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Co-jumps, co-jump tests, and volatility forecasting : Monte Carlo and empirical evidence
Peng, Weijia; Yao, Chun - In: Journal of risk and financial management : JRFM 15 (2022) 8, pp. 1-21
predict the sector-level S&P500 exchange-traded fund (ETF) volatility. It was found that the predictive content of co-jumps is … volatility forecasting. Additionally, we carried out Monte Carlo experiments designed to examine the relative performances of the …
Persistent link: https://www.econbiz.de/10013375217
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Bayesian analysis of intraday stochastic volatility models of high-frequency stock returns with skew heavy-tailed errors
Nakakita, Makoto; Nakatsuma, Teruo - In: Journal of risk and financial management : JRFM 14 (2021) 4, pp. 1-29
Intraday high-frequency data of stock returns exhibit not only typical characteristics (e.g., volatility clustering and … the leverage effect) but also a cyclical pattern of return volatility that is known as intraday seasonality. In this paper …, we extend the stochastic volatility (SV) model for application with such intraday high-frequency data and develop an …
Persistent link: https://www.econbiz.de/10012520275
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COVID-19 pandemic and Romanian stock market volatility : a GARCH approach
Gherghina, Ștefan Cristian; Armeanu, Daniel Ștefan; … - In: Journal of risk and financial management : JRFM 14 (2021) 8, pp. 1-29
This paper investigates the volatility of daily returns on the Romanian stock market between January 2020 and April … 2021. Volatility is analyzed by means of the representative index for Bucharest Stock Exchange (BSE), namely, the Bucharest … GARCH approach. In the survey, the GARCH model (1,1) was applied to explore the volatility of the BET and BSE traded shares …
Persistent link: https://www.econbiz.de/10012626337
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Temporal aggregation and long memory for asset price volatility
Perron, Pierre; Shi, Wendong - In: Journal of risk and financial management : JRFM 13 (2020) 8/182, pp. 1-18
asset price volatility. We show how the squared low-frequency returns can be expressed in terms of the temporal aggregation … properties of the spectral density function of realized volatility series, constructed from squared returns with different … new features of volatility in financial market indices. The theoretical findings are illustrated via the analysis of both …
Persistent link: https://www.econbiz.de/10012321959
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Quasi-maximum likelihood estimation for long memory stock transaction data - under conditional heteroskedasticity framework
Quoreshi, A. M. M. Shahiduzzaman; Uddin, Reaz; Khan, … - In: Journal of risk and financial management : JRFM 12 (2019) 2/74, pp. 1-13
This paper introduces Quasi-Maximum Likelihood Estimation for Long Memory Stock Transaction Data of unknown underlying distribution. The moments with conditional heteroscedasticity have been discussed. In a Monte Carlo experiment, it was found that the QML estimator performs as well as CLS and...
Persistent link: https://www.econbiz.de/10012022130
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Portfolio volatility estimation relative to stock market cross-sectional intrinsic entropy
Vint̜e, Claudiu; Ausloos, Marcel - In: Journal of risk and financial management : JRFM 16 (2023) 2, pp. 1-24
Selecting stock portfolios and assessing their relative volatility risk compared to the market as a whole, market … uses the cross-sectional intrinsic entropy (CSIE) model to estimate the cross-sectional volatility of the stock groups that … can be considered together as portfolio constituents. The CSIE market volatility estimate is based on daily traded prices …
Persistent link: https://www.econbiz.de/10014305795
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Clarifying the response of gold return to financial indicators : an empirical comparative analysis using ordinary least squares, robust and quantile regressions
Miyazaki, Takashi - In: Journal of risk and financial management : JRFM 12 (2019) 1/33, pp. 1-18
returns fall sharply; (2) it rises as the stock market volatility increases; (3) it also rises when general financial market …
Persistent link: https://www.econbiz.de/10012022330
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Volatility integration in spot, futures and options markets : a regulatory perspective
Rastogi, Shailesh; Athaley, Chaitaly - In: Journal of risk and financial management : JRFM 12 (2019) 2/98, pp. 1-15
The aim of this paper is to study the integration of volatility in the three markets, viz. spot, futures and options … moments (GMM) is used to capture the simultaneous equation modelling of volatility in the three markets. The integration of … the volatility in the three markets is also tested for structural breaks. The main finding of the paper is that the …
Persistent link: https://www.econbiz.de/10012022005
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Financial time series: methods and models
Caporin, Massimiliano; Storti, Giuseppe - In: Journal of risk and financial management : JRFM 13 (2020) 5/86, pp. 1-3
The statistical analysis of financial time series is a rich and diversified research field whose inherent complexity requires an interdisciplinary approach, gathering together several disciplines, such as statistics, economics, and computational sciences. This special issue of the Journal of...
Persistent link: https://www.econbiz.de/10012304649
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Forecast combinations for structural breaks in volatility : evidence from BRICS countries
De Gaetano, Davide - In: Journal of risk and financial management : JRFM 11 (2018) 4, pp. 1-13
The aim of this paper is to investigate the relevance of structural breaks for forecasting the volatility of daily … evident. In forecasting volatility, the combination that averages forecasts obtained using different rolling estimation …
Persistent link: https://www.econbiz.de/10011961363