Stochastic volatility

While the stochastic volatility (SV) generalization has been shown to improve the explanatory power over the BlackScholes model, empirical implications of SV models on option pricing have not yet been adequately tested. The purpose of this paper is to ﬁrst estimate a multivariate SV model using the efﬁcient method of moments (EMM) technique from observations of underlying state variables and then investigate the respective effect of stochastic interest rates, systematic volatility and idiosyncratic volatility on option prices....
48p batoan 16072009 169 45 Download

ADVANCED TEXTS IN ECONOMETRICS General Editors Manuel Arellano Guido Imbens Grayham E. Mizon Adrian Pagan Mark Watson Advisory Editor C. W. J. Granger.Other Advanced Texts in conometrics ARCH: Selected Readings Edited by Robert F. Engle Asymptotic Theory for Integrated Processes By H. Peter Boswijk Bayesian Inference in Dynamic Econometric Models By Luc Bauwens, Michel Lubrano, and JeanFran¸ois Richard c Cotegration, Error Correction, and the Econometric Analysis of NonStationary Data By Anindya Banerjee, Juan J. ...
534p transang3 29092012 49 12 Download

Stochastic volatility (SV) is the main concept used in the fields of financial economics and mathematical finance to deal with timevarying volatility in financial markets. In this book I bring together some of the main papers which have influenced the field of the econometrics of stochastic volatility with the hope that this will allow students and scholars to place this literature in a wider context.
534p vigro23 29082012 22 10 Download

It is a pleasure to edit the second volume of papers presented at the Mathematical Finance Seminar of New York University. These articles, written by some of the leading experts in financial modeling cover a variety of topics in this field. The volume is divided into three parts: (I) Estimation and DataDriven Models, (II) Model Calibration and Option Volatility and (III) Pricing and Hedging. The papers in the section on "Estimation and DataDriven Models" develop new econometric techniques for finance and, in some cases, apply them to derivatives.
379p haiduong_1 03042013 22 13 Download

In this note we consider the filtering problem for financial volatility that is an OrnsteinUlhenbeck process from point process observation. This problem is investigated for a MarkovFeller process of which the OrnsteinUlhenbeck process is a particular case.
10p tuanlocmuido 19122012 24 2 Download

Driven by the necessity to incorporate the observed stylized features of asset prices, continuoustime stochastic modeling has taken a predominant role in the financial literature over the past two decades. Most of the proposed models are particular cases of a stochastic volatility component driven by a Wiener process superposed with a purejump component accounting for the
0p baobinh1311 25092012 18 8 Download

Continuoustime modeling in finance, though introduced by Louis Bachelier's 1900 thesis on the theory of speculation, really started with Merton's seminal work in the 1970s. Since then, the continuoustime paradigm has proved to be an immensely useful tool in finance and more generally economics. Continuoustime models are widely used to study issues that include the decision to optimally consume, save, and invest, portfolio choice under a variety of constraints, contingent claim pricing, capital accumulation, resource extraction, game theory, and more recently contract theory....
379p camchuong_1 10122012 19 5 Download

Financial markets have undergone tremendous growth and dramatic changes in the past two decades, with the volume of daily trading in currency markets hitting over a trillion US dollars and hundreds of billions of dollars in bond and stock markets. Deregulation and globalization have led to largescale capital flows; this has raised new problems for finance as well as has further spurred competition among banks and financial institutions.
334p haiduong_1 03042013 19 5 Download

We build a threefactor termstructure of interest rates model and use it to price corporate bonds. The first two factors allow the riskfree term structure to shift and tilt. The third factor generates a stochastic creditrisk premium. To implement the model, we apply the Peterson and Stapleton (2002) diffusion approximation methodology. The method approximates a correlated and laggeddependent lognormal diffusion processes. We then price options on creditsensitive bonds.
27p taisaocothedung 12012013 19 3 Download

Our methodology is based on a dynamic stochastic general equilibrium (DSGE) calibrated model augmented with endogenous market structures in line with recent developments in the macroeconomic literature (see Etro, 2009, for a survey). This model is perturbed with a realistic structural change to the cost structure, with the purpose to study the short and long term reactions of the economy. Therefore, our methodology is based on a solid theoretical framework and provides results that can be easily replicated by economists. However, it has some limitations that we need to point out.
48p bi_ve_sau 05022013 14 3 Download

Issuance of Stability Bonds under joint and several guarantees would a priori lead to a situation where the prohibition on bailing out would be breached. In such a situation, a Member State would indeed be held liable irrespective of its 'regular' contributing key, should another Member State be unable to honour its financial commitments. In this case, an amendment to the Treaty would be necessary.
33p enter1cai 16012013 14 2 Download

Web search engine: Markov chain theory Data Mining, Machine Learning: Data mining, Machine learning: Stochastic gradient, Markov chain Monte Carlo, Image processing: Markov random fields, Design of wireless communication systems: random matrix theory, Optimization of engineering processes: simulated annealing, genetic algorithms, Finance (option pricing, volatility models): Monte Carlo, dynamic models, Design of atomic bomb (Los Alamos): Markov chain Monte Carlo.
16p quangchien2205 30032011 33 4 Download