Econometric applications of maximum likelihood methods

Econometric Applications of Maximum Like

📁 Econometric Applications of Maximum Likelihood Methods

✍ Jan Salomon Cramer 📂 Library 📅 1986 🌐 English

Econometric Applications of Maximum Like

📁 Econometric Applications of Maximum Likelihood Methods

✍ Jan Salomon Cramer 📂 Library 📅 1986 🌐 English

The advent of electronic computing permits the empirical analysis of economic models of far greater subtlety and rigour than before, when many interesting ideas were not followed up because the calculations involved made this impracticable. The estimation and testing of these more intricate models i

Maximum Simulated Likelihood Methods and

📁 Maximum Simulated Likelihood Methods and Applications (Advances in Econometrics)

✍ William Greene 📂 Library 📅 2010 🏛 Emerald Group Publishing Limited 🌐 English

This volume is a collection of methodological developments and applications of simulation-based methods that were presented at a workshop at Louisiana State University in November, 2009. The first two papers are extensions of the GHK simulator: one reconsiders the computation of the probabilities in

Applied Financial Econometrics: Theory,

📁 Applied Financial Econometrics: Theory, Method and Applications

✍ Moinak Maiti 📂 Library 📅 2021 🏛 Palgrave Macmillan 🌐 English

<div>This textbook gives students an approachable, down to earth resource for the study of financial econometrics. While the subject can be intimidating, primarily due to the mathematics and modelling involved, it is rewarding for students of finance and can be taught and learned in a straightforwar

Applied Financial Econometrics: Theory,

📁 Applied Financial Econometrics: Theory, Method and Applications

✍ Moinak Maiti 📂 Library 📅 2021 🏛 Palgrave Macmillan 🌐 English

<div>This textbook gives students an approachable, down to earth resource for the study of financial econometrics. While the subject can be intimidating, primarily due to the mathematics and modelling involved, it is rewarding for students of finance and can be taught and learned in a straightforwar

Separating Information Maximum Likelihoo

📁 Separating Information Maximum Likelihood Method for High-Frequency Financial Data

✍ Naoto Kunitomo, Seisho Sato, Daisuke Kurisu 📂 Library 📅 2018 🏛 Springer Japan 🌐 English

<p>This book presents a systematic explanation of the SIML (Separating Information Maximum Likelihood) method, a new approach to financial econometrics.<br>Considerable interest has been given to the estimation problem of integrated volatility and covariance by using high-frequency financial data. A