Perspectives on Risk Measurement - A Critical Assessment of PC-GARCH Against the Main Volatility Forecasting Models

The paper makes a critical assessment of the Principal Components-GARCH (PCGARCH) model and argues why, when dealing with hundreds or thousands of variables, this model comes up as the most appropriate to be used. The suitability originates from the perspective of quality/cost ratio of volatility forecasts, allowing for a trade-off between quality and costs when computational efforts are significant. PCGARCH not only provides a method that allows for simpler volatility modeling, reducing significantly the computational time and getting rid of any problem that may arise from complex data manipulations, but also improves the modeling process quality by ensuring a stricter control of noise due to more stable correlation estimates.