Download or read book Estimation of Time varying Parameter Multifactor Asset Pricing Models Using Kalman Filtering Techniques written by Thomas Mendoza-Hauptmann and published by . This book was released on 1994 with total page 568 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Kalman Filter in Finance written by C. Wells and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: A non-technical introduction to the question of modeling with time-varying parameters, using the beta coefficient from Financial Economics as the main example. After a brief introduction to this coefficient for those not versed in finance, the book presents a number of rather well known tests for constant coefficients and then performs these tests on data from the Stockholm Exchange. The Kalman filter is then introduced and a simple example is used to demonstrate the power of the filter. The filter is then used to estimate the market model with time-varying betas. The book concludes with further examples of how the Kalman filter may be used in estimation models used in analyzing other aspects of finance. Since both the programs and the data used in the book are available for downloading, the book is especially valuable for students and other researchers interested in learning the art of modeling with time varying coefficients.

Download or read book Applications of State Space Models in Finance written by Sascha Mergner and published by Universitätsverlag Göttingen. This book was released on 2009 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: State space models play a key role in the estimation of time-varying sensitivities in financial markets. The objective of this book is to analyze the relative merits of modern time series techniques, such as Markov regime switching and the Kalman filter, to model structural changes in the context of widely used concepts in finance. The presented material will be useful for financial economists and practitioners who are interested in taking time-variation in the relationship between financial assets and key economic factors explicitly into account. The empirical part illustrates the application of the various methods under consideration. As a distinctive feature, it includes a comprehensive analysis of the ability of time-varying coefficient models to estimate and predict the conditional nature of systematic risks for European industry portfolios.

Download or read book Financial Pricing Models in Continuous Time and Kalman Filtering written by B.Philipp Kellerhals and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: Straight after its invention in the early sixties, the Kalman filter approach became part of the astronautical guidance system of the Apollo project and therefore received immediate acceptance in the field of electrical engineer ing. This sounds similar to the well known success story of the Black-Scholes model in finance, which has been implemented by the Chicago Board of Op tions Exchange (CBOE) within a few month after its publication in 1973. Recently, the Kalman filter approach has been discovered as a comfortable estimation tool in continuous time finance, bringing together seemingly un related methods from different fields. Dr. B. Philipp Kellerhals contributes to this topic in several respects. Specialized versions of the Kalman filter are developed and implemented for three different continuous time pricing models: A pricing model for closed-end funds, taking advantage from the fact, that the net asset value is observable, a term structure model, where the market price of risk itself is a stochastic variable, and a model for electricity forwards, where the volatility of the price process is stochastic. Beside the fact that these three models can be treated independently, the book as a whole gives the interested reader a comprehensive account of the requirements and capabilities of the Kalman filter applied to finance models. While the first model uses a linear version of the filter, the second model using LIBOR and swap market data requires an extended Kalman filter. Finally, the third model leads to a non-linear transition equation of the filter algorithm.

Download or read book Smoothing Filtering and Prediction written by Garry Einicke and published by BoD – Books on Demand. This book was released on 2012-02-24 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the classical smoothing, filtering and prediction techniques together with some more recently developed embellishments for improving performance within applications. It aims to present the subject in an accessible way, so that it can serve as a practical guide for undergraduates and newcomers to the field. The material is organised as a ten-lecture course. The foundations are laid in Chapters 1 and 2, which explain minimum-mean-square-error solution construction and asymptotic behaviour. Chapters 3 and 4 introduce continuous-time and discrete-time minimum-variance filtering. Generalisations for missing data, deterministic inputs, correlated noises, direct feedthrough terms, output estimation and equalisation are described. Chapter 5 simplifies the minimum-variance filtering results for steady-state problems. Observability, Riccati equation solution convergence, asymptotic stability and Wiener filter equivalence are discussed. Chapters 6 and 7 cover the subject of continuous-time and discrete-time smoothing. The main fixed-lag, fixed-point and fixed-interval smoother results are derived. It is shown that the minimum-variance fixed-interval smoother attains the best performance. Chapter 8 attends to parameter estimation. As the above-mentioned approaches all rely on knowledge of the underlying model parameters, maximum-likelihood techniques within expectation-maximisation algorithms for joint state and parameter estimation are described. Chapter 9 is concerned with robust techniques that accommodate uncertainties within problem specifications. An extra term within Riccati equations enables designers to trade-off average error and peak error performance. Chapter 10 rounds off the course by applying the afore-mentioned linear techniques to nonlinear estimation problems. It is demonstrated that step-wise linearisations can be used within predictors, filters and smoothers, albeit by forsaking optimal performance guarantees.

Download or read book Multi factor Models and Signal Processing Techniques written by Serges Darolles and published by John Wiley & Sons. This book was released on 2013-08-02 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: With recent outbreaks of multiple large-scale financial crises, amplified by interconnected risk sources, a new paradigm of fund management has emerged. This new paradigm leverages “embedded” quantitative processes and methods to provide more transparent, adaptive, reliable and easily implemented “risk assessment-based” practices. This book surveys the most widely used factor models employed within the field of financial asset pricing. Through the concrete application of evaluating risks in the hedge fund industry, the authors demonstrate that signal processing techniques are an interesting alternative to the selection of factors (both fundamentals and statistical factors) and can provide more efficient estimation procedures, based on lq regularized Kalman filtering for instance. With numerous illustrative examples from stock markets, this book meets the needs of both finance practitioners and graduate students in science, econometrics and finance. Contents Foreword, Rama Cont. 1. Factor Models and General Definition. 2. Factor Selection. 3. Least Squares Estimation (LSE) and Kalman Filtering (KF) for Factor Modeling: A Geometrical Perspective. 4. A Regularized Kalman Filter (rgKF) for Spiky Data. Appendix: Some Probability Densities. About the Authors Serge Darolles is Professor of Finance at Paris-Dauphine University, Vice-President of QuantValley, co-founder of QAMLab SAS, and member of the Quantitative Management Initiative (QMI) scientific committee. His research interests include financial econometrics, liquidity and hedge fund analysis. He has written numerous articles, which have been published in academic journals. Patrick Duvaut is currently the Research Director of Telecom ParisTech, France. He is co-founder of QAMLab SAS, and member of the Quantitative Management Initiative (QMI) scientific committee. His fields of expertise encompass statistical signal processing, digital communications, embedded systems and QUANT finance. Emmanuelle Jay is co-founder and President of QAMLab SAS. She has worked at Aequam Capital as co-head of R&D since April 2011 and is member of the Quantitative Management Initiative (QMI) scientific committee. Her research interests include SP for finance, quantitative and statistical finance, and hedge fund analysis.

Download or read book Multi moment Asset Allocation and Pricing Models written by Emmanuel Jurczenko and published by John Wiley & Sons. This book was released on 2006-10-02 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: While mainstream financial theories and applications assume that asset returns are normally distributed and individual preferences are quadratic, the overwhelming empirical evidence shows otherwise. Indeed, most of the asset returns exhibit “fat-tails” distributions and investors exhibit asymmetric preferences. These empirical findings lead to the development of a new area of research dedicated to the introduction of higher order moments in portfolio theory and asset pricing models. Multi-moment asset pricing is a revolutionary new way of modeling time series in finance which allows various degrees of long-term memory to be generated. It allows risk and prices of risk to vary through time enabling the accurate valuation of long-lived assets. This book presents the state-of-the art in multi-moment asset allocation and pricing models and provides many new developments in a single volume, collecting in a unified framework theoretical results and applications previously scattered throughout the financial literature. The topics covered in this comprehensive volume include: four-moment individual risk preferences, mathematics of the multi-moment efficient frontier, coherent asymmetric risks measures, hedge funds asset allocation under higher moments, time-varying specifications of (co)moments and multi-moment asset pricing models with homogeneous and heterogeneous agents. Written by leading academics, Multi-moment Asset Allocation and Pricing Models offers a unique opportunity to explore the latest findings in this new field of research.

Download or read book Filtering Methods for the Estimation of the Long Run Risk Asset Pricing Model written by Eva-Maria Küchlin and published by . This book was released on 2016 with total page 49 pages. Available in PDF, EPUB and Kindle. Book excerpt: Previous attempts to estimate the long-run risk (LRR) model revealed serious methodological issues and low estimation precision of the existing econometric approaches. However, this study shows that despite the presence of latent variables asymptotically efficient maximum likelihood (ML) estimation is possible through application of filtering methods. A three-step estimation strategy is suggested that involves ML estimation relying on the Kalman filter and a particle filter, which allows to identify all LRR model parameters. A Monte Carlo study assesses the estimation precision for different sample sizes, an empirical application presents estimation results obtained from U.S. data.

Download or read book Restricted Kalman Filtering written by Adrian Pizzinga and published by Springer Science & Business Media. This book was released on 2012-07-25 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt: ​​​​​​​​ ​In statistics, the Kalman filter is a mathematical method whose purpose is to use a series of measurements observed over time, containing random variations and other inaccuracies, and produce estimates that tend to be closer to the true unknown values than those that would be based on a single measurement alone. This Brief offers developments on Kalman filtering subject to general linear constraints. There are essentially three types of contributions: new proofs for results already established; new results within the subject; and applications in investment analysis and macroeconomics, where the proposed methods are illustrated and evaluated. The Brief has a short chapter on linear state space models and the Kalman filter, aiming to make the book self-contained and to give a quick reference to the reader (notation and terminology). The prerequisites would be a contact with time series analysis in the level of Hamilton (1994) or Brockwell & Davis (2002) and also with linear state models and the Kalman filter – each of these books has a chapter entirely dedicated to the subject. The book is intended for graduate students, researchers and practitioners in statistics (specifically: time series analysis and econometrics).

Download or read book Testing Conditional Asset Pricing Models Using a Markov Chain Monte Carlo Approach written by Manuel Ammann and published by . This book was released on 2014 with total page 41 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose a new approach for the estimation of conditional asset pricing models based on a Markov Chain Monte Carlo (MCMC) approach. In contrast to existing approaches, it is truly conditional because the assumption that time variation in betas is driven by a set of conditioning variables is not necessary. Moreover, the approach has exact finite sample properties and accounts for errors-in-variables in a one-step estimation procedure. Using Samp;P 500 panel data, we analyze the empirical performance of the CAPM and the Fama and French (1993) three-factor model. We find that time-variation of betas in the CAPM and the time variation of the coefficients for the size factor (SMB) and the distress factor (HML) in the three-factor model improve the empirical performance by a similar amount. Therefore, our findings are consistent with time variation of firm-specific exposure to market risk, systematic credit risk and systematic size effects. However, a Bayesian model comparison trading off goodness of fit and model complexity indicates that the conditional CAPM performs best, followed by the conditional three-factor model, the unconditional CAPM, and the unconditional three-factor model.

Download or read book Time Varying Asset Pricing Models in the Context of Segmented Markets written by Chris Bilson and published by . This book was released on 2002 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper explores and tests two multi-factor asset pricing models in an international context. One model focuses only on local risk factors and therefore assumes that the market is completely segmented. The other model focuses only on global risk factors and assumes that the market is fully integrated. The models incorporate time-variation in both the risk exposures and risk premia. The models are applied in cross-section to a range of developed and emerging markets so that varying levels of integration are examined. Expected returns are formed using time-varying estimates of risk premia that allow for out-of-sample testing. Using a range of performance metrics, the findings show that returns in developed markets are better approximated by a global pricing model, whereas returns in emerging markets are better represented by a local pricing model. These results are found to be generally robust to a range of research design issues.

Download or read book Tests of International CAPM with Time varying Covariances written by Charles Engel and published by . This book was released on 1987 with total page 43 pages. Available in PDF, EPUB and Kindle. Book excerpt: We perform maximum likelihood estimation of a model of international asset pricing based on CAPM. We test the restrictions imposed by CAPM against a more general asset pricing model. The "betas" in our CAPM vary over time from two sources -- the supplies of the assets (government obligations of France, Germany, Italy, Japan, the U.K. and the U.S.) change over time, and so do the conditional covariances of returns on these assets. We let the covariances change over time as a function of macroeconomic data. We also estimate the model when the covariances follow a multivariate ARCH process. When the covariance of forecast errors are time-varying, we can identify a modified CAFM model with measurement error -- which we also estimate. We find that the model in which the CAPM restrictions are imposed (which involve cross-equation constraints between coefficients and the variances of the residuals) perform much better when variances are not constant over time. Nonetheless, the CAPM model is rejected in favor of the less restricted model of asset pricing

Download or read book Nonparametric Estimation of the Time varying Sharpe Ratio in Dynamic Asset Pricing Models written by Peter Woehrmann and published by . This book was released on 2005 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Advanced Kalman Filtering Least Squares and Modeling written by Bruce P. Gibbs and published by Jossey-Bass Publishers. This book was released on 2011-03 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work is intended primarily as a handbook for engineers who must design practical systems. It discusses model development in detail so that the reader may design an estimator that meets all application requirements and is robust to modelling assumptions.

Download or read book Asset Pricing with Time Varying Volatility written by Victor Ng and published by . This book was released on 1989 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book American Doctoral Dissertations written by and published by . This book was released on 1994 with total page 800 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Out of sample Forecasting Performance of Linear Asset Pricing Models with Time varying Parameters written by Chintan Huang and published by . This book was released on 1988 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: