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Dissertations / Theses on the topic 'Factor stochastic volatility'

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1

Hafner, Reinhold. "Stochastic implied volatility : a factor-based model /." Berlin [u.a.] : Springer, 2004. http://www.loc.gov/catdir/enhancements/fy0813/2004109369-d.html.

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2

Häfner, Reinhold. "Stochastic implied volatility : a factor-based model /." Berlin ; New York : Springer, 2004. http://www.loc.gov/catdir/enhancements/fy0813/2004109369-d.html.

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3

Ahy, Nathaniel, and Mikael Sierra. "Implied Volatility Surface Approximation under a Two-Factor Stochastic Volatility Model." Thesis, Mälardalens högskola, Akademin för utbildning, kultur och kommunikation, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-40039.

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Due to recent research disproving old claims in financial mathematics such as constant volatility in option prices, new approaches have been incurred to analyze the implied volatility, namely stochastic volatility models. The use of stochastic volatility in option pricing is a relatively new and unexplored field of research with a lot of unknowns, where new answers are of great interest to anyone practicing valuation of derivative instruments such as options. With both single and two-factor stochastic volatility models containing various correlation structures with respect to the asset price and
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Kastner, Gregor, Sylvia Frühwirth-Schnatter, and Hedibert Freitas Lopes. "Efficient Bayesian Inference for Multivariate Factor Stochastic Volatility Models." WU Vienna University of Economics and Business, 2016. http://epub.wu.ac.at/4875/1/research_report_updated.pdf.

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We discuss efficient Bayesian estimation of dynamic covariance matrices in multivariate time series through a factor stochastic volatility model. In particular, we propose two interweaving strategies (Yu and Meng, Journal of Computational and Graphical Statistics, 20(3), 531-570, 2011) to substantially accelerate convergence and mixing of standard MCMC approaches. Similar to marginal data augmentation techniques, the proposed acceleration procedures exploit non-identifiability issues which frequently arise in factor models. Our new interweaving strategies are easy to implement and come at almo
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5

Rafiou, AS. "Foreign Exchange Option Valuation under Stochastic Volatility." University of the Western Cape, 2009. http://hdl.handle.net/11394/7777.

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>Magister Scientiae - MSc<br>The case of pricing options under constant volatility has been common practise for decades. Yet market data proves that the volatility is a stochastic phenomenon, this is evident in longer duration instruments in which the volatility of underlying asset is dynamic and unpredictable. The methods of valuing options under stochastic volatility that have been extensively published focus mainly on stock markets and on options written on a single reference asset. This work probes the effect of valuing European call option written on a basket of currencies, under constant
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6

Rios, Benavides Renato, and Chrysafis Bourelos. "Times Series Analysis of Calibrated Parameters of Two-factor Stochastic Volatility Model." Thesis, Mälardalens högskola, Akademin för utbildning, kultur och kommunikation, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-44644.

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Stochastic volatility models have become essential for financial modelling and forecasting.The present thesis works with a two-factor stochastic volatility model that is reduced to four parameters. We start by making the case for the model that best fits data, use that modelto produce said parameters and then analyse the time series of these parameters. Suitable ARIMA models were then used to forecast the parameters and in turn, the implied volatilities.It was established that fitting the model for different groups of maturities produced better results. Moreover, we managed to reduce the forec
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7

Hauzenberger, Niko, Maximilian Böck, Michael Pfarrhofer, Anna Stelzer, and Gregor Zens. "Implications of Macroeconomic Volatility in the Euro Area." 261, 2018. http://epub.wu.ac.at/6246/1/wp261.pdf.

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In this paper, we estimate a Bayesian vector autoregressive (VAR) model with factor stochastic volatility in the error term to assess the effects of an uncertainty shock in the Euro area (EA). This allows us to incorporate uncertainty directly into the econometric framework and treat it as a latent quantity. Only a limited number of papers estimates impacts of uncertainty and macroeconomic consequences jointly, and most literature in this sphere is based on single countries. We analyze the special case of a shock restricted to the Euro area, whose countries are highly related by definition. Am
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8

Ladkau, Marcel. "Stochastic volatility Libor modeling and efficient algorithms for optimal stopping problems." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät, 2016. http://dx.doi.org/10.18452/17559.

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Die vorliegende Arbeit beschäftigt sich mit verschiedenen Aspekten der Finanzmathematik. Ein erweitertes Libor Markt Modell wird betrachtet, welches genug Flexibilität bietet, um akkurat an Caplets und Swaptions zu kalibrieren. Weiterhin wird die Bewertung komplexerer Finanzderivate, zum Beispiel durch Simulation, behandelt. In hohen Dimensionen können solche Simulationen sehr zeitaufwendig sein. Es werden mögliche Verbesserungen bezüglich der Komplexität aufgezeigt, z.B. durch Faktorreduktion. Zusätzlich wird das sogenannte Andersen-Simulationsschema von einer auf mehrere Dimensionen erwe
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9

Crespo, Cuaresma Jesus, Florian Huber, and Luca Onorante. "The macroeconomic effects of international uncertainty shocks." WU Vienna University of Economics and Business, 2017. http://epub.wu.ac.at/5462/1/wp245.pdf.

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We propose a large-scale Bayesian VAR model with factor stochastic volatility to investigate the macroeconomic consequences of international uncertainty shocks on the G7 countries. The factor structure enables us to identify an international uncertainty shock by assuming that it is the factor most correlated with forecast errors related to equity markets and permits fast sampling of the model. Our findings suggest that the estimated uncertainty factor is strongly related to global equity price volatility, closely tracking other prominent measures commonly adopted to assess global uncertainty.
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10

Moura, Rodolfo Chiabai. "Spillovers and jumps in global markets: a comparative analysis." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/96/96131/tde-02082018-160351/.

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We analyze the relation between volatility spillovers and jumps in financial markets. For this, we compared the volatility spillover index proposed by Diebold and Yilmaz (2009) with a global volatility component, estimated through a multivariate stochastic volatility model with jumps in the mean and in the conditional volatility. This model allows a direct dating of events that alter the global volatility structure, based on a permanent/transitory decomposition in the structure of returns and volatilities, and also the estimation of market risk measures. We conclude that the multivariate stoch
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11

Kastner, Gregor. "Sparse Bayesian Time-Varying Covariance Estimation in Many Dimensions." WU Vienna University of Economics and Business, 2016. http://epub.wu.ac.at/5172/1/resreport129.pdf.

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Dynamic covariance estimation for multivariate time series suffers from the curse of dimensionality. This renders parsimonious estimation methods essential for conducting reliable statistical inference. In this paper, the issue is addressed by modeling the underlying co-volatility dynamics of a time series vector through a lower dimensional collection of latent time-varying stochastic factors. Furthermore, we apply a Normal-Gamma prior to the elements of the factor loadings matrix. This hierarchical shrinkage prior effectively pulls the factor loadings of unimportant factors towards zero, ther
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12

Huber, Florian. "Dealing with heterogeneity in panel VARs using sparse finite mixtures." WU Vienna University of Economics and Business, 2018. http://epub.wu.ac.at/6247/1/wp262.pdf.

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In this paper, we provide a parsimonious means of estimating panel VARs with stochastic volatility. We assume that coefficients associated with domestic lagged endogenous variables arise from a finite mixture of Gaussian distribution. Shrinkage on the cluster size is introduced through suitable priors on the component weights and cluster-relevant quantities are identified through novel normal-gamma shrinkage priors. To assess whether dynamic interdependencies between units are needed, we moreover impose shrinkage priors on the coefficients related to other countries' endogenous variables. Fi
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13

Lee, Hyoung Il. "Stochastic volatility models with persistent latent factors: theory and its applications to asset prices." Texas A&M University, 2008. http://hdl.handle.net/1969.1/86017.

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We consider the stochastic volatility model with smooth transition and persistent la- tent factors. We argue that this model has advantages over the conventional stochastic model for the persistent volatility factor. Though the linear filtering is widely used in the state space model, the simulation result, as well as theory, shows that it does not work in our model. So we apply the density-based filtering method; in particular, we develop two methods to get solutions. One is the conventional approach using the Maximum Likelihood estimation and the other is the Bayesian approach using Gibbs sa
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14

Backwell, Alexander. "Term structure models with unspanned factors and unspanned stochastic volatility." Doctoral thesis, University of Cape Town, 2018. http://hdl.handle.net/11427/29460.

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Certain models of the term structure of interest rates exhibit unspanned stochastic volatility (USV). A model has this property if it involves a source of stochastic variation — called an unspanned factor — that does not affect the model’s interest rates directly, but does affect the extent to which future interests are liable to change (that is, interest-rate volatility). This thesis is concerned with these models, from a variety of perspectives. Firstly, the theoretical foundation of the USV property is addressed. Formal definitions of unspanned factors and USV are developed, generalising on
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15

Diallo, Ibrahima Amadou. "Exchange rates policy and productivity." Thesis, Clermont-Ferrand 1, 2013. http://www.theses.fr/2013CLF10405/document.

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Cette thèse étudie comment le taux de change effectif réel (TCER) et ses mesures associées (volatilité du TCER et désalignement du TCER) affectent la croissance de la productivité totale des facteurs (CPTF). Elle analyse également les canaux par lesquels le TCER et ses mesures associées agissent sur la productivité totale des facteurs (PTF). La première partie étudie comment le TCER lui-Même, d'une part, et la volatilité du TCER, d'autre part, influencent la productivité. Une analyse du lien entre le niveau du TCER et la PTF dans le chapitre 1 indique qu'une appréciation de taux de change caus
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16

Tang, Meini. "BICNet: A Bayesian Approach for Estimating Task Effects on Intrinsic Connectivity Networks in fMRI Data." Thesis, 2020. http://hdl.handle.net/10754/666140.

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Intrinsic connectivity networks (ICNs) refer to brain functional networks that are consistently found under various conditions, during tasks or at rest. Some studies demonstrated that while some stimuli do not impact intrinsic connectivity, other stimuli actually activate intrinsic connectivity through suppression, excitation, moderation or modi cation. Most analyses of functional magnetic resonance imaging (fMRI) data use ad-hoc methods to estimate the latent structure of ICNs. Modeling the effects on ICNs has also not been fully investigated. Bayesian Intrinsic Connectivity Network (BICNet)
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17

Park, Ha-Il. "Term Structure Dynamics with Macroeconomic Factors." 2009. http://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7456.

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Affine term structure models (ATSMs) are known to have a trade-off in predicting future Treasury yields and fitting the time-varying volatility of interest rates. First, I empirically study the role of macroeconomic variables in simultaneously achieving these two goals under affine models. To this end, I incorporate a liquidity demand theory via a measure of the velocity of money into affine models. I find that this considerably reduces the statistical tension between matching the first and second moments of interest rates. In terms of forecasting yields, the models with the velocity of money
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18

Dovonon, Prosper. "Common factors in stochastic volatility of asset returns and new developments of the generalized method of moments." Thèse, 2007. http://hdl.handle.net/1866/1962.

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19

Mergner, Sascha. "Applications of Advanced Time Series Models to Analyze the Time-varying Relationship between Macroeconomics, Fundamentals and Pan-European Industry Portfolios." Doctoral thesis, 2008. http://hdl.handle.net/11858/00-1735-0000-000D-F159-E.

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20

Kemoe, Laurent. "Three essays in macro-finance, international economics and macro-econometrics." Thèse, 2017. http://hdl.handle.net/1866/19308.

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This thesis brings new evidence on different strands of the literature in macro-finance, international economics and macroeconometrics. The first two chapters combine both theoretical models and empirical techniques to deepen the analysis of important economic phenomena such as the effects of economic policy uncertainty on financial markets, and convergence between emerging market economies and advanced economies on these markets. The third chapter of the thesis, which is co-authored with Hafedh Bouakez, contributes to the literature on the identification of news shocks about future productivi
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21

El-Khatib, Mayar. "Highway Development Decision-Making Under Uncertainty: Analysis, Critique and Advancement." Thesis, 2010. http://hdl.handle.net/10012/5741.

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While decision-making under uncertainty is a major universal problem, its implications in the field of transportation systems are especially enormous; where the benefits of right decisions are tremendous, the consequences of wrong ones are potentially disastrous. In the realm of highway systems, decisions related to the highway configuration (number of lanes, right of way, etc.) need to incorporate both the traffic demand and land price uncertainties. In the literature, these uncertainties have generally been modeled using the Geometric Brownian Motion (GBM) process, which has been used extens
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