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Why frequency matters for unit root testing

Boswijk, Herman Peter; Klaassen, Franc - 2004 - Rev.

It is generally believed that for the power of unit root tests, only the time span and not the observation frequency matters. In this paper we show that the observation frequency does matter when the high-frequency data display fat tails and volatility clustering, as is typically the case for...

Persistent link: https://www.econbiz.de/10011342578

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

Unit roots and long-run causality : investigating the relationship between output, money and interest rates

Caporale, Guglielmo Maria - In: Economic modelling 15 (1998) 1, pp. 91-112

Persistent link: https://www.econbiz.de/10001247848

New panel unit root tests of PPP

Coakley, Jerry - In: Economics letters 57 (1997) 1, pp. 17-22

Persistent link: https://www.econbiz.de/10001229597

Estimating Continuous-Time Stochastic Volatility Models of the Short-Term Interest Rate : A Comparison of the Generalized Method of Moments and the Kalman Filter

Sapp, Travis - 2009

conditions. The GMM procedure is compared to a Kalman filter estimation approach. Empirical estimation is implemented on US …

Persistent link: https://www.econbiz.de/10013156585

Periodic Integration and Cointegration of U.S. Stock Prices, Dividends, and Interest Rates : A New Test of the Present Value Model

Shirwani, Hassan; Delcoure, Natalya; Wilbratte, Barry J. - 2012

This paper presents a new test of the present value model of stock price determination, using some of the recent advances in the econometrics of seasonal time series. Unlike earlier studies which generally find stock prices, dividends, and interest rates to be characterized by standard...

Persistent link: https://www.econbiz.de/10014043638

The Distribution of the Mean Reversion Estimator in the Ornstein-Uhlenbeck Process

Bao, Yong - 2016

We derive the exact distribution of the maximum likelihood estimator of the mean reversion parameter (k) in the Ornstein-Uhlenbeck process by employing numerical integration via analytical evaluation of a joint characteristic function. Different scenarios are considered: known or unknown drift...

Persistent link: https://www.econbiz.de/10012998090

Estimation of a Nonparametric model for Bond Prices from Cross-section and Time series Information

Koo, Bonsoo - 2019

We develop estimation methodology for an additive nonparametric panel model that is suitable for capturing the pricing … techniques: cross-sectional nonparametric methods and kernel estimation for time varying dynamics in the time series context. The …

Persistent link: https://www.econbiz.de/10012891762

A Markov-Switching Range-Based Volatility Model with Applications in Volatility Adjusted VAR Estimation

Wu, Chun-Chou - 2012

for exogenous shock to market data. After the data fitting and VaR estimation, we conclude that the range-based volatility … regime switching into volatility process can boost the efficiency for VaR estimation. We also present an empirical … with non-regime switching volatility model, our model outperforms other alternatives on the estimation of volatility …

Persistent link: https://www.econbiz.de/10013109345

Periodic heteroskedastic RegARFIMA models for daily electricity spot prices

Carnero, M. Angeles; Koopman, Siem Jan; Ooms, Marius - 2003

electricity markets that we consider (APX in The Netherlands, EEX in Germany and Powernext in France) periodicity in the …

Persistent link: https://www.econbiz.de/10011334362