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A novel implementation of Siamese type neural networks in predicting rare fluctuations in financial time series

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Stock trading has tremendous importance not just as a profession but also as an income source for individuals. Many investment account holders use the appreciation of their portfolio (as a combination of stocks or indexes) as income for their retirement years, mostly betting on stocks or indexes...

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On a bivariate hysteretic AR-GARCH model with conditional asymmetry in correlations

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Forecasting volatility for an optimal portfolio with stylized facts using copulas

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A new bootstrapped hybrid artificial neural network approach for time series forecasting

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Does capacity utilization predict inflation? : a wavelet based evidence from United States

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Multiple kernel learning with Fisher kernels for high frequency currency prediction

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Nonlinearity in forecasting of high-frequency stock returns

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Unemployment rate forecasting : a hybrid approach

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Prediction of unemployment rates with time series and machine learning techniques

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