Similar Search Results

Predicting the Probability of a Recession with Nonlinear Autoregressive Leading Indicator Models.

Anderson, H.M.; Vahid, F. - Department of Econometrics and Business Statistics, … - 2000

We develop nonlinear leading indicator models for GDP growth, with the interest rate spread and growth in M2 as leading indicators. Since policy makers are typically interested in whether or not a recession is imminent, we evaluate these models according to their ability to predict the...

Persistent link: https://www.econbiz.de/10005125275

Market Architecture and Nonlinear Dynamics of Australian Stock and Future Indices.

Anderson, H.M.; Vahid, F. - Department of Econometrics and Business Statistics, … - 2001

This paper studies the All Ordinaries Index in Australia, and its futures contract known as the Share Price Index. We use a new form of smooth transition model to account for a variety of nonlinearities caused by transaction costs and other market/data imperfections, and given the recent...

Persistent link: https://www.econbiz.de/10005427633

Capturing the Shape of Business Cycles with Nonlinear Autoregressive Leading Indicator Models.

Athanasopoulos, G.; Anderson, H.M.; Vahid, F. - Department of Econometrics and Business Statistics, … - 2001

This paper studies linear and linear autoregressive leading indicator models of business cycles in OECD countries. The models use the spread between short-term and long-term interest rates as leading indicators for GDP, and their success in capturing business cycles gauged by the non-parametric...

Persistent link: https://www.econbiz.de/10005149057

Nonlinear Autoregresssive Leading Indicator Models of Output in G-7 Countries

Anderson, Heather M.; Athanasopoulos, George; Vahid, Farshid - Department of Econometrics and Business Statistics, … - 2002

This paper studies linear and nonlinear autoregressive leading indicator models of business cycles in G7 countries. The models use the spread between short-term and long-term interest rates as leading indicators for GDP, and their success in capturing business cycles is gauged by non-parametric...

Persistent link: https://www.econbiz.de/10005087584

A New Class of Bivariate Threshold Cointegration Models

Cai, Biqing; Gao, Jiti; Tjostheim, Dag - Department of Econometrics and Business Statistics, … - 2015

In this paper, we introduce a new class of bivariate threshold VAR cointegration models. In the models, outside a compact region, the processes are cointegrated, while in the compact region, we allow different kinds of possibilities. We show that the bivariate processes from a 1/2-null recurrent...

Persistent link: https://www.econbiz.de/10011193729

Inference on Self-Exciting Jumps in Prices and Volatility using High Frequency Measures

Maneesoonthorn, Worapree; Forbes, Catherine S.; Martin, … - Department of Econometrics and Business Statistics, … - 2014

Dynamic jumps in the price and volatility of an asset are modelled using a joint Hawkes process in conjunction with a bivariate jump diffusion. A state space representation is used to link observed returns, plus nonparametric measures of integrated volatility and price jumps, to the specified...

Persistent link: https://www.econbiz.de/10011141014

Structural-break models under mis-specification: implications for forecasting

Koo, Boonsoo; Seo, Myung Hwan - Department of Econometrics and Business Statistics, … - 2013

continuously or with some jumps. This view is widely held in the forecasting literature and under this view, the time series … contemporary forecasting methods is compared to ours using a number of macroeconomic data. …

Persistent link: https://www.econbiz.de/10010860411

Structural-break models under mis-specification: implications for forecasting

Koo, Boonsoo; Seo, Myung Hwan - Department of Econometrics and Business Statistics, … - 2013

distribution theory involves cube-root asymptotics and it is used to shed light on forecasting practice. We show that the … conventional forecasting methods do not necessarily produce the best forecasts in our setting. We also propose a new forecasting … strategy, which incorporates our new distribution theory, and apply our forecasting method to numerous macroeconomic data. The …

Persistent link: https://www.econbiz.de/10010860415

Low-dimensional decomposition, smoothing and forecasting of sparse functional data

Dokumentov, Alexander; Hyndman, Rob J - Department of Econometrics and Business Statistics, … - 2014

decomposing, smoothing and forecasting two-dimensional sparse data. In some ways, ROPES is similar to Ridge Regression, the LASSO … practical method of forecasting mortality rates, as well as a new method for interpolating and extrapolating sparse longitudinal …

Persistent link: https://www.econbiz.de/10010958945

Forecasting age-related changes in breast cancer mortality among white and black US women: A functional approach

Yasmeen, Farah; Hyndman, Rob J; Erbas, Bircan - Department of Econometrics and Business Statistics, … - 2010

The disparity in breast cancer mortality rates among white and black US women is widening with higher mortality rates among black women. We apply functional time series models on age-specific breast cancer mortality rates for each group of women, and forecast their mortality curves using...

Persistent link: https://www.econbiz.de/10008467330