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q-fin.RM2024
Loss-based Bayesian Sequential Prediction of Value at Risk with a Long-Memory and Non-linear Realized Volatility Model
Rangika Peiris, Minh-Ngoc Tran, Chao Wang +1
A long memory and non-linear realized volatility model class is proposed for direct Value at Risk (VaR) forecasting. This model, referred to as RNN-HAR, extends the heterogeneous a…
q-fin.RM2024
Semi-parametric financial risk forecasting incorporating multiple realized measures
Rangika Peiris, Chao Wang, Richard Gerlach +1
A semi-parametric joint Value-at-Risk (VaR) and Expected Shortfall (ES) forecasting framework employing multiple realized measures is developed. The proposed framework extends the…