Pages that link to "Item:Q2468372"
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The following pages link to Support vector machine as an efficient framework for stock market volatility forecasting (Q2468372):
Displaying 15 items.
- Supervised classification and mathematical optimization (Q339559) (← links)
- Forecasting NIKKEI 225 index with support vector machine (Q1433515) (← links)
- Simulation and evaluation of the distribution of interest rate risk (Q1722765) (← links)
- Volatility forecasting via SVR-GARCH with mixture of Gaussian kernels (Q1789603) (← links)
- Time series adaptive online prediction method combined with modified LS-SVR and AGO (Q1955446) (← links)
- A derivative-free optimization approach for the autotuning of a forex trading strategy (Q2037890) (← links)
- Forecasting stock market in high and low volatility periods: a modified multifractal volatility approach (Q2123691) (← links)
- Tightening big Ms in integer programming formulations for support vector machines with ramp loss (Q2184093) (← links)
- Intraday volume percentages forecasting using a dynamic SVM-based approach (Q2400458) (← links)
- Forecasting volatility with support vector machine-based GARCH model (Q3065523) (← links)
- Boosting-Based Frameworks in Financial Modeling: Application to Symbolic Volatility Forecasting (Q3571980) (← links)
- (Q3611454) (← links)
- On conditional risk estimation considering model risk (Q5138086) (← links)
- Nonlinear support vector machines can systematically identify stocks with high and low future returns (Q5420705) (← links)
- Statistical methods for decision support systems in finance: how Benford's law predicts financial risk (Q6666701) (← links)
