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Scenarios of the Romanian GDP Evolution with Neural Models
Saman, Corina - 2014
This paper aims to explore the nonlinear relation between investments and GDP. The method of neural network is used to … construct two nonlinear models of GDP in relation to domestic investments, foreign direct investments and real interest rate … accuracy may be capturing more fundamental non-linearities between investment and financial variables and the real output for a …
Persistent link: https://www.econbiz.de/10013059876
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OUT-OF-SAMPLE FORECASTING PERFORMANCE OF A ROBUST NEURAL EXCHANGE RATE MODEL OF RON/USD
SAMAN, Corina - In: Journal for Economic Forecasting (2015) 1, pp. 93-106
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
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Out-of-Sample Forecasting Performance of a Robust Neural Exchange Rate Model of RON/USD
Saman, Corina - 2016
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/10013001999
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FuNVol : A Multi-Asset Implied Volatility Market Simulator using Functional Principal Components and Neural SDEs
Choudhary, Vedant; Jaimungal, Sebastian; Bergeron, Maxime - 2023
Here, we introduce a new approach for generating sequences of implied volatility (IV) surfaces across multiple assets that is faithful to historical prices. We do so using a combination of functional data analysis and neural stochastic differential equations (SDEs) combined with a probability...
Persistent link: https://www.econbiz.de/10014254286
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The benefits of the Velvet Revolution in Armenia : estimation of the short-term economic gains using deep neural networks
Nahapetyan, Yervand - In: Central European economic journal 6 (2019) 53, pp. 286-303
models using an ensembling mechanism. As a result, CNN overperformed the rest of the models. The CNN simulation on post …-revolutionary data indicates that during the period 2018-Q2-2019-Q1, Armenia gained approximately 850 million EUR in terms of GDP, thanks …
Persistent link: https://www.econbiz.de/10012303300
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Choosing Lag Lengths in Nonlinear Dynamic Models
Anderson, Heather M. - Department of Econometrics and Business Statistics, … - 2002
nonlinear behavior. A simulation study compares the properties of these proposed procedures with the properties of linear …
Persistent link: https://www.econbiz.de/10005149065
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Testing for ARCH in the Presence of Nonlinearity of Unknown Form in the Conditional Mean
Blake, Andrew P.; Kapetanios, George - School of Economics and Finance, Queen Mary - 2003
Tests of ARCH are a routine diagnostic in empirical econometric and financial analysis. However, it is well known that misspecification of the conditional mean may lead to spurious rejections of the null hypothesis of no ARCH. Nonlinearity is a prime example of this phenomenon. There is little...
Persistent link: https://www.econbiz.de/10005106375
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Testing for Structural Breaks in Nonlinear Dynamic Models Using Artificial Neural Network Approximations
Kapetanios, George - School of Economics and Finance, Queen Mary - 2002
In this paper we suggest a number of statistical tests based on neural network models, that are designed to be powerful against structural breaks in otherwise stationary time series processes while allowing for a variety of nonlinear specifications for the dynamic model underlying them. It is...
Persistent link: https://www.econbiz.de/10005106377
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Consistent Model Specification Tests Against Smooth Transition Alternatives
Hill, Jonathan B. - EconWPA - 2004
regarding when and whether Bierens-type tests are asymptotically degenerate. In a simulation experiment in which all parameters …
Persistent link: https://www.econbiz.de/10005556316
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Neural Networks to Predict Financial Time Series in a Minority Game Context
Grilli, Luca; Sfrecola, Angelo - Dipartimento di Scienze Economiche, Matematiche e … - 2005
In this paper we consider financial time series from U.S. Fixed Income Market, S&P500, Exchange Market and Oil Market. It is well known that financial time series reveal some anomalies as regards the Efficient Market Hypotesis and some scaling behavior is evident such as fat tails and clustered...
Persistent link: https://www.econbiz.de/10005628770