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computation (OD-NC) algorithm has greater accuracy than several common prediction methods, such as RBF (Radial Basis Function) and … GRNN (General Regression Neural Network). The prediction mean relative errors of RBF, GRNN and OD-NC are 7.812%, 5.674% and …
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In this paper, we document that realized variation measures constructed from high-frequency returns reveal a large degree of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which forecasting errors in realized volatility are substantive. Even...
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For forecasting volatility of futures returns, the paper proposes an indirect method based on the relationship between futures and the underlying asset for the returns and time-varying volatility. For volatility forecasting, the paper considers the stochastic volatility model with asymmetry and...
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The Basel Committee on Banking Supervision (BCBS) (2013) recently proposed shifting the quantitative risk metrics system from Value-at-Risk (VaR) to Expected Shortfall (ES). The BCBS (2013) noted that - a number of weaknesses have been identified with using VaR for determining regulatory capital...
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