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Volatility behavior of asset returns based on robust volatility ratio : empirical analysis on global stock indices
Shaik, Muneer; Maheswaran, S. - In: Cogent economics & finance 7 (2019) 1, pp. 1-27
In this paper we come up with an alternate theoretical proof for the independence and unbiased property of extreme value robust volatility estimator with respect to the standard robust volatility estimator as proposed in the paper by Muneer & Maheswaran (2018b). We show that the robust...
Persistent link: https://www.econbiz.de/10012023869
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Estimation of the long-memory stochastic volatility model parameters that is robust to level shifts and deterministic trends
McCloskey, Adam - 2012 - This version: October 2012
I provide conditions under which the trimmed FDQML estimator, advanced by McCloskey (2010) in the context of fully parametric short-memory models, can be used to estimate the long-memory stochastic volatility model parameters in the presence of additive low-frequency contamination in log-squared...
Persistent link: https://www.econbiz.de/10009660446
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Estimation of the Long-Memory Stochastic Volatility Model Parameters that is Robust to Level Shifts and Deterministic Trends
McCloskey, Adam - 2012
I provide conditions under which the trimmed FDQML estimator, advanced by McCloskey (2010) in the context of fully parametric short-memory models, can be used to estimate the long-memory stochastic volatility model parameters in the presence of additive low-frequency contamination in log-squared...
Persistent link: https://www.econbiz.de/10013098304
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Particle Efficient Importance Sampling
Scharth, Marcel; Kohn, Robert - 2013
The efficient importance sampling (EIS) method is a general principle for the numerical evaluation of high … number of successful applications in high dimensions, it is well known that importance sampling strategies are subject to an … sampling squared algorithms …
Persistent link: https://www.econbiz.de/10014153378
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The Gibbs Sampler with Particle Efficient Importance Sampling for State-Space Models
Grothe, Oliver - 2017
Monte Carlo (MC) approximation of the standard Gibbs procedure which uses sequential MC (SMC) importance sampling inside the … generic and easily implementable SMC approach known as Particle Efficient Importance Sampling (PEIS). By using SMC importance … sampling densities which are approximately fully globally adapted to the targeted density of the states, PEIS can substantially …
Persistent link: https://www.econbiz.de/10012970355
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Efficient Importance Sampling Maximum Likelihood Estimation of Stochastic Differential Equations
Rossi, Eduardo; Pastorello, Sergio - 2011
based on efficient importance sampling (EIS) is detailed. Monte Carlo experiments, based on widely used diffusion processes …, evaluate its performance against an alternative importance sampling (IS) strategy, showing that EIS is at least equivalent, if …
Persistent link: https://www.econbiz.de/10014183458
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Relating stochastic volatility estimation methods
Bos, Charles S. - 2011
Estimation of the volatility of time series has taken off since the introduction of the GARCH and stochastic volatility models. While variants of the GARCH model are applied in scores of articles, use of the stochastic volatility model is less widespread. In this article it is argued that one...
Persistent link: https://www.econbiz.de/10011386124
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Simulated Likelihood Estimators for Discretely Observed Jump-Diffusions
Giesecke, Kay - 2019
This paper develops an unbiased Monte Carlo approximation to the transition density of a jump-diffusion process with state-dependent drift, volatility, jump intensity, and jump magnitude. The approximation is used to construct a likelihood estimator of the parameters of a jump-diffusion observed...
Persistent link: https://www.econbiz.de/10012904646
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Modeling Stock Prices by Multifractional Brownian Motion : An Improved Estimation of the Pointwise Regularity
Bianchi, Sergio - 2017
The paper deals with the problem of estimating the pointwise regularity of the multifractional Brownian motion, assumed as a model of the stock price dynamics. We (a) correct the shifting bias affecting a class of absolute moment-based estimators and (b) build a data-driven algorithm in order to...
Persistent link: https://www.econbiz.de/10012975887
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Maximum entropy evaluation of asymptotic hedging error under a generalised jump-diffusion model
Fard, Farzad Alavi; Doko Tchatoka, Firmin; … - In: Journal of risk and financial management : JRFM 14 (2021) 3/97, pp. 1-19
In this paper we propose a maximum entropy estimator for the asymptotic distribution of the hedging error for options. Perfect replication of financial derivatives is not possible, due to market incompleteness and discrete-time hedging. We derive the asymptotic hedging error for options under a...
Persistent link: https://www.econbiz.de/10012484861