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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

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

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

GARCH modelling of cryptocurrencies

Chu, Jeffrey; Chan, Stephen; Nadarajah, Saralees; … - In: Journal of risk and financial management : JRFM 10 (2017) 4, pp. 1-15

With the exception of Bitcoin, there appears to be little or no literature on GARCH modelling of cryptocurrencies. This paper provides the first GARCH modelling of the seven most popular cryptocurrencies. Twelve GARCH models are fitted to each cryptocurrency, and their fits are assessed in terms...

Persistent link: https://www.econbiz.de/10011854856

Predicting volatility based on interval regression models

Qu, Hui; He, Mengying - In: Journal of risk and financial management : JRFM 15 (2022) 12, pp. 1-21

Considering the inferior volatility tracking capability of the point-data-based models, we propose using the more … informative price interval data and building interval regression models for volatility forecasting. To characterize the … heterogeneity of the market and the nonlinearity of volatility, we incorporated the heterogeneous autoregressive structure and the …

Persistent link: https://www.econbiz.de/10014284403

Dimension reduction via penalized GLMs for non-Gaussian response : application to stock market volatility

Li, Tao; Desmond, Anthony F.; Stengos, Thanasēs - In: Journal of risk and financial management : JRFM 14 (2021) 12, pp. 1-26

financial ratios. Stock market volatility is non-Gaussian distributed. It can be approximated by an inverse Gaussian (IG … indicators to help us forecast stock market volatility. Via simulation, we validated the use of four models, i.e., a univariate … us forecast stock market volatility. These are the credit spread between the U.S. Aaa corporate bond yield and the 10 …

Persistent link: https://www.econbiz.de/10012798738

Stock returns and risk : evidence from quantile

Chiang, Thomas C.; Li, Jiandong - In: Journal of risk and financial management : JRFM 5 (2012) 1, pp. 20-58

This paper employs weighted least squares to examine the risk-return relation by applying high-frequency data from four major stock indexes in the US market and finds some evidence in favor of a positive relation between the mean of the excess returns and expected risk. However, by using...

Persistent link: https://www.econbiz.de/10011555867

Is one diagnostic test for COVID-19 enough?

McAleer, Michael - In: Journal of risk and financial management : JRFM 13 (2020) 4/77, pp. 1-3

There is no doubt about the importance of diagnostic testing in an emergency; specifically, which range of tests is available, where and when they are dispensed, and who might be tested using laboratory-developed tests, or other diagnostic tests including experimental tests. This includes...

Persistent link: https://www.econbiz.de/10012302713

The Burr X Pareto Distribution : properties, applications and VaR estimation

Korkmaz, Mustafa Ç.; Altun, Emrah; Yousof, Haitham M.; … - In: Journal of risk and financial management : JRFM 11 (2018) 1, pp. 1-16

In this paper, a new three-parameter Pareto distribution is introduced and studied. We discuss various mathematical and statistical properties of the new model. Some estimation methods of the model parameters are performed. Moreover, the peaks-over-threshold method is used to estimate...

Persistent link: https://www.econbiz.de/10011854963

Smoothed maximum score estimation of discrete duration models

Reza, Sadat; Rilstone, Paul - In: Journal of risk and financial management : JRFM 12 (2019) 2/64, pp. 1-16

This paper extends Horowitz's smoothed maximum score estimator to discrete-time duration models. The estimator's consistency and asymptotic distribution are derived. Monte Carlo simulations using various data generating processes with varying error distributions and shapes of the hazard rate are...

Persistent link: https://www.econbiz.de/10012022194