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Use of adapted particle filters in SVJD models
Fičura, Milan; Witzany, Jiří - In: European financial and accounting journal : EFAJ 13 (2018) 3, pp. 5-20
Particle Filter algorithms for filtering latent states (volatility and jumps) of Stochastic-Volatility Jump-Diffusion (SVJD) models are being explained. Three versions of the SIR particle filter with adapted proposal distributions to the jump occurrences, jump sizes, and both are derived and...
Persistent link: https://www.econbiz.de/10012118579
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Are long-run output growth rates falling?
Li, Mengheng; Mendieta-Muñoz, Ivan - 2018
This paper studies the evolution of long-run output and labour productivity growth rates in the G-7 countries during the post-war period. We estimate the growth rates consistent with a constant unemployment rate using time-varying parameter models that incorporate both stochastic volatility and...
Persistent link: https://www.econbiz.de/10011823990
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GARCH models, tail indexes and error distributions : an empirical investigation
Šopov, Boril; Horváth, Roman - 2015
heteroskedasticity (GARCH) models capture extreme events in stock market returns. We estimate Hill's tail indexes for individual S&P 500 … stock market returns ranging from 1995-2014 and compare these to the tail indexes produced by simulating GARCH models. Our … results suggest that actual and simulated values differ greatly for GARCH models with normal conditional distributions, which …
Persistent link: https://www.econbiz.de/10010529886
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Improving Value-at-Risk estimation from the normal EGARCH model
Gorji, Mahsa; Sajjad, Rasoul - In: Contemporary economics 11 (2017) 1, pp. 91-106
-correction method can improve the n-GARCH and n-EGARCH VaR forecasts so much that the acquired VaR predictions are different from the … distribution instead of GARCH improves the performance of the bias-correction method in forecasting the VaR for almost all …
Persistent link: https://www.econbiz.de/10011632622
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Indirect inference with(out) constraints
Frazier, David T.; Renault, Eric - In: Quantitative economics : QE ; journal of the … 11 (2020) 1, pp. 113-159
possibly strict inequality constraints g(β)>0, such as, when I‐I is based on GARCH auxiliary models. In these settings, we …
Persistent link: https://www.econbiz.de/10012202226
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Indirect Inference for Lévy-Driven Continuous-Time GARCH Models
do Rego Sousa, Thiago - 2018
We advocate the use of an Indirect Inference method to estimate the parameter of a COGARCH(1,1) process for equally spaced observations. This requires that the true model can be simulated and a reasonable estimation method for an approximate auxiliary model. We follow previous approaches and use...
Persistent link: https://www.econbiz.de/10012928980
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Volatility Forecasting Using Threshold Heteroskedastic Models of the Intra-day Range
Chen, Cathy W. S.; Gerlach, Richard H.; Lin, Edward M.H - 2009
An effective approach for forecasting return volatility via threshold nonlinear heteroskedastic models of the daily asset price range is provided. The return is defined as the difference between the highest and lowest log intra-day asset price. A general model specification is proposed, allowing...
Persistent link: https://www.econbiz.de/10014207634
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Is intraday data the key to better volatility estimation?
Foster, Sam; Leveau, Daniel - 2023
Volatility is a central tenet of financial markets, impacting a wide range of investors’ daily activities, including risk management, portfolio construction and option pricing. To improve their investment decisions, investors are spending considerable time and effort on finding new ways to...
Persistent link: https://www.econbiz.de/10014350504
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EmmPack 1.01 : C/C++ code for use with Ox for estimation of univariate stochastic volatility models with the efficient method of moments
Sluis, Pieter J. van der - 1998
Econometric estimation using simulation techniques, such as the efficient method of moments, may betime consuming. The use of ordinary matrix programming languages such as Gauss, Matlab, Ox or S-plus will very often cause extra delay. For the Efficient Method of Moments implemented to...
Persistent link: https://www.econbiz.de/10010533201
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Sequential Gibbs Particle Filter Algorithm with an Application to Stochastic Volatility and Jumps Estimation
Witzany, Jiri - 2018
The aim of this paper is to propose and test a novel PF method called Sequential Gibbs Particle Filter allowing to estimate complex latent state variable models with unknown parameters. The framework is applied to a stochastic volatility model with independent jumps in returns and volatility....
Persistent link: https://www.econbiz.de/10012916933