Simulation-based Econometric Methods PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Simulation-based Econometric Methods PDF full book. Access full book title Simulation-based Econometric Methods by Christian Gouriéroux. Download full books in PDF and EPUB format.
Author: Christian Gouriéroux
Publisher: OUP Oxford
ISBN: 019152509X
Category : Business & Economics
Languages : en
Pages : 190
Get Book Here
Book Description
This book introduces a new generation of statistical econometrics. After linear models leading to analytical expressions for estimators, and non-linear models using numerical optimization algorithms, the availability of high- speed computing has enabled econometricians to consider econometric models without simple analytical expressions. The previous difficulties presented by the presence of integrals of large dimensions in the probability density functions or in the moments can be circumvented by a simulation-based approach. After a brief survey of classical parametric and semi-parametric non-linear estimation methods and a description of problems in which criterion functions contain integrals, the authors present a general form of the model where it is possible to simulate the observations. They then move to calibration problems and the simulated analogue of the method of moments, before considering simulated versions of maximum likelihood, pseudo-maximum likelihood, or non-linear least squares. The general principle of indirect inference is presented and is then applied to limited dependent variable models and to financial series.
Author: Christian Gouriéroux
Publisher: OUP Oxford
ISBN: 019152509X
Category : Business & Economics
Languages : en
Pages : 190
Get Book Here
Book Description
This book introduces a new generation of statistical econometrics. After linear models leading to analytical expressions for estimators, and non-linear models using numerical optimization algorithms, the availability of high- speed computing has enabled econometricians to consider econometric models without simple analytical expressions. The previous difficulties presented by the presence of integrals of large dimensions in the probability density functions or in the moments can be circumvented by a simulation-based approach. After a brief survey of classical parametric and semi-parametric non-linear estimation methods and a description of problems in which criterion functions contain integrals, the authors present a general form of the model where it is possible to simulate the observations. They then move to calibration problems and the simulated analogue of the method of moments, before considering simulated versions of maximum likelihood, pseudo-maximum likelihood, or non-linear least squares. The general principle of indirect inference is presented and is then applied to limited dependent variable models and to financial series.
Author: Makoto Takahashi
Publisher: Springer Nature
ISBN: 981990935X
Category : Business & Economics
Languages : en
Pages : 120
Get Book Here
Book Description
This treatise delves into the latest advancements in stochastic volatility models, highlighting the utilization of Markov chain Monte Carlo simulations for estimating model parameters and forecasting the volatility and quantiles of financial asset returns. The modeling of financial time series volatility constitutes a crucial aspect of finance, as it plays a vital role in predicting return distributions and managing risks. Among the various econometric models available, the stochastic volatility model has been a popular choice, particularly in comparison to other models, such as GARCH models, as it has demonstrated superior performance in previous empirical studies in terms of fit, forecasting volatility, and evaluating tail risk measures such as Value-at-Risk and Expected Shortfall. The book also explores an extension of the basic stochastic volatility model, incorporating a skewed return error distribution and a realized volatility measurement equation. The concept of realized volatility, a newly established estimator of volatility using intraday returns data, is introduced, and a comprehensive description of the resulting realized stochastic volatility model is provided. The text contains a thorough explanation of several efficient sampling algorithms for latent log volatilities, as well as an illustration of parameter estimation and volatility prediction through empirical studies utilizing various asset return data, including the yen/US dollar exchange rate, the Dow Jones Industrial Average, and the Nikkei 225 stock index. This publication is highly recommended for readers with an interest in the latest developments in stochastic volatility models and realized stochastic volatility models, particularly in regards to financial risk management.
Author: Charles-albert Lehalle
Publisher: World Scientific
ISBN: 9813231149
Category : Business & Economics
Languages : en
Pages : 366
Get Book Here
Book Description
This book exposes and comments on the consequences of Reg NMS and MiFID on market microstructure. It covers changes in market design, electronic trading, and investor and trader behaviors. The emergence of high frequency trading and critical events like the'Flash Crash' of 2010 are also analyzed in depth.Using a quantitative viewpoint, this book explains how an attrition of liquidity and regulatory changes can impact the whole microstructure of financial markets. A mathematical Appendix details the quantitative tools and indicators used through the book, allowing the reader to go further independently.This book is written by practitioners and theoretical experts and covers practical aspects (like the optimal infrastructure needed to trade electronically in modern markets) and abstract analyses (like the use on entropy measurements to understand the progress of market fragmentation).As market microstructure is a recent academic field, students will benefit from the book's overview of the current state of microstructure and will use the Appendix to understand important methodologies. Policy makers and regulators will use this book to access theoretical analyses on real cases. For readers who are practitioners, this book delivers data analysis and basic processes like the designs of Smart Order Routing and trade scheduling algorithms.In this second edition, the authors have added a large section on orderbook dynamics, showing how liquidity can predict future price moves, and how High Frequency Traders can profit from it. The section on market impact has also been updated to show how buying or selling pressure moves prices not only for a few hours, but even for days, and how prices relax (or not) after a period of intense pressure.Further, this edition includes pages on Dark Pools, Circuit Breakers and added information outside of Equity Trading, because MiFID 2 is likely to push fixed income markets towards more electronification. The authors explore what is to be expected from this change in microstructure. The appendix has also been augmented to include the propagator models (for intraday price impact), a simple version of Kyle's model (1985) for daily market impact, and a more sophisticated optimal trading framework, to support the design of trading algorithms.
Author: William Johnson
Publisher: HiTeX Press
ISBN:
Category : Business & Economics
Languages : en
Pages : 524
Get Book Here
Book Description
"Volatility Modeling in Finance: Techniques for Trading Strategies" offers an incisive look into the pivotal concept of volatility, essential for anyone navigating the financial markets. This comprehensive guide demystifies the intricate dynamics of volatility, combining theoretical insights with practical applications. From understanding the foundational types of volatility to leveraging advanced models like GARCH and stochastic frameworks, the book equips readers with the necessary tools to assess risk and seize opportunities within fluctuating markets. Each chapter is meticulously structured to build on core principles, while incorporating cutting-edge techniques such as machine learning and algorithmic trading. Whether you're a novice seeking to deepen your understanding or a seasoned professional aiming to refine your strategies, this book presents a wealth of knowledge, enriched with case studies and real-world examples. Through its detailed exploration, readers will gain the foresight and strategies needed to capitalize on volatility, transforming a formidable challenge into a powerful ally in the pursuit of financial success.
Author: Hagen Kleinert
Publisher: World Scientific
ISBN: 9814273554
Category : Science
Languages : en
Pages : 1626
Get Book Here
Book Description
This is the fifth, expanded edition of the comprehensive textbook published in 1990 on the theory and applications of path integrals. It is the first book to explicitly solve path integrals of a wide variety of nontrivial quantum-mechanical systems, in particular the hydrogen atom. The solutions have been made possible by two major advances. The first is a new euclidean path integral formula which increases the restricted range of applicability of Feynman's time-sliced formula to include singular attractive 1/r- and 1/r2-potentials. The second is a new nonholonomic mapping principle carrying physical laws in flat spacetime to spacetimes with curvature and torsion, which leads to time-sliced path integrals that are manifestly invariant under coordinate transformations. In addition to the time-sliced definition, the author gives a perturbative, coordinate-independent definition of path integrals, which makes them invariant under coordinate transformations. A consistent implementation of this property leads to an extension of the theory of generalized functions by defining uniquely products of distributions. The powerful FeynmanKleinert variational approach is explained and developed systematically into a variational perturbation theory which, in contrast to ordinary perturbation theory, produces convergent results. The convergence is uniform from weak to strong couplings, opening a way to precise evaluations of analytically unsolvable path integrals in the strong-coupling regime where they describe critical phenomena. Tunneling processes are treated in detail, with applications to the lifetimes of supercurrents, the stability of metastable thermodynamic phases, and thelarge-order behavior of perturbation expansions. A variational treatment extends the range of validity to small barriers. A corresponding extension of the large-order perturbation theory now also applies to small orders. Special attention is devoted to path integrals with topological restrictions needed to understand the statistical properties of elementary particles and the entanglement phenomena in polymer physics and biophysics. The ChernSimons theory of particles with fractional statistics (anyons) is introduced and applied to explain the fractional quantum Hall effect. The relevance of path integrals to financial markets is discussed, and improvements of the famous BlackScholes formula for option prices are developed which account for the fact, recently experienced in the world markets, that large fluctuations occur much more frequently than in Gaussian distributions.
Author: Stephen J. Taylor
Publisher: World Scientific
ISBN: 9812770852
Category : Business & Economics
Languages : en
Pages : 297
Get Book Here
Book Description
This book contains several innovative models for the prices of financial assets. First published in 1986, it is a classic text in the area of financial econometrics. It presents ARCH and stochastic volatility models that are often used and cited in academic research and are applied by quantitative analysts in many banks. Another often-cited contribution of the first edition is the documentation of statistical characteristics of financial returns, which are referred to as stylized facts. This second edition takes into account the remarkable progress made by empirical researchers during the past two decades from 1986 to 2006. In the new Preface, the author summarizes this progress in two key areas: firstly, measuring, modelling and forecasting volatility; and secondly, detecting and exploiting price trends. Sample Chapter(s). Chapter 1: Introduction (1,134 KB). Contents: Features of Financial Returns; Modelling Price Volatility; Forecasting Standard Deviations; The Accuracy of Autocorrelation Estimates; Testing the Random Walk Hypothesis; Forecasting Trends in Prices; Evidence Against the Efficiency of Futures Markets; Valuing Options; Appendix: A Computer Program for Modelling Financial Time Series. Readership: Academic researchers in finance & economics; quantitative analysts.
Author:
Publisher: Elsevier
ISBN: 0444643125
Category : Mathematics
Languages : en
Pages : 332
Get Book Here
Book Description
Conceptual Econometrics Using R, Volume 41 provides state-of-the-art information on important topics in econometrics, including quantitative game theory, multivariate GARCH, stochastic frontiers, fractional responses, specification testing and model selection, exogeneity testing, causal analysis and forecasting, GMM models, asset bubbles and crises, corporate investments, classification, forecasting, nonstandard problems, cointegration, productivity and financial market jumps and co-jumps, among others. - Presents chapters authored by distinguished, honored researchers who have received awards from the Journal of Econometrics or the Econometric Society - Includes descriptions and links to resources and free open source R, allowing readers to not only use the tools on their own data, but also jumpstart their understanding of the state-of-the-art
Author: Yacine Ait-Sahalia
Publisher: Elsevier
ISBN: 0444535497
Category : Business & Economics
Languages : en
Pages : 385
Get Book Here
Book Description
Applied financial econometrics subjects are featured in this second volume, with papers that survey important research even as they make unique empirical contributions to the literature. These subjects are familiar: portfolio choice, trading volume, the risk-return tradeoff, option pricing, bond yields, and the management, supervision, and measurement of extreme and infrequent risks. Yet their treatments are exceptional, drawing on current data and evidence to reflect recent events and scholarship. A landmark in its coverage, this volume should propel financial econometric research for years. - Presents a broad survey of current research - Contributors are leading econometricians - Offers a clarity of method and explanation unavailable in other financial econometrics collections
Author: Peter H. Rossi
Publisher: Elsevier
ISBN: 0080511872
Category : Business & Economics
Languages : en
Pages : 505
Get Book Here
Book Description
This essay collection focuses on the relationship between continuous time models and Autoregressive Conditionally Heteroskedastic (ARCH) models and applications. For the first time, Modelling Stock Market Volatility provides new insights about the links between these two models and new work on practical estimation methods for continuous time models. Featuring the pioneering scholarship of Daniel Nelson, the text presents research about the discrete time model, continuous time limits and optimal filtering of ARCH models, and the specification and estimation of continuous time processes. This work will lead to a rapid growth in their empirical application as they are increasingly subjected to routine specification testing. - Provides for the first time new insights on the links between continuous time and ARCH models - Collects seminal scholarship by some of the most renowned researchers in finance and econometrics - Captures complex arguments underlying the approximation and proper statistical modelling of continuous time volatility dynamics
Author: Jean Jacod
Publisher: Springer Science & Business Media
ISBN: 3642241271
Category : Mathematics
Languages : en
Pages : 596
Get Book Here
Book Description
In applications, and especially in mathematical finance, random time-dependent events are often modeled as stochastic processes. Assumptions are made about the structure of such processes, and serious researchers will want to justify those assumptions through the use of data. As statisticians are wont to say, “In God we trust; all others must bring data.” This book establishes the theory of how to go about estimating not just scalar parameters about a proposed model, but also the underlying structure of the model itself. Classic statistical tools are used: the law of large numbers, and the central limit theorem. Researchers have recently developed creative and original methods to use these tools in sophisticated (but highly technical) ways to reveal new details about the underlying structure. For the first time in book form, the authors present these latest techniques, based on research from the last 10 years. They include new findings. This book will be of special interest to researchers, combining the theory of mathematical finance with its investigation using market data, and it will also prove to be useful in a broad range of applications, such as to mathematical biology, chemical engineering, and physics.
