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Do crude oil prices drive the relationship between stock markets of oil-importing and oil-exporting countries?
Youssegf, Manel; Mokni, Khaled - In: Economies : open access journal 7 (2019) 3/70, pp. 1-22
The impact that oil market shocks have on stock markets of oil-related economies has several implications for both domestic and foreign investors. Thus, we investigate the role of the oil market in deriving the dynamic linkage between stock markets of oil-exporting and oil-importing countries....
Persistent link: https://www.econbiz.de/10012029324
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Value-at-risk and expected shortfall when there is long range dependence
Härdle, Wolfgang (contributor); Mungo, Julius (contributor) - 2008
characterized by volatility clustering and asymmetry. Also revealed as a stylized fact is Long memory or long range dependence in … market volatility, with significant impact on pricing and forecasting of market volatility. The implication is that models … that accomodate long memory hold the promise of improved long-run volatility forecast as well as accurate pricing of long …
Persistent link: https://www.econbiz.de/10003636008
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Intraday Conditional Value at Risk : A Periodic Mixed-Frequency GAS Approach
Gribisch, Bastian; Eckernkemper, Tobias - 2020
We propose a copula-based periodic mixed frequency GAS framework in order to model and forecast the intraday Exposure Conditional Value at Risk (ECoVaR) for an intraday asset return and the corresponding market return. In particular we analyze GAS models which account for long-memory-type of...
Persistent link: https://www.econbiz.de/10014352170
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Bivariate volatility modeling with high-frequency data
Matei, Marius; Rovira, Xari; Agell, Núria - In: Econometrics : open access journal 7 (2019) 3/41, pp. 1-15
We propose a methodology to include night volatility estimates in the day volatility modeling problem with high … the natural relationship between the realized measure and the conditional variance. This improves volatility modeling by … leverage effect and maintains a mathematical structure that facilitates volatility estimation. A class of bivariate models that …
Persistent link: https://www.econbiz.de/10012160811
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A high-low model of daily stock price ranges
Cheung, Stephen Y. L. (contributor);  … - 2008
volatility …
Persistent link: https://www.econbiz.de/10003749656
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A High-Low Model of Daily Stock Price Ranges
Cheung, Stephen Yan-Leung - 2015
We observe that daily highs and lows of stock prices do not diverge over time and, hence, adopt the cointegration concept and the related vector error correction model (VECM) to model the daily high, the daily low, and the associated daily range data. The in-sample results attest the importance...
Persistent link: https://www.econbiz.de/10012707381
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The factor-spline-GARCH model for high and low frequency correlations
Rangel, Jose Gonzalo; Engle, Robert F. - 2009
frequency volatilities and correlations ; Dynamic conditional correlation ; Spline-GARCH ; Idiosyncratic volatility ; Long …
Persistent link: https://www.econbiz.de/10003821063
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A latent dynamic factor approach to forecasting multivariate stock market volatility : conference paper
Gribisch, Bastian - 2013
This paper proposes a latent dynamic factor model for low- as well as high-dimensional realized covariance matrices of stock returns. The approach is based on the matrix logarithm and allows for flexible dynamic dependence patterns by combining common latent factors driven by HAR dynamics and...
Persistent link: https://www.econbiz.de/10010341025
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Measuring High-Frequency Causality between Returns, Realized Volatility and Implied Volatility
Dufour, Jean-Marie - 2011
theory assumes that return shocks can be caused by changes in conditional volatility through a time-varying risk premium. On … leverage effect and the volatility feedback effect. We stress the importance of distinguishing between realized volatility and … implied volatility, and find that implied volatilities are essential for assessing the volatility feedback effect. The …
Persistent link: https://www.econbiz.de/10013128856
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Volatility Modeling and Forecasting for NIFTY Stock Returns
Singh, Gurmeet - 2016
In this paper, an attempt has been made to model the volatility of NIFTY index of National Stock Exchange (NSE) and … comprises 3736 data points for the analysis by using Box-Jenkins or ARIMA model. The volatility in the Indian stock market … suggested by Hannan-Rissanen. As per the analysis, ARIMA (1,0,1) model was found to be the best fit to forecast the volatility …
Persistent link: https://www.econbiz.de/10013001574