State-Space Models: Applications in Economics and Finance: 1 (Statistics and Econometrics for Finance, 1) - Image 1

£114.16

Springer State-Space Models: Applications in Economics and Finance: 1 (Statistics and Econometrics for Finance, 1)

Name: State-Space Models: Applications in Economics and Finance: 1 (Statistics and Econometrics for Finance, 1)
Brand: Springer
Price: 111.91 GBP
Availability: InStock

Econometrics

Price History & Forecast

Last 90 days • 90 data points

Historical

Generating forecast...

Price Distribution

Price distribution over 90 days • 7 price levels

Days at Price

Current Price

Price Analysis

Most common price: £107 (32 days, 35.6%)

Price range: £107 - £115

Price levels: 7 different prices over 90 days

Description

State-space models as an important mathematical tool has been widely used in many different fields. This edited collection explores recent theoretical developments of the models and their applications in economics and finance. The book includes nonlinear and non-Gaussian time series models, regime-switching and hidden Markov models, continuous- or discrete-time state processes, and models of equally-spaced or irregularly-spaced (discrete or continuous) observations. The contributed chapters are divided into four parts. The first part is on Particle Filtering and Parameter Learning in Nonlinear State-Space Models. The second part focuses on the application of Linear State-Space Models in Macroeconomics and Finance. The third part deals with Hidden Markov Models, Regime Switching and Mathematical Finance and the fourth part is on Nonlinear State-Space Models for High Frequency Financial Data. The book will appeal to graduate students and researchers studying state-space modeling in economics, statistics, and mathematics, as well as to finance professionals.

Product Specifications

Brand: Springer
Format: paperback
ASIN: 1489992537
Category: Books > Subjects > Business, Finance & Law > Economics > Econometrics
Domain: Amazon UK
Release Date: 25 August 2015
Listed Since: 25 August 2015

Barcode

No barcode data available

Springer State-Space Models: Applications in Economics and Finance: 1 (Statistics and Econometrics for Finance, 1)

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

State-Space Models: Applications in Economics and Finance: 1 (Statistics and Econometrics for Finance, 1)

Continuous-Time Markov Chains and Applications: A Two-Time-Scale Approach: 37 (Stochastic Modelling and Applied Probability, 37)

Introduction to Time Series Modeling with Applications in R (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)

Linear Stochastic Systems: A Geometric Approach to Modeling, Estimation and Identification: 1 (Series in Contemporary Mathematics, 1)

Linear Time Series with MATLAB and OCTAVE (Statistics and Computing)

Stationary Stochastic Models: An Introduction: 4 (World Scientific Series On Probability Theory And Its Applications)

The Kalman Filter in Finance: 32 (Advanced Studies in Theoretical and Applied Econometrics, 32)

Linear Stochastic Systems (Classics in Applied Mathematics)

Further Topics on Discrete-Time Markov Control Processes: 42 (Stochastic Modelling and Applied Probability, 42)

Forecasting, Structural Time Series Models and the Kalman Filter

SELECTED TOPICS ON CONTINUOUS-TIME CONTROLLED MARKOV CHAINS AND MARKOV GAMES: 5 (Icp Advanced Texts In Mathematics)

Dynamics of Markets: The New Financial Economics

Elements of Nonlinear Time Series Analysis and Forecasting (Springer Series in Statistics)

Dynamic Models for Volatility and Heavy Tails: With Applications to Financial and Economic Time Series: 52 (Econometric Society Monographs, Series Number 52)

Matrix-Analytic Methods in Stochastic Models: 27 (Springer Proceedings in Mathematics & Statistics, 27)

Time Series and Dynamic Models (Themes in Modern Econometrics)

Weak Convergence Methods and Singularly Perturbed Stochastic Control and Filtering Problems (Systems & Control: Foundations & Applications)

Copula-Based Markov Models for Time Series: Parametric Inference and Process Control (SpringerBriefs in Statistics)

Optimal Filtering: Volume I: Filtering of Stochastic Processes: 457 (Mathematics and Its Applications, 457)

Linear Time Varying Systems and Sampled-data Systems: 265 (Lecture Notes in Control and Information Sciences, 265)

Modern Control: State-Space Analysis and Design Methods (ELECTRONICS)

Multivariate Modelling of Non-Stationary Economic Time Series (Palgrave Texts in Econometrics)

Optimal Stochastic Control, Stochastic Target Problems, and Backward SDE: 29 (Fields Institute Monographs, 29)

Simulation and Inference for Stochastic Processes with YUIMA: A Comprehensive R Framework for SDEs and Other Stochastic Processes (Use R!)