Academic literature on the topic 'Stock-Market Volatility Tests'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Stock-Market Volatility Tests.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Journal articles on the topic "Stock-Market Volatility Tests"
1
Magner Pulgar, Nicolás, Esteban José Antonio Terán Sánchez, and Vicente Alfonso Guzmán Muñoz. "Stock Market Synchronization and Stock Volatility: The Case of an Emerging Market." Revista Mexicana de Economía y Finanzas 17, no. 3 (2022): 1–22. http://dx.doi.org/10.21919/remef.v17i3.747.
Full textAbstract:
The purpose of this paper is to study the effect of stock market synchronization on the volatility of its component assets. For this objective, we calculate the stock market's synchronization using the Minimum Spanning Tree Length (MSTL) network analysis method. Then, we implement forecasting tests in and out the sample to assess the forecasting power on the stock market's synchronization to predict the individual stock realized volatility. Additionally, we test a VAR and a forecast error variance decomposition analysis to study Granger causality's presence on volatility. Our results show that synchronization within a market exists and changes over time. Our main results show that an increase in synchronization causes an increase in financial assets' realized volatility in the following month. Our results made it possible to study financial markets' synchronization and take a systemic risk approach to improve investment management. Our main idea was that the stock markets' synchronization positively correlates with financial assets' volatility. The greater the synchronization, the greater the volatility in the following period. This study offers a new approach to study the stock market volatility.
2
Acuña, Andrés, and Cristián Pinto. "Eficiencia del mercado accionario Chileno: un enfoque dinámico usando test de volatilidad." Lecturas de Economía, no. 70 (September 11, 2009): 39–61. http://dx.doi.org/10.17533/udea.le.n70a2254.
Full textAbstract:
En este artículo estudiamos la eficiencia del Mercado Accionario Chileno (MAC). Para su comprobación usamos un modelo de equilibrio parcial que representa la manera como se forma el precio de los activos financieros. Contrastamos la volatilidad observada en los precios de las acciones y la volatilidad esperada en un modelo de mercado accionario eficiente. El análisis estadístico comprende datos de frecuencia mensual de títulos transados en la Bolsa de Comercio de Santiago de Chile en el periodo 1987-2007. Utilizando tests de volatilidad, encontramos evidencia de exceso de volatilidad en los precios del mercado accionario chileno; no podemos vincular el exceso de volatilidad a la existencia de una burbuja especulativa racional, y tampoco a un exceso de volatilidad en la tasa de descuento. Palabras clave: eficiencia, mercado accionario, valoración de activos, CAPM. Clasificación JEL: D53, G14 Abstract: This article studies the Chilean Stock Market's efficiency. To corroborate efficiency, we use a partial equilibrium model for financial asset pricing. We contrast between observed and expected Chilean stock price volatility under an efficient stock market framework. For the statistical analysis, we use monthly data for Chilean Stock Market prices from 1987 to 2007. Performing volatility tests, we find evidence of excess volatility in Chilean stock market prices. We cannot link this stock price excess volatility to the existence of a rational speculative bubble, nor to discount rate's excess volatility. Keywords: efficiency, stock market, asset pricing, CAPM. JEL Classification: D53, G14 Résumé: Dans cet article nous étudions l'efficience du marché actionnaire chilien (MAC). Pour ce faire, nous utilisons un modèle d'équilibre partiel qui représente la manière dont le prix des actifs financiers est déterminé. Nous contrastons la volatilité observée dans les prix des actions et la volatilité attendue à l'intérieur d'un modèle de marché actionnaire efficient. L'analyse statistique comprend un ensemble de données de fréquence mensuelle des titres échangés à la Bourse de Commerce de Santiago du Chili pour la période 1987-2007. En utilisant des tests de volatilité, nous montrons qu'il existe un excès de volatilité dans les prix du marché actionnaire chilien; sans qu'il soit posible lier cet excès de volatilité ni à l'existence d'une bulle spéculative rationnelle, ni au taux d'escompte. Mots clé: efficience, marché actionnaire, évaluation d'actifs, CAPM. Classification JEL : D53, G14
3
Ogbulu, Onyemachi Maxwell. "Oil Price Volatility, Exchange Rate Movements and Stock Market Reaction: The Nigerian Experience (1985-2017)." American Finance & Banking Review 3, no. 1 (2018): 12–25. http://dx.doi.org/10.46281/amfbr.v3i1.200.
Full textAbstract:
Given the observed volatility in crude oil prices in the international oil market and the role which oil and gas play in the Nigerian economy, this paper is an attempt to investigate the impact of crude oil prices and foreign exchange rate movements on stock market prices in Nigeria. In addition, the paper examined whether there is any volatility pass-through between the dollar price of Nigerian crude oil, foreign exchange rate of the Naira and stock market prices respectively. Data employed for the study are monthly values of the Nigerian Stock Exchange (NSE) All-Share Index (ASI), Dollar price of Nigerian Crude Oil (DPO) and the Official Exchange Rate of the Naira to the US Dollar (FXR) from January, 1985 to August, 2017. The methodology adopted for the study include the ADF unit root tests, Johansen co-integration tests, the ECM technique, Granger causality tests, variance decomposition as well as the GARCH(1,1) to model the volatility relationships among the variables. Findings reveal that there is one long-run dynamic co-integrating relationship among the variables ASI, DPO and FXR while the ECM results indicate that Crude oil price (DPO) significantly impact on Stock market prices. The Granger causality test reports a bi-directional causality relationship between ASI and DPO and a unidirectional causality running from FXR to ASI. The ARCH-GARCH volatility analysis demonstrates vividly that stock market prices in the NSE exhibit ARCH effect with a significant and positive first order ARCH term. The GARCH term is also positive and significant indicating that previous month’s stock market price volatility significantly influences current stock market volatility in the NSE. In addition, findings show that the volatility of dollar price of Nigerian oil (DPO) in the world oil market is significantly transmitted to the volatility of stock market prices in Nigeria. The pass-through effect of the volatility of exchange rate (FXR) to the volatility of stock market prices is also positive and significant. These findings offer significant informational signal to policy makers, portfolio managers/advisors and the investing public in achieving optimal asset and portfolio profile.
4
Mecagni, Mauro, and Maged Sawky Sourial. "The Egyptian Stock Market: Efficiency Tests and Volatility Effects." IMF Working Papers 99, no. 48 (1999): 1. http://dx.doi.org/10.5089/9781451846720.001.
Full text
5
Nguyen, Hien Thu, and Nghi Dinh Le. "TESTING THE GARCH MODEL IN THE VIETNAMESE STOCK MARKET." Science and Technology Development Journal 13, no. 4 (2010): 5–14. http://dx.doi.org/10.32508/stdj.v13i4.2182.
Full textAbstract:
An important factor of interest of investors on stock markets is investment risk. Risk can undergo a quantitative process through volatility, be measured by conditional variance of stock returns. GARCH is an effective and popularly used model for volatility effect on stock returns. This study tests the GARCH model and analyzes other aspects of volatility on stock returns on the two stock markets of Vietnam. In addition, the study provides evidence of the existence of GARCH effect on Vietnamese stock markets. Besides, the study also assesses price margin policy, trading volume and leverage effects on volatility of stock returns.
6
Bhuva, Krunal K., and Vijay H. Vyas. "Expiry day Impact on return on Indian Stock market (NSE)- an Empirical Study." Journal of Management and Science 1, no. 3 (2013): 402–9. http://dx.doi.org/10.26524/jms.2013.45.
Full textAbstract:
Derivative products are alleged to have a sharp affect on the stock market in various ways ever since their inception in June 2000. Currently, derivative trading constitutes approximately 90% of the total turnover of the NSE (National Stock Exchange). Launching of derivatives and their expiration (last Thursday of every month) in the Indian stock market has been perceived to have direct corollary on the return, volatility, efficiency and marketability of the stock market. This paper tries to analyze empirically the expiration day effect of stock derivatives on underlying securities. This study tests the presence of the last Thursday of the montheffect on stock market volatility by using the S&P 500 market index during the period of January 2012 and December 2012 and sample companies which are trading on derivative market. The findings show that the last Thursday of the month effect on stock market volatility is not present in volatility and return equations.
7
Leblang, David, and Bumba Mukherjee. "Presidential Elections and the Stock Market: Comparing Markov-Switching and Fractionally Integrated GARCH Models of Volatility." Political Analysis 12, no. 3 (2004): 296–322. http://dx.doi.org/10.1093/pan/mph020.
Full textAbstract:
Existing research on electoral politics and financial markets predicts that when investors expect left parties—Democrats (US), Labor (UK)—to win elections, market volatility increases. In addition, current econometric research on stock market volatility suggests that Markov-switching models provide more accurate volatility forecasts and fit stock price volatility data better than linear or nonlinear GARCH (generalized autoregressive conditional heteroskedasticity) models. Contrary to the existing literature, we argue here that when traders anticipate that the Democratic candidate will win the presidential election, stock market volatility decreases. Using two data sets from the 2000 U.S. presidential election, we test our claim by estimating several GARCH, exponential GARCH (EGARCH), fractionally integrated exponential GARCH (FIEGARCH), and Markov-switching models. We also conduct extensive forecasting tests—including RMSE and MAE statistics as well as realized volatility regressions—to evaluate these competing statistical models. Results from forecasting tests show, in contrast to prevailing claims, that GARCH and EGARCH models provide substantially more accurate forecasts than the Markov-switching models. Estimates from all the statistical models support our key prediction that stock market volatility decreases when traders anticipate a Democratic victory.
8
Wanyama, Dr David W. "EFFECT OF STOCK MARKET VOLATILITY ON THE GROWTH OF CORPORATE BOND MARKET IN KENYA." International Journal of Finance 2, no. 2 (2017): 76. http://dx.doi.org/10.47941/ijf.57.
Full textAbstract:
Purpose: The purpose of this study was to analyze how stock market volatility influences the growth of corporate bond market in Kenya.Methodology: The study used descriptive and causal research designs. Secondary data was used. The sample of the study consisted of daily and monthly time series covering six years beginning January 2009 to December 2014. Unit root tests using Augmented Dickey-Fuller (ADF) and Phillips-Perron tests were done. The study used Eviews econometric software to facilitate empirical analysis of data.Results: Regression of coefficients results shows that stock market volatility and corporate bonds are positively and significant related (r=0.000023, p=0.0001).Unique Contribution to Theory, Practice and Policy: The study recommended that Policy makers should be aware of and monitor the level of stock market volatility that is appropriate for promoting the growth of the corporate bond markets and indeed other financial markets.
9
GIL-ALANA, LUIS A. "FRACTIONAL INTEGRATION IN THE STOCK MARKET VOLATILITY SERIES." International Journal of Theoretical and Applied Finance 05, no. 08 (2002): 775–83. http://dx.doi.org/10.1142/s0219024902001663.
Full textAbstract:
In this article we model the stock market volatility in the US, the UK, France, Germany and Japan by means of using fractionally integrated techniques. The results, based on the tests of Robinson [24] show that the volatility series can be well described in terms of I(d) statistical processes, with d higher than 0.5 but smaller than 1, implying thus nonstationary but mean-reverting behaviour.
10
Badshah, Koerniadi, and Kolari. "Testing the Information-Based Trading Hypothesis in the Option Market: Evidence from Share Repurchases." Journal of Risk and Financial Management 12, no. 4 (2019): 179. http://dx.doi.org/10.3390/jrfm12040179.
Full textAbstract:
The informed options trading hypothesis posits that option prices lead stock prices. In this paper, we extended the research on this hypothesis to open-market share repurchases. Empirical tests showed that the implied volatility spread was not significantly related to buy-and-hold abnormal stock returns. However, further evidence reveal a significant relationship between implied volatility spread and subsequent stock return volatility around open-market share repurchase events. We concluded that option traders have private information on the volatility of stock returns and superior information processing ability that accounts for prescient pricing behavior in options relative to stocks.
Dissertations / Theses on the topic "Stock-Market Volatility Tests"
1
Shabi, Sarosh. "Stock market volatility, business cycles and the recent financial crisis : evidence from linear and non-linear causality tests." Thesis, University of Southampton, 2014. https://eprints.soton.ac.uk/373080/.
Full textAbstract:
The relationship between stock market volatility and the business cycle is macrofinancial as it links the fields of financial markets and macro-economics. This relationship links to theories of rational expectations/efficient market hypotheses and asset pricing theory. This thesis investigates the long run relationship between stock market volatility and business cycles by means of linear and non linear bivariate and multivariate causality tests. Moreover, it investigates the impact of the recent global financial crisis on the stock market volatility (SMV) and business cycles (BC) relationship. The contributions of this research to the literature include: a) analyzing the non-linear causal relationship between stock market volatility and the business cycle; b) exploring the cross-country causality between these variables; and c) looking at the impact of the financial crisis on the said relationship. To the best of our knowledge this is the first time that any of these three aspects of the relationship between stock market volatility and the business cycle have been studied. The countries investigated are the US, the UK, Canada, and Japan (among the developed countries) and Brazil, Malaysia and Turkey (from the developing countries). Monthly data from January 1990 to December 2011 are applied in the empirical investigation. Stock market volatilities are estimated using the GARCH model, and industrial production indices are used for the business cycles. Bivariate non-linear causality tests are conducted by means of the Diks and Panchenko (2006) and Hiemstra and Jones (1994) methods. Non-linear multivariate tests are conducted by means of the Bai et al. (2010) method. Multivariate tests investigate the cross-country spill-over between two countries, with the US as the main country. The results indicate that a non-linear causal relationship does exist between stock market volatility (SMV) and business cycles (BC). There is strong evidence to suggest that the SMV-BC relationship is not limited to within country only, as we find significant cross-country causal relationships. Both linear and non-linear bivariate causality tests indicate evidence of a stronger causality between variables when the financial crisis is taken into consideration. Also, both the linear and non-linear multivariate tests indicate that the US has a greater impact on the SMV and BC of developed countries than developing countries. And this impact has further increased during the recent financial crisis. The findings from this research have implications not only for investors and portfolio managers, but also for economists and policy makers. In addition, the research results signal that in countries such as the UK, inclusion of the US stock market as a business cycle indicator, in addition to the UK’s own stock market, may be beneficial in identifying the turning points of the UK’s business cycle, and vice versa.
2
BUONAGUIDI, DAMIANO. "Choice of Exogenous Variables, Stock Market Dynamics, Financial Sector: Three Essays on Macroeconomic Theory." Doctoral thesis, Università di Siena, 2018. http://hdl.handle.net/11365/1061353.
Full textAbstract:
The choice of exogenous variables is a fundamental element for the logical structure of economic models, leading to different positive and normative implications about growth, distribution and economic policies. In this dissertation a comparative approach is used both to study different models from a theoretical point of view and to analyze the link between the financial and the real sector of the economy.
In the first chapter we present a comparison between the neoclassical model and the alternative approach, drawn from the classical and post-keynesian literature, within a common mathematical framework based on the Solow growth model. Several variations in the canonical models are considered. We shall show in a convenient analytical framework how the fundamental differences between the two paradigms ultimately lie in the choice of the exogenous variables: factors endowments in the neoclassical approach or effective demand and, in some cases, income distribution in the alternative approach.
In the second chapter, we adopt a comparative approach to interpret stock market dynamics, pursuing two objectives. First, we shall show how the prevailing interpretation of Shiller tests on stock price volatility can all be traced back to the neoclassical model, which makes them exposed to several criticisms. Second, we shall present an alternative macroeconomic model drawn from Sraffian and Keynesian literature which suggests a different interpretation of the empirical evidence on stock market volatility.
In the third chapter we propose an integration between the classical-Keynesian model and the monetary circuit framework, evaluating its consistency and its policy implications. In particular, we shall verify whether the Keynesian multiplier can be consistently introduced in the monetary circuit framework, how monetary authorities can affect economic dynamics, how monetary circuits are intertemporally linked to each other and how the problem of interest repayments can be solved.
3
Karadag, Mehmet Ali. "Analysis Of Turkish Stock Market With Markov Regime Switching Volatility Models." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/3/12609787/index.pdf.
Full textAbstract:
In this study, both uni-regime GARCH and Markov Regime Switching GARCH (SW-GARCH) models are examined to analyze Turkish Stock Market volatility. We investigate various models to find out whether SW-GARCH models are an
improvement on the uni-regime GARCH models in terms of modelling and forecasting Turkish Stock Market volatility. As well as using seven statistical loss functions, we apply Superior Predictive Ability (SPA) test of Hansen (2005) and
Reality Check test (RC) of White (2000) to compare forecast performance of various models.
4
Rossetti, Nara. "Análise das volatilidades dos mercados brasileiros de renda fixa e renda variável no período 1986 - 2006." Universidade de São Paulo, 2007. http://www.teses.usp.br/teses/disponiveis/96/96133/tde-29042008-115430/.
Full textAbstract:
O presente trabalho tem como objetivo analisar a volatilidade dos mercados de renda fixa e renda variável no Brasil, no período de março de 1986 até fevereiro de 2006, por meio do CDI (Certificado de Depósito Interfinanceiro) e IRF-M (Índice de Renda Fixa de Mercado), como indicadores do mercado de renda fixa, e o IBOVESPA (Índice da BOVESPA), como indicador de renda variável. Por meio da comparação da volatilidade destes ativos é possível observar se há coincidência temporal entre os dois mercados, em relação aos picos de volatilidade devido, principalmente, a influência de variáveis macroeconômicas. Tal análise é importante para que os gestores de portfólios, que tomam decisões de como alocar os investimentos, conheçam o histórico e o corrente relacionamento entre as volatilidades dos dois mercados. As volatilidades do mercado de renda fixa e do mercado de renda variável foram calculadas por meio do desvio padrão anual dos retornos mensais e por meio de um modelo GARCH(1,1). Os resultados mostram que, no Brasil, durante o período analisado, os dois mercados apresentaram: períodos coincidentes de picos de volatilidade, grande mudança no padrão comportamental das volatilidades após a implantação do Plano Real e pouca estabilidade na relação entre as volatilidades.<br>This work aims to study the volatility of the fixed income market and the stock market in Brazil, from March 1986 to February 2006, through CDI (Interbank Interest Rate), IRF-M (Fixed Income Index), as a fixed income market indicators, and IBOVESPA (BOVESPA index), as a stock market indicator. Through the comparison of the volatility of these assets it is possible to observe if there is time frame coincidence between the two markets, in relation to the peaks of volatility due to, mainly the influence of macroeconomics variables. Such analysis is important so that portfolio managers, responsible for decisions such investments allocation, know the history and the actual relationship between the markets volatility. Such analysis is important so that portfolio managers, responsible for decisions such investments allocation, know the history and the actual relationship between the markets volatility. Those fixed income market and stock markets volatilities were calculated through the annual standard deviation of the monthly returns and from a GARCH(1,1) model. The results show that, in Brazil, during the studied period, both markets presents: coincident volatility peaks periods, high change in the behavioral pattern of volatility after the deployment of the Plano Real and little stability in the relationship between the volatility.
5
Rossetti, Nara. "Análise da volatilidade dos mercados de renda fixa e renda variável de países emergentes e desenvolvidos no período de 2000 a 2011." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/18/18157/tde-10092015-094310/.
Full textAbstract:
O presente trabalho analisou as volatilidades dos mercados de renda fixa e variável de onze países, sendo eles: Brasil, Rússia, Índia, China, África do Sul (neste país apenas renda fixa), Argentina, Chile, México, Estados Unidos, Alemanha e Japão no período de janeiro de 2000 a dezembro de 2011. Os indicadores utilizados para representar cada mercado foram os índices dos mercados de ações e as taxas de juros interbancárias. Para tanto, o estudo se utilizou de modelos de heterocedasticidade condicional auto-regressiva: ARCH, GARCH, EGARCH, TGARCH e PGARCH, verificando quais destes processos eram mais eficientes para modelagem da volatilidade dos mercados dos países da amostra. Esta pesquisa também verificou qual dos modelos (ARIMA ou modelos GARCH e suas extensões) conseguiria prever melhor as séries de tempo analisadas. Além disso, por meio dos índices de correlação, covariância e causalidade Granger, foram comparados os retornos e a volatilidade do mercado de ações entre os países BRIC, entre os países latinos americanos e entre os países desenvolvidos e o Brasil. Os resultados sugerem que a volatilidade, tanto do mercado de renda fixa quanto do mercado de renda variável, é mais bem modelada por processos GARCH assimétricos (EGARCH e TGARCH), demonstrando efeitos de alavancagem nas séries estudadas. Quanto aos modelos de previsão, os modelos ARIMA, também para os dois mercados, mostrou-se mais eficiente que os modelos GARCH e suas extensões. Além disso, as volatilidades dos mercados de ações entre os países analisados parecem ser mais correlacionadas e possuir maior causalidade Granger do que os retornos destes países. Entre os dois mercados, renda fixa e variável dentro de cada país, as correlações dos retornos e da volatilidade são muito baixas, em algumas vezes negativa, e há pouca relação de causalidade Granger.<br>This study analyzed the volatility of fixed income and stocks markets for eleven countries, namely: Brazil, Russia, India, China, South Africa (just fixed income), Argentina, Chile, Mexico, United States, Germany and Japan from January 2000 to December 2011, using interbank interest rate as a fixed income market indicator and stock index to each country, as a stock market indicator. Therefore, the study used models of autoregressive conditional heteroscedasticity: ARCH, GARCH, EGARCH, TGARCH e PGARCH to verify which of these processes were more effective for in volatility modeling in each country. This research also found that the models (ARIMA or GARCH models and their extensions) could be used as the best forecast models. Moreover, by means of correlation coefficients, covariance and Granger causality, were used to compare the returns and volatility of the stock market among the BRIC countries, among the Latin American countries and between developed countries and Brazil. The results suggest that the volatility of both the fixed income market as the stock market is best modeled by processes asymmetric GARCH (EGARCH and TGARCH) demonstrating leverage effects in the time series. Regarding prediction ARIMA models was more efficient for both markets than GARCH models and extensions. In addition, the volatility of stock markets across countries analyzed seem to be more correlated and have higher Granger causality than returns these countries. Between the two markets, for each country, the correlations of returns and volatility are very low, if not positive, and there is low Granger causality.
6
Pinto, Rinaldo Caldeira. "Uma análise da utilização do coeficiente Beta no setor elétrico brasileiro." Universidade de São Paulo, 2008. http://www.teses.usp.br/teses/disponiveis/86/86131/tde-18112008-150903/.
Full textAbstract:
O coeficiente beta, definido no contexto do modelo de avaliação de ativos denominado Capital Asset Pricing Model, tem sido amplamente utilizado no Setor Elétrico Brasileiro. Sua aplicação tem sido importante não apenas no âmbito das revisões tarifárias conduzidas pelo órgão regulador, mas também para análise das empresas do setor pelos investidores em mercado de capitais. Embora a aplicação do modelo CAPM seja simples, ele é construído sobre hipóteses rigorosas, que nem sempre são observáveis no mercado real, principalmente em países emergentes. Inserido no referencial teórico deste Modelo, o presente trabalho tem como o objetivo analisar a utilização do coeficiente beta no setor elétrico brasileiro, identificando potenciais distorções que decorram de sua aplicação. Adicionalmente, este trabalho busca analisar o comportamento desse coeficiente de mercado ao longo do período de 1999 a 2007, identificando possíveis tendências. Para isso, lança-se mão de dados que são amplamente utilizados pelos agentes do mercado de capitais, oriundos de uma amostra de empresas que, por possuírem dados disponibilizados em bolsa de valores tornam viável gerar este coeficiente. Das análises realizadas é possível concluir que o coeficiente beta obtido com dados do mercado brasileiro apresentou valores bem próximos aos coeficientes obtidos em mercados desenvolvidos. Também foi possível constatar que os segmentos de distribuição e geração apresentam, no mercado brasileiro, betas desalavancados de mesma ordem de grandeza entre si, embora o segmento de geração seja mais concorrencial e, no de distribuição, predomine um contexto de monopólio natural.<br>The coefficient beta, defined in the context of the Capital Asset Pricing Model, has been widely applied within the Brazilian electricity industry. Its application has been conducted not only by the regulatory authority regarding tariff review of regulated electricity concessionaires, but also largely used by investors in Brazilian the capital market. Although the CAPM tool is a straight forward one, the Model itself was built under strict assumptions which are not often found in the real world, mainly in developing countries. Departing from this theoretical framework, this master thesis analyses the coefficient beta within the Brazilian electricity industry, identifying potential distortions derived from its application. Additionally, this work examines the coefficient beta behavior throughout 1999 up to 2007, pointing possible trends. For generating the beta coefficient, it is used the same sort of data usually selected by market investors, applied to a set of select companies belonging to the Brazilian electricity industry that have their information publicly disclosed in the financial and stock markets. The result of the analysis pointed that the coefficient beta generated for the Brazilian companies analyzed did not differ much form those of companies belonging to the electricity industry of developed countries. It was also perceived that the segments of electricity distribution and electricity generation presented unlevered betas of the same magnitude although generating companies operates in a competitive market and distribution concessionaires face predominantly a natural monopoly context.
7
Chang, Che-Wei, and 張哲維. "Using the Short-term volatility and the Long-term volatility to Test the Performance of Investment in Taiwan Stock-Index Options Market." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/57242481317110625478.
Full textAbstract:
碩士<br>逢甲大學<br>經營管理碩士在職專班<br>96<br>The purpose of this research is make a simulation as an empirical study through the short-term volatility and the long-term volatility, to find out the turning point of the Taiwan Stock-Index Options Market by the approach and out signals with these two indicators. And hope to get additional compensation in the market. As the observation period from 1/1/2005 to 12/31/2006, Two of in-the-money strike price and five of out-the-money strike price to the sample, use 2-10 days for the Short-term volatility and 3-20 days for the long-term volatility to study. In bull strategy it is approach signal when the Short-term volatility break up the long-term volatility, and the out signal when the Short-term volatility down below the long-term volatility. Analysis and find out the operation strategy of the Short-term volatility and the long-term volatility from the most profitable of these four basic strategies:buy call, sell put, sell call and buy put. And enter the test period from 1/1/2007 to 12/31/2007, divided into “considering transaction costs” and “without consider transaction costs” these two kinds of situations. To verify if the best operation strategy in observation period apply to the test period. In addition, in order to avoid can not buy for less turn over the study all set numbers of the turn over must be more then 1000, to meet with the reality of the situation.
The results found the operation sarategy of sell put and buy put got the excess reward of consistency, whether considering transaction costs or not, but it caused inconsistent situation of observation period profit and test period loss by the operation strategy of buy call and sell call. The buy call and sell call could not get excess reward in test period, for this point, further analysis found that there were two decline more then 1500 points in 2007(July and November),which were never happened in 2005 and 2006,coupled with the loss of time, caused the poor earnings of buy call. As for the sell call of bear strategy, it was used 7 days for the Short-term volatility and 20 days for the long-term volatility, and reflect the huge fluctuations were slower in 2007 because of the longer volatility, so it was the reason for the loss.
Books on the topic "Stock-Market Volatility Tests"
1
Mecagni, Mauro. The Egyptian stock market: Efficiency tests and volatility effects. International Monetary Fund, Middle Eastern Department, 1999.
Find full text
2
Sourial, Maged Sawky, and Mauro Mecagni. Egyptian Stock Market: Efficiency Tests and Volatility Effects. International Monetary Fund, 1999.
Find full text
3
Sourial, Maged Sawky, and Mauro Mecagni. Egyptian Stock Market - Efficiency Tests and Volatility Effects. International Monetary Fund, 1999.
Find full text
4
Sourial, Maged Sawky, and Mauro Mecagni. Egyptian Stock Market - Efficiency Tests and Volatility Effects. International Monetary Fund, 1999.
Find full textBook chapters on the topic "Stock-Market Volatility Tests"
1
Filipovski, Vladimir, and Dragan Tevdovski. "Stock Market Efficiency in South Eastern Europe." In Regaining Global Stability After the Financial Crisis. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-4026-7.ch011.
Full textAbstract:
The purpose of this chapter is to empirically test the informational efficiency and to examine the presence of the calendar effects in 10 South Eastern European (SEE) stock markets' daily returns during the period 2007–2014. The authors use variance ratio test for exploration of random walk hypothesis. Regarding the calendar effects, the authors focus on the day-of-the-week effect, the half-month effect, and the turn-of-the-month effect. The existence of each calendar effect is analyzed by applying regression models with dummy variables for the effects in the mean returns and GARCH (1,1) models with dummy variables for the effects in the volatility of returns. The results indicate that the day-of-the-week effects in both mean and volatility are present in nine SEE stock markets. Contrary, the half-month effect in mean returns is present only in one, while half-month effect in volatility is present in five SEE stock markets. The turn-of-the- month effect in mean returns is present in six, while the turn-of-the-month effect in volatility is present in all 10 SEE stock markets.
2
Ben Sassi, Salim, and Azza Bejaoui. "On the Impact of Long Memory on Market Risk." In Advances in Finance, Accounting, and Economics. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-3767-0.ch003.
Full textAbstract:
This chapter investigates the influence of the long memory behavior in returns and volatility on the market risk for four emerging stock markets during the pre- and post-crisis periods. In this respect, the authors consider four major political events (Tunisian revolution, Egyptian revolution, assassination of Prime Minister Rafik El Hariri, and a series of suicide bombings in Morocco). Using the modified R/S test and GPH test, they show the long memory property in returns and volatility over the two sub-periods. To explore the dual long memory property, the authors apply the joint ARFIMA–FIGARCH specification on the returns and volatility of the four emerging stock markets. The dual long memory property is prevalent in the returns and volatility of the emerging stock markets over the pre-crisis period. During the post-crisis period, the dual long memory process is only detected in the Moroccan market. The authors also display the dynamic behavior of VaR during the two sub-periods. In addition, based on the backtesting test, VaR performed better during the two sub-periods for all countries.
3
Jawad, Muhammad, and Munazza Naz. "An Econometric Investigation of Market Volatility and Efficiency: A Study of Small Cap’s Stock Indices." In Linear and Non-Linear Financial Econometrics -Theory and Practice [Working Title]. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.94119.
Full textAbstract:
By utilization the context of econometric models, this chapter investigates three significant research parameters and tries to find out the positive outcome for further studies. The first question, is the volatility of Small Cap foreseeable?. The second question, does the volatility of Small Cap exhibition the same pragmatic regularities stated in the literature about the behavior of further stock prices?, The third and Final question, can Small Cap clear the test of market efficiency?. The results of these research questions will provide the answers of following objectives: First, economic representatives investing in Small Cap Stock markets. Second, the business professors/professionals/educationist is more concerned in Small Cap for their teaching and research. Third, the policy makers who are observing the stock market volatilities because of its significances and impulsive behavior to invest for more incentives among other consequences.
4
Oluseun Olayungbo, David. "Volatility Effects of the Global Oil Price on Stock Price in Nigeria: Evidence from Linear and Non-Linear GARCH." In Linear and Non-Linear Financial Econometrics -Theory and Practice. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.93497.
Full textAbstract:
This present study examines the volatility effects of the oil price on the stock price returns in Nigeria from the period of 2000M(12) to 2020M(4) on a monthly data using both standard GARCH and non-linear GARCH models. The motivation for the present study is the recent fall in the global oil price of Brent Crude to US$15.25 per barrel due to the outbreak of the Corona Virus (COVID-19). Consequentially, the Nigerian stock market (NSE) responded with a fall of 4172 point or by a fall of 15.53%. After establishing the presence of heteroscedasticity through the ARCH test and volatility clustering through the returns, the outcome of the study contributes to knowledge by providing financial information and signals to investors about the best GARCH model response to proactively and successfully use to model global oil price shocks so as to reduce financial risk in Nigeria’s stock market.
5
Van Hai, Hoang, Phan Kim Tuan, and Le The Phiet. "Firm-specific News and Anomalies." In Investment, Asset Pricing and Portfolio Choice Strategies [Working Title]. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.94286.
Full textAbstract:
This study investigates the relation between idiosyncratic volatility and future returns around the firm-specific news announcements in the Korean stock market from July 1995 to June 2018. The excess returns of decile portfolios that are formed by sorting the stocks based on news and non-news idiosyncratic volatility measures. The Fama and French three-factor model is also examined to see whether systematic risk affects news and non-news idiosyncratic volatility profits. The pricing of our news and non-news idiosyncratic volatility are confirmed in the cross-sectional regression using the Fama and MacBeth method. Market beta, size, book to market, momentum, liquidity, and maximum return are controlled to determine robustness. Our empirical evidence suggests that the pricing of the non-news idiosyncratic volatility is more strongly negative compared to the news idiosyncratic volatility, which is contrary to the limited arbitrage explanation for the negative price of the idiosyncratic volatility. We find that the non-news idiosyncratic volatility has a robust negative relation to returns in non-January months. Macro-finance factors drive the conditioned on the missing risk factor hypothesis, the pricing of idiosyncratic volatility. This study contributes to a better understanding of the role of the conditional idiosyncratic volatility in asset pricing. As the Korean stocks provide a fresh sample, our non-U.S. investigation delivers a useful out-of-sample test on the pervasiveness of the non-news volatility effect across the emerging markets.
Conference papers on the topic "Stock-Market Volatility Tests"
1
Fu, Yiting, and Xiongwei Wang. "Tests for the Transmission Mechanism of Stock Market Volatility between China and U.S during Subprime Crisis." In 2011 International Conference on Business Computing and Global Informatization (BCGIn). IEEE, 2011. http://dx.doi.org/10.1109/bcgin.2011.30.
Full text
2
Bogdan, Siniša, Luka Šikić, and Suzana Bareša. "THE EFFECT OF THE COVID-19 PANDEMIC ON THE CROATIAN TOURIST SECTOR." In Tourism in Southern and Eastern Europe 2021: ToSEE – Smart, Experience, Excellence & ToFEEL – Feelings, Excitement, Education, Leisure. University of Rijeka, Faculty of Tourism and Hospitality Management, 2021. http://dx.doi.org/10.20867/tosee.06.8.
Full textAbstract:
Purpose – The COVID-19 pandemic, unprecedented in terms of the speed at which it spread globally, affected the whole world swiftly after the initial outbreak and has produced heterogeneous effects on various industrial sectors and particularly pronounced effects on the tourism industry. This paper analyses the effect of the spread of the COVID-19 pandemic through Europe on the tourist stocks in Croatia by means of application of the event study methodology. Methodology – The analysis starts with a descriptive overview of the market-wide performance of different sectors in the period before, during and after the initial pandemic outbreak and subsequently explicitly tests for the COVID-19 outbreak effects on the tourist sector. First, a 35- day event window is specified so that important events related to the pandemic can be identified. Second, the first officially reported COVID-19 incidence in Italy and the World Health Organization’s declaration of a global pandemic are used as identified events in a shorter 10day window event study estimation. Findings – The results robustly point to the significant negative effect of the COVID-19 pandemic on the returns of tourist stocks on the Zagreb Stock Exchange. However, the overall results do not provide evidence of the relatively stronger COVID-19 effects on the tourist sector, but rather equal effects across different sectors. Contribution – This research offers a novel comprehensive review of the literature regarding the research topic and provides insights into the sectoral effects of the global financial shock caused by the COVID-19 pandemic on the local market. As this pandemic is increasing the market volatility, this research will be of importance to fund managers and carries implications for economic policy in terms of sectoral stimulus distribution and debt refinancing.
3
Algan, Neşe, Mehmet Balcılar, Harun Bal, and Müge Manga. "Impact of Terrorism on Financial Markets: The Case of Turkey." In International Conference on Eurasian Economies. Eurasian Economists Association, 2016. http://dx.doi.org/10.36880/c07.01706.
Full textAbstract:
This study investigates the impact of terrorism on the Turkish financial market using daily data from Jan 4, 1988 to May 24, 2016. In order to measure the impacts of terrorist attacks in Turkey we test for causality from terrorism index to returns and volatilities of 3 aggregate and 16 sector level stock indices using a recently developed nonparametric causality-in-test test of Balcilar et al. (2016). The results obtained indicate that there is no causality from terrorist activities to stock market returns (1st moment). However, we find significant causality at various quantiles from terrorist activates to volatility (2nd moment) of tourism, food and basic materials sectors.
4
Chen, A. P., H. Y. Chiu, C. C. Sheng, and Y. H. Huang. "Do markets behave as expected? Empirical test using both implied volatility and futures prices for the Taiwan Stock Market." In COMPUTATIONAL FINANCE 2006. WIT Press, 2006. http://dx.doi.org/10.2495/cf060291.
Full text