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Using Macro-Financial Variables To Forecast Recessions. An Analysis Of Canada, 1957-2002

KIANI, Khurshid M.; KASTENS, Terry L. - In: Applied Econometrics and International Development 6 (2006) 3

We employ artificial neural networks using macro-financial variables to predict recessions. We model the relationship between indicator variables and recessions to periods into the future and employ a procedure that penalizes a misclassified recession more than a misclassified non-recession. Our...

Persistent link: https://www.econbiz.de/10005063012

Chapter 8 Forecasting economic variables with nonlinear models

Teräsvirta, Timo - 2006

The topic of this chapter is forecasting with nonlinear models. First, a number of well-known nonlinear models are introduced and their properties discussed. These include the smooth transition regression model, the switching regression model whose univariate counterpart is called threshold...

Persistent link: https://www.econbiz.de/10014023698

Neural Networks to Detect Nonlinearities in Time Series: Analysis of Business Cycle in France and the United Kingdom,

Kiani, K.M. - In: Applied Econometrics and International Development 9 (2009) 1

In this research we investigate possible existence of nonlinearities in business cycle fluctuations in France and … network linearity tests for possible existence of nonlinearities due to Terasvirta el al. (1993) using in-sample forecasts … from neural nets in France and U.K. show statistically significant evidence of nonlinearities in both the series. Similarly …

Persistent link: https://www.econbiz.de/10005012226

On business cycle fluctuations in USA macroeconomic time series

Kiani, Khurshid M. - In: Economic modelling 53 (2016), pp. 179-186

Persistent link: https://www.econbiz.de/10011640993

Tracking activity in real time with Google Trends

Woloszko, Nicolas - 2020

This paper introduces the OECD Weekly Tracker of economic activity for 46 OECD and G20 countries using Google Trends search data. The Tracker performs well in pseudo-real time simulations including around the COVID-19 crisis. The underlying model adds to the previous Google Trends literature in...

Persistent link: https://www.econbiz.de/10012420946

Forecasting tourism demand to Catalonia: Neural networks vs. time series models

Claveria, Oscar; Torra, Salvador - In: Economic Modelling 36 (2014) C, pp. 220-228

The increasing interest aroused by more advanced forecasting techniques, together with the requirement for more accurate forecasts of tourism demand at the destination level due to the constant growth of world tourism, has lead us to evaluate the forecasting performance of neural modelling...

Persistent link: https://www.econbiz.de/10010729816

Comparing Neural Networks and ARMA Models in Artificial Stock Market

Krtek, Jiri; Vošvrda, Miloslav - In: Bulletin of the Czech Econometric Society 18 (2011)

Neural networks - feed-forward neural networks and Elman's simplerecurrent neural networks - are compared with vector ARMA models- VAR and VARMA - in this paper. They are compared in anartificial stock market. One risk free and one risky asset aretraded in the market. There are only trend...

Persistent link: https://www.econbiz.de/10009371041

New Evidence on the Predictability of South Africa FX Volatility in Heterogeneous Bilateral Markets

Dash, Gordon H.; Kajiji, Nina - In: The African Finance Journal 5 (2003) 1, pp. 1-15

The purpose of this paper is to model the nonparametric realized volatility of the U.S. based futures contract for dollar exchange with the South African Rand (ZAR). We find that the Kajiji-4 Bayesian regularization radial basis function neural network confirms the hypothesis that bilateral...

Persistent link: https://www.econbiz.de/10008503558

Caracterización no lineal y predicción no paramétrica en el IBEX35/Nonlinear Characterization and Predictions of IBEX 35

OLMEDO, E.; VELASCO, F.; VALDERAS, J.M. - In: Estudios de Economía Aplicada 25 (2007) Diciembre, pp. 815-815

The nonlinear modelization has experimented a great resurgence of the hand of Chaos Theory, which shown the possibility of obtaining complex behaviors produced endogenously by the dynamics of the model, without the necessity to include exogenous random shocks. On the other hand, the importance...

Persistent link: https://www.econbiz.de/10005736967

The output gap and stock returns: Do cyclical fluctuations predict portfolio returns?

Vivian, Andrew; Wohar, Mark E. - In: International Review of Financial Analysis 26 (2013) C, pp. 40-50

This study examines whether the output gap leads portfolio stock returns. The paper conducts in-sample and out-of-sample forecasting of US stock portfolios formed on the basis of size and value. First, the paper finds cross-sectional portfolios are predictable in-sample by the output gap....

Persistent link: https://www.econbiz.de/10010617260

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