financial time series modeling
Application of Higher Order Neural Networks to Financial Time Series Prediction
... unit time delays (memory elements) to turn the MLP/BP into a recurrent network, in order to recognize (classify) dynamic rather than static input ...across time leads to time-delay neural networks, ...
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A Hybrid Approach for Modeling Financial Time Series
... forecasting time series in financial ...for time series forecasting based on a hybrid combination of ARMA and Gene Expression Programming (GEP) induced ...models. Time ...
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Performance evaluation of series and parallel strategies for financial time series forecasting
... for time series forecasting. Sec- ond, scholars have introduced series and parallel combination methodologies to con- nect the components of hybrid ...in modeling and ...a time ...
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Time Series Modeling and Forecasting of CPI of Bangladesh
... Time series data is very important in the case of financial development of any ...with time series data. This study is consists of time series modeling and ...
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Bayesian Inference of Stochastic Volatility Models and Applications in Risk Management.
... of financial time series distribution is that it often displays a heavy tail with asymmetry and positive ...for modeling financial ...
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Non-Linear Volatility Modeling of Economic and Financial Time Series Using High Frequency Data
... concerns modeling and forecasting realized ...in modeling volatility topic, highlighting the problems posed by the properties of financial time series (like the long memory pattern of ...
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Fractal Geometry of Financial Time Series
... in time-series in general and in the stock market in particular is the scaling behavior of the absolute size of the jumps across lags of size ...first time introduced L´ evy’s stable random variables ...
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Time Scale and Fractionality in Financial Time Series
... different time lags, none was discovered to violate time independence at the highest significance level after adjustment for the multiplicity of ...fractional modeling approach is ...
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Modeling the Residuals of Financial Time Series with Missing Values for Risk Measures Using R
... the series, estimation of the missing values in time series and outright use of GARCH models without the determination of the presence of ARCH in the ...purely financial time ...
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On observation-driven time series modeling
... ibility conditions often impose restrictions on the parameter space that are unfeasible to be checked in practice. This occurs because these invertibility conditions depend on the properties of the Data Generating ...
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Financial-Economic Time Series Modeling and Prediction Techniques – Review
... to financial time series forcasting, little or no attention has been paid to selecting the input features for training these ...the financial time series ...
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Modeling and prediction of time-series of monthly copper prices
... Long-term forecasts are more unreliable than short-term ones and it should be remembered that no forecasting methodology will be fully accurate all of the time so there are risks associated with using them. As Van ...
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The Ups and Downs of Modeling Financial Time Series with Wiener Process Mixtures
... Since in this model the volatility is constant in each realization and bound to decrease unless a restart occurs, it is quite clear that it does not contain all the richness of financial market price dynamics. ...
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Testing extreme dependence in financial time series
... multivariate time series analysis are not suitable in this setting, since they concentrate on the joint behavior during stable and stationary ...different series occur concurrently. Given the ...
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Spurious long range dependence: evidence from Malaysian equity markets
... For KLCI, FIN, IND and PRP indices, the pre-period analysis included the events such as the Asian financial and currency crises. Exceptional, only the PLN index indicated short-range dependence with the value ...
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Modelling and Analysis on Noisy Financial Time Series
... of time series has at- tracted much attention from statistical and machine learning perspectives [1,2], with a variety of applications in different fields ...analyzing financial time ...
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Factor modeling for high dimensional time series
... of modeling the dynamic behavior of IBM, Microsoft and Dell implied volatility ...from time to maturity, delta, moneyness or ...in time of this surface captures the evolution of prices in the option ...
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An Introductory Study on Time Series Modeling and Forecasting
... for time series modeling and ...to time series forecasting and it gained immense popularity in last few ...for time series analysis and ...
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Forecasting Liquidity Ratio of Commercial Banks in Nigeria
... Abstract In this paper, autoregressive fractionally integrated moving average (ARFIMA) model was proposed and was used for modeling and forecasting of liquidity ratio of commercial banks in Nigeria. Augmented ...
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