Exchange-rate forecasts with simultaneous nearest-neighbour methods: evidence from the EMS

Rodríguez, Fernando Fernández; Sosvilla‐Rivero, Simón; Félix, Julián Andrada

doi:10.1016/s0169-2070(99)00003-5

Cited by 80 publications

(30 citation statements)

References 25 publications

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“…Two groups of countries were differentiated: those that maintained broadly stable bilateral exchange rates against the Deutschmark, and those whose currencies either entered the ERM later or suspended its participation in the ERM, fluctuating in value to a great extent relative to the Deutschmark. Finally, the same two groups are found in Fernández-Rodríguez et al (1999) to have relevant information helping to improve the prediction of currencies in each group based on the behaviour of the rest of the currencies, information that can be used to generate simple trading rules that outperform the moving average trading rules widely used in the markets (see Fernández-Rodríguez et al., 2003). 18 We consider three basic panel regression methods: the fixed-effects (FE) method, the random effects (RE) model and the pooled-OLS method.…”

Section: Resultssupporting

confidence: 67%

An update on EMU sovereign yield spread drivers in times of crisis: A panel data analysis

Gómez‐Puig

Sosvilla‐Rivero

Ramos-Herrera

2014

The North American Journal of Economics and Finance

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We empirically investigate the determinants of EMU sovereign bond yield spreads with respect to the German bund. Using panel data techniques, we examine the role of a wide set of potential drivers. To our knowledge, this paper presents one of the most exhaustive compilations of the variables used in the literature to study the behaviour of sovereign yield spreads and, in particular, to gauge the effect on these spreads of changes in market sentiment and risk aversion. We use a sample of both central and peripheral countries from January 1999 to December 2012 and assess whether there were significant changes after the outbreak of the euro area debt crisis. Our results suggest that the rise in sovereign risk in central countries can only be partially explained by the evolution of local macroeconomic variables in those countries. Besides, without exception, the marginal effects of sovereign spread drivers (specifically, the variables that measure global market sentiment) increased during the crisis compared to the pre-crisis period, especially in peripheral countries. Moreover, the increase in the significance of the banking level of indebtedness and foreign bank's claims in the public sector (mainly in peripheral countries) along with the crisis unfolding seems to highlight the interconnection between private and public debt and thus, between banking and sovereign crises.

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Section: Resultssupporting

confidence: 67%

An update on EMU sovereign yield spread drivers in times of crisis: A panel data analysis

Gómez‐Puig

Sosvilla‐Rivero

Ramos-Herrera

2014

The North American Journal of Economics and Finance

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“…The capability of generating profits by means of these yield curve predictions, transforming them into technical trading strategies, is also considered. By re-interpreting the Nelson-Siegel yield curve as a dynamic model that achieves a reduction in dimensionality, the factors level, slope and curvature are predicted using different econometric models, namely the parametric ones suggested by Diebold and Li (2006) and Rezende and Ferreira (2013), and two non-parametric models suggested by Fernández-Rodríguez et al (1999) for exchange rates. Our findings show that the random walk model is competitive from the standpoint of point predictions for Spanish yield curves.…”

Section: Discussionmentioning

confidence: 99%

“…Following Fernández-Rodríguez et al (1999), it is also possible to generalize theTherefore, the difference between the NN predictionx T +h of x T +h given by (13) and the SNN prediction given by (15) is the way in which the nearest neighbours employed in (12) and (14) are selected to estimate the parameters.…”

Section: Discussionmentioning

confidence: 99%

“…The econometric models used in these predictions are those developed in Diebold and Li (2006) and Rezende and Ferreira (2013) for forecasting the Brazilian zerocoupon data, and in other non-parametric models successfully employed in the prediction of exchange rates by Fernández-Rodríguez et al (1999). Using the Diebold and Li (2006) notation,β i,t , i = 1, 2, 3 represents the beta corresponding to day t, andβ i,t+h/t represents the prediction ofβ i,t h days ahead.…”

Section: Methodology and Datamentioning

confidence: 99%

“…The NN regression models are developed in the Appendix. (9) Simultaneous nearest neighbours (SNN)(h): Non-parametric regression model by Fernández-Rodríguez et al (1999) …”

Section: Methodology and Datamentioning

confidence: 99%

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Fixed income strategies based on the prediction of parameters in the NS model for the Spanish public debt market

Félix

Fernández-Pérez

Rodríguez

2015

SERIEs

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Using different econometric models, Diebold and Li (J Econom 130:337-364, 2006) addressed the practical problem of forecasting the yield curve by predicting the factors level, slope and curvature in the Nelson-Siegel framework. This paper has two main aims: on the one hand, to investigate the predictive possibilities of the yield curve for the Spanish public debt market, using the methodology proposed by Diebold and Li (J Econom 130:337-364, 2006); and on the other hand, to study the capability of generating profits by transforming these yield curve predictions into technical trading strategies. The Sharpe ratios of our strategies outperform the hedging strategy benchmarks for long (1 year) horizons in our prediction period (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010) and also for the current crisis period (2008)(2009)(2010). Nevertheless, these strategies do not outperform their benchmarks for short (1 month) horizons. The introduction of nonparametric models improves the profitability of the strategies in terms of the Sharpe ratio, especially in the 1-year-ahead predictions. This finding is in line with Diebold and Li (J Econom 130:337-364, 2006), whose forecasts for long horizons are much more accurate than those of several standard benchmark models.

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Non‐linear forecasts of stock returns

Kanas

2003

Journal of Forecasting

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Following recent non-linear extensions of the present-value model, this paper examines the out-of-sample forecast performance of two parametric and two non-parametric nonlinear models of stock returns. The parametric models include the standard regime switching and the Markov regime switching, whereas the non-parametric are the nearest-neighbour and the artificial neural network models. We focused on the US stock market using annual observations spanning the period 1872-1999. Evaluation of forecasts was based on two criteria, namely forecast accuracy and forecast encompassing. In terms of accuracy, the Markov and the artificial neural network models produce at least as accurate forecasts as the other models. In terms of encompassing, the Markov model outperforms all the others. Overall, both criteria suggest that the Markov regime switching model is the most preferable non-linear empirical extension of the present-value model for out-of-sample stock return forecasting. Copyright © 2003 John Wiley & Sons, Ltd.

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Exchange-rate forecasts with simultaneous nearest-neighbour methods: evidence from the EMS

Cited by 80 publications

References 25 publications

An update on EMU sovereign yield spread drivers in times of crisis: A panel data analysis

An update on EMU sovereign yield spread drivers in times of crisis: A panel data analysis

Fixed income strategies based on the prediction of parameters in the NS model for the Spanish public debt market

Non‐linear forecasts of stock returns

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