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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

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

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

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

Stochastic conditional duration model with intraday seasonality and limit order book information

Toyabe, Tomoki; Nakatsuma, Teruo - In: Journal of risk and financial management : JRFM 15 (2022) 10, pp. 1-25

It is a widely known fact that the intraday seasonality of trading intervals for financial transactions such as stocks is short at the beginning of business hours and long in the middle of the day. In this paper, we extend the stochastic conditional duration (SCD) model to capture the pattern of...

Persistent link: https://www.econbiz.de/10013471159

On financial distributions modelling methods : application on regression models for time series

Dewick, Paul R. - In: Journal of risk and financial management : JRFM 15 (2022) 10, pp. 1-15

, as the distribution and stylized facts can determine if volatility is present, resulting in financial risk and contagion …

Persistent link: https://www.econbiz.de/10013471223

Revisiting the long-run dynamic linkage between dividends and share price with advanced panel econometrics techniques

Mohapatra, Sudatta Bharati; Kar, Nirmal Chandra - In: Journal of risk and financial management : JRFM 15 (2022) 10, pp. 1-19

The log-linearized present value model (PVM) has been widely used in corporate finance to understand the long-run relationship between share price and dividends using panel data. However, the application of recently established panel econometric approaches that account for slope heterogeneity...

Persistent link: https://www.econbiz.de/10013470997

Realized measures to explain volatility changes over time

Floros, Christos; Gillas, Konstantinos Gkillas; … - In: Journal of risk and financial management : JRFM 13 (2020) 6/125, pp. 1-19

We studied (i) the volatility feedback effect, defined as the relationship between contemporaneous returns and the … market-based volatility, and (ii) the leverage effect, defined as the relationship between lagged returns and the current … market-based volatility. For our analysis, we used daily measures of volatility estimated from high frequency data to explain …

Persistent link: https://www.econbiz.de/10012309061

Testing for a single-factor stochastic volatility in bivariate series

Chiba, Masaru; Kobayashi, Masahito - In: Journal of risk and financial management : JRFM 6 (2013) 1, pp. 31-61

single common stochastic volatility factor and noidiosyncratic volatility factor. The test statistic is derived by …

Persistent link: https://www.econbiz.de/10011555751

Estimating and forecasting generalized fractional long memory stochastic volatility models

Peiris, Shelton; Asai, Manabu; McAleer, Michael - In: Journal of risk and financial management : JRFM 10 (2017) 4, pp. 1-16

memory in stochastic volatility (SV) components in order to develop the General Long Memory SV (GLMSV) model. We examine the …

Persistent link: https://www.econbiz.de/10011854876