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neural networks for testing business cycle nonlinearities in U.S. stock returns. Our results based on nonlinear augmented and … evidence of business cycle nonlinearities in US stock returns. The magnitude of these nonlinearities is more obvious in post …
Persistent link: https://www.econbiz.de/10005607427
present. Our results indicate fairly strong evidence of nonlinearities in the conditional mean dynamics of the GDP growth …
Persistent link: https://www.econbiz.de/10005636520
This research studies possible existence of business cycle asymmetries in Canada, France, Germany, Italy, Japan, UK, and US real GDP growth rates. Asymmetries in these countries are modeled using in-sample as well as jackknife out-of-sample forecasts approximated from artificial neural networks....
Persistent link: https://www.econbiz.de/10010598967
The design of models for time series forecasting has found a solid foundation on statistics and mathematics. On this basis, in recent years, using intelligence-based techniques for forecasting has proved to be extremely successful and also is an appropriate choice as approximators to model and...
Persistent link: https://www.econbiz.de/10011109292
The design of models for time series forecasting has found a solid foundation on statistics and mathematics. On this basis, in recent years, using intelligence-based techniques for forecasting has proved to be extremely successful and also is an appropriate choice as approximators to model and...
Persistent link: https://www.econbiz.de/10011111726
The main purpose of the present study was to investigate the capabilities of two generations of models such as those based on dynamic neural network (e.g., Nonlinear Neural network Auto Regressive or NNAR model) and a regressive (Auto Regressive Fractionally Integrated Moving Average model which...
Persistent link: https://www.econbiz.de/10011260249
Recently, with the development of financial markets and due to the importance of these markets and their close relationship with other macroeconomic variables, using advanced mathematical models with complicated structures for forecasting these markets has become very popular. Besides, neural...
Persistent link: https://www.econbiz.de/10011112434
The main purpose of the present study was to investigate the capabilities of two generations of models such as those based on dynamic neural network (e.g., Nonlinear Neural network Auto Regressive or NNAR model) and a regressive (Auto Regressive Fractionally Integrated Moving Average model which...
Persistent link: https://www.econbiz.de/10010701148
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
This paper aims to explore the forecasting accuracy of RON/USD exchange rate structural models with monetary fundamentals. I used robust regression approach for constructing robust neural models less sensitive to contamination with outliers and I studied its predictability on 1 to 6-month...
Persistent link: https://www.econbiz.de/10011265554