Literatura académica sobre el tema "Stock-Market Volatility Tests"
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Artículos de revistas sobre el tema "Stock-Market Volatility Tests"
Magner Pulgar, Nicolás, Esteban José Antonio Terán Sánchez y Vicente Alfonso Guzmán Muñoz. "Stock Market Synchronization and Stock Volatility: The Case of an Emerging Market". Revista Mexicana de Economía y Finanzas 17, n.º 3 (24 de mayo de 2022): 1–22. http://dx.doi.org/10.21919/remef.v17i3.747.
Texto completoAcuña, Andrés y Cristián Pinto. "Eficiencia del mercado accionario Chileno: un enfoque dinámico usando test de volatilidad". Lecturas de Economía, n.º 70 (11 de septiembre de 2009): 39–61. http://dx.doi.org/10.17533/udea.le.n70a2254.
Texto completoOgbulu, Onyemachi Maxwell. "Oil Price Volatility, Exchange Rate Movements and Stock Market Reaction: The Nigerian Experience (1985-2017)". American Finance & Banking Review 3, n.º 1 (12 de noviembre de 2018): 12–25. http://dx.doi.org/10.46281/amfbr.v3i1.200.
Texto completoMecagni, Mauro y Maged Sawky Sourial. "The Egyptian Stock Market: Efficiency Tests and Volatility Effects". IMF Working Papers 99, n.º 48 (1999): 1. http://dx.doi.org/10.5089/9781451846720.001.
Texto completoNguyen, Hien Thu y Nghi Dinh Le. "TESTING THE GARCH MODEL IN THE VIETNAMESE STOCK MARKET". Science and Technology Development Journal 13, n.º 4 (30 de diciembre de 2010): 5–14. http://dx.doi.org/10.32508/stdj.v13i4.2182.
Texto completoBhuva, Krunal K. y Vijay H. Vyas. "Expiry day Impact on return on Indian Stock market (NSE)- an Empirical Study". Journal of Management and Science 1, n.º 3 (30 de diciembre de 2013): 402–9. http://dx.doi.org/10.26524/jms.2013.45.
Texto completoLeblang, David y Bumba Mukherjee. "Presidential Elections and the Stock Market: Comparing Markov-Switching and Fractionally Integrated GARCH Models of Volatility". Political Analysis 12, n.º 3 (2004): 296–322. http://dx.doi.org/10.1093/pan/mph020.
Texto completoWanyama, Dr David W. "EFFECT OF STOCK MARKET VOLATILITY ON THE GROWTH OF CORPORATE BOND MARKET IN KENYA". International Journal of Finance 2, n.º 2 (5 de febrero de 2017): 76. http://dx.doi.org/10.47941/ijf.57.
Texto completoGIL-ALANA, LUIS A. "FRACTIONAL INTEGRATION IN THE STOCK MARKET VOLATILITY SERIES". International Journal of Theoretical and Applied Finance 05, n.º 08 (diciembre de 2002): 775–83. http://dx.doi.org/10.1142/s0219024902001663.
Texto completoBadshah, Koerniadi y Kolari. "Testing the Information-Based Trading Hypothesis in the Option Market: Evidence from Share Repurchases". Journal of Risk and Financial Management 12, n.º 4 (29 de noviembre de 2019): 179. http://dx.doi.org/10.3390/jrfm12040179.
Texto completoTesis sobre el tema "Stock-Market Volatility Tests"
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/.
Texto completoBUONAGUIDI, 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.
Texto completoKaradag, 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.
Texto completoRossetti, 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/.
Texto completoThis 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.
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/.
Texto completoThis 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.
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/.
Texto completoThe 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.
Chang, Che-Wei y 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.
Texto completo逢甲大學
經營管理碩士在職專班
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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.
Libros sobre el tema "Stock-Market Volatility Tests"
Mecagni, Mauro. The Egyptian stock market: Efficiency tests and volatility effects. [Washington, D.C.]: International Monetary Fund, Middle Eastern Department, 1999.
Buscar texto completoSourial, Maged Sawky y Mauro Mecagni. Egyptian Stock Market: Efficiency Tests and Volatility Effects. International Monetary Fund, 1999.
Buscar texto completoSourial, Maged Sawky y Mauro Mecagni. Egyptian Stock Market - Efficiency Tests and Volatility Effects. International Monetary Fund, 1999.
Buscar texto completoSourial, Maged Sawky y Mauro Mecagni. Egyptian Stock Market - Efficiency Tests and Volatility Effects. International Monetary Fund, 1999.
Buscar texto completoCapítulos de libros sobre el tema "Stock-Market Volatility Tests"
Filipovski, Vladimir y Dragan Tevdovski. "Stock Market Efficiency in South Eastern Europe". En Regaining Global Stability After the Financial Crisis, 214–37. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-4026-7.ch011.
Texto completoBen Sassi, Salim y Azza Bejaoui. "On the Impact of Long Memory on Market Risk". En Advances in Finance, Accounting, and Economics, 42–62. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-3767-0.ch003.
Texto completoJawad, Muhammad y Munazza Naz. "An Econometric Investigation of Market Volatility and Efficiency: A Study of Small Cap’s Stock Indices". En Linear and Non-Linear Financial Econometrics -Theory and Practice [Working Title]. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.94119.
Texto completoOluseun Olayungbo, David. "Volatility Effects of the Global Oil Price on Stock Price in Nigeria: Evidence from Linear and Non-Linear GARCH". En Linear and Non-Linear Financial Econometrics -Theory and Practice. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.93497.
Texto completoVan Hai, Hoang, Phan Kim Tuan y Le The Phiet. "Firm-specific News and Anomalies". En Investment, Asset Pricing and Portfolio Choice Strategies [Working Title]. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.94286.
Texto completoActas de conferencias sobre el tema "Stock-Market Volatility Tests"
Fu, Yiting y Xiongwei Wang. "Tests for the Transmission Mechanism of Stock Market Volatility between China and U.S during Subprime Crisis". En 2011 International Conference on Business Computing and Global Informatization (BCGIn). IEEE, 2011. http://dx.doi.org/10.1109/bcgin.2011.30.
Texto completoBogdan, Siniša, Luka Šikić y Suzana Bareša. "THE EFFECT OF THE COVID-19 PANDEMIC ON THE CROATIAN TOURIST SECTOR". En 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.
Texto completoAlgan, Neşe, Mehmet Balcılar, Harun Bal y Müge Manga. "Impact of Terrorism on Financial Markets: The Case of Turkey". En International Conference on Eurasian Economies. Eurasian Economists Association, 2016. http://dx.doi.org/10.36880/c07.01706.
Texto completoChen, A. P., H. Y. Chiu, C. C. Sheng y Y. H. Huang. "Do markets behave as expected? Empirical test using both implied volatility and futures prices for the Taiwan Stock Market". En COMPUTATIONAL FINANCE 2006. Southampton, UK: WIT Press, 2006. http://dx.doi.org/10.2495/cf060291.
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