklık göstergeleri hakkında bilgi edinilebilmektedir (Karolyi, 1995;Kearney ve Patton, 2000 (Yavuz, 2015:37). Jarque-Bera normallik testinin istatistiki anlamlılığının yüksek olduğu, bu nedenle serilerin normal dağılmadığı ifade edilebilir. ...
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The development of money changes with technology. The shift of monetary paradigm led by Bitcoin, which is one of the crypto currencies appeared on the market as a new form of money, is accelerated by the adaptation of both institutions and individuals. It has been considered that the term Crypto Monetization, which is used for the first time in the literature with this study in order to explain the interest in crypto currencies, will be used together with dollarization to express the escape from local currencies especially in developing countries. In the study, volatility spillovers in USD/TRY exchange rate, BIST100 Index and Gold Futures Contracts were investigated by discussing about the volume of crypto-currency Bitcoin exchanges operating in Turkey. In the study, it is aimed to investigate the volatility spillover of variables on Bitcoin volume in Turkey. In order to determine the volatility spillover, the results of the study using the BEKK model which is one of the multivariate GARCH models showed that when the volatility in the USD/TRY exchange rate increases, the BTC volume increases and receives a negative or positive value periodically. Similarly, the increase in volatility in the BIST100 Index leads investors to BTC. When Gold Futures Contracts are analyzed, it is stated that the volatility spillover is positive and therefore both commodities can be used for hedging.
... Thus, the impact of material information about fundamentals might be masked by information that may be important to the developed market but that is approximately noise for the emerging market. For example, Table 1 shows that the fraction 1 Studies focusing on information transmission among developed markets are Eun and Shim (1989), Hamao, Masulis, and Ng (1990), Engle, Ito, and Lin (1990), Lin and Ito (1994), Karolyi (1995), and Karolyi and Stulz (1996). Studies focusing on transmission from developed markets (mainly the U.S. and Japan) to emerging markets are Cheung, He, and Ng (1994), Kim and Rogers (1995), Bekaert and Harvey (1997), and Ng (2000). of emerging market volatility that can be explained by developed market volatilities is small. ...
... In the early studies, most of research in volatility spillover has focused on the developed markets, as examed by Hamao, Masulis, and Ng [7] indicate that the volatility spillovers of stock markets are from New York to Tokyo, London to Tokyo, and New York to London. Similar examples abound in the literature [13] [14] [15] [16] [17]. ...
... However, these findings are not strong. Karolyi (1995) examined the dynamics of returns and volatility for stock markets between New York stock exchange and Toronto stock exchange of Canada in short run by using the multivariate GARCH model and found weak linkages between both stock exchanges. Lin, Engle, and Ito (1994) investigated the return correlation and volatility spillover between Tokyo and New York stock markets. ...
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This study investigates the dynamics of volatility spillover among Asian emerging stock markets over the period from 1 January 2002 to 29 December 2017. This study applies extended EGARCH model to estimate the asymmetric volatility spillovers. The findings of this study are interesting. This study finds statistically significant own past volatility spillovers in all selected stock markets. We find bidirectional significant spillovers of volatility in most of the selected markets. Moreover, we find significant asymmetric volatility spillover in all case of stock markets. Furthermore, the findings reveal statistically insignificant volatility spillover from China to India, China to Indonesia, China to Pakistan, Pakistan to China, Pakistan to Indonesia, Pakistan to Korea and Pakistan to Taiwan in this study period. The knowledge of return linkages and volatility spillover amongst Asian emerging financial markets has great implications for global investors, portfolio managers and policymakers.
... Lien and Luo (1994) evaluated the multiperiod hedge ratios of currency futures in a MGARCH framework. Karolyi (1995) examined the international transmission of stock returns and volatility using different versions of MGARCH models. Baillie and Myers (1991) estimated the optimal hedge ratios of commodity futures and argued that these ratios are nonstationary. ...
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─ This study analyzes the effect of fluctuations in gold prices on ISE 100 index using daily prices and the index data from 01.01.2009 to 31.12.2012. The raw data has been converted into earnings yields and analyzed. The study first determines whether or not the use of a GARCH model would be appropriate using a heteroskedasticity test. The test results show that there was an ARCH effect in both variables, and that GARCH modeling could be used. The results obtained from MGARCH modeling show that gold and stock exchange yields have been affected both by their own shocks and by shocks of each other.
... In many of the multivariate generalized autoregressive conditional heteroskedasticity (GARCH) models, conditional variance and covariance are allowed to influence one another through their cross-market lagged values (as well as their cross-market squared innovation terms). For example, authors such as Karolyi (1995), Kearney and Patton (2000), and Ma-lik and Ewing (2009) study volatility transmission phenomena across closely related markets using the BEKK (Baba, Engle, Kraft, and Kroner, 1989) model, a type of multivariate GARCH models. ...
... Multidimensional models generate more reliable and accurate estimates of volatility than single-I www.irmbrjournal.com (Karolyi, 1995). Thus, it is possible to make effective decisions in the areas of risk management, forecasting, and portfolio formation. ...
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This study investigates the financial linkage of Pakistan stock market with those of its three major trade partners i.e., China, UK and USA and the impact of ongoing global health crisis (Covid-19) on this linkage. A Dynamic Conditional Generalized Autoregressive Conditional Heteroscedasticity (DCC-GARCH) approach was used to calculate dynamic correlation coefficient between the countries’ stock markets by using the daily price data of MSCI indices spanning the period 1st January 2016 to 31 December 2019 (Pre COVID-19 period) and 1st January 2020 to 30th June 2020 (COVID-19 period). The empirical results of the study highlighted that the integration of Pakistan stock market with the sampled countries was relatively low before the COVID 19 pandemic – which indicated a positive sign for market participants to diversify their portfolios. However, after the pandemic breakout, the correlation among stock markets increased substantially, indicating the significant role played by the shock events in the transmission of financial contagion between different stock markets. Keywords: Stock Market, Dynamic Conditions, Covid-19, Pakistan.
... This addresses the well-known issue of estimation bias in the presence of heteroskedasticity raised in Rigobon (2000, 2002). Third, we are able to l See, e.g., Lin et al. (1994), Karolyi (1995), Koutmos and Booth (1995), Karolyi and Stulz (1996), Booth et al. (1997), Worthington and Higgs (2004), and Cha and Jithendranathan (2009). m Additional applications include Tse (2000), and Scheicher (2001). ...
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Contagion occurs when cross-market correlation increases because of a shock to one market. Identifying shocks as episodes of house price exuberance, we provide evidence for contagion effects among the largest metropolitan markets in the US. We find that changes in income, interest rates, and unemployment also create contagion effects. These empirical findings are consistent with a model in which shocks to house prices and economic variables relaxes households down payment constraints and increases household mobility and housing demand. These effects are established in an equilibrium framework in which house prices and household choices are determined endogenously, and we account for this endogeneity in our empirical study. Our results are robust to various empirical specifications, and we discuss the implications of these findings for households and investors.
... This addresses the well-known issue of estimation bias in the presence of heteroskedasticity raised in Rigobon (2000, 2002). Third, we are able to l See, e.g., Lin et al. (1994), Karolyi (1995), Koutmos and Booth (1995), Karolyi and Stulz (1996), Booth et al. (1997), Worthington and Higgs (2004), and Cha and Jithendranathan (2009). m Additional applications include Tse (2000), and Scheicher (2001). ...
... Bae and Karolyi (1994) found that the spillover of stock volatility between Japan and the United States is closely related to goods news or bad news. Karolyi (1995) Little or no work has been done on dollar-Naira exchange rate together with the exchange rates of the major currencies in the world particularly using Multivariate GARCH family models. The exchange rate volatility has implications for many issues in the area of finance and economics. ...
... The first academic research tests domestic and geographically similar equity markets, U.S. and Canada. Using vector autoregression, multivariate GARCH-BEKK, which assumes conditional covariance and multivariate GARCH-CCC, which assumes constant conditional correlation (CCC) processes, Karolyi (1995) finds that there is significant volatility spillover effect between the Canadian and U.S. equity market, where the Canadian market is dependent on the U.S. market. Simultaneously, Karolyi concludes that the VAR model overestimates this dependency. ...
Research
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We study spillover effects between commodity price and the US dollar to Brazilian real exchange rate returns and volatility at the daily and intraday frequency. We model the spillover between commodity price and the exchange rate returns using vector autoregression (VAR). To analyze volatility spillover we use a multivariate GARCH model. We discover strong evidence for bidirectional predictability between the USD/BRL exchange rate and commodities prices at the intraday level and inter-market return spillovers. Moreover, we find substantial evidence of volatility spillovers between the USD/BRL exchange rate and commodities prices at both the daily and intraday level. We find that the 7% of variance in returns to commodities prices are from shocks to the returns to the exchange rate. Moreover, we discover that both return and volatility spillover effects strengthen moving from daily to intraday data; thus spillover effects are increasingly substantial in higher frequency data.
... Bae and karolyi [23] found that the spillover of stock volatility between Japan and the United States is closely related to goods news or bad news. Karolyi [24] used a bivariate GARCH model to investigate the transmission of stock returns and volatility between the United States and Canada, finding that volatility is transferred from U.S. to Canada most of the time. See King et al. [25] and Ng [26] for more evidences of volatility transmission and linkage. ...
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The main objective of this paper is to utilize a Bivariate Generalized Autoregressive Conditional Heteroskedasticity (Bivariate GARCH) time series models to analyze the daily exchange rate of the domestic currencies of the African and Asian tigers (Nigeria and China) against the U.S dollar simultaneously between the periods of 4 th January, 1999-21 st February, 2014 inclusive and to observe some stylize facts of good volatility modeling on financial time series. The result shows that the skewness for Nigerian Naira is greater than zero (for the normal distribution), that is to say that the distribution is positively skewed which is an indication of a non-symmetric series, but it is less than zero for the Chinese Yuan; an indication of negatively skewed distribution, meaning that there is an asymmetric effects in these models. The kurtosis is also greater than 3 (the kurtosis of a normal distribution). Recall that; relatively large kurtosis suggests that the distribution of the exchange rate return series is leptokurtic (i.e. exhibit fat tail) which is another stylize fact. Thereafter, Jarque Bera normality test statistic indicates that neither of the two returns series follows a normal distribution. We also found that Nigeria as a market performed better than the Asian Giant (China) as Nigerian Naira has least variability than the Chinese Yuan. We finally concluded that among the three fitted models, the Constant Conditional Correlation (CCC) model was found to be the best model because it has maximum log likelihood, lower Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC) and Hannan-Quinn Information Criteria (HIC), it has least number of parameters and the convergence achieved after only four iterations.
... The globalization of financial markets made scholars and practitioners very interested in knowing if the volatility of a market affects the volatility of other markets; or how the volatility of an asset transmits to another asset directly, through its conditional variance or indirectly, through its conditional covariances. Financial volatilities have the tendency to move together across financial markets without any regard for boundaries, as proven by the studies of Hafner and Herwartz (2006) and Bubak et al. (2011) using exchange rates, and Karolyi (1995) and Zhu (2009) in stock markets. It is also a widely accepted fact that financial asset return volatility, covariances and correlations changed over time with persistent dynamics, as seen by Fleming et al. (1998) in the bond and stock markets and Du et al. (2011) in the commodities markets. ...
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This study uses the Granger Causality test, three Multivariate General Autoregressive Conditional Heteroskedasticity (MGARCH) models and a robustness check to analyze seven commodity ETNs with their corresponding futures contract returns. The study found that a majority of lagged ETNs is a leading indicator to the present values of futures contract, which supports the MGARCH model results indicating the presence of long-run persistence, wherein shocks in ETNs may have an effect on the futures contracts over a long time horizon. Constant conditional correlations between the volatilities of ETN and future contract returns are also discovered. However, additional testing shows the strong presence of time-varying correlations suggest that dynamic models are more appropriate than constant correlation assumptions. This research also finds conditional covariances of the ETNs and futures contracts to be a function of their lagged covariances and lagged cross-products of the shocks, which proves that the volatilities of ETN returns have an impact on their futures contracts.
... Early research -such as Arshanapalli and Doukas (1993); Karolyi (1995) -focused on the correlations between the mature markets because investors were not that much interested in emerging markets before mid-1990s. Some studies prefer to use volatility spillovers as a measure of connectedness between two markets. ...
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The main purpose of this study is to examine the connectedness between the sectors in the Indian stock market for the period 01/2011 through 12/2020. It uses TVP-VAR (Time-Varying Parameter Vector Autoregression) based con-nectedness approach to measure the time-varying connectedness between sectors. For the whole study period, almost 84% of the forecast error variance is explained by cross-sectional shocks within the network of Indian stock market sectors. Thus, own impact only accounts for 16% of the total variability, suggesting a robust overall dependence among the sectors. In general, results suggest that cyclical stocks are usually net transmitters of shocks, whereas non-cyclical stocks are net receivers. Important political events in the past had profound impact on the connectedness between the sectors in the Indian economy. For the portfolio managers, the main implication of the findings is that they should not overly depend on sectors to diversify their portfolios-rather, they should look at the relationship between individual stocks in this regard. And, for the policymakers, the implication is that they should keep in mind that any policy changes (shocks) to cyclical sectors should be cautiously dealt with.. JEL classification: C32, C58, G10, G40, G41
... Early research -such as Arshanapalli and Doukas (1993); Karolyi (1995) -focused on the correlations between the mature markets because investors were not that much interested in emerging markets before mid-1990s. Some studies prefer to use volatility spillovers as a measure of connectedness between two markets. ...
Article
Full-text available
The main purpose of this study is to examine the connectedness between the sectors in the Indian stock market for the period 01/2011 through 12/2020. It uses TVP-VAR (Time-Varying Parameter Vector Autoregression) based con-nectedness approach to measure the time-varying connectedness between sectors. For the whole study period, almost 84% of the forecast error variance is explained by cross-sectional shocks within the network of Indian stock market sectors. Thus, own impact only accounts for 16% of the total variability, suggesting a robust overall dependence among the sectors. In general, results suggest that cyclical stocks are usually net transmitters of shocks, whereas non-cyclical stocks are net receivers. Important political events in the past had profound impact on the connectedness between the sectors in the Indian economy. For the portfolio managers, the main implication of the findings is that they should not overly depend on sectors to diversify their portfolios-rather, they should look at the relationship between individual stocks in this regard. And, for the policymakers, the implication is that they should keep in mind that any policy changes (shocks) to cyclical sectors should be cautiously dealt with.. JEL classification: C32, C58, G10, G40, G41
... Over the past decades, volatility transmission and linkage between the domestic and international financial markets attract immense interest among finance researchers, especially market experts. Therefore, a growing number of studies have been performed to expose the association between domestics and international financial markets; see, for instance, [4][5][6][7][8][9][10][11][12]. Likewise, another line of interlinkage between the financial market and other domestic market segments is also investigated in the empirical literature, see [13,14]. ...
... The cointegration estimates the long-term association without capturing the co-movement in the volatility. Therefore, the multivariate GARCH models are utilized for the co-movement of volatility including co-variance and volatility spillover effect (Karolyi, 1995;Kearney and Patton, 2000;Rastogi and Agarwal, 2020). Thus, GARCH models have evolved from univariate to multivariate (M-GARCH) and the restricted GARCH models can be used to measure volatility between multiple time series variables. ...
Article
Purpose Crude oil, gold and interest rates are some of the key indicators of the health of domestic as well as global economy. The purpose of the study is to find the shock volatility and price volatility effects of gold and crude oil market on interest rates in India. Design/methodology/approach This study finds the mutual and directional association of the volatility of gold, crude oil and interest rates in India. The bi-variate GARCH models (Diagonal VEC GARCH and BEKK GARCH) are applied on the sample data of gold price, crude oil price and yield (interest rate) gathered from November 30, 2015 to November 16, 2020 (weekly basis) to investigate the volatility association including the volatility spillover effect in the three markets. Findings The main findings of the study focus on having a long-term conditional correlation between gold and interest rates, but there is no evidence of volatility spillover from gold and crude oil on the interest rates. The findings of the study are of great importance especially to the policymakers, as they state that the fluctuations in prices of gold and crude oil do not adversely impact the interest rates in India. Therefore, the fluctuations in prices of gold and crude may generally impact the economy, but it has nothing to do with interest rate in particular. This implies that domestic and foreign investments in the country will not be affected by gold and crude oil that are largely driven by interest rates in the country. Practical implications Gold and crude oil are two very important commodities that have their importance not only for domestic affairs but also for international business. They veritably influence the economy including forex exchange for any nation. In addition to this, the researchers believe the findings will provide insights to policymakers, stakeholders and investors. Originality/value Gold and crude oil undoubtedly influence the exchange rates but their impact on the interest rates in an economy is not definite and remains ambiguous owing to the mixed findings of the studies. The lack of studies related to the impact of gold and crude oil on the interest rates, despite them being essentials for the health of any economy is the main motivation of this study. This study is novel as it investigates the volatility impact of crude oil and gold on interest rates and contributes to the existing literature with its findings.
... And from the estimated parameters, in high volatility state, the correlation is even higher, which is also observed financial anomaly, e.g. volatility spillover (Karolyi 1995). Tables 5, 6 and 7 reports daily, weekly and monthly data estimation results. ...
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Markov regime switching (MRS) models successfully describe the cyclical behavior of time series by introducing hidden states and can better explain some stylised facts of asset returns. However, due to the complexity of the model, especially for multi-variate and multi-state cases, traditional maximum likelihood estimation (MLE) methods for MRS model suffers from strict assumptions and prone to converge to local optima. In this paper, we design a spectral clustering algorithm to predict hidden states of multi-variate MRS model by constructing feature vector and derive the parameter estimation. Monte-Carlo simulation results show that our algorithm is more robust than MLE. Meanwhile, we also give an application example of the algorithm by implementing a MRS asset allocation strategy in Chinese stock market.
... In the BEKK specification, the variance-covariance matrix of equations depends on the squares and cross-products of innovations εt and lagged volatility Ht for each market under study. An important feature of this specification is that it builds in sufficient generality, allowing the conditional variances and covariances of the markets under study to influence each other; at the same time, it does not require the estimation of a large number of parameters (Karolyi 1995). The model also ensures the condition of a positive semi-definite conditional variance-covariance matrix in the optimization process, and is a necessary condition for the estimated variances to be zero or positive. ...
Conference Paper
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This study analyses information spillover effects and shock transmission between shipping, oil and stock markets. A VAR(1)-bivariate BEKK GARCH(1,1) model is employed to estimate dynamic conditional volatility and correlations between these markets. The empirical evidence supports market interactions and volatility spillover effects between the shipping, oil and stock markets. Different shipping market segments exhibit varying degrees of dynamic volatility response and lead-lag behavior with the other markets. This exercise is considered to be useful, as the empirical findings have implications for efficient corporate decisions, risk management and hedging strategies.
... The stock market spillover literature generally concludes that the US market provides information leadership to other markets in terms of exporting its market sentiments, which influence both the first and second moments of market returns in other national markets. See inter alia Karolyi (1995) for the US and Canada, Theodossiou, Kahya, Koutmoa, and Christifi (1997) for the US, Japan, and the UK, Liu and Pan (1997) between the US and Asian countries; and Baele (2002) between the US and European countries. Since national stock market indexes are denominated in local currencies, one needs to consider the role played by exchange rates in information transmission. ...
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This paper examines the time-varying relationship between the stock and the foreign exchange markets for China, Japan and Korea for the period July 2005 to November 2013. The cross-market relationship within each country differs among the three countries and varies over time. There is no evidence of a significant and consistent pattern of causality between the two market segments in China for the whole sample. However, there is some evidence of causality, mostly from the foreign exchange to the stock market during major crisis periods. For Japan, we find a significant causality from the foreign exchange to the stock market for most of the sample period. During the periods of stock market turmoil (2007 and 2011) in Japan, however, the stock market drives the foreign exchange market. In contrast, there is a strong and consistent causality from the stock to the foreign exchange market in Korea throughout the sample except for 2009.
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Thesis
p>This thesis conducts the first-ever detailed examination of the impacts of the international stock markets on the Shanghai stock market. The main aim is to investigate whether information originated from other stock markets has adverse effects on the Shanghai stock market, and consequently, to derive some implications for policy agents, investors, and further research. This study is based on four relatively related research papers, which focus on the impacts of information from different perspectives. It has identified the significant decline of the Shanghai stock price volatility after 1<sup>st</sup> July 1997. It has also analysed factors from the Hong Kong stock market that impact on Shanghai stock prices. To make this study more robust, the concept of co-persistence in variances is adopted to examine the validity of the methodologies used in the first paper. Moreover, functions of the futures market is also discussed in order to achieve a better understanding of how information coming from the derivative market improves its underlying spot market. This research study supports the main hypothesised notation that we place more emphasis on improving inter-market information linkages. As a by-product the financial portfolio frontier is discussed when the variance-covariance matrix in singular.</p
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We examine the intraday relationship between returns and returns volatility in the stock index and stock index futures markets. Our results indicate a strong intermarket dependence in the volatility of the cash and futures returns. Price innovations that originate in either the stock or futures markets can predict the future volatility in the other market. We show that this relationship persists even during periods in which the dependence in the returns themselves appears to weaken. The findings are robust to controlling for potential market frictions such as asynchronous trading in the stock index. Our results have implications for understanding the pattern of information flows between the two markets.
Article
New evidence is provided on the determinants of stock-return variances. First, when the Tokyo Stock Exchange is open on Saturday, the weekend variance increases; weekly variance is unaffected, however, despite an increase in weekly volume. Second, the listing of U.S. stocks in Tokyo substantially increases the number of trading hours, but Tokyo volume is negligible for these U.S. stocks and their 24-hour variance is unaffected. The overall results are consistent with the predictions of private-information-based rational trading models, but inconsistent with both the irrational trading noise and public-information hypotheses.
Article
This paper reexamines the integration of the Canadian and U.S. stock markets in the 1977-86 period that is relatively free from capital controls. The study employs both the capital asset pricing model and the arbitrage pricing theory frameworks. Under both models, the evidence is consistent with segmentation in the 1977-81 subperiod, but supports integration in the 1982-86 subperiod. Using the arbitrage pricing theory framework, the author finds that the Canadian stocks interlisted on the U.S. exchanges and NASDAQ are priced.in an integrated market and segmentation is predominant for the noninterlisted Canadian stocks. Copyright 1992 by American Finance Association.
Article
Previous studies have established that public information cannot explain the decrease in return volatility during the closing of a stock exchange. The present study shows that the failure of the public information hypothesis in explaining the trading/nontrading volatility differential is merely a domestic phenomenon. The manifestation of public information in an international setting is very different. Specifically, the absence of price information due to the closing of the US market affects both volatility and trading volume in the Canadian market.
Article
Traditional econometric models assume a constant one-period forecast variance. To generalize this implausible assumption, a new class of stochastic processes called autoregressive conditional heteroscedastic (ARCH) processes are introduced in this paper. These are mean zero, serially uncorrelated processes with nonconstant variances conditional on the past, but constant unconditional variances. For such processes, the recent past gives information about the one-period forecast variance. A regression model is then introduced with disturbances following an ARCH process. Maximum likelihood estimators are described and a simple scoring iteration formulated. Ordinary least squares maintains its optimality properties in this set-up, but maximum likelihood is more efficient. The relative efficiency is calculated and can be infinite. To test whether the disturbances follow an ARCH process, the Lagrange multiplier procedure is employed. The test is based simply on the autocorrelation of the squared OLS residuals. This model is used to estimate the means and variances of inflation in the U.K. The ARCH effect is found to be significant and the estimated variances increase substantially during the chaotic seventies.
Article
A natural generalization of the ARCH (Autoregressive Conditional Heteroskedastic) process introduced in Engle (1982) to allow for past conditional variances in the current conditional variance equation is proposed. Stationarity conditions and autocorrelation structure for this new class of parametric models are derived. Maximum likelihood estimation and testing are also considered. Finally an empirical example relating to the uncertainty of the inflation rate is presented.
Article
We use a multivariate generalized autoregressive heteroskedasticity model (M-GARCH) to examine three stock indexes and their associated futures prices: the New York Stock Exchange Composite, S&P 500, and Toronto 35. The North American context is significant because markets in Canada and the United States share similar structures and regulatory environments. Our model allows examination of dependence in volatility as it captures time variation in volatility and cross-market influences. Estimated time variation in volatility is significant and the volatilities are highly positively correlated. Yet, we find that the correlation in North American index and futures markets has declined over time.
Article
The authors use predictions of aggregate stock return variances from daily data to estimate time-varying monthly variances for size-ranked portfolios. The authors propose and estimate a single factor model of heteroskedasticity for portfolio returns. This model implies time-varying betas. Implications of heteroskedasticity and time-varying betas for tests of the capital asset pricing model are then documented. Accounting for heteroskedasticity increases the evidence that risk-adjusted returns are related to firm size. The authors also estimate a constant correlation model. Portfolio volatilities predicted by this model are similar to those predicated by more complex multivariate generalized autoregressive conditional heteroskedasticity procedures. Copyright 1990 by American Finance Association.
Article
With some simple assumptions the ex‐dividend day price drop and the associated dividend can be used to measure the market's marginal tax rate. Previous research has estimated the implied tax rate for the U.S. This paper extends the analysis to Canada, where the tax treatment of dividends and capital gains is completely different from that in the U.S. The paper also presents estimates from 1970–80 to include four distinct periods when the tax treatment was different. Hence, we include an implied test of market efficiency as well as those for the “relevance” of taxes and the existence of tax based dividend clienteles.
Article
This paper examines the issue of integration versus segmentation of the Canadian equity market relative to a global North American market. We compare the international and domestic versions of the CAPM, and find that integration, or the mean‐variance efficiency of the global market index, is rejected by the data. Segmentation is the preferred model, based on a maximum likelihood procedure correcting for thin trading. We further divide the sample into securities that are interlisted in Canada and the U.S., and those that are not. Integration is rejected for both groups, which indicates that the source of segmentation can be traced to legal barriers based on the nationality of issuing firms.
I993), "'Common 'Jolatility In Znlernarion. Eq-Jiiy Mwkets Joi~rnul :!;"Busi:zess Q Economic Stati.i.rics, ? 1
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Engle. R., an6 Susmel, R. (I993), "'Common 'Jolatility In Znlernarion. Eq-Jiiy Mwkets," Joi~rnul :!;"Busi:zess Q Economic Stati.i.rics, ? 1. 167-176.
in, ?s,ess), ',Misspecification in Vector Auroregres-sions and Thsir Effec? on Emptnlse Responses and Ihiance Decomposi-tions Jozcr:zal (?if'Economefric.s, 39
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Ysaun, P., and Milinik, S. (in, ?s,ess), ',Misspecification in Vector Auroregres-sions and Thsir Effec? on Emptnlse Responses and Ihiance Decomposi-tions," Jozcr:zal (?if'Economefric.s, 39. Chan, I(., Chm, IK. C., azd Mzolyi.
4ntmationd Listings and Stock Retons: Some Empirical EvidenceA M~liivariate Generalized ARCH Approach , . o Koddling K!sk Prernia in Forwad Foreign Exchange Rate M~ketsThe Message ir
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Structure and Perfcraance: Global Interdepeedence of Seoeic Mivkets Around the Crash ofGeneralized Autoregressive Conditional Het-erosce3asficicy
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Bertera, E., and Ma)~e:, C. (1985), "Structure and Perfcraance: Global Interdepeedence of Seoeic Mivkets Around the Crash of October 1987," uiipcblished manuscript, Centre for Bcononnic Policy Research, London. 3ollerslev, % (:086), "Generalized Autoregressive Conditional Het-erosce3asficicy," Joi'(~'izal qfEconiimeirics, 3 1, 307-327.
ARCH Modeling in Fi-nance: Theory and Empiricai Evidence
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BolIerslev, T., Chou, W., and :Kroner, K. (1992), "ARCH Modeling in Fi-nance: Theory and Empiricai Evidence," Jorernui of Ecoizometrics, 37, 231-356.
The Ex-dividenC Day Behaviour of Cnnadim S:9c!: Prices. Tax Changes and Clientele Effects Journczi of Fir:ance
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Booth, L., and Johnsion, D. (1984), "The Ex-dividenC Day Behaviour of Cnnadim S:9c!: Prices. Tax Changes and Clientele Effects," Journczi of Fir:ance, 39, 4574.76.
Do Circuit Breakers Moder-ate Volatility? Evidence From October i989," unpublished manuscript, Commodity Futures Trading Commission
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ICuhn, B., I(Qs€rk, B., and Locke, P. (!990), "Do Circuit Breakers Moder-ate Volatility? Evidence From October i989," unpublished manuscript, Commodity Futures Trading Commission. Washington.
Qrrasi-Maximum Likelihood Es-tirnatio:: and Inference in Dynamic Models With Time-VaPy.ng Covar-aiices
  • J T Bolleisiev
Bolleisiev. T., and Wooldri-ndge, J. (19921, "Qrrasi-Maximum Likelihood Es-tirnatio:: and Inference in Dynamic Models With Time-VaPy.ng Covar-aiices," Econome;ric Reviews, i i, 143-172.
A Capital Asset Pricing icIodei Wiri-~ T~~~e-vao.ing CwiaPiances
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T., Engle, R., and VIoold~idge, J. (1988), "A Capital Asset Pricing icIodei Wiri-~ T~~~e-vao.ing CwiaPiances," Journal qf Political Economy, 96, 116-131.
The lr~temational Transmission of Stock Price Eismption in Gctober Federul Reserve Bank qfNew jhric Qrtar:ei?y Revie><
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Bennett, P., and Melieher, J. (198S), "The lr~temational Transmission of Stock Price Eismption in Gctober 1987,'' Federul Reserve Bank qfNew jhric Qrtar:ei?y Revie><,', 13, ? 7-32.
GlobalRnancialMarkets and the Risk Prerniu~. on U.S. Bqui:y;' ,bamul of Financial Economics
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Chan, I (. C.. KxolyE, G. A., and Stulz, R. (19921, "GlobalRnancialMarkets and the Risk Prerniu~. on U.S. Bqui:y;',bamul of Financial Economics, 32, 137-167.
Estimation and Inferencd in Nonlinea Sin~ctilral Models
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Berndt, E., Hall, B., Wall, R., and Nansmm, Jr. (1974), "Estimation and Inferencd in Nonlinea Sin~ctilral Models,"Annals ufEconomic andSociul Meo~ur~:menr, 3, 653-665.
A8;co;egressive Conditiond Heteroscedasticity With Es-:irnates of th5 of U.K. Inflatioc
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Engle, R, (i982). ".A8;co;egressive Conditiond Heteroscedasticity With Es-:irnates of th5 of U.K. Inflatioc," Ec~inometricu, 50, 987-1008.
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International Listings and Stock Returns: Some Empirical Evidence Gordon J. Alexander; Cheol S. Eun; S. Janakiramanan The Journal of Financial and Quantitative Analysis, Vol. 23, No. 2. (Jun., 1988), pp. 135-151.
jstor.org/sici?sici=0022-1082%28199009%2945%3A4%3C1129%3AHISR%3E2.0.CO%3B2-M Macroeconomics and Reality Christopher A
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Stable URL: http://links.jstor.org/sici?sici=0022-1082%28199009%2945%3A4%3C1129%3AHISR%3E2.0.CO%3B2-M Macroeconomics and Reality Christopher A. Sims Econometrica, Vol. 48, No. 1. (Jan., 1980), pp. 1-48.
org/sici?sici=0022-1082%28198406%2939%3A2%3C457%3ATEDBOC%3E2.0.CO%3B2-%23 Intraday Volatility in the Stock Index and Stock Index Futures Markets Kalok Chan
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jstor.org/sici?sici=0022-1082%28199212%2947%3A5%3C2035%3AAEOIIT%3E2.0.CO%3B2-X Vector Autoregressions and Reality David E
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org/sici?sici=0893-9454%28199423%297%3A3%3C507%3ADBABMA%3E2.0.CO%3B2-%23 Additional Evidence on Integration in the Canadian Stock Market Usha R
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org/sici?sici=0893-9454%281990%293%3A2%3C281%3ACIPCAV%3E2.0.CO%3B2-O The Relationship Between Equity Indices on World Exchanges Jimmy E
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Stable URL: http://links.jstor.org/sici?sici=0893-9454%281990%293%3A2%3C281%3ACIPCAV%3E2.0.CO%3B2-O The Relationship Between Equity Indices on World Exchanges Jimmy E. Hilliard The Journal of Finance, Vol. 34, No. 1. (Mar., 1979), pp. 103-114.
org/sici?sici=0012-9682%28198001%2948%3A1%3C1%3AMAR%3E2.0.CO%3B2-A International Stock Price Movements: Links and Messages George M. von Furstenberg; Bang Nam Jeon
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Stable URL: http://links.jstor.org/sici?sici=0022-1082%28197903%2934%3A1%3C103%3ATRBEIO%3E2.0.CO%3B2-K Integration vs. Segmentation in the Canadian Stock Market Philippe Jorion; Eduardo Schwartz The Journal of Finance, Vol. 41, No. 3, Papers and Proceedings of the Forty-Fourth Annual Meeting of the America Finance Association, New York, New York, December 28-30, 1985. (Jul., 1986), pp. 603-614.
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