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Essays in the econometrics of dynamic duration models with application to tick by tick financial data

Galli, Fausto - 2009

Persistent link: https://www.econbiz.de/10003986565

Bayesian inference in a stochastic volatility Nelson-Siegel Model

Hautsch, Nikolaus; Yang, Fuyu - 2010

In this paper, we develop and apply Bayesian inference for an extended Nelson-Siegel (1987) term structure model capturing interest rate risk. The so-called Stochastic Volatility Nelson-Siegel (SVNS) model allows for stochastic volatility in the underlying yield factors. We propose a Markov...

Persistent link: https://www.econbiz.de/10003952795

An estimator for the quadratic covariation of asynchronously observed Itô processes with noise : asymptotic distribution theory

Bibinger, Markus - 2011

distribution theory for a generalized multiscale estimator including a feasible central limit theorem with optimal convergence rate …

Persistent link: https://www.econbiz.de/10009151649

Local projections, autocorrelation, and efficiency

Lusompa, Amaze - In: Quantitative economics : QE ; journal of the … 14 (2023) 4, pp. 1199-1220

estimated by OLS and that GLS is not possible because the autocorrelation process is unknown and/or because the GLS estimator … would be inconsistent. I show that the autocorrelation process of LP can be written as a Vector Moving Average (VMA) process … of the Wold errors and impulse responses and that autocorrelation can be corrected for using a consistent GLS estimator …

Persistent link: https://www.econbiz.de/10014496501

Common Periodic Correlation Features and the Interaction of Stocks and Flows in Daily Airport Data

Haldrup, Niels; Hylleberg, Svend; Pons, Gabriel; … - 2008

This paper presents a new framework for coping with problems often encountered when modeling seasonal high frequency data containing both flow and stock variables. The idea is to apply a multivariate weekly representation of a daily periodic model and to exploit the possible cointegration and...

Persistent link: https://www.econbiz.de/10014217224

Modeling Time Series with Both Permanent and Transient Components Using the Partially Autoregressive Model

Clegg, Matthew - 2015

A time series model is discussed that incorporates both permanent and transient effects. Estimation techniques are given, and the power of the likelihood ratio test is assessed. When applied to the monthly price/earnings series of the S&P 500 over the period 1871-2013, both permanent and...

Persistent link: https://www.econbiz.de/10013029325

A Primer on Bootstrap Testing of Hypotheses in Time Series Models : With an Application to Double Autoregressive Models

Cavaliere, Giuseppe - 2019

In this paper we discuss the general application of the bootstrap as a tool for statistical inference in econometric time series models. We do this by considering the implementation of bootstrap inference in the class of double-autoregressive [DAR] models discussed in Ling (2004). DAR models are...

Persistent link: https://www.econbiz.de/10012889326

On Fitting the Autoregressive Investment Models to Real Financial Data

Medvedev, Gennady - 2009

The successful investment policy is an integral part of successful activity of the insurance company. The return to the shareholders of the insurance company usually thought of as comprising the underwriting result and investment income. The investment income is very important even for an...

Persistent link: https://www.econbiz.de/10013156306

Matrix Autoregressive Models : Generalization and Bayesian Estimation

Celani, Alessandro; Pagnottoni, Paolo - 2022

The issue of modelling observations generated in matrix form over time is key in economics, finance and many domains of application. While it is common to model vectors of observations through standard vector time series analysis, original matrix-valued data often reflect different types of...

Persistent link: https://www.econbiz.de/10014237100

Midastar : Threshold Autoregression with Data Sampled at Mixed Frequencies

Motegi, Kaiji; Dennis, Jay - 2022

We propose Midastar models by combining the Mixed Data Sampling (MIDAS) and the threshold autoregression (TAR). The Midastar model of the first kind is designed for a low frequency target variable and a high frequency threshold variable. The proposed model can detect threshold effects...

Persistent link: https://www.econbiz.de/10014240508