Threshold cointegration in international exchange rates:A Bayesian approach

Huber, Florian; Zörner, Thomas O.

doi:10.1016/j.ijforecast.2018.07.012

Cited by 15 publications

(13 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…More recently, several studies emphasized the usefulness of accounting for nonlinearities in the underlying econometric models to provide more precise exchange rate predictions (see, for example, Canova, 1993;Sarno et al, 2004;Mark, 2009;Byrne et al, 2016;Huber, 2016Huber, , 2017Huber and Zörner, 2018). These non-linearities may relate to movements in the error variances of the models or to changes in the regression coefficients over time.…”

Section: Introductionmentioning

confidence: 99%

“…More recently, several studies emphasized the usefulness of accounting for nonlinearities in the underlying econometric models to provide more precise exchange rate predictions (see, for example, Byrne, Korobilis, & Ribeiro, 2016;Canova, 1993;Huber, 2016Huber, , 2017Huber & Zörner, 2019;Mark, 2009;Sarno, Valente, & Wohar, 2004). The majority of this literature deals with the question on whether a given empirical model, that is loosely based on an underlying structural model, outperforms a set of competing models.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Model instability in predictive exchange rate regressions

Hauzenberger

Huber

2019

Journal of Forecasting

Self Cite

View full text Add to dashboard Cite

In this paper we aim to improve existing empirical exchange rate models by accounting for uncertainty with respect to the underlying structural representation.Within a flexible Bayesian non-linear time series framework, our modeling approach assumes that different regimes are characterized by commonly used structural exchange rate models, with their evolution being driven by a Markov process.We assume a time-varying transition probability matrix with transition probabilities depending on a measure of the monetary policy stance of the central bank at the home and foreign country. We apply this model to a set of eight exchange rates against the US dollar. In a forecasting exercise, we show that model evidence varies over time and a model approach that takes this empirical evidence seriously yields improvements in accuracy of density forecasts for most currency pairs considered.

show abstract

Section: Introductionmentioning

confidence: 99%

“…More recently, several studies emphasized the usefulness of accounting for nonlinearities in the underlying econometric models to provide more precise exchange rate predictions (see, for example, Byrne, Korobilis, & Ribeiro, 2016;Canova, 1993;Huber, 2016Huber, , 2017Huber & Zörner, 2019;Mark, 2009;Sarno, Valente, & Wohar, 2004). The majority of this literature deals with the question on whether a given empirical model, that is loosely based on an underlying structural model, outperforms a set of competing models.…”

Section: Introductionmentioning

confidence: 99%

Model instability in predictive exchange rate regressions

Hauzenberger

Huber

2019

Journal of Forecasting

Self Cite

View full text Add to dashboard Cite

show abstract

“…Similarly, several papers have used the cointegration VAR and vector error correction model (VECM) framework to forecast exchange rates. A very recent paper by Huber and Thomas (2019) has summarized some of the findings in the cointegration domain. Although recent advances in the cointegration framework have improved the forecast accuracy of financial time series over the traditional cointegration methods, the basic problem of short-term forecasting remains true even here.…”

Section: Implications Of the Resultsmentioning

confidence: 99%

The Dynamics of India’s Major Exchange Rates

Bhattacharyya

Datta

2020

Global Business Review

View full text Add to dashboard Cite

In this article, we analyze the dynamic properties of India’s major exchange rates, both in the short and the long runs. The particular issue of our concern is to find whether present values of the exchange rates depend (a) on their own past values and (b) on the past values of India’s other exchange rates. Since the series exhibit long memory, the autoregressive fractionally integrated moving average (ARFIMA) model is used for the first purpose and the cross-correlation, entropy transfer and vector auto regression (VAR) models are used for the later purpose. Combining the results of these models, we conclude that, in general, the Indian exchange rates are persistent and depend only on their immediate past values. In particular, past values, older than two periods (days in this case), do not appear to be consistently relevant in modelling the current value. These observations have clear implications for exchange rate trades using technical analysis (TA) and for exporters and importers.

show abstract

“…The parameter φ governs how smoothly the economy transitions between states. In the limiting case with φ → ∞, the state indicator S t (u t−1 ) switches between zero and one (marking clearly separated regimes), closely related to conventional threshold VARs (see, e.g., Alessandri and Mumtaz, 2019;Huber and Zörner, 2019). For the case of φ → 0, the logistic function turns constant, with S t (u t−1 ) = 0.5 effectively resulting in a linear VAR specification.…”

Section: The Smooth-transition Vector Autoregressionmentioning

confidence: 96%

On the effectiveness of the European Central Bank's conventional and unconventional policies under uncertainty

Hauzenberger¹,

Pfarrhofer²,

Stelzer³

2020

Preprint

View full text Add to dashboard Cite

In this paper, we investigate the effectiveness of conventional and unconventional monetary policy measures by the European Central Bank (ECB) conditional on the prevailing level of uncertainty. To obtain exogenous variation in central bank policy, we rely on high-frequency surprises in financial market data for the euro area (EA) around policy announcement dates. We trace the dynamic effects of shocks to the short-term policy rate, forward guidance and quantitative easing on several key macroeconomic and financial quantities alongside survey-based measures of expectations. For this purpose, we propose a Bayesian smooth-transition vector autoregression (ST-VAR). Our results suggest that transmission channels are impaired when uncertainty is elevated. While conventional monetary policy is less effective during such periods, and sometimes also forward guidance, quantitative easing measures seem to work comparatively well in uncertain times.

show abstract

Threshold cointegration in international exchange rates:A Bayesian approach

Cited by 15 publications

References 54 publications

Model instability in predictive exchange rate regressions

Model instability in predictive exchange rate regressions

The Dynamics of India’s Major Exchange Rates

On the effectiveness of the European Central Bank's conventional and unconventional policies under uncertainty

Contact Info

Product

Resources

About